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211 Commits

Author SHA1 Message Date
Daylen Yang
81490ebc75 Enable NEON for armv8 2020-08-05 10:45:17 -07:00
Dominik Schlösser
c402fe7d26 apple silicon platform with NEON
USE_NEON instead of IS_ARM
New platform apple-silicon with default USE_NEON
nnue_common.h includes arm_neon.h for USE_NEON
2020-08-05 16:45:07 +02:00
Joost VandeVondele
2b8bb8e226 Revert stray functional part of 6e2236c37a 2020-08-05 07:46:45 +02:00
Joost VandeVondele
8a3df0f92f Add and adjust copyright headers/authors.
Add missing copyright headers, and refer to the AUTHORS file for copyright owners.

Refer to 'The Stockfish developers (see AUTHORS file)' for authors.
2020-08-05 07:29:12 +02:00
Joost VandeVondele
6e2236c37a Makefile: small follow-up for comp=msys2 removal 2020-08-05 07:20:23 +02:00
Joost VandeVondele
d8d1ecca8c Fixes Makefile issues, #2870 2020-08-04 22:25:01 +02:00
Joost VandeVondele
bb9c6bc6a1 Update default net to nn-97f742aaefcd.nnue
uploaded by Sergio Vieri

NNUE signature: 4254913
Bench: 4746616
2020-08-04 08:12:43 +02:00
Joost VandeVondele
97724370e7 Merge branch 'master' into nnue-player-wip
Bench: 4746616
2020-08-04 08:03:52 +02:00
Joost VandeVondele
b16db14c87 Merge branch 'netDownloadMakefile' into nnue-player-wip 2020-08-03 20:14:52 +02:00
Joost VandeVondele
2c51afdb14 A new make target to download the default net
```
make net
```

will download the default net as specified in ucioption.cpp file.

This target assumes that `curl` or `wget` is available (in addition to grep and sed).

Needs some testing on different systems (windows, mac, etc.) to see if the implementation is portable enough.

Note that this is not part executed as part of a `make build` to make sure that a build doesn't need a network connection.
2020-08-03 14:28:54 +02:00
Joost VandeVondele
1d01b275ce Small Makefile doc fix 2020-08-03 07:23:11 +02:00
Joost VandeVondele
dbbb3fa477 Add info string showing which evaluation is in use 2020-08-02 17:22:19 +02:00
Joost VandeVondele
18686e29c7 Revisit NNUE initialization
this revisits the initialization of NNUE, basically only changing
the state on the UCI options 'Use NNUE' and 'EvalFile' calling init_NNUE(),
which sets the Eval::useNNUE variable, and loads the network if needed
(i.e. useNNUE is true and the same network is not yet loaded)

init_NNUE is silent (i.e. no info strings), so that it can be called at startup
without confusing certain GUIs.

An error message on wrong setting when asking for (i.e. the net failed to load),
is delayed to the point where everything must be consistent (start of search or eval).
The engine will stop if the settings are wrong at that point.

Also works if the default value of Use NNUE would become true.
2020-08-02 17:22:19 +02:00
Joost VandeVondele
e45d4f1b65 Small whitespace changes 2020-08-02 16:30:00 +02:00
Joost VandeVondele
f4ecc899d8 Minimal whitespace changes 2020-08-01 22:43:14 +02:00
Dariusz Orzechowski
122c78b521 [NNUE] More cleanup in nnue folder
No functional change.
2020-08-01 22:24:26 +02:00
Joost VandeVondele
aa339506db Small target adjustments 2020-08-01 19:19:10 +02:00
Dariusz Orzechowski
292c9efb1d [NNUE] Remove not used network architecture
No functional change.
2020-08-01 17:31:20 +02:00
Joost VandeVondele
9f2f46c212 [NNUE] adjust Makefile targets
clearly differentiate between sse3 and ssse3.
assume popcnt from sse4.
2020-08-01 17:30:29 +02:00
Joost VandeVondele
61ab908db3 Some coding style changes, white space 2020-08-01 09:25:00 +02:00
Joost VandeVondele
6cd70676b4 Update README.md
Mostly restores the previous README.md with some info and new UCI options, retaining only the info needed for the player.
The valuable training documentation is best preserved elsewhere.

Comments / fixes welcome.
2020-08-01 08:27:59 +02:00
Joost VandeVondele
56c9b608c9 Remove unused variable 2020-08-01 08:18:35 +02:00
Joost VandeVondele
dbab8b03cf Recreate Position object for eval
takes the current option settings into account.

Fixes #2859
Fixes #2579
2020-07-31 19:16:38 +02:00
Joost VandeVondele
8e28c99f79 Use a global instead of a variable in pos 2020-07-31 15:58:33 +02:00
Joost VandeVondele
e42258db5a Merge branch 'nnue-notemplate2' of https://github.com/dorzechowski/Stockfish into dorzechowski-nnue-notemplate2 2020-07-31 12:19:26 +02:00
Dariusz Orzechowski
69fa1111e6 [NNUE] StateInfo handling speed improvement
Don't copy NNUE parts of StateInfo when not needed in do_null_move().
Measurement vs master at STC shows only ~3 Elo regression when NNUE
is not used, was ~5 Elo before.

https://tests.stockfishchess.org/tests/view/5f23a9052f7e63962b99f51b
ELO: -3.02 +-1.7 (95%) LOS: 0.0%
Total: 60000 W: 11145 L: 11666 D: 37189
Ptnml(0-2): 1018, 6945, 14494, 6626, 917

No functional change.
2020-07-31 11:58:13 +02:00
Dariusz Orzechowski
ffae13edff Remove some code unused in the current network architecture
No functional change.
2020-07-30 05:05:27 +02:00
mstembera
21d43e9500 Remove some unnecessary declarations and headers.
bench: 4578298
2020-07-28 20:08:10 -07:00
NguyenPham
5c616bc46b Change data file extension of nnue networks
move from .bin (used for polyglot books etc) to .nnue
2020-07-28 14:02:35 +02:00
Joost VandeVondele
2f459fb161 Add authors to the AUTHORS file
add missing contributors based on git commit history
2020-07-28 10:27:07 +02:00
Joost VandeVondele
c8f7fa6a02 [NNUE] update compiler info with flags
as several new flags are added document compilation specifics under the compiler command.

No functional change.
2020-07-28 09:28:10 +02:00
Dariusz Orzechowski
7bb14c2489 Clamp NNUE evaluation score
No functional change.
2020-07-28 04:30:47 +02:00
Joost VandeVondele
6349062d42 [NNUE] remove evalnn command
instead eval uses the evaluation according to the state of Use NNUE

No functional change.
2020-07-27 20:14:25 +02:00
erbsenzaehler
7182c55e5c Update appveyor to use MSVC 2019 2020-07-27 13:09:48 +02:00
Joost VandeVondele
b536b0ac67 [NNUE] init networks also for cmdline use
`./stockfish go depth 10`

now works if `Use NNUE` defaults to true.

No functional change
2020-07-27 09:43:19 +02:00
mstembera
60497a85d6 Fix a crash on Use NNUE default true
This was because the UCI::use_nnue variable was never updated to true.

closes https://github.com/official-stockfish/Stockfish/pull/2843

bench: 4578298
NNUE: 3377227
2020-07-27 07:17:41 +02:00
Joost VandeVondele
a8bdf69c71 Use _mm_malloc on _WIN32 2020-07-26 22:22:36 +02:00
Joost VandeVondele
a6c614da03 Include header if _MSC_VER 2020-07-26 20:44:47 +02:00
Joost VandeVondele
98ffe0cd97 [NNUE] Wrap aligned_alloc
For some systems std::aligned_alloc is not available even if c++17 is specified.
Wrap the function and use specific solutions.

Update macosx-version-min to the required minimum.

No functional change.
2020-07-26 20:32:00 +02:00
Joost VandeVondele
2b0ba70436 [NNUE] update travis CI to use new toolchain
No functional change.
2020-07-26 18:03:54 +02:00
Joost VandeVondele
27b87ddf5d [NNUE] use_nue=false for getting the material key
No functional change.
2020-07-26 14:57:38 +02:00
Joost VandeVondele
319b8e8e7b Fix unused variable warning
for certain targets. Only define variable when needed.

No functional change.
2020-07-26 14:57:38 +02:00
Joost VandeVondele
44461911f7 [NNUE] Add C++17 to appveyor
update CMakeList.txt to add required C++ standard version.

Fix signature.

the code is up-to-date with master d89730d5c8 adjust signature

Bench: 4578298
2020-07-26 14:57:29 +02:00
Dariusz Orzechowski
a285850bf6 Fix valgrind issue
No functional change.
2020-07-26 08:52:22 +02:00
Dariusz Orzechowski
cae61bbb65 Fix memset/memcpy warnings
No functional change.
2020-07-26 08:52:22 +02:00
Joost VandeVondele
ab09c74783 Revert "[NNUE] Update travis clang on linux."
This reverts commit e3367756b5.
2020-07-25 19:48:20 +02:00
Joost VandeVondele
e3367756b5 [NNUE] Update travis clang on linux.
move from 6.0 to 7.0 (minimum version for std::aligned_alloc)
2020-07-25 19:13:59 +02:00
Joost VandeVondele
49d2cd8b13 [NNUE] update x86-64-modern target
slightly increase requirements on modern from sse3 to ssse3.
2020-07-25 17:23:07 +02:00
Dariusz Orzechowski
beb956f823 NNUE: Fix debug build
No functional change
2020-07-25 17:22:25 +02:00
Joost VandeVondele
faf08671ff [NNUE] default net
change default net to nn-c157e0a5755b.bin as available in https://github.com/official-stockfish/networks
2020-07-25 12:45:19 +02:00
Dariusz Orzechowski
458a920788 Fix makefile option x86-64-modern 2020-07-20 13:53:21 +02:00
Dariusz Orzechowski
871e6b8c83 Merge latest changes from nodchip repo 2020-07-20 13:19:25 +02:00
Dariusz Orzechowski
76d8f6128a Fix popcnt option in makefile 2020-07-20 11:39:52 +02:00
nodchip
c0e1235fef Added a description to Makefile. 2020-07-20 17:36:09 +09:00
No name
74049a450c Add NNUE targets to the output of 'make help' 2020-07-20 17:29:20 +09:00
nodchip
fbdb373b64 Changed to set the binary directory to the current working directory. 2020-07-20 17:17:50 +09:00
Dariusz Orzechowski
c0bbce092b Restore ARCH=x86-64-modern in the makefile 2020-07-20 09:59:40 +02:00
Dariusz Orzechowski
cf8a50e654 Don't use NNUE by default - changed for an attempt on fishtest 2020-07-20 08:39:21 +02:00
Dariusz Orzechowski
675672cfc1 Use std::aligned_alloc 2020-07-20 06:20:31 +02:00
Dariusz Orzechowski
4cceeb7380 Remove code unneeded for playing, refactor, update to latest master dev 2020-07-20 05:45:24 +02:00
mstembera
77018c77cc Fix profile builds for AVX512. 2020-07-19 21:25:50 +09:00
No name
fd78fb05f6 Hide NNUE options if building without NNUE support
Also remove an unused option.
2020-07-19 20:17:01 +09:00
nodchip
afd7d0ea4d Fixed a bug that Makefile specifies -mpopcnt for armv8-a. 2020-07-19 18:34:35 +09:00
nodchip
36092b855a Removed the x86-64-ssse3-popcnt architecture. 2020-07-19 14:17:35 +09:00
nodchip
3bbe4802b1 Removed the sse41-popcnt architecture. 2020-07-19 14:02:49 +09:00
nodchip
c001a4e62d Revert "Removed x86-64-ssse3-popcnt and x86-64-sse41-popcnt."
This reverts commit 92c2167481.
2020-07-19 13:58:19 +09:00
No name
1536e31065 Load the parameter set on an `isready' as well
Unbreaks Scid vs. PC, which doesn't send `ucinewgame'.
2020-07-19 13:22:40 +09:00
nodchip
92c2167481 Removed x86-64-ssse3-popcnt and x86-64-sse41-popcnt. 2020-07-19 12:52:20 +09:00
nodchip
a4786db4c2 Added support for architectures which supports SSE3+POPCNT, SSSE3+POPCNT and SSE41+POPCNT. 2020-07-19 12:41:50 +09:00
nodchip
c24ad8d8b5 Supported sse3 build. 2020-07-19 12:26:37 +09:00
mstembera
961a4dad5c Add AVX512 support.
bench: 3909820
2020-07-19 12:07:28 +09:00
nodchip
7a13d4ed60 Changed the default eval file path so that more GUIs can use Stockfish NNUE. 2020-07-17 15:40:01 +09:00
xXH4CKST3RXx
4d4c80d7fd Update README.md
Added logo, reinforcement learning instructions, and resources list.
2020-07-17 12:40:47 +09:00
nodchip
2b821682aa Update README.md 2020-07-17 11:55:30 +09:00
xXH4CKST3RXx
be754a2379 Update README.md 2020-07-16 13:21:14 +09:00
xXH4CKST3RXx
ec5ef2b6df Update README.md 2020-07-16 13:21:14 +09:00
xXH4CKST3RXx
df4da8dc41 Update README.md 2020-07-16 13:21:14 +09:00
xXH4CKST3RXx
6118151c66 Create README.md
Added and cleaned up Gekkehenker's training guide.
2020-07-16 13:21:14 +09:00
xXH4CKST3RXx
2fd1c48e60 Rename Readme.md to stockfish.md 2020-07-16 13:21:14 +09:00
No name
961047ed6e Experimental support for PGO builds of NNUE
Only 'nnue' target and only gcc/mingw.
(does not clean profile data generated by other compilers)
To use:
 make profile-nnue ARCH=arch
(see 'make help' for list of supported archs)
2020-07-16 08:53:03 +09:00
J. Oster
e29499ee4b Use the path and filename for restoring parameter files. 2020-07-15 19:29:29 +09:00
nodchip
7f4b72cdfd Merge branch 'master' of github.com:nodchip/Stockfish 2020-07-13 22:25:56 +09:00
nodchip
686a5a0df9 Fixed a bug that gensfen command does not accept the use_draw_in_training_data_generation option. 2020-07-13 22:25:23 +09:00
Anson Hu
df40de9486 game result bugfix 2020-07-12 15:56:03 +09:00
No name
fcb391919f Disable EVAL_HASH for 'nnue' target
Gives a 7% speed gain for me, without any parameter set loaded
(all-zero).
2020-07-11 19:29:05 +09:00
nodchip
ae4db5ebfd Merge pull request #45 from joergoster/sf-nnue-update
Sf nnue update
2020-07-11 19:17:38 +09:00
joergoster
db0615eed9 Merge branch 'master' into sf-nnue-update 2020-07-11 12:03:17 +02:00
zz4032
d6e8089f50 Saving new network in correct path. 2020-07-11 17:46:43 +09:00
zz4032
b521e405d3 Default network path in Linux. 2020-07-11 00:07:15 +09:00
nodchip
d7c358cf19 Fixed descriptions and sanity checks in Makefile. 2020-07-10 16:55:32 +09:00
nodchip
bc6a8d09e9 Unified the nnue-learn and nnue-learn-use-blas targets into nnue-learn. 2020-07-10 16:17:35 +09:00
nodchip
df05ecb1d5 Added halfkp_384x2-32-32. 2020-07-10 16:14:19 +09:00
nodchip
1de1eb2d0d Refactoring: Restructured the architecture list in Makefile. 2020-07-10 16:13:21 +09:00
No name
081761d084 Add support for SSSE3-only compiles
For Core 2 Duo.

To compile:
make ARCH=x86-64 ssse3=yes nnue

No observable difference in speed to SSE4.1 on my machine.
2020-07-10 15:21:50 +09:00
No name
b9a32fe331 Define USE_SSE2 for any x86-64 target
Rather than only when popcnt=yes
x86-64 instruction set includes SSE2.
2020-07-10 14:56:33 +09:00
tttak
a06234c639 enable convert_plain
learn convert_plain output_file_name xxx.txt xxx.bin
2020-07-09 09:51:00 +09:00
FireFather
df9b2a87db Update misc.cpp
change name to Stockfish+NNUE
and add 3 more authors
2020-07-08 23:20:36 +09:00
FireFather
821aaf3836 Update misc.cpp
do not clutter console window
remove "Windows large pages not used."
only show message when/if successful
2020-07-08 23:20:36 +09:00
nodchip
272f0f88c3 Merge pull request #40 from FireFather/master
Update evaluate_nnue_learner.cpp
2020-07-08 20:52:39 +09:00
FireFather
76d124ed70 Update evaluate_nnue_learner.cpp
replace NNUE::kFileName with NNUE::fileName
2020-07-08 13:42:28 +02:00
FireFather
ec3eaad64f update evaluate_nnue.cpp
rename kFileName and change to std:string
2020-07-08 11:59:18 +09:00
FireFather
f7420652b7 UCI option EvalFile
Replace EvalDir with EvalFile
Can now browse filesystem for net (eval\nn.bin is default)
nn.bin no longer hard-coded
2020-07-08 11:59:18 +09:00
FireFather
d1760a1f15 update evaluate_nnue.cpp
rename kFileName and change to std:string
2020-07-08 04:23:50 +02:00
FireFather
c59583bbf0 UCI option EvalFile
Replace EvalDir with EvalFile
Can now browse filesystem for net (eval\nn.bin is default)
nn.bin no longer hard-coded
2020-07-07 23:25:20 +02:00
FireFather
d61378cacb Merge pull request #1 from nodchip/master
Merge
2020-07-07 13:06:40 +02:00
joergoster
cd55c268cb Bugfix.
Otherwise creating a new net fails.
2020-07-07 18:51:22 +09:00
joergoster
a5af8510a5 Rework loading the net. 2020-07-07 15:13:59 +09:00
nodchip
288fdc5597 Added "nodes" option to the "gensfen" command to specify the number of the nodes to be searched. 2020-07-06 17:38:43 +09:00
nodchip
85c802d0b9 Revert "use winning_percentage_wdl in learn"
This reverts commit c964e902c5.

# Conflicts:
#	src/uci.cpp
2020-07-06 11:07:46 +09:00
nodchip
3b535b5ade Merge pull request #36 from tttak/WDL_20200703b
use winning_percentage_wdl in learn
2020-07-04 07:36:33 +09:00
nodchip
cea5240909 Merge branch 'master' into WDL_20200703b 2020-07-04 07:36:16 +09:00
tttak
5dec3e547e merge "Provide WDL statistics"
110068808b
https://github.com/official-stockfish/Stockfish/pull/2778
https://github.com/official-stockfish/Stockfish/pull/2788
2020-07-04 07:35:15 +09:00
tttak
c964e902c5 use winning_percentage_wdl in learn 2020-07-03 23:21:49 +09:00
tttak
9ce0ef3ac0 merge "Provide WDL statistics"
110068808b
https://github.com/official-stockfish/Stockfish/pull/2778
https://github.com/official-stockfish/Stockfish/pull/2788
2020-07-03 23:01:37 +09:00
FireFather
9c19021808 update translation
1 line src\eval\nnue\features\half_kp.cpp
1 line src\movegen.h
2020-07-03 09:24:15 +09:00
FireFather
c679e8f360 Update search.h
1 line of translation
2020-07-03 09:24:15 +09:00
joergoster
13824d8b96 Explicitly specify SSE41. 2020-07-02 16:15:39 +09:00
joergoster
145e4c2a10 Add SSE41 switch.
This allows building modern compiles with SSE41 enabled,
which gives a nice speedup on my Bulldozer CPU.

For example:
make nnue ARCH=x86-64-modern sse41=yes -j
2020-07-02 16:15:39 +09:00
nodchip
c8262f8aec Fixed a compile error. 2020-06-30 15:58:51 +09:00
tttak
486f72af54 バグ修正(learn convert_bin_from_pgn-extract) 2020-06-30 14:01:04 +09:00
tttak
fda3945c07 learn convert_bin_from_pgn-extractコマンドを追加
http://rebel13.nl/download/data.html
Download Selected Lichess games
pgn-extract --fencomments -Wlalg --nochecks --nomovenumbers --noresults -w500000 -N -V -o comp-2019-06.txt comp-2019-06.pgn
stockfish.exe
learn convert_bin_from_pgn-extract pgn_eval_side_to_move 0 output_file_name fens_comp-2019-06.bin comp-2019-06.txt

https://github.com/glinscott/fishtest/wiki/PGN-files-of-games-played-on-fishtest
pgn-extract --fencomments -Wlalg --nochecks --nomovenumbers --noresults -w500000 -N -V -o fishtest.txt fishtest.pgn
stockfish.exe
learn convert_bin_from_pgn-extract pgn_eval_side_to_move 1 output_file_name fens_fishtest.bin fishtest.txt
2020-06-30 14:01:04 +09:00
FireFather
8f31d74cf6 More comment translation
including 11 files in /src
2020-06-30 00:45:32 +09:00
FireFather
f5cc77bc7c EOL
add eol at eof
2020-06-29 08:27:41 +09:00
nodchip
9dc62809c8 Merge pull request #24 from FireFather/master
Comment translation
2020-06-28 11:43:53 +09:00
nodchip
123dd68452 Merge branch 'master' into master 2020-06-28 11:42:23 +09:00
nodchip
f1a8580118 Merge branch 'master' of github.com:nodchip/Stockfish 2020-06-28 11:37:42 +09:00
nodchip
87c8b324f8 Simplified source code to estimate the winning ratio from an eval value.
We need to adjust the eta again after this commit is pushed.
2020-06-28 11:37:15 +09:00
nodchip
6324c2de75 Merge pull request #23 from joergoster/linux_sse41
Linux sse41
2020-06-28 10:29:14 +09:00
FireFather
aea08de018 Translation
Files in /eval, /extra, & /learn - comments translated from Japanese to English
2020-06-28 03:12:55 +02:00
FireFather
2f8c692caa Merge pull request #2 from nodchip/master
merge
2020-06-28 01:37:01 +02:00
joergoster
96f2541191 Fix compilation under Linux with -DUSE_SSE41. 2020-06-27 19:41:13 +02:00
nodchip
cb8accada2 Merge branch 'master' of github.com:nodchip/Stockfish 2020-06-27 22:19:33 +09:00
nodchip
13eb540020 Changed the formula to calculate winning ratio to 1/(1+10^(-Eval/4)). 2020-06-27 22:19:22 +09:00
joergoster
32c204fb56 Merge branch 'master' into sf-nnue-nodchip 2020-06-27 10:57:09 +02:00
tttak
e229015127 learn convert_bin_from_pgn-extractコマンドを追加
http://rebel13.nl/download/data.html
Download Selected Lichess games
pgn-extract --fencomments -Wlalg --nochecks --nomovenumbers --noresults -w500000 -N -V -o comp-2019-06.txt comp-2019-06.pgn
stockfish.exe
setoption name SkipLoadingEval value true
isready
learn convert_bin_from_pgn-extract output_file_name fens_comp-2019-06.bin comp-2019-06.txt
2020-06-27 16:33:36 +09:00
nodchip
aa2dc962f5 Added use_draw_in_training_data_generation option to write out draw games to the training data. 2020-06-27 14:00:12 +09:00
rqs
4c926b8eb4 add pgn_to_plain 2020-06-27 13:17:54 +09:00
rqs
0761d9504e add convert_bin and option for draw positions 2020-06-27 13:17:54 +09:00
joergoster
2af46deede Fix include. 2020-06-26 09:12:24 +09:00
joergoster
a5fb69008c Bugfix. No legal move is either mate or stalemate. 2020-06-26 09:12:24 +09:00
nodchip
1c8a931309 Merge pull request #18 from joergoster/sf-nnue-nodchip
Update to SF master
2020-06-25 23:09:45 +09:00
joergoster
151a0dda91 Merge branch 'master' into sf-nnue-nodchip 2020-06-25 15:10:12 +02:00
FireFather
8c8a30233c Update evaluate_nnue.cpp 2020-06-25 12:41:32 +09:00
FireFather
86e3fedf7e Update evaluate_nnue.cpp 2020-06-25 04:38:39 +02:00
FireFather
7a3c3eacdf added header guards
5 include files in \eval\nnue\architectures
2020-06-25 10:39:29 +09:00
nodchip
ff31d92b94 Merge pull request #14 from joergoster/sf-nnue-nodchip
Update to SF master
2020-06-25 10:38:16 +09:00
FireFather
08d8adbade added header guards
5 include files in \eval\nnue\architectures
2020-06-24 22:41:00 +02:00
joergoster
5e119f5139 Finally. 2020-06-24 20:22:56 +02:00
joergoster
0e932757e5 Re-enable increment operator for Piece.
No functional change.
2020-06-24 20:18:32 +02:00
joergoster
8ef6c837b7 Fix.
Bench: 4471740
2020-06-24 18:04:28 +02:00
joergoster
89bbe86800 Merge branch 'master' of https://github.com/nodchip/Stockfish into sf-nnue-nodchip 2020-06-24 17:47:55 +02:00
nodchip
7818d23afb Merge pull request #13 from zz4032/linux-identifier
Linux identifier corrected.
2020-06-24 09:35:44 +09:00
nodchip
0abd692543 Fixed a build error on Visual Studio. 2020-06-24 09:33:46 +09:00
zz4032
5ae64e2244 Adding mm_malloc.h
Otherwise compiling with 'modern' or 'avx2' architecture on Linux aborts with errors.
2020-06-24 09:28:45 +09:00
zz4032
5aa801e721 Update misc.h 2020-06-23 20:54:50 +02:00
zz4032
3102896a00 Linux identifier corrected. 2020-06-23 20:53:32 +02:00
zz4032
ccd2e602a0 Adding mm_malloc.h
Otherwise compiling with 'modern' or 'avx2' architecture on Linux aborts with errors.
2020-06-23 19:55:54 +02:00
nodchip
999f5ec446 COMP=msys2を指定できるようにした 2020-06-24 00:47:34 +09:00
nodchip
43e78187d7 ARCH=x86-64-avx2を指定できるようにした 2020-06-24 00:27:45 +09:00
nodchip
76b0de40a1 コンパイラーオプションを-std=c++14から-std=c++17に変更した 2020-06-23 23:47:59 +09:00
nodchip
c7884470fb Merge branch 'master' of github.com:nodchip/Stockfish 2020-06-22 10:28:02 +09:00
nodchip
6c7a594362 Added "-Wl,-s" option. 2020-06-22 10:27:52 +09:00
tttak
2d5c50d85b eval_nnueコマンド追加 2020-06-22 09:50:22 +09:00
nodchip
33772a0418 コンパイルエラーを修正した 2020-06-08 23:46:06 +09:00
nodchip
5c936572e9 Merge branch 'master' of github.com:official-stockfish/Stockfish
# Conflicts:
#	src/Makefile
#	src/position.cpp
#	src/position.h
#	src/search.cpp
#	src/types.h
#	src/uci.cpp
2020-06-08 23:09:51 +09:00
tttak
91a7557ab4 test nnue test_features等の有効化 2020-06-08 15:07:48 +09:00
nodchip
d23f96d156 No pruning at low plies.
This makes those very early depths a bit more reliable.

Thanks, joergoster!

be7f37187b
2020-06-06 18:50:15 +09:00
nodchip
2523f72ff9 盤上から取り除かれた駒に関する差分計算を省き、高速化した 2020-06-03 23:32:08 +09:00
nodchip
a85e3055f4 いくつかのターゲットでOpenMPを有効にした 2020-06-02 00:13:35 +09:00
tttak
78134b7641 OpenMPの有効化 2020-06-01 23:51:05 +09:00
nodchip
6703ec8ab0 nnue-gen-sfen-from-original-evalターゲットを追加した 2020-05-30 09:50:29 +09:00
nodchip
dd9818c2c1 Added "-static" compiler option. 2020-05-29 09:36:24 +09:00
nodchip
f18acf97ed Added the "nnue" target.
Fixed build errors on the "nnue-learn-use-blas" target.
2020-05-28 10:08:51 +09:00
Hisayori Noda
e2165155d1 Enabled halfkp_256x2-32-32.h. 2019-07-11 22:47:55 +09:00
Hisayori Noda
1d5f79db1c Merge branch 'master' of github.com:nodchip/Stockfish into k-p_256x2-32-32 2019-07-10 08:18:57 +09:00
tttak
c4d30f3649 set_from_packed_sfen()でmirrorをepSquareにも適用するように修正 2019-07-10 08:16:38 +09:00
Hisayori Noda
2d70487caa Enabled k-p_256x2-32-32. 2019-07-08 19:02:09 +09:00
tttak
0be41dbb67 nullmoveとpromotionの場合に評価値の差分計算と全計算の結果が異なっていたのを修正 2019-07-08 18:51:08 +09:00
HiraokaTakuya
c643ee0b45 Fix a compile error. 2019-07-08 18:49:47 +09:00
HiraokaTakuya
10aa774d08 Fix a compile error. 2019-07-08 18:49:47 +09:00
HiraokaTakuya
8718438943 std::conditional_t can be used from C++14. 2019-07-08 18:49:47 +09:00
HiraokaTakuya
fc5f64b383 Add targets nnue-learn, nnue-learn-use-blas 2019-07-08 18:49:47 +09:00
tttak
3dcd2bb69b Makefileのobjclean:に「./eval/nnue/*.o」等を追加 2019-07-08 18:46:24 +09:00
Hisayori Noda
b300a9d43e Enabled halfkp_256x2-32-32. 2019-07-07 21:44:02 +09:00
Hisayori Noda
747d98bf1b Added halfkp-cr-ep_256x2-32-32 architecture. 2019-07-07 20:31:54 +09:00
Hisayori Noda
df827ea7ee Added enpassant feature. Added k-p-cr-ep_256x2-32-32 architecture. 2019-07-07 19:24:46 +09:00
Hisayori Noda
92052bc16b Fixed build errors. 2019-07-07 17:22:07 +09:00
Hisayori Noda
5c0037de7f Added the castling right feature. Added k-p-cr_256x2-32-32 architecture. 2019-07-07 17:02:34 +09:00
Hisayori Noda
09e529edd3 Added a hack to avoid crash with binaries compiled by g++ on MSYS2. 2019-07-05 00:22:41 +09:00
Hisayori Noda
89e846c476 Fixed a bug that Learner::qsearch() recognizes stalemate as checkmated. 2019-07-04 23:44:58 +09:00
Hisayori Noda
81262320c3 Revert "Changed the constant value to calculate the winning percentage."
This reverts commit 00f84ed99a.
2019-06-30 11:29:43 +09:00
Hisayori Noda
00f84ed99a Changed the constant value to calculate the winning percentage. 2019-06-26 08:48:48 +09:00
Hisayori Noda
26271586cb Added #if to fix compile errors. 2019-06-24 23:18:17 +09:00
Hisayori Noda
a413bf7aad Added hack to avoid crash during machine learning. 2019-06-24 23:17:46 +09:00
Hisayori Noda
9a73df7379 Added test commands. 2019-06-22 00:40:46 +09:00
Hisayori Noda
5772509e8b Disabled TT when EVAL_LEARN is enabled. 2019-06-22 00:40:25 +09:00
Hisayori Noda
641724e3a5 Added debug code. 2019-06-22 00:39:21 +09:00
Hisayori Noda
57ead90f18 Fixed a bug that the game play is invalid. 2019-06-22 00:38:24 +09:00
Hisayori Noda
07dc336b0f Added validation logic. 2019-06-22 00:37:59 +09:00
Hisayori Noda
84a96a3d9c Fixed a compilation error. 2019-06-22 00:37:31 +09:00
Hisayori Noda
998d8721bd Fixed a bug that White and Black are reversed. 2019-06-22 00:37:10 +09:00
Hisayori Noda
9dab4660ce Added source files. 2019-06-22 00:36:42 +09:00
Hisayori Noda
90ef97dcbd Fixed crash bugs. 2019-06-20 00:25:40 +09:00
Hisayori Noda
24576d77ab Merged uci parse logic. 2019-06-18 21:19:51 +09:00
Hisayori Noda
f58d616198 Fixed compile errors when EVAL_LEARN or EVAL_NNUE are defined. 2019-06-18 20:28:50 +09:00
Hisayori Noda
bcd6985871 Merged the training data generator and the machine learning logic from YaneuraOu. 2019-06-18 08:48:05 +09:00
Hisayori Noda
87445881ec Added #ifdef statements to switch the legacy evaluation function and NNUE evaluation function. 2019-06-16 11:11:16 +09:00
Hisayori Noda
48bfe86d27 Implemented the logic to update Eval List and Dirty Pieces. 2019-06-16 10:33:53 +09:00
Hisayori Noda
b330602cdc Fixed compile errors. 2019-06-15 17:08:47 +09:00
Hisayori Noda
9964fbbe25 Reverted evaluate.cpp. 2019-06-15 11:46:54 +09:00
Hisayori Noda
db02ddcc90 Added files for NNUE. 2019-06-09 10:40:12 +09:00
114 changed files with 12632 additions and 20013 deletions

View File

@@ -1,44 +0,0 @@
AccessModifierOffset: -1
AlignAfterOpenBracket: Align
AlignConsecutiveAssignments: Consecutive
AlignConsecutiveDeclarations: Consecutive
AlignEscapedNewlines: DontAlign
AlignOperands: AlignAfterOperator
AlignTrailingComments: true
AllowAllParametersOfDeclarationOnNextLine: true
AllowShortCaseLabelsOnASingleLine: false
AllowShortEnumsOnASingleLine: false
AllowShortIfStatementsOnASingleLine: false
BreakTemplateDeclarations: Yes
BasedOnStyle: WebKit
BitFieldColonSpacing: After
BinPackParameters: false
BreakBeforeBinaryOperators: NonAssignment
BreakBeforeBraces: Custom
BraceWrapping:
AfterFunction: false
AfterClass: false
AfterControlStatement: true
BeforeElse: true
BreakBeforeTernaryOperators: true
BreakConstructorInitializers: AfterColon
BreakStringLiterals: false
ColumnLimit: 100
ContinuationIndentWidth: 2
Cpp11BracedListStyle: true
IndentGotoLabels: false
IndentPPDirectives: BeforeHash
IndentWidth: 4
MaxEmptyLinesToKeep: 2
NamespaceIndentation: None
PackConstructorInitializers: Never
ReflowComments: false
SortIncludes: false
SortUsingDeclarations: false
SpaceAfterCStyleCast: true
SpaceAfterTemplateKeyword: false
SpaceBeforeCaseColon: true
SpaceBeforeCpp11BracedList: false
SpaceBeforeInheritanceColon: false
SpaceInEmptyBlock: false
SpacesBeforeTrailingComments: 2

View File

@@ -1,7 +0,0 @@
# .git-blame-ignore-revs
# Ignore commit which added clang-format
2d0237db3f0e596fb06e3ffbadba84dcc4e018f6
# Post commit formatting fixes
0fca5605fa2e5e7240fde5e1aae50952b2612231
08ed4c90db31959521b7ef3186c026edd1e90307

View File

@@ -1,65 +0,0 @@
name: Report issue
description: Create a report to help us fix issues with the engine
body:
- type: textarea
attributes:
label: Describe the issue
description: A clear and concise description of what you're experiencing.
validations:
required: true
- type: textarea
attributes:
label: Expected behavior
description: A clear and concise description of what you expected to happen.
validations:
required: true
- type: textarea
attributes:
label: Steps to reproduce
description: |
Steps to reproduce the behavior.
You can also use this section to paste the command line output.
placeholder: |
```
position startpos moves g2g4 e7e5 f2f3
go mate 1
info string NNUE evaluation using nn-6877cd24400e.nnue enabled
info depth 1 seldepth 1 multipv 1 score mate 1 nodes 33 nps 11000 tbhits 0 time 3 pv d8h4
bestmove d8h4
```
validations:
required: true
- type: textarea
attributes:
label: Anything else?
description: |
Anything that will give us more context about the issue you are encountering.
You can also use this section to propose ideas on how to solve the issue.
validations:
required: false
- type: dropdown
attributes:
label: Operating system
options:
- All
- Windows
- Linux
- MacOS
- Android
- Other or N/A
validations:
required: true
- type: input
attributes:
label: Stockfish version
description: |
This can be found by running the engine.
You can also use the commit ID.
placeholder: Stockfish 15 / e6e324e
validations:
required: true

View File

@@ -1,8 +0,0 @@
blank_issues_enabled: false
contact_links:
- name: Discord server
url: https://discord.gg/GWDRS3kU6R
about: Feel free to ask for support or have a chat with us on our Discord server!
- name: Discussions, Q&A, ideas, show us something...
url: https://github.com/official-stockfish/Stockfish/discussions/new
about: Do you have an idea for Stockfish? Do you want to show something that you made? Please open a discussion about it!

View File

@@ -1,51 +0,0 @@
{
"config": [
{
"name": "Android NDK aarch64",
"os": "ubuntu-22.04",
"simple_name": "android",
"compiler": "aarch64-linux-android29-clang++",
"emu": "qemu-aarch64",
"comp": "ndk",
"shell": "bash",
"archive_ext": "tar"
},
{
"name": "Android NDK arm",
"os": "ubuntu-22.04",
"simple_name": "android",
"compiler": "armv7a-linux-androideabi29-clang++",
"emu": "qemu-arm",
"comp": "ndk",
"shell": "bash",
"archive_ext": "tar"
}
],
"binaries": ["armv8-dotprod", "armv8", "armv7", "armv7-neon"],
"exclude": [
{
"binaries": "armv8-dotprod",
"config": {
"compiler": "armv7a-linux-androideabi29-clang++"
}
},
{
"binaries": "armv8",
"config": {
"compiler": "armv7a-linux-androideabi29-clang++"
}
},
{
"binaries": "armv7",
"config": {
"compiler": "aarch64-linux-android29-clang++"
}
},
{
"binaries": "armv7-neon",
"config": {
"compiler": "aarch64-linux-android29-clang++"
}
}
]
}

View File

@@ -1,22 +0,0 @@
[
# Mappings for libcxx's internal headers
{ include: [ "<__fwd/fstream.h>", private, "<iosfwd>", public ] },
{ include: [ "<__fwd/ios.h>", private, "<iosfwd>", public ] },
{ include: [ "<__fwd/istream.h>", private, "<iosfwd>", public ] },
{ include: [ "<__fwd/ostream.h>", private, "<iosfwd>", public ] },
{ include: [ "<__fwd/sstream.h>", private, "<iosfwd>", public ] },
{ include: [ "<__fwd/streambuf.h>", private, "<iosfwd>", public ] },
{ include: [ "<__fwd/string_view.h>", private, "<string_view>", public ] },
{ include: [ "<__system_error/errc.h>", private, "<system_error>", public ] },
# Mappings for includes between public headers
{ include: [ "<ios>", public, "<iostream>", public ] },
{ include: [ "<streambuf>", public, "<iostream>", public ] },
{ include: [ "<istream>", public, "<iostream>", public ] },
{ include: [ "<ostream>", public, "<iostream>", public ] },
{ include: [ "<iosfwd>", public, "<iostream>", public ] },
# Missing mappings in include-what-you-use's libcxx.imp
{ include: ["@<__condition_variable/.*>", private, "<condition_variable>", public ] },
{ include: ["@<__mutex/.*>", private, "<mutex>", public ] },
]

282
.github/ci/matrix.json vendored
View File

@@ -1,282 +0,0 @@
{
"config": [
{
"name": "Ubuntu 22.04 GCC",
"os": "ubuntu-22.04",
"simple_name": "ubuntu",
"compiler": "g++",
"comp": "gcc",
"shell": "bash",
"archive_ext": "tar",
"sde": "/home/runner/work/Stockfish/Stockfish/.output/sde-temp-files/sde-external-9.27.0-2023-09-13-lin/sde -future --"
},
{
"name": "MacOS 13 Apple Clang",
"os": "macos-13",
"simple_name": "macos",
"compiler": "clang++",
"comp": "clang",
"shell": "bash",
"archive_ext": "tar"
},
{
"name": "MacOS 14 Apple Clang M1",
"os": "macos-14",
"simple_name": "macos-m1",
"compiler": "clang++",
"comp": "clang",
"shell": "bash",
"archive_ext": "tar"
},
{
"name": "Windows 2022 Mingw-w64 GCC x86_64",
"os": "windows-2022",
"simple_name": "windows",
"compiler": "g++",
"comp": "mingw",
"msys_sys": "mingw64",
"msys_env": "x86_64-gcc",
"shell": "msys2 {0}",
"ext": ".exe",
"sde": "/d/a/Stockfish/Stockfish/.output/sde-temp-files/sde-external-9.27.0-2023-09-13-win/sde.exe -future --",
"archive_ext": "zip"
},
{
"name": "Windows 11 Mingw-w64 Clang arm64",
"os": "windows-11-arm",
"simple_name": "windows",
"compiler": "clang++",
"comp": "clang",
"msys_sys": "clangarm64",
"msys_env": "clang-aarch64-clang",
"shell": "msys2 {0}",
"ext": ".exe",
"archive_ext": "zip"
}
],
"binaries": [
"x86-64",
"x86-64-sse41-popcnt",
"x86-64-avx2",
"x86-64-bmi2",
"x86-64-avxvnni",
"x86-64-avx512",
"x86-64-vnni256",
"x86-64-vnni512",
"apple-silicon",
"armv8",
"armv8-dotprod"
],
"exclude": [
{
"binaries": "x86-64",
"config": {
"os": "macos-14"
}
},
{
"binaries": "x86-64-sse41-popcnt",
"config": {
"os": "macos-14"
}
},
{
"binaries": "x86-64-avx2",
"config": {
"os": "macos-14"
}
},
{
"binaries": "x86-64-bmi2",
"config": {
"os": "macos-14"
}
},
{
"binaries": "x86-64-avxvnni",
"config": {
"os": "macos-14"
}
},
{
"binaries": "x86-64-avx512",
"config": {
"os": "macos-14"
}
},
{
"binaries": "x86-64-vnni256",
"config": {
"os": "macos-14"
}
},
{
"binaries": "x86-64-vnni512",
"config": {
"os": "macos-14"
}
},
{
"binaries": "x86-64-avxvnni",
"config": {
"os": "macos-13"
}
},
{
"binaries": "x86-64-avx512",
"config": {
"os": "macos-13"
}
},
{
"binaries": "x86-64-vnni256",
"config": {
"os": "macos-13"
}
},
{
"binaries": "x86-64-vnni512",
"config": {
"os": "macos-13"
}
},
{
"binaries": "x86-64",
"config": {
"os": "windows-11-arm"
}
},
{
"binaries": "x86-64-sse41-popcnt",
"config": {
"os": "windows-11-arm"
}
},
{
"binaries": "x86-64-avx2",
"config": {
"os": "windows-11-arm"
}
},
{
"binaries": "x86-64-bmi2",
"config": {
"os": "windows-11-arm"
}
},
{
"binaries": "x86-64-avxvnni",
"config": {
"os": "windows-11-arm"
}
},
{
"binaries": "x86-64-avx512",
"config": {
"os": "windows-11-arm"
}
},
{
"binaries": "x86-64-vnni256",
"config": {
"os": "windows-11-arm"
}
},
{
"binaries": "x86-64-vnni512",
"config": {
"os": "windows-11-arm"
}
},
{
"binaries": "apple-silicon",
"config": {
"os": "windows-2022"
}
},
{
"binaries": "apple-silicon",
"config": {
"os": "windows-11-arm"
}
},
{
"binaries": "apple-silicon",
"config": {
"os": "ubuntu-20.04"
}
},
{
"binaries": "apple-silicon",
"config": {
"os": "ubuntu-22.04"
}
},
{
"binaries": "apple-silicon",
"config": {
"os": "macos-13"
}
},
{
"binaries": "armv8",
"config": {
"os": "windows-2022"
}
},
{
"binaries": "armv8",
"config": {
"os": "ubuntu-20.04"
}
},
{
"binaries": "armv8",
"config": {
"os": "ubuntu-22.04"
}
},
{
"binaries": "armv8",
"config": {
"os": "macos-13"
}
},
{
"binaries": "armv8",
"config": {
"os": "macos-14"
}
},
{
"binaries": "armv8-dotprod",
"config": {
"os": "windows-2022"
}
},
{
"binaries": "armv8-dotprod",
"config": {
"os": "ubuntu-20.04"
}
},
{
"binaries": "armv8-dotprod",
"config": {
"os": "ubuntu-22.04"
}
},
{
"binaries": "armv8-dotprod",
"config": {
"os": "macos-13"
}
},
{
"binaries": "armv8-dotprod",
"config": {
"os": "macos-14"
}
}
]
}

View File

@@ -1,98 +0,0 @@
name: Compilation
on:
workflow_call:
inputs:
matrix:
type: string
required: true
jobs:
Compilation:
name: ${{ matrix.config.name }} ${{ matrix.binaries }}
runs-on: ${{ matrix.config.os }}
env:
COMPCXX: ${{ matrix.config.compiler }}
COMP: ${{ matrix.config.comp }}
EMU: ${{ matrix.config.emu }}
EXT: ${{ matrix.config.ext }}
BINARY: ${{ matrix.binaries }}
strategy:
fail-fast: false
matrix: ${{ fromJson(inputs.matrix) }}
defaults:
run:
working-directory: src
shell: ${{ matrix.config.shell }}
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0
persist-credentials: false
- name: Download required linux packages
if: runner.os == 'Linux'
run: |
sudo apt update
sudo apt install qemu-user
- name: Install NDK
if: runner.os == 'Linux'
run: |
if [ $COMP == ndk ]; then
NDKV="27.2.12479018"
ANDROID_ROOT=/usr/local/lib/android
ANDROID_SDK_ROOT=$ANDROID_ROOT/sdk
SDKMANAGER=$ANDROID_SDK_ROOT/cmdline-tools/latest/bin/sdkmanager
echo "y" | $SDKMANAGER "ndk;$NDKV"
ANDROID_NDK_ROOT=$ANDROID_SDK_ROOT/ndk/$NDKV
ANDROID_NDK_BIN=$ANDROID_NDK_ROOT/toolchains/llvm/prebuilt/linux-x86_64/bin
echo "ANDROID_NDK_BIN=$ANDROID_NDK_BIN" >> $GITHUB_ENV
fi
- name: Extract the bench number from the commit history
run: |
for hash in $(git rev-list -100 HEAD); do
benchref=$(git show -s $hash | tac | grep -m 1 -o -x '[[:space:]]*\b[Bb]ench[ :]\+[1-9][0-9]\{5,7\}\b[[:space:]]*' | sed 's/[^0-9]//g') && break || true
done
[[ -n "$benchref" ]] && echo "benchref=$benchref" >> $GITHUB_ENV && echo "From commit: $hash" && echo "Reference bench: $benchref" || echo "No bench found"
- name: Download the used network from the fishtest framework
run: make net
- name: Check compiler
run: |
if [ $COMP == ndk ]; then
export PATH=${{ env.ANDROID_NDK_BIN }}:$PATH
fi
$COMPCXX -v
- name: Test help target
run: make help
- name: Check git
run: git --version
# Compile profile guided builds
- name: Compile ${{ matrix.binaries }} build
run: |
if [ $COMP == ndk ]; then
export PATH=${{ env.ANDROID_NDK_BIN }}:$PATH
export LDFLAGS="-static -Wno-unused-command-line-argument"
fi
make clean
make -j4 profile-build ARCH=$BINARY COMP=$COMP WINE_PATH=$EMU
make strip ARCH=$BINARY COMP=$COMP
WINE_PATH=$EMU ../tests/signature.sh $benchref
mv ./stockfish$EXT ../stockfish-android-$BINARY$EXT
- name: Remove non src files
run: git clean -fx
- name: Upload artifact for (pre)-release
uses: actions/upload-artifact@v4
with:
name: ${{ matrix.config.simple_name }} ${{ matrix.binaries }}
path: |
.
!.git
!.output

View File

@@ -1,57 +0,0 @@
# This workflow will run clang-format and comment on the PR.
# Because of security reasons, it is crucial that this workflow
# executes no shell script nor runs make.
# Read this before editing: https://securitylab.github.com/research/github-actions-preventing-pwn-requests/
name: Clang-Format
on:
pull_request_target:
branches:
- "master"
paths:
- "**.cpp"
- "**.h"
permissions:
pull-requests: write
jobs:
Clang-Format:
name: Clang-Format
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v4
with:
ref: ${{ github.event.pull_request.head.sha }}
- name: Run clang-format style check
uses: jidicula/clang-format-action@4726374d1aa3c6aecf132e5197e498979588ebc8 # @v4.15.0
id: clang-format
continue-on-error: true
with:
clang-format-version: "20"
exclude-regex: "incbin"
- name: Comment on PR
if: steps.clang-format.outcome == 'failure'
uses: thollander/actions-comment-pull-request@fabd468d3a1a0b97feee5f6b9e499eab0dd903f6 # @v2.5.0
with:
message: |
clang-format 20 needs to be run on this PR.
If you do not have clang-format installed, the maintainer will run it when merging.
For the exact version please see https://packages.ubuntu.com/plucky/clang-format-20.
_(execution **${{ github.run_id }}** / attempt **${{ github.run_attempt }}**)_
comment_tag: execution
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Comment on PR
if: steps.clang-format.outcome != 'failure'
uses: thollander/actions-comment-pull-request@fabd468d3a1a0b97feee5f6b9e499eab0dd903f6 # @v2.5.0
with:
message: |
_(execution **${{ github.run_id }}** / attempt **${{ github.run_attempt }}**)_
create_if_not_exists: false
comment_tag: execution
mode: delete
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

View File

@@ -1,55 +0,0 @@
name: "CodeQL"
on:
push:
branches: ["master"]
pull_request:
# The branches below must be a subset of the branches above
branches: ["master"]
schedule:
- cron: "17 18 * * 1"
jobs:
analyze:
name: Analyze
runs-on: ubuntu-latest
permissions:
actions: read
contents: read
security-events: write
strategy:
fail-fast: false
matrix:
language: ["cpp"]
# CodeQL supports [ 'cpp', 'csharp', 'go', 'java', 'javascript', 'python', 'ruby' ]
# Use only 'java' to analyze code written in Java, Kotlin, or both
# Use only 'javascript' to analyze code written in JavaScript, TypeScript or both
# Learn more about CodeQL language support at https://aka.ms/codeql-docs/language-support
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
persist-credentials: false
# Initializes the CodeQL tools for scanning.
- name: Initialize CodeQL
uses: github/codeql-action/init@v3
with:
languages: ${{ matrix.language }}
# If you wish to specify custom queries, you can do so here or in a config file.
# By default, queries listed here will override any specified in a config file.
# Prefix the list here with "+" to use these queries and those in the config file.
# For more details on CodeQL's query packs, refer to: https://docs.github.com/en/code-security/code-scanning/automatically-scanning-your-code-for-vulnerabilities-and-errors/configuring-code-scanning#using-queries-in-ql-packs
# queries: security-extended,security-and-quality
- name: Build
working-directory: src
run: make -j build
- name: Perform CodeQL Analysis
uses: github/codeql-action/analyze@v3
with:
category: "/language:${{matrix.language}}"

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@@ -1,94 +0,0 @@
name: Compilation
on:
workflow_call:
inputs:
matrix:
type: string
required: true
jobs:
Compilation:
name: ${{ matrix.config.name }} ${{ matrix.binaries }}
runs-on: ${{ matrix.config.os }}
env:
COMPCXX: ${{ matrix.config.compiler }}
COMP: ${{ matrix.config.comp }}
EXT: ${{ matrix.config.ext }}
NAME: ${{ matrix.config.simple_name }}
BINARY: ${{ matrix.binaries }}
SDE: ${{ matrix.config.sde }}
strategy:
fail-fast: false
matrix: ${{ fromJson(inputs.matrix) }}
defaults:
run:
working-directory: src
shell: ${{ matrix.config.shell }}
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Install fixed GCC on Linux
if: runner.os == 'Linux'
uses: egor-tensin/setup-gcc@eaa888eb19115a521fa72b65cd94fe1f25bbcaac # @v1.3
with:
version: 11
- name: Setup msys and install required packages
if: runner.os == 'Windows'
uses: msys2/setup-msys2@v2
with:
msystem: ${{ matrix.config.msys_sys }}
install: mingw-w64-${{ matrix.config.msys_env }} make git zip
- name: Download SDE package
if: runner.os == 'Linux' || runner.os == 'Windows'
uses: petarpetrovt/setup-sde@91a1a03434384e064706634125a15f7446d2aafb # @v2.3
with:
environmentVariableName: SDE_DIR
sdeVersion: 9.27.0
- name: Download the used network from the fishtest framework
run: make net
- name: Check compiler
run: $COMPCXX -v
- name: Test help target
run: make help
- name: Check git
run: git --version
- name: Check compiler
run: $COMPCXX -v
- name: Show compiler cpu info
run: |
if [[ "$COMPCXX" == clang* ]]; then
$COMPCXX -E - -march=native -###
else
$COMPCXX -Q -march=native --help=target
fi
# x86-64 with newer extensions tests
- name: Compile ${{ matrix.config.binaries }} build
run: |
make clean
make -j4 profile-build ARCH=$BINARY COMP=$COMP WINE_PATH="$SDE"
make strip ARCH=$BINARY COMP=$COMP
WINE_PATH="$SDE" ../tests/signature.sh $benchref
mv ./stockfish$EXT ../stockfish-$NAME-$BINARY$EXT
- name: Remove non src files
run: git clean -fx
- name: Upload artifact for (pre)-release
uses: actions/upload-artifact@v4
with:
name: ${{ matrix.config.simple_name }} ${{ matrix.binaries }}
path: |
.
!.git
!.output

View File

@@ -1,43 +0,0 @@
# This workflow will play games with a debug enabled SF using the PR
name: Games
on:
workflow_call:
jobs:
Matetrack:
name: Games
runs-on: ubuntu-22.04
steps:
- name: Checkout SF repo
uses: actions/checkout@v4
with:
ref: ${{ github.event.pull_request.head.sha }}
path: Stockfish
persist-credentials: false
- name: build debug enabled version of SF
working-directory: Stockfish/src
run: make -j build debug=yes
- name: Checkout fastchess repo
uses: actions/checkout@v4
with:
repository: Disservin/fastchess
path: fastchess
ref: 894616028492ae6114835195f14a899f6fa237d3
persist-credentials: false
- name: fastchess build
working-directory: fastchess
run: make -j
- name: Run games
working-directory: fastchess
run: |
./fastchess -rounds 4 -games 2 -repeat -concurrency 4 -openings file=app/tests/data/openings.epd format=epd order=random -srand $RANDOM\
-engine name=sf1 cmd=/home/runner/work/Stockfish/Stockfish/Stockfish/src/stockfish\
-engine name=sf2 cmd=/home/runner/work/Stockfish/Stockfish/Stockfish/src/stockfish\
-ratinginterval 1 -report penta=true -each proto=uci tc=4+0.04 -log file=fast.log | tee fast.out
cat fast.log
! grep "Assertion" fast.log > /dev/null
! grep "disconnect" fast.out > /dev/null

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@@ -1,49 +0,0 @@
name: IWYU
on:
workflow_call:
jobs:
Analyzers:
name: Check includes
runs-on: ubuntu-22.04
defaults:
run:
working-directory: Stockfish/src
shell: bash
steps:
- name: Checkout Stockfish
uses: actions/checkout@v4
with:
path: Stockfish
persist-credentials: false
- name: Checkout include-what-you-use
uses: actions/checkout@v4
with:
repository: include-what-you-use/include-what-you-use
ref: f25caa280dc3277c4086ec345ad279a2463fea0f
path: include-what-you-use
persist-credentials: false
- name: Download required linux packages
run: |
sudo add-apt-repository 'deb http://apt.llvm.org/jammy/ llvm-toolchain-jammy-17 main'
wget -O - https://apt.llvm.org/llvm-snapshot.gpg.key | sudo apt-key add -
sudo apt update
sudo apt install -y libclang-17-dev clang-17 libc++-17-dev
- name: Set up include-what-you-use
run: |
mkdir build && cd build
cmake -G "Unix Makefiles" -DCMAKE_PREFIX_PATH="/usr/lib/llvm-17" ..
sudo make install
working-directory: include-what-you-use
- name: Check include-what-you-use
run: include-what-you-use --version
- name: Check includes
run: >
make analyze
COMP=clang
CXX=include-what-you-use
CXXFLAGS="-stdlib=libc++ -Xiwyu --comment_style=long -Xiwyu --mapping='${{ github.workspace }}/Stockfish/.github/ci/libcxx17.imp' -Xiwyu --error"

View File

@@ -1,71 +0,0 @@
# This workflow will run matetrack on the PR
name: Matetrack
on:
workflow_call:
jobs:
Matetrack:
name: Matetrack
runs-on: ubuntu-22.04
steps:
- name: Checkout SF repo
uses: actions/checkout@v4
with:
ref: ${{ github.event.pull_request.head.sha }}
path: Stockfish
persist-credentials: false
- name: build SF
working-directory: Stockfish/src
run: make -j profile-build
- name: Checkout matetrack repo
uses: actions/checkout@v4
with:
repository: vondele/matetrack
path: matetrack
ref: 4f8a80860ed8f3607f05a9195df8b40203bdc360
persist-credentials: false
- name: matetrack install deps
working-directory: matetrack
run: pip install -r requirements.txt
- name: cache syzygy
id: cache-syzygy
uses: actions/cache@v4
with:
path: |
matetrack/3-4-5-wdl/
matetrack/3-4-5-dtz/
key: key-syzygy
- name: download syzygy 3-4-5 if needed
working-directory: matetrack
if: steps.cache-syzygy.outputs.cache-hit != 'true'
run: |
wget --no-verbose -r -nH --cut-dirs=2 --no-parent --reject="index.html*" -e robots=off https://tablebase.lichess.ovh/tables/standard/3-4-5-wdl/
wget --no-verbose -r -nH --cut-dirs=2 --no-parent --reject="index.html*" -e robots=off https://tablebase.lichess.ovh/tables/standard/3-4-5-dtz/
- name: Run matetrack
working-directory: matetrack
run: |
python matecheck.py --syzygyPath 3-4-5-wdl/:3-4-5-dtz/ --engine /home/runner/work/Stockfish/Stockfish/Stockfish/src/stockfish --epdFile mates2000.epd --nodes 100000 | tee matecheckout.out
! grep "issues were detected" matecheckout.out > /dev/null
- name: Run matetrack with --syzygy50MoveRule false
working-directory: matetrack
run: |
grep 5men cursed.epd > cursed5.epd
python matecheck.py --syzygyPath 3-4-5-wdl/:3-4-5-dtz/ --engine /home/runner/work/Stockfish/Stockfish/Stockfish/src/stockfish --epdFile cursed5.epd --nodes 100000 --syzygy50MoveRule false | tee matecheckcursed.out
! grep "issues were detected" matecheckcursed.out > /dev/null
- name: Verify mate and TB win count for matecheckcursed.out
working-directory: matetrack
run: |
mates=$(grep "Found mates:" matecheckcursed.out | awk '{print $3}')
tbwins=$(grep "Found TB wins:" matecheckcursed.out | awk '{print $4}')
if [ $(($mates + $tbwins)) -ne 32 ]; then
echo "Sum of mates and TB wins is not 32 in matecheckcursed.out" >&2
exit 1
fi

View File

@@ -1,87 +0,0 @@
name: Sanitizers
on:
workflow_call:
jobs:
Test-under-sanitizers:
name: ${{ matrix.sanitizers.name }}
runs-on: ${{ matrix.config.os }}
env:
COMPCXX: ${{ matrix.config.compiler }}
COMP: ${{ matrix.config.comp }}
CXXFLAGS: "-Werror"
strategy:
fail-fast: false
matrix:
config:
- name: Ubuntu 22.04 GCC
os: ubuntu-22.04
compiler: g++
comp: gcc
shell: bash
sanitizers:
- name: Run with thread sanitizer
make_option: sanitize=thread
cxx_extra_flags: ""
instrumented_option: sanitizer-thread
- name: Run with UB sanitizer
make_option: sanitize=undefined
cxx_extra_flags: ""
instrumented_option: sanitizer-undefined
- name: Run under valgrind
make_option: ""
cxx_extra_flags: ""
instrumented_option: valgrind
- name: Run under valgrind-thread
make_option: ""
cxx_extra_flags: ""
instrumented_option: valgrind-thread
- name: Run non-instrumented
make_option: ""
cxx_extra_flags: ""
instrumented_option: none
- name: Run with glibcxx assertions
make_option: ""
cxx_extra_flags: -D_GLIBCXX_ASSERTIONS
instrumented_option: non
defaults:
run:
working-directory: src
shell: ${{ matrix.config.shell }}
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Download required linux packages
run: |
sudo apt update
sudo apt install expect valgrind g++-multilib
- name: Download the used network from the fishtest framework
run: make net
- name: Check compiler
run: $COMPCXX -v
- name: Test help target
run: make help
- name: Check git
run: git --version
# Since Linux Kernel 6.5 we are getting false positives from the ci,
# lower the ALSR entropy to disable ALSR, which works as a temporary workaround.
# https://github.com/google/sanitizers/issues/1716
# https://bugs.launchpad.net/ubuntu/+source/linux/+bug/2056762
- name: Lower ALSR entropy
run: sudo sysctl -w vm.mmap_rnd_bits=28
# Sanitizers
- name: ${{ matrix.sanitizers.name }}
run: |
export CXXFLAGS="-O1 -fno-inline ${{ matrix.sanitizers.cxx_extra_flags }}"
make clean
make -j4 ARCH=x86-64-sse41-popcnt ${{ matrix.sanitizers.make_option }} debug=yes optimize=no build > /dev/null
python3 ../tests/instrumented.py --${{ matrix.sanitizers.instrumented_option }} ./stockfish

View File

@@ -1,122 +0,0 @@
name: Stockfish
on:
push:
tags:
- "*"
branches:
- master
- tools
- github_ci
pull_request:
branches:
- master
- tools
jobs:
Prerelease:
if: github.repository == 'official-stockfish/Stockfish' && (github.ref == 'refs/heads/master' || (startsWith(github.ref_name, 'sf_') && github.ref_type == 'tag'))
runs-on: ubuntu-latest
permissions:
contents: write # For deleting/creating a prerelease
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
# returns null if no pre-release exists
- name: Get Commit SHA of Latest Pre-release
run: |
# Install required packages
sudo apt-get update
sudo apt-get install -y curl jq
echo "COMMIT_SHA_TAG=$(jq -r 'map(select(.prerelease)) | first | .tag_name' <<< $(curl -s https://api.github.com/repos/${{ github.repository_owner }}/Stockfish/releases))" >> $GITHUB_ENV
# delete old previous pre-release and tag
- run: gh release delete ${{ env.COMMIT_SHA_TAG }} --cleanup-tag
if: env.COMMIT_SHA_TAG != 'null'
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Make sure that an old ci that still runs on master doesn't recreate a prerelease
- name: Check Pullable Commits
id: check_commits
run: |
git fetch
CHANGES=$(git rev-list HEAD..origin/master --count)
echo "CHANGES=$CHANGES" >> $GITHUB_ENV
- name: Get last commit SHA
id: last_commit
run: echo "COMMIT_SHA=$(git rev-parse HEAD | cut -c 1-8)" >> $GITHUB_ENV
- name: Get commit date
id: commit_date
run: echo "COMMIT_DATE=$(git show -s --date=format:'%Y%m%d' --format=%cd HEAD)" >> $GITHUB_ENV
# Create a new pre-release, the other upload_binaries.yml will upload the binaries
# to this pre-release.
- name: Create Prerelease
if: github.ref_name == 'master' && env.CHANGES == '0'
uses: softprops/action-gh-release@4634c16e79c963813287e889244c50009e7f0981
with:
name: Stockfish dev-${{ env.COMMIT_DATE }}-${{ env.COMMIT_SHA }}
tag_name: stockfish-dev-${{ env.COMMIT_DATE }}-${{ env.COMMIT_SHA }}
prerelease: true
Matrix:
runs-on: ubuntu-latest
outputs:
matrix: ${{ steps.set-matrix.outputs.matrix }}
arm_matrix: ${{ steps.set-arm-matrix.outputs.arm_matrix }}
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- id: set-matrix
run: |
TASKS=$(echo $(cat .github/ci/matrix.json) )
echo "MATRIX=$TASKS" >> $GITHUB_OUTPUT
- id: set-arm-matrix
run: |
TASKS_ARM=$(echo $(cat .github/ci/arm_matrix.json) )
echo "ARM_MATRIX=$TASKS_ARM" >> $GITHUB_OUTPUT
Compilation:
needs: [Matrix]
uses: ./.github/workflows/compilation.yml
with:
matrix: ${{ needs.Matrix.outputs.matrix }}
ARMCompilation:
needs: [Matrix]
uses: ./.github/workflows/arm_compilation.yml
with:
matrix: ${{ needs.Matrix.outputs.arm_matrix }}
IWYU:
uses: ./.github/workflows/iwyu.yml
Sanitizers:
uses: ./.github/workflows/sanitizers.yml
Tests:
uses: ./.github/workflows/tests.yml
Matetrack:
uses: ./.github/workflows/matetrack.yml
Games:
uses: ./.github/workflows/games.yml
Binaries:
if: github.repository == 'official-stockfish/Stockfish'
needs: [Matrix, Prerelease, Compilation]
uses: ./.github/workflows/upload_binaries.yml
with:
matrix: ${{ needs.Matrix.outputs.matrix }}
permissions:
contents: write # For deleting/creating a (pre)release
secrets:
token: ${{ secrets.GITHUB_TOKEN }}
ARM_Binaries:
if: github.repository == 'official-stockfish/Stockfish'
needs: [Matrix, Prerelease, ARMCompilation]
uses: ./.github/workflows/upload_binaries.yml
with:
matrix: ${{ needs.Matrix.outputs.arm_matrix }}
permissions:
contents: write # For deleting/creating a (pre)release
secrets:
token: ${{ secrets.GITHUB_TOKEN }}

View File

@@ -1,379 +0,0 @@
name: Tests
on:
workflow_call:
jobs:
Test-Targets:
name: ${{ matrix.config.name }}
runs-on: ${{ matrix.config.os }}
env:
COMPCXX: ${{ matrix.config.compiler }}
COMP: ${{ matrix.config.comp }}
CXXFLAGS: "-Werror"
strategy:
fail-fast: false
matrix:
config:
- name: Ubuntu 22.04 GCC
os: ubuntu-22.04
compiler: g++
comp: gcc
run_32bit_tests: true
run_64bit_tests: true
shell: bash
- name: Ubuntu 22.04 Clang
os: ubuntu-22.04
compiler: clang++
comp: clang
run_32bit_tests: true
run_64bit_tests: true
shell: bash
- name: Android NDK aarch64
os: ubuntu-22.04
compiler: aarch64-linux-android29-clang++
comp: ndk
run_armv8_tests: true
shell: bash
- name: Android NDK arm
os: ubuntu-22.04
compiler: armv7a-linux-androideabi29-clang++
comp: ndk
run_armv7_tests: true
shell: bash
# Currently segfaults in the CI unrelated to a Stockfish change.
# - name: Linux GCC riscv64
# os: ubuntu-22.04
# compiler: g++
# comp: gcc
# run_riscv64_tests: true
# base_image: "riscv64/alpine:edge"
# platform: linux/riscv64
# shell: bash
- name: Linux GCC ppc64
os: ubuntu-22.04
compiler: g++
comp: gcc
run_ppc64_tests: true
base_image: "ppc64le/alpine:latest"
platform: linux/ppc64le
shell: bash
- name: MacOS 13 Apple Clang
os: macos-13
compiler: clang++
comp: clang
run_64bit_tests: true
shell: bash
- name: MacOS 14 Apple Clang M1
os: macos-14
compiler: clang++
comp: clang
run_64bit_tests: false
run_m1_tests: true
shell: bash
- name: MacOS 13 GCC 11
os: macos-13
compiler: g++-11
comp: gcc
run_64bit_tests: true
shell: bash
- name: Windows 2022 Mingw-w64 GCC x86_64
os: windows-2022
compiler: g++
comp: mingw
run_64bit_tests: true
msys_sys: mingw64
msys_env: x86_64-gcc
shell: msys2 {0}
- name: Windows 2022 Mingw-w64 GCC i686
os: windows-2022
compiler: g++
comp: mingw
run_32bit_tests: true
msys_sys: mingw32
msys_env: i686-gcc
shell: msys2 {0}
- name: Windows 2022 Mingw-w64 Clang x86_64
os: windows-2022
compiler: clang++
comp: clang
run_64bit_tests: true
msys_sys: clang64
msys_env: clang-x86_64-clang
shell: msys2 {0}
- name: Windows 11 Mingw-w64 Clang arm64
os: windows-11-arm
compiler: clang++
comp: clang
run_armv8_tests: true
msys_sys: clangarm64
msys_env: clang-aarch64-clang
shell: msys2 {0}
defaults:
run:
working-directory: src
shell: ${{ matrix.config.shell }}
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0
persist-credentials: false
- name: Download required linux packages
if: runner.os == 'Linux'
run: |
sudo apt update
sudo apt install expect valgrind g++-multilib qemu-user-static
- name: Install NDK
if: runner.os == 'Linux'
run: |
if [ $COMP == ndk ]; then
NDKV="27.2.12479018"
ANDROID_ROOT=/usr/local/lib/android
ANDROID_SDK_ROOT=$ANDROID_ROOT/sdk
SDKMANAGER=$ANDROID_SDK_ROOT/cmdline-tools/latest/bin/sdkmanager
echo "y" | $SDKMANAGER "ndk;$NDKV"
ANDROID_NDK_ROOT=$ANDROID_SDK_ROOT/ndk/$NDKV
ANDROID_NDK_BIN=$ANDROID_NDK_ROOT/toolchains/llvm/prebuilt/linux-x86_64/bin
echo "ANDROID_NDK_BIN=$ANDROID_NDK_BIN" >> $GITHUB_ENV
fi
- name: Set up QEMU
if: matrix.config.base_image
uses: docker/setup-qemu-action@v3
- name: Set up Docker Buildx
if: matrix.config.base_image
uses: docker/setup-buildx-action@v3
- name: Build Docker container
if: matrix.config.base_image
run: |
docker buildx build --platform ${{ matrix.config.platform }} --load -t sf_builder - << EOF
FROM ${{ matrix.config.base_image }}
WORKDIR /app
RUN apk update && apk add make g++
CMD ["sh", "src/script.sh"]
EOF
- name: Download required macOS packages
if: runner.os == 'macOS'
run: brew install coreutils gcc@11
- name: Setup msys and install required packages
if: runner.os == 'Windows'
uses: msys2/setup-msys2@v2
with:
msystem: ${{ matrix.config.msys_sys }}
install: mingw-w64-${{ matrix.config.msys_env }} make git expect
- name: Download the used network from the fishtest framework
run: make net
- name: Extract the bench number from the commit history
run: |
for hash in $(git rev-list -100 HEAD); do
benchref=$(git show -s $hash | tac | grep -m 1 -o -x '[[:space:]]*\b[Bb]ench[ :]\+[1-9][0-9]\{5,7\}\b[[:space:]]*' | sed 's/[^0-9]//g') && break || true
done
[[ -n "$benchref" ]] && echo "benchref=$benchref" >> $GITHUB_ENV && echo "From commit: $hash" && echo "Reference bench: $benchref" || echo "No bench found"
- name: Check compiler
run: |
if [ -z "${{ matrix.config.base_image }}" ]; then
if [ $COMP == ndk ]; then
export PATH=${{ env.ANDROID_NDK_BIN }}:$PATH
fi
$COMPCXX -v
else
echo "$COMPCXX -v" > script.sh
docker run --rm --platform ${{ matrix.config.platform }} -v ${{ github.workspace }}:/app sf_builder
fi
- name: Test help target
run: make help
- name: Check git
run: git --version
# x86-32 tests
- name: Test debug x86-32 build
if: matrix.config.run_32bit_tests
run: |
export CXXFLAGS="-Werror -D_GLIBCXX_DEBUG"
make clean
make -j4 ARCH=x86-32 optimize=no debug=yes build
../tests/signature.sh $benchref
- name: Test x86-32 build
if: matrix.config.run_32bit_tests
run: |
make clean
make -j4 ARCH=x86-32 build
../tests/signature.sh $benchref
- name: Test x86-32-sse41-popcnt build
if: matrix.config.run_32bit_tests
run: |
make clean
make -j4 ARCH=x86-32-sse41-popcnt build
../tests/signature.sh $benchref
- name: Test x86-32-sse2 build
if: matrix.config.run_32bit_tests
run: |
make clean
make -j4 ARCH=x86-32-sse2 build
../tests/signature.sh $benchref
- name: Test general-32 build
if: matrix.config.run_32bit_tests
run: |
make clean
make -j4 ARCH=general-32 build
../tests/signature.sh $benchref
# x86-64 tests
- name: Test debug x86-64-avx2 build
if: matrix.config.run_64bit_tests
run: |
export CXXFLAGS="-Werror -D_GLIBCXX_DEBUG"
make clean
make -j4 ARCH=x86-64-avx2 optimize=no debug=yes build
../tests/signature.sh $benchref
- name: Test x86-64-bmi2 build
if: matrix.config.run_64bit_tests
run: |
make clean
make -j4 ARCH=x86-64-bmi2 build
../tests/signature.sh $benchref
- name: Test x86-64-avx2 build
if: matrix.config.run_64bit_tests
run: |
make clean
make -j4 ARCH=x86-64-avx2 build
../tests/signature.sh $benchref
# Test a deprecated arch
- name: Test x86-64-modern build
if: matrix.config.run_64bit_tests
run: |
make clean
make -j4 ARCH=x86-64-modern build
../tests/signature.sh $benchref
- name: Test x86-64-sse41-popcnt build
if: matrix.config.run_64bit_tests
run: |
make clean
make -j4 ARCH=x86-64-sse41-popcnt build
../tests/signature.sh $benchref
- name: Test x86-64-ssse3 build
if: matrix.config.run_64bit_tests
run: |
make clean
make -j4 ARCH=x86-64-ssse3 build
../tests/signature.sh $benchref
- name: Test x86-64-sse3-popcnt build
if: matrix.config.run_64bit_tests
run: |
make clean
make -j4 ARCH=x86-64-sse3-popcnt build
../tests/signature.sh $benchref
- name: Test x86-64 build
if: matrix.config.run_64bit_tests
run: |
make clean
make -j4 ARCH=x86-64 build
../tests/signature.sh $benchref
- name: Test general-64 build
if: matrix.config.run_64bit_tests
run: |
make clean
make -j4 ARCH=general-64 build
../tests/signature.sh $benchref
- name: Test apple-silicon build
if: matrix.config.run_m1_tests
run: |
make clean
make -j4 ARCH=apple-silicon build
../tests/signature.sh $benchref
# armv8 tests
- name: Test armv8 build
if: matrix.config.run_armv8_tests
run: |
if [ $COMP == ndk ]; then
export PATH=${{ env.ANDROID_NDK_BIN }}:$PATH
export LDFLAGS="-static -Wno-unused-command-line-argument"
fi
make clean
make -j4 ARCH=armv8 build
../tests/signature.sh $benchref
- name: Test armv8-dotprod build
if: matrix.config.run_armv8_tests
run: |
if [ $COMP == ndk ]; then
export PATH=${{ env.ANDROID_NDK_BIN }}:$PATH
export LDFLAGS="-static -Wno-unused-command-line-argument"
fi
make clean
make -j4 ARCH=armv8-dotprod build
../tests/signature.sh $benchref
# armv7 tests
- name: Test armv7 build
if: matrix.config.run_armv7_tests
run: |
export PATH=${{ env.ANDROID_NDK_BIN }}:$PATH
export LDFLAGS="-static -Wno-unused-command-line-argument"
make clean
make -j4 ARCH=armv7 build
../tests/signature.sh $benchref
- name: Test armv7-neon build
if: matrix.config.run_armv7_tests
run: |
export PATH=${{ env.ANDROID_NDK_BIN }}:$PATH
export LDFLAGS="-static -Wno-unused-command-line-argument"
make clean
make -j4 ARCH=armv7-neon build
../tests/signature.sh $benchref
# riscv64 tests
- name: Test riscv64 build
if: matrix.config.run_riscv64_tests
run: |
echo "cd src && export LDFLAGS='-static' && make clean && make -j4 ARCH=riscv64 build" > script.sh
docker run --rm --platform ${{ matrix.config.platform }} -v ${{ github.workspace }}:/app sf_builder
../tests/signature.sh $benchref
# ppc64 tests
- name: Test ppc64 build
if: matrix.config.run_ppc64_tests
run: |
echo "cd src && export LDFLAGS='-static' && make clean && make -j4 ARCH=ppc-64 build" > script.sh
docker run --rm --platform ${{ matrix.config.platform }} -v ${{ github.workspace }}:/app sf_builder
../tests/signature.sh $benchref
# Other tests
- name: Check perft and search reproducibility
if: matrix.config.run_64bit_tests
run: |
make clean
make -j4 ARCH=x86-64-avx2 build
../tests/perft.sh
../tests/reprosearch.sh

View File

@@ -1,114 +0,0 @@
name: Upload Binaries
on:
workflow_call:
inputs:
matrix:
type: string
required: true
secrets:
token:
required: true
jobs:
Artifacts:
name: ${{ matrix.config.name }} ${{ matrix.binaries }}
runs-on: ${{ matrix.config.os }}
env:
COMPCXX: ${{ matrix.config.compiler }}
COMP: ${{ matrix.config.comp }}
EXT: ${{ matrix.config.ext }}
NAME: ${{ matrix.config.simple_name }}
BINARY: ${{ matrix.binaries }}
SDE: ${{ matrix.config.sde }}
strategy:
fail-fast: false
matrix: ${{ fromJson(inputs.matrix) }}
defaults:
run:
shell: ${{ matrix.config.shell }}
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Download artifact from compilation
uses: actions/download-artifact@v4
with:
name: ${{ matrix.config.simple_name }} ${{ matrix.binaries }}
path: ${{ matrix.config.simple_name }} ${{ matrix.binaries }}
- name: Setup msys and install required packages
if: runner.os == 'Windows'
uses: msys2/setup-msys2@v2
with:
msystem: ${{ matrix.config.msys_sys }}
install: mingw-w64-${{ matrix.config.msys_env }} make git zip
- name: Create Package
run: |
mkdir stockfish
- name: Download wiki
run: |
git clone https://github.com/official-stockfish/Stockfish.wiki.git wiki
rm -rf wiki/.git
mv wiki stockfish/
- name: Copy files
run: |
mv "${{ matrix.config.simple_name }} ${{ matrix.binaries }}" stockfish-workflow
cd stockfish-workflow
cp -r src ../stockfish/
cp -r scripts ../stockfish/
cp stockfish-$NAME-$BINARY$EXT ../stockfish/
cp "Top CPU Contributors.txt" ../stockfish/
cp Copying.txt ../stockfish/
cp AUTHORS ../stockfish/
cp CITATION.cff ../stockfish/
cp README.md ../stockfish/
cp CONTRIBUTING.md ../stockfish/
- name: Create tar
if: runner.os != 'Windows'
run: |
chmod +x ./stockfish/stockfish-$NAME-$BINARY$EXT
tar -cvf stockfish-$NAME-$BINARY.tar stockfish
- name: Create zip
if: runner.os == 'Windows'
run: |
zip -r stockfish-$NAME-$BINARY.zip stockfish
- name: Release
if: startsWith(github.ref_name, 'sf_') && github.ref_type == 'tag'
uses: softprops/action-gh-release@4634c16e79c963813287e889244c50009e7f0981
with:
files: stockfish-${{ matrix.config.simple_name }}-${{ matrix.binaries }}.${{ matrix.config.archive_ext }}
token: ${{ secrets.token }}
- name: Get last commit sha
id: last_commit
run: echo "COMMIT_SHA=$(git rev-parse HEAD | cut -c 1-8)" >> $GITHUB_ENV
- name: Get commit date
id: commit_date
run: echo "COMMIT_DATE=$(git show -s --date=format:'%Y%m%d' --format=%cd HEAD)" >> $GITHUB_ENV
# Make sure that an old ci that still runs on master doesn't recreate a prerelease
- name: Check Pullable Commits
id: check_commits
run: |
git fetch
CHANGES=$(git rev-list HEAD..origin/master --count)
echo "CHANGES=$CHANGES" >> $GITHUB_ENV
- name: Prerelease
if: github.ref_name == 'master' && env.CHANGES == '0'
continue-on-error: true
uses: softprops/action-gh-release@4634c16e79c963813287e889244c50009e7f0981
with:
name: Stockfish dev-${{ env.COMMIT_DATE }}-${{ env.COMMIT_SHA }}
tag_name: stockfish-dev-${{ env.COMMIT_DATE }}-${{ env.COMMIT_SHA }}
prerelease: true
files: stockfish-${{ matrix.config.simple_name }}-${{ matrix.binaries }}.${{ matrix.config.archive_ext }}
token: ${{ secrets.token }}

17
.gitignore vendored
View File

@@ -1,17 +0,0 @@
# Files from build
**/*.o
**/*.s
src/.depend
# Built binary
src/stockfish*
src/-lstdc++.res
# Neural network for the NNUE evaluation
**/*.nnue
# Files generated by the instrumented tests
tsan.supp
__pycache__/
tests/syzygy
tests/bench_tmp.epd

80
.travis.yml Normal file
View File

@@ -0,0 +1,80 @@
language: cpp
dist: bionic
matrix:
include:
- os: linux
compiler: gcc
addons:
apt:
packages: ['g++-8', 'g++-8-multilib', 'g++-multilib', 'valgrind', 'expect', 'curl']
env:
- COMPILER=g++-8
- COMP=gcc
- os: linux
compiler: clang
addons:
apt:
packages: ['clang-10', 'llvm-10-dev', 'g++-multilib', 'valgrind', 'expect', 'curl']
env:
- COMPILER=clang++-10
- COMP=clang
- os: osx
osx_image: xcode12
compiler: gcc
env:
- COMPILER=g++
- COMP=gcc
- os: osx
osx_image: xcode12
compiler: clang
env:
- COMPILER=clang++
- COMP=clang
branches:
only:
- master
before_script:
- cd src
script:
# Obtain bench reference from git log
- git log HEAD | grep "\b[Bb]ench[ :]\+[0-9]\{7\}" | head -n 1 | sed "s/[^0-9]*\([0-9]*\).*/\1/g" > git_sig
- export benchref=$(cat git_sig)
- echo "Reference bench:" $benchref
#
# Compiler version string
- $COMPILER -v
#
# Verify bench number against various builds
- export CXXFLAGS="-Werror -D_GLIBCXX_DEBUG"
- make clean && make -j2 ARCH=x86-64 optimize=no debug=yes build && ../tests/signature.sh $benchref
- if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then make clean && make -j2 ARCH=x86-32 optimize=no debug=yes build && ../tests/signature.sh $benchref; fi
- if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then make clean && make -j2 ARCH=x86-32 build && ../tests/signature.sh $benchref; fi
#
# Check perft and reproducible search
- export CXXFLAGS="-Werror"
- make clean && make -j2 ARCH=x86-64 build
- ../tests/perft.sh
- ../tests/reprosearch.sh
#
# Valgrind
#
- export CXXFLAGS="-O1 -fno-inline"
- if [ -x "$(command -v valgrind )" ]; then make clean && make -j2 ARCH=x86-64 debug=yes optimize=no build > /dev/null && ../tests/instrumented.sh --valgrind; fi
- if [ -x "$(command -v valgrind )" ]; then ../tests/instrumented.sh --valgrind-thread; fi
#
# Sanitizer
#
- if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then make clean && make -j2 ARCH=x86-64 sanitize=undefined optimize=no debug=yes build > /dev/null && ../tests/instrumented.sh --sanitizer-undefined; fi
- if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then make clean && make -j2 ARCH=x86-64 sanitize=thread optimize=no debug=yes build > /dev/null && ../tests/instrumented.sh --sanitizer-thread; fi

129
AUTHORS
View File

@@ -1,146 +1,99 @@
# Founders of the Stockfish project and Fishtest infrastructure
# List of authors for Stockfish, as of August 4, 2020
# Founders of the Stockfish project and fishtest infrastructure
Tord Romstad (romstad)
Marco Costalba (mcostalba)
Joona Kiiski (zamar)
Gary Linscott (glinscott)
# Authors and inventors of NNUE, training, and NNUE port
# Authors and inventors of NNUE, training, NNUE port
Yu Nasu (ynasu87)
Motohiro Isozaki (yaneurao)
Hisayori Noda (nodchip)
# All other authors of Stockfish code (in alphabetical order)
# all other authors of the code in alphabetical order
Aditya (absimaldata)
Adrian Petrescu (apetresc)
Ahmed Kerimov (wcdbmv)
Ajith Chandy Jose (ajithcj)
Alain Savard (Rocky640)
Alayan Feh (Alayan-stk-2)
Alexander Kure
Alexander Pagel (Lolligerhans)
Alfredo Menezes (lonfom169)
Ali AlZhrani (Cooffe)
AliceRoselia
Andreas Jan van der Meulen (Andyson007)
Andreas Matthies (Matthies)
Andrei Vetrov (proukornew)
Andrew Grant (AndyGrant)
Andrey Neporada (nepal)
Andy Duplain
Antoine Champion (antoinechampion)
Aram Tumanian (atumanian)
Arjun Temurnikar
Artem Solopiy (EntityFX)
Auguste Pop
Balazs Szilagyi
Balint Pfliegel
Baptiste Rech (breatn)
Ben Chaney (Chaneybenjamini)
Ben Koshy (BKSpurgeon)
Bill Henry (VoyagerOne)
Bojun Guo (noobpwnftw, Nooby)
borg323
Boštjan Mejak (PedanticHacker)
braich
Brian Sheppard (SapphireBrand, briansheppard-toast)
Bruno de Melo Costa (BM123499)
Bruno Pellanda (pellanda)
Bryan Cross (crossbr)
candirufish
Carlos Esparza Sánchez (ces42)
Chess13234
Chris Bao (sscg13)
Chris Cain (ceebo)
Ciekce
clefrks
Clemens L. (rn5f107s2)
Cody Ho (aesrentai)
Dale Weiler (graphitemaster)
Dan Schmidt (dfannius)
Daniel Axtens (daxtens)
Daniel Dugovic (ddugovic)
Daniel Monroe (Ergodice)
Daniel Samek (DanSamek)
Dan Schmidt (dfannius)
Dariusz Orzechowski (dorzechowski)
David (dav1312)
Dariusz Orzechowski
David Zar
Daylen Yang (daylen)
Deshawn Mohan-Smith (GoldenRare)
Dieter Dobbelaere (ddobbelaere)
DiscanX
Dominik Schlösser (domschl)
double-beep
Douglas Matos Gomes (dsmsgms)
Dubslow
Eduardo Cáceres (eduherminio)
Eelco de Groot (KingDefender)
Ehsan Rashid (erashid)
Elvin Liu (solarlight2)
erbsenzaehler
Ernesto Gatti
evqsx
Linmiao Xu (linrock)
Fabian Beuke (madnight)
Fabian Fichter (ianfab)
Fanael Linithien (Fanael)
fanon
Fauzi Akram Dabat (fauzi2)
Fauzi Akram Dabat (FauziAkram)
Felix Wittmann
gamander
Gabriele Lombardo (gabe)
Gahtan Nahdi
Gary Heckman (gheckman)
George Sobala (gsobala)
gguliash
Giacomo Lorenzetti (G-Lorenz)
Gian-Carlo Pascutto (gcp)
Goh CJ (cj5716)
Gontran Lemaire (gonlem)
Goodkov Vasiliy Aleksandrovich (goodkov)
Gregor Cramer
GuardianRM
Guy Vreuls (gvreuls)
Günther Demetz (pb00067, pb00068)
Guy Vreuls (gvreuls)
Henri Wiechers
Hiraoka Takuya (HiraokaTakuya)
homoSapiensSapiens
Hongzhi Cheng
Ivan Ivec (IIvec)
Jacques B. (Timshel)
Jake Senne (w1wwwwww)
Jan Ondruš (hxim)
Jared Kish (Kurtbusch, kurt22i)
Jared Kish (Kurtbusch)
Jarrod Torriero (DU-jdto)
Jasper Shovelton (Beanie496)
Jean-Francois Romang (jromang)
Jean Gauthier (OuaisBla)
Jean-Francois Romang (jromang)
Jekaa
Jerry Donald Watson (jerrydonaldwatson)
jjoshua2
Jonathan Buladas Dumale (SFisGOD)
Jonathan Calovski (Mysseno)
Jonathan McDermid (jonathanmcdermid)
Jonathan Dumale (SFisGOD)
Joost VandeVondele (vondele)
Jörg Oster (joergoster)
Joseph Ellis (jhellis3)
Joseph R. Prostko
Jörg Oster (joergoster)
Julian Willemer (NightlyKing)
jundery
Justin Blanchard (UncombedCoconut)
Kelly Wilson
Ken Takusagawa
Kenneth Lee (kennethlee33)
Kian E (KJE-98)
kinderchocolate
Kiran Panditrao (Krgp)
Kirill Zaripov (kokodio)
Kojirion
Krisztián Peőcz
Krystian Kuzniarek (kuzkry)
Leonardo Ljubičić (ICCF World Champion)
Leonid Pechenik (lp--)
Li Ying (yl25946)
Liam Keegan (lkeegan)
Linmiao Xu (linrock)
Linus Arver (listx)
loco-loco
Lub van den Berg (ElbertoOne)
@@ -149,16 +102,10 @@ Lucas Braesch (lucasart)
Lyudmil Antonov (lantonov)
Maciej Żenczykowski (zenczykowski)
Malcolm Campbell (xoto10)
Mark Marosi (Mapika)
Mark Tenzer (31m059)
marotear
Mathias Parnaudeau (mparnaudeau)
Matt Ginsberg (mattginsberg)
Matthew Lai (matthewlai)
Matthew Sullivan (Matt14916)
Max A. (Disservin)
Maxim Masiutin (maximmasiutin)
Maxim Molchanov (Maxim)
Michael An (man)
Michael Byrne (MichaelB7)
Michael Chaly (Vizvezdenec)
@@ -167,94 +114,66 @@ Michael Whiteley (protonspring)
Michel Van den Bergh (vdbergh)
Miguel Lahoz (miguel-l)
Mikael Bäckman (mbootsector)
Mike Babigian (Farseer)
Mira
Miroslav Fontán (Hexik)
Moez Jellouli (MJZ1977)
Mohammed Li (tthsqe12)
Muzhen J (XInTheDark)
Nathan Rugg (nmrugg)
Nguyen Pham (nguyenpham)
Nicklas Persson (NicklasPersson)
Nick Pelling (nickpelling)
Nicklas Persson (NicklasPersson)
Niklas Fiekas (niklasf)
Nikolay Kostov (NikolayIT)
Nguyen Pham (nguyenpham)
Norman Schmidt (FireFather)
notruck
Nour Berakdar (Nonlinear)
Ofek Shochat (OfekShochat, ghostway)
Ondrej Mosnáček (WOnder93)
Ondřej Mišina (AndrovT)
Oskar Werkelin Ahlin
Ömer Faruk Tutkun (OmerFarukTutkun)
Pablo Vazquez
Panthee
Pascal Romaret
Pasquale Pigazzini (ppigazzini)
Patrick Jansen (mibere)
Peter Schneider (pschneider1968)
pellanda
Peter Zsifkovits (CoffeeOne)
PikaCat
Praveen Kumar Tummala (praveentml)
Prokop Randáček (ProkopRandacek)
Rahul Dsilva (silversolver1)
Ralph Stößer (Ralph Stoesser)
Raminder Singh
renouve
Reuven Peleg (R-Peleg)
Richard Lloyd (Richard-Lloyd)
Robert Nürnberg (robertnurnberg)
Reuven Peleg
Richard Lloyd
Rodrigo Exterckötter Tjäder
Rodrigo Roim (roim)
Ronald de Man (syzygy1, syzygy)
Ron Britvich (Britvich)
Ronald de Man (syzygy1, syzygy)
rqs
Rui Coelho (ruicoelhopedro)
Ryan Schmitt
Ryan Takker
Sami Kiminki (skiminki)
Sebastian Buchwald (UniQP)
Sergei Antonov (saproj)
Sergei Ivanov (svivanov72)
Sergio Vieri (sergiovieri)
sf-x
Shahin M. Shahin (peregrine)
Shane Booth (shane31)
Shawn Varghese (xXH4CKST3RXx)
Shawn Xu (xu-shawn)
Siad Daboul (Topologist)
Stefan Geschwentner (locutus2)
Stefano Cardanobile (Stefano80)
Stefano Di Martino (StefanoD)
Steinar Gunderson (sesse)
Stéphane Nicolet (snicolet)
Stephen Touset (stouset)
Syine Mineta (MinetaS)
Taras Vuk (TarasVuk)
Thanar2
thaspel
theo77186
TierynnB
Ting-Hsuan Huang (fffelix-huang)
Tobias Steinmann
Tomasz Sobczyk (Sopel97)
Tom Truscott
Tom Vijlbrief (tomtor)
Tomasz Sobczyk (Sopel97)
Torsten Franz (torfranz, tfranzer)
Torsten Hellwig (Torom)
Tracey Emery (basepr1me)
tttak
Unai Corzo (unaiic)
Uri Blass (uriblass)
Vince Negri (cuddlestmonkey)
Viren
Wencey Wang
windfishballad
xefoci7612
Xiang Wang (KatyushaScarlet)
zz4032
# Additionally, we acknowledge the authors and maintainers of fishtest,
# an amazing and essential framework for Stockfish development!
# an amazing and essential framework for the development of Stockfish!
#
# https://github.com/official-stockfish/fishtest/blob/master/AUTHORS
# https://github.com/glinscott/fishtest/blob/master/AUTHORS

View File

@@ -1,23 +0,0 @@
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: Stockfish
message: >-
Please cite this software using the metadata from this
file.
type: software
authors:
- name: The Stockfish developers (see AUTHORS file)
repository-code: 'https://github.com/official-stockfish/Stockfish'
url: 'https://stockfishchess.org/'
repository-artifact: 'https://stockfishchess.org/download/'
abstract: Stockfish is a free and strong UCI chess engine.
keywords:
- chess
- artificial intelligence (AI)
- tree search
- alpha-beta search
- neural networks (NN)
- efficiently updatable neural networks (NNUE)
license: GPL-3.0

View File

@@ -1,96 +0,0 @@
# Contributing to Stockfish
Welcome to the Stockfish project! We are excited that you are interested in
contributing. This document outlines the guidelines and steps to follow when
making contributions to Stockfish.
## Table of Contents
- [Building Stockfish](#building-stockfish)
- [Making Contributions](#making-contributions)
- [Reporting Issues](#reporting-issues)
- [Submitting Pull Requests](#submitting-pull-requests)
- [Code Style](#code-style)
- [Community and Communication](#community-and-communication)
- [License](#license)
## Building Stockfish
In case you do not have a C++ compiler installed, you can follow the
instructions from our wiki.
- [Ubuntu][ubuntu-compiling-link]
- [Windows][windows-compiling-link]
- [macOS][macos-compiling-link]
## Making Contributions
### Reporting Issues
If you find a bug, please open an issue on the
[issue tracker][issue-tracker-link]. Be sure to include relevant information
like your operating system, build environment, and a detailed description of the
problem.
_Please note that Stockfish's development is not focused on adding new features.
Thus any issue regarding missing features will potentially be closed without
further discussion._
### Submitting Pull Requests
- Functional changes need to be tested on fishtest. See
[Creating my First Test][creating-my-first-test] for more details.
The accompanying pull request should include a link to the test results and
the new bench.
- Non-functional changes (e.g. refactoring, code style, documentation) do not
need to be tested on fishtest, unless they might impact performance.
- Provide a clear and concise description of the changes in the pull request
description.
_First time contributors should add their name to [AUTHORS](./AUTHORS)._
_Stockfish's development is not focused on adding new features. Thus any pull
request introducing new features will potentially be closed without further
discussion._
## Code Style
Changes to Stockfish C++ code should respect our coding style defined by
[.clang-format](.clang-format). You can format your changes by running
`make format`. This requires clang-format version 20 to be installed on your system.
## Navigate
For experienced Git users who frequently use git blame, it is recommended to
configure the blame.ignoreRevsFile setting.
This setting is useful for excluding noisy formatting commits.
```bash
git config blame.ignoreRevsFile .git-blame-ignore-revs
```
## Community and Communication
- Join the [Stockfish discord][discord-link] to discuss ideas, issues, and
development.
- Participate in the [Stockfish GitHub discussions][discussions-link] for
broader conversations.
## License
By contributing to Stockfish, you agree that your contributions will be licensed
under the GNU General Public License v3.0. See [Copying.txt][copying-link] for
more details.
Thank you for contributing to Stockfish and helping us make it even better!
[copying-link]: https://github.com/official-stockfish/Stockfish/blob/master/Copying.txt
[discord-link]: https://discord.gg/GWDRS3kU6R
[discussions-link]: https://github.com/official-stockfish/Stockfish/discussions/new
[creating-my-first-test]: https://github.com/official-stockfish/fishtest/wiki/Creating-my-first-test#create-your-test
[issue-tracker-link]: https://github.com/official-stockfish/Stockfish/issues
[ubuntu-compiling-link]: https://github.com/official-stockfish/Stockfish/wiki/Developers#user-content-installing-a-compiler-1
[windows-compiling-link]: https://github.com/official-stockfish/Stockfish/wiki/Developers#user-content-installing-a-compiler
[macos-compiling-link]: https://github.com/official-stockfish/Stockfish/wiki/Developers#user-content-installing-a-compiler-2

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<div align="center">
[![Stockfish][stockfish128-logo]][website-link]
<h3>Stockfish</h3>
A free and strong UCI chess engine.
<br>
<strong>[Explore Stockfish docs »][wiki-link]</strong>
<br>
<br>
[Report bug][issue-link]
·
[Open a discussion][discussions-link]
·
[Discord][discord-link]
·
[Blog][website-blog-link]
[![Build][build-badge]][build-link]
[![License][license-badge]][license-link]
<br>
[![Release][release-badge]][release-link]
[![Commits][commits-badge]][commits-link]
<br>
[![Website][website-badge]][website-link]
[![Fishtest][fishtest-badge]][fishtest-link]
[![Discord][discord-badge]][discord-link]
</div>
## Overview
[Stockfish][website-link] is a **free and strong UCI chess engine** derived from
Glaurung 2.1 that analyzes chess positions and computes the optimal moves.
[![Build Status](https://travis-ci.org/official-stockfish/Stockfish.svg?branch=master)](https://travis-ci.org/official-stockfish/Stockfish)
[![Build Status](https://ci.appveyor.com/api/projects/status/github/official-stockfish/Stockfish?branch=master&svg=true)](https://ci.appveyor.com/project/mcostalba/stockfish/branch/master)
Stockfish **does not include a graphical user interface** (GUI) that is required
to display a chessboard and to make it easy to input moves. These GUIs are
developed independently from Stockfish and are available online. **Read the
documentation for your GUI** of choice for information about how to use
[Stockfish](https://stockfishchess.org) is a free, powerful UCI chess engine
derived from Glaurung 2.1. It features two evaluation functions, the classical
evaluation based on handcrafted terms, and the NNUE evaluation based on
efficiently updateable neural networks. The classical evaluation runs efficiently
on most 64bit CPU architectures, while the NNUE evaluation benefits strongly from the
vector intrinsics available on modern CPUs (avx2 or similar).
Stockfish is not a complete chess program and requires a
UCI-compatible GUI (e.g. XBoard with PolyGlot, Scid, Cute Chess, eboard, Arena,
Sigma Chess, Shredder, Chess Partner or Fritz) in order to be used comfortably.
Read the documentation for your GUI of choice for information about how to use
Stockfish with it.
See also the Stockfish [documentation][wiki-usage-link] for further usage help.
## Files
This distribution of Stockfish consists of the following files:
* [README.md][readme-link], the file you are currently reading.
* Readme.md, the file you are currently reading.
* [Copying.txt][license-link], a text file containing the GNU General Public
License version 3.
* Copying.txt, a text file containing the GNU General Public License version 3.
* [AUTHORS][authors-link], a text file with the list of authors for the project.
* src, a subdirectory containing the full source code, including a Makefile
that can be used to compile Stockfish on Unix-like systems.
* [src][src-link], a subdirectory containing the full source code, including a
Makefile that can be used to compile Stockfish on Unix-like systems.
To use the NNUE evaluation an additional data file with neural network parameters
needs to be downloaded. The filename for the default set can be found as the default
value of the `EvalFile` UCI option, with the format
`nn-[SHA256 first 12 digits].nnue` (e.g. nn-c157e0a5755b.nnue). This file can be downloaded from
```
https://tests.stockfishchess.org/api/nn/[filename]
```
replacing `[filename]` as needed.
* a file with the .nnue extension, storing the neural network for the NNUE
evaluation. Binary distributions will have this file embedded.
## Contributing
## UCI options
__See [Contributing Guide](CONTRIBUTING.md).__
Currently, Stockfish has the following UCI options:
* #### Threads
The number of CPU threads used for searching a position. For best performance, set
this equal to the number of CPU cores available.
* #### Hash
The size of the hash table in MB. It is recommended to set Hash after setting Threads.
* #### Ponder
Let Stockfish ponder its next move while the opponent is thinking.
* #### MultiPV
Output the N best lines (principal variations, PVs) when searching.
Leave at 1 for best performance.
* #### Use NNUE
Toggle between the NNUE and classical evaluation functions. If set to "true",
the network parameters must be availabe to load from file (see also EvalFile).
* #### EvalFile
The name of the file of the NNUE evaluation parameters. Depending on the GUI the
filename should include the full path to the folder/directory that contains the file.
* #### Contempt
A positive value for contempt favors middle game positions and avoids draws,
effective for the classical evaluation only.
* #### Analysis Contempt
By default, contempt is set to prefer the side to move. Set this option to "White"
or "Black" to analyse with contempt for that side, or "Off" to disable contempt.
* #### UCI_AnalyseMode
An option handled by your GUI.
* #### UCI_Chess960
An option handled by your GUI. If true, Stockfish will play Chess960.
* #### UCI_ShowWDL
If enabled, show approximate WDL statistics as part of the engine output.
These WDL numbers model expected game outcomes for a given evaluation and
game ply for engine self-play at fishtest LTC conditions (60+0.6s per game).
* #### UCI_LimitStrength
Enable weaker play aiming for an Elo rating as set by UCI_Elo. This option overrides Skill Level.
* #### UCI_Elo
If enabled by UCI_LimitStrength, aim for an engine strength of the given Elo.
This Elo rating has been calibrated at a time control of 60s+0.6s and anchored to CCRL 40/4.
* #### Skill Level
Lower the Skill Level in order to make Stockfish play weaker (see also UCI_LimitStrength).
Internally, MultiPV is enabled, and with a certain probability depending on the Skill Level a
weaker move will be played.
* #### SyzygyPath
Path to the folders/directories storing the Syzygy tablebase files. Multiple
directories are to be separated by ";" on Windows and by ":" on Unix-based
operating systems. Do not use spaces around the ";" or ":".
Example: `C:\tablebases\wdl345;C:\tablebases\wdl6;D:\tablebases\dtz345;D:\tablebases\dtz6`
It is recommended to store .rtbw files on an SSD. There is no loss in storing
the .rtbz files on a regular HD. It is recommended to verify all md5 checksums
of the downloaded tablebase files (`md5sum -c checksum.md5`) as corruption will
lead to engine crashes.
* #### SyzygyProbeDepth
Minimum remaining search depth for which a position is probed. Set this option
to a higher value to probe less agressively if you experience too much slowdown
(in terms of nps) due to TB probing.
* #### Syzygy50MoveRule
Disable to let fifty-move rule draws detected by Syzygy tablebase probes count
as wins or losses. This is useful for ICCF correspondence games.
* #### SyzygyProbeLimit
Limit Syzygy tablebase probing to positions with at most this many pieces left
(including kings and pawns).
* #### Move Overhead
Assume a time delay of x ms due to network and GUI overheads. This is useful to
avoid losses on time in those cases.
* #### Slow Mover
Lower values will make Stockfish take less time in games, higher values will
make it think longer.
* #### nodestime
Tells the engine to use nodes searched instead of wall time to account for
elapsed time. Useful for engine testing.
* #### Clear Hash
Clear the hash table.
* #### Debug Log File
Write all communication to and from the engine into a text file.
## classical and NNUE evaluation
Both approaches assign a value to a position that is used in alpha-beta (PVS) search
to find the best move. The classical evaluation computes this value as a function
of various chess concepts, handcrafted by experts, tested and tuned using fishtest.
The NNUE evaluation computes this value with a neural network based on basic
inputs (e.g. piece positions only). The network is optimized and trained
on the evalutions of millions of positions at moderate search depth.
The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward.
It can be evaluated efficiently on CPUs, and exploits the fact that only parts
of the neural network need to be updated after a typical chess move.
[The nodchip repository](https://github.com/nodchip/Stockfish) provides additional
tools to train and develop the NNUE networks.
On CPUs supporting modern vector instructions (avx2 and similar), the NNUE evaluation
results in stronger playing strength, even if the nodes per second computed by the engine
is somewhat lower (roughly 60% of nps is typical).
Note that the NNUE evaluation depends on the Stockfish binary and the network parameter
file (see EvalFile). Not every parameter file is compatible with a given Stockfish binary.
The default value of the EvalFile UCI option is the name of a network that is guaranteed
to be compatible with that binary.
## What to expect from Syzygybases?
If the engine is searching a position that is not in the tablebases (e.g.
a position with 8 pieces), it will access the tablebases during the search.
If the engine reports a very large score (typically 153.xx), this means
that it has found a winning line into a tablebase position.
If the engine is given a position to search that is in the tablebases, it
will use the tablebases at the beginning of the search to preselect all
good moves, i.e. all moves that preserve the win or preserve the draw while
taking into account the 50-move rule.
It will then perform a search only on those moves. **The engine will not move
immediately**, unless there is only a single good move. **The engine likely
will not report a mate score even if the position is known to be won.**
It is therefore clear that this behaviour is not identical to what one might
be used to with Nalimov tablebases. There are technical reasons for this
difference, the main technical reason being that Nalimov tablebases use the
DTM metric (distance-to-mate), while Syzygybases use a variation of the
DTZ metric (distance-to-zero, zero meaning any move that resets the 50-move
counter). This special metric is one of the reasons that Syzygybases are
more compact than Nalimov tablebases, while still storing all information
needed for optimal play and in addition being able to take into account
the 50-move rule.
## Large Pages
Stockfish supports large pages on Linux and Windows. Large pages make
the hash access more efficient, improving the engine speed, especially
on large hash sizes. Typical increases are 5..10% in terms of nps, but
speed increases up to 30% have been measured. The support is
automatic. Stockfish attempts to use large pages when available and
will fall back to regular memory allocation when this is not the case.
### Support on Linux
Large page support on Linux is obtained by the Linux kernel
transparent huge pages functionality. Typically, transparent huge pages
are already enabled and no configuration is needed.
### Support on Windows
The use of large pages requires "Lock Pages in Memory" privilege. See
[Enable the Lock Pages in Memory Option (Windows)](https://docs.microsoft.com/en-us/sql/database-engine/configure-windows/enable-the-lock-pages-in-memory-option-windows)
on how to enable this privilege. Logout/login may be needed
afterwards. Due to memory fragmentation, it may not always be
possible to allocate large pages even when enabled. A reboot
might alleviate this problem. To determine whether large pages
are in use, see the engine log.
## Compiling Stockfish yourself from the sources
Stockfish has support for 32 or 64-bit CPUs, certain hardware
instructions, big-endian machines such as Power PC, and other platforms.
On Unix-like systems, it should be easy to compile Stockfish
directly from the source code with the included Makefile in the folder
`src`. In general it is recommended to run `make help` to see a list of make
targets with corresponding descriptions.
```
cd src
make help
make build ARCH=x86-64-modern
```
When not using the Makefile to compile (for instance with Microsoft MSVC) you
need to manually set/unset some switches in the compiler command line; see
file *types.h* for a quick reference.
When reporting an issue or a bug, please tell us which version and
compiler you used to create your executable. These informations can
be found by typing the following commands in a console:
```
./stockfish
compiler
```
## Understanding the code base and participating in the project
Stockfish's improvement over the last couple of years has been a great
community effort. There are a few ways to help contribute to its growth.
### Donating hardware
Improving Stockfish requires a massive amount of testing. You can donate your
hardware resources by installing the [Fishtest Worker][worker-link] and viewing
the current tests on [Fishtest][fishtest-link].
Improving Stockfish requires a massive amount of testing. You can donate
your hardware resources by installing the [Fishtest Worker](https://github.com/glinscott/fishtest/wiki/Running-the-worker:-overview)
and view the current tests on [Fishtest](https://tests.stockfishchess.org/tests).
### Improving the code
In the [chessprogramming wiki][programming-link], many techniques used in
Stockfish are explained with a lot of background information.
The [section on Stockfish][programmingsf-link] describes many features
and techniques used by Stockfish. However, it is generic rather than
focused on Stockfish's precise implementation.
If you want to help improve the code, there are several valuable resources:
The engine testing is done on [Fishtest][fishtest-link].
If you want to help improve Stockfish, please read this [guideline][guideline-link]
* [In this wiki,](https://www.chessprogramming.org) many techniques used in
Stockfish are explained with a lot of background information.
* [The section on Stockfish](https://www.chessprogramming.org/Stockfish)
describes many features and techniques used by Stockfish. However, it is
generic rather than being focused on Stockfish's precise implementation.
Nevertheless, a helpful resource.
* The latest source can always be found on [GitHub](https://github.com/official-stockfish/Stockfish).
Discussions about Stockfish take place in the [FishCooking](https://groups.google.com/forum/#!forum/fishcooking)
group and engine testing is done on [Fishtest](https://tests.stockfishchess.org/tests).
If you want to help improve Stockfish, please read this [guideline](https://github.com/glinscott/fishtest/wiki/Creating-my-first-test)
first, where the basics of Stockfish development are explained.
Discussions about Stockfish take place these days mainly in the Stockfish
[Discord server][discord-link]. This is also the best place to ask questions
about the codebase and how to improve it.
## Compiling Stockfish
Stockfish has support for 32 or 64-bit CPUs, certain hardware instructions,
big-endian machines such as Power PC, and other platforms.
On Unix-like systems, it should be easy to compile Stockfish directly from the
source code with the included Makefile in the folder `src`. In general, it is
recommended to run `make help` to see a list of make targets with corresponding
descriptions. An example suitable for most Intel and AMD chips:
```
cd src
make -j profile-build
```
Detailed compilation instructions for all platforms can be found in our
[documentation][wiki-compile-link]. Our wiki also has information about
the [UCI commands][wiki-uci-link] supported by Stockfish.
## Terms of use
Stockfish is free and distributed under the
[**GNU General Public License version 3**][license-link] (GPL v3). Essentially,
this means you are free to do almost exactly what you want with the program,
including distributing it among your friends, making it available for download
from your website, selling it (either by itself or as part of some bigger
software package), or using it as the starting point for a software project of
your own.
Stockfish is free, and distributed under the **GNU General Public License version 3**
(GPL v3). Essentially, this means that you are free to do almost exactly
what you want with the program, including distributing it among your
friends, making it available for download from your web site, selling
it (either by itself or as part of some bigger software package), or
using it as the starting point for a software project of your own.
The only real limitation is that whenever you distribute Stockfish in some way,
you MUST always include the license and the full source code (or a pointer to
where the source code can be found) to generate the exact binary you are
distributing. If you make any changes to the source code, these changes must
also be made available under GPL v3.
The only real limitation is that whenever you distribute Stockfish in
some way, you must always include the full source code, or a pointer
to where the source code can be found. If you make any changes to the
source code, these changes must also be made available under the GPL.
## Acknowledgements
Stockfish uses neural networks trained on [data provided by the Leela Chess Zero
project][lc0-data-link], which is made available under the [Open Database License][odbl-link] (ODbL).
[authors-link]: https://github.com/official-stockfish/Stockfish/blob/master/AUTHORS
[build-link]: https://github.com/official-stockfish/Stockfish/actions/workflows/stockfish.yml
[commits-link]: https://github.com/official-stockfish/Stockfish/commits/master
[discord-link]: https://discord.gg/GWDRS3kU6R
[issue-link]: https://github.com/official-stockfish/Stockfish/issues/new?assignees=&labels=&template=BUG-REPORT.yml
[discussions-link]: https://github.com/official-stockfish/Stockfish/discussions/new
[fishtest-link]: https://tests.stockfishchess.org/tests
[guideline-link]: https://github.com/official-stockfish/fishtest/wiki/Creating-my-first-test
[license-link]: https://github.com/official-stockfish/Stockfish/blob/master/Copying.txt
[programming-link]: https://www.chessprogramming.org/Main_Page
[programmingsf-link]: https://www.chessprogramming.org/Stockfish
[readme-link]: https://github.com/official-stockfish/Stockfish/blob/master/README.md
[release-link]: https://github.com/official-stockfish/Stockfish/releases/latest
[src-link]: https://github.com/official-stockfish/Stockfish/tree/master/src
[stockfish128-logo]: https://stockfishchess.org/images/logo/icon_128x128.png
[uci-link]: https://backscattering.de/chess/uci/
[website-link]: https://stockfishchess.org
[website-blog-link]: https://stockfishchess.org/blog/
[wiki-link]: https://github.com/official-stockfish/Stockfish/wiki
[wiki-compile-link]: https://github.com/official-stockfish/Stockfish/wiki/Compiling-from-source
[wiki-uci-link]: https://github.com/official-stockfish/Stockfish/wiki/UCI-&-Commands
[wiki-usage-link]: https://github.com/official-stockfish/Stockfish/wiki/Download-and-usage
[worker-link]: https://github.com/official-stockfish/fishtest/wiki/Running-the-worker
[lc0-data-link]: https://storage.lczero.org/files/training_data
[odbl-link]: https://opendatacommons.org/licenses/odbl/odbl-10.txt
[build-badge]: https://img.shields.io/github/actions/workflow/status/official-stockfish/Stockfish/stockfish.yml?branch=master&style=for-the-badge&label=stockfish&logo=github
[commits-badge]: https://img.shields.io/github/commits-since/official-stockfish/Stockfish/latest?style=for-the-badge
[discord-badge]: https://img.shields.io/discord/435943710472011776?style=for-the-badge&label=discord&logo=Discord
[fishtest-badge]: https://img.shields.io/website?style=for-the-badge&down_color=red&down_message=Offline&label=Fishtest&up_color=success&up_message=Online&url=https%3A%2F%2Ftests.stockfishchess.org%2Ftests%2Ffinished
[license-badge]: https://img.shields.io/github/license/official-stockfish/Stockfish?style=for-the-badge&label=license&color=success
[release-badge]: https://img.shields.io/github/v/release/official-stockfish/Stockfish?style=for-the-badge&label=official%20release
[website-badge]: https://img.shields.io/website?style=for-the-badge&down_color=red&down_message=Offline&label=website&up_color=success&up_message=Online&url=https%3A%2F%2Fstockfishchess.org
For full details, read the copy of the GPL v3 found in the file named
*Copying.txt*.

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@@ -1,322 +1,154 @@
Contributors to Fishtest with >10,000 CPU hours, as of 2025-03-22.
Contributors with >10,000 CPU hours as of January 7, 2020
Thank you!
Username CPU Hours Games played
------------------------------------------------------------------
noobpwnftw 41712226 3294628533
vdv 28993864 954145232
technologov 24984442 1115931964
linrock 11463033 741692823
mlang 3026000 200065824
okrout 2726068 248285678
olafm 2420096 161297116
pemo 1838361 62294199
TueRens 1804847 80170868
dew 1689162 100033738
sebastronomy 1655637 67294942
grandphish2 1474752 92156319
JojoM 1130625 73666098
rpngn 973590 59996557
oz 921203 60370346
tvijlbrief 796125 51897690
gvreuls 792215 55184194
mibere 703840 46867607
leszek 599745 44681421
cw 519602 34988289
fastgm 503862 30260818
CSU_Dynasty 474794 31654170
maximmasiutin 441753 28129452
robal 437950 28869118
ctoks 435150 28542141
crunchy 427414 27371625
bcross 415724 29061187
mgrabiak 380202 27586936
velislav 342588 22140902
ncfish1 329039 20624527
Fisherman 327231 21829379
Sylvain27 317021 11494912
marrco 310446 19587107
Dantist 296386 18031762
Fifis 289595 14969251
tolkki963 286043 23596996
Calis007 272677 17281620
cody 258835 13301710
nordlandia 249322 16420192
javran 212141 16507618
glinscott 208125 13277240
drabel 204167 13930674
mhoram 202894 12601997
bking_US 198894 11876016
Wencey 198537 9606420
Thanar 179852 12365359
sschnee 170521 10891112
armo9494 168141 11177514
DesolatedDodo 160605 10392474
spams 157128 10319326
maposora 155839 13963260
sqrt2 147963 9724586
vdbergh 140514 9242985
jcAEie 140086 10603658
CoffeeOne 137100 5024116
malala 136182 8002293
Goatminola 134893 11640524
xoto 133759 9159372
markkulix 132104 11000548
naclosagc 131472 4660806
Dubslow 129685 8527664
davar 129023 8376525
DMBK 122960 8980062
dsmith 122059 7570238
Wolfgang 120919 8619168
CypressChess 120902 8683904
amicic 119661 7938029
cuistot 116864 7828864
sterni1971 113754 6054022
Data 113305 8220352
BrunoBanani 112960 7436849
megaman7de 109139 7360928
skiminki 107583 7218170
zeryl 104523 6618969
MaZePallas 102823 6633619
sunu 100167 7040199
thirdlife 99178 2246544
ElbertoOne 99028 7023771
TataneSan 97257 4239502
romangol 95662 7784954
bigpen0r 94825 6529241
brabos 92118 6186135
Maxim 90818 3283364
psk 89957 5984901
szupaw 89775 7800606
jromang 87260 5988073
racerschmacer 85805 6122790
Vizvezdenec 83761 5344740
0x3C33 82614 5271253
Spprtr 82103 5663635
BRAVONE 81239 5054681
MarcusTullius 78930 5189659
Mineta 78731 4947996
Torom 77978 2651656
nssy 76497 5259388
woutboat 76379 6031688
teddybaer 75125 5407666
Pking_cda 73776 5293873
Viren6 73664 1356502
yurikvelo 73611 5046822
Bobo1239 70579 4794999
solarlight 70517 5028306
dv8silencer 70287 3883992
manap 66273 4121774
tinker 64333 4268790
qurashee 61208 3429862
DanielMiao1 60181 1317252
AGI 58316 4336328
jojo2357 57435 4944212
robnjr 57262 4053117
Freja 56938 3733019
MaxKlaxxMiner 56879 3423958
ttruscott 56010 3680085
rkl 55132 4164467
jmdana 54988 4041917
notchris 53936 4184018
renouve 53811 3501516
CounterFlow 52536 3203740
finfish 51360 3370515
eva42 51272 3599691
eastorwest 51117 3454811
rap 49985 3219146
pb00067 49733 3298934
GPUex 48686 3684998
OuaisBla 48626 3445134
ronaldjerum 47654 3240695
biffhero 46564 3111352
oryx 46141 3583236
jibarbosa 45890 4541218
DeepnessFulled 45734 3944282
abdicj 45577 2631772
VoyagerOne 45476 3452465
mecevdimitar 44240 2584396
speedycpu 43842 3003273
jbwiebe 43305 2805433
gopeto 43046 2821514
YvesKn 42628 2177630
Antihistamine 41788 2761312
mhunt 41735 2691355
somethingintheshadows 41502 3330418
homyur 39893 2850481
gri 39871 2515779
vidar808 39774 1656372
Garf 37741 2999686
SC 37299 2731694
Gaster319 37229 3289674
csnodgrass 36207 2688994
ZacHFX 35528 2486328
icewulf 34782 2415146
strelock 34716 2074055
EthanOConnor 33370 2090311
slakovv 32915 2021889
shawnxu 32144 2814668
Gelma 31771 1551204
srowen 31181 1732120
kdave 31157 2198362
manapbk 30987 1810399
votoanthuan 30691 2460856
Prcuvu 30377 2170122
anst 30301 2190091
jkiiski 30136 1904470
spcc 29925 1901692
hyperbolic.tom 29840 2017394
chuckstablers 29659 2093438
Pyafue 29650 1902349
WoodMan777 29300 2579864
belzedar94 28846 1811530
chriswk 26902 1868317
xwziegtm 26897 2124586
Jopo12321 26818 1816482
achambord 26582 1767323
Patrick_G 26276 1801617
yorkman 26193 1992080
Ulysses 25517 1711634
SFTUser 25182 1675689
nabildanial 25068 1531665
Sharaf_DG 24765 1786697
rodneyc 24376 1416402
jsys14 24297 1721230
AndreasKrug 24235 1934711
agg177 23890 1395014
Ente 23752 1678188
JanErik 23408 1703875
Isidor 23388 1680691
Norabor 23371 1603244
Nullvalue 23155 2022752
fishtester 23115 1581502
wizardassassin 23073 1789536
Skiff84 22984 1053680
cisco2015 22920 1763301
ols 22914 1322047
Hjax 22561 1566151
Zirie 22542 1472937
team-oh 22272 1636708
mkstockfishtester 22253 2029566
Roady 22220 1465606
MazeOfGalious 21978 1629593
sg4032 21950 1643373
tsim67 21939 1343944
ianh2105 21725 1632562
Serpensin 21704 1809188
xor12 21628 1680365
dex 21612 1467203
nesoneg 21494 1463031
IslandLambda 21468 1239756
user213718 21454 1404128
sphinx 21211 1384728
qoo_charly_cai 21136 1514927
jjoshua2 21001 1423089
Zake9298 20938 1565848
horst.prack 20878 1465656
0xB00B1ES 20590 1208666
Dinde 20459 1292774
t3hf1sht3ster 20456 670646
j3corre 20405 941444
0x539 20332 1039516
Adrian.Schmidt123 20316 1281436
malfoy 20313 1350694
purpletree 20019 1461026
wei 19973 1745989
teenychess 19819 1762006
rstoesser 19569 1293588
eudhan 19274 1283717
nalanzeyu 19211 396674
vulcan 18871 1729392
Karpovbot 18766 1053178
jundery 18445 1115855
Farseer 18281 1074642
sebv15 18267 1262588
whelanh 17887 347974
ville 17883 1384026
chris 17698 1487385
purplefishies 17595 1092533
dju 17414 981289
iisiraider 17275 1049015
Karby 17177 1030688
DragonLord 17014 1162790
pirt 16991 1274215
redstone59 16842 1461780
Alb11747 16787 1213990
Naven94 16414 951718
scuzzi 16155 995347
IgorLeMasson 16064 1147232
ako027ako 15671 1173203
xuhdev 15516 1528278
infinigon 15285 965966
Nikolay.IT 15154 1068349
Andrew Grant 15114 895539
OssumOpossum 14857 1007129
LunaticBFF57 14525 1190310
enedene 14476 905279
YELNAMRON 14475 1141330
RickGroszkiewicz 14272 1385984
joendter 14269 982014
bpfliegel 14233 882523
mpx86 14019 759568
jpulman 13982 870599
getraideBFF 13871 1172846
crocogoat 13817 1119086
Nesa92 13806 1116101
joster 13710 946160
mbeier 13650 1044928
Pablohn26 13552 1088532
wxt9861 13550 1312306
Dark_wizzie 13422 1007152
Rudolphous 13244 883140
Jackfish 13177 894206
MooTheCow 13091 892304
Machariel 13010 863104
mabichito 12903 749391
thijsk 12886 722107
AdrianSA 12860 804972
Flopzee 12698 894821
szczur90 12684 977536
Kyrega 12661 456438
mschmidt 12644 863193
korposzczur 12606 838168
fatmurphy 12547 853210
Oakwen 12532 855759
SapphireBrand 12416 969604
deflectooor 12386 579392
modolief 12386 896470
ckaz 12273 754644
Hongildong 12201 648712
pgontarz 12151 848794
dbernier 12103 860824
FormazChar 12051 913497
shreven 12044 884734
rensonthemove 11999 971993
stocky 11954 699440
3cho 11842 1036786
ImperiumAeternum 11482 979142
infinity 11470 727027
aga 11412 695127
Def9Infinity 11408 700682
torbjo 11395 729145
Thomas A. Anderson 11372 732094
savage84 11358 670860
d64 11263 789184
ali-al-zhrani 11245 779246
vaskoul 11144 953906
snicolet 11106 869170
dapper 11032 771402
Ethnikoi 10993 945906
Snuuka 10938 435504
Karmatron 10871 678306
gerbil 10871 1005842
OliverClarke 10696 942654
basepi 10637 744851
michaelrpg 10624 748179
Cubox 10621 826448
dragon123118 10421 936506
OIVAS7572 10420 995586
GBx3TV 10388 339952
Garruk 10365 706465
dzjp 10343 732529
borinot 10026 902130
Username CPU Hours Games played
--------------------------------------------------
noobpwnftw 9305707 695548021
mlang 780050 61648867
dew 621626 43921547
mibere 524702 42238645
crunchy 354587 27344275
cw 354495 27274181
fastgm 332801 22804359
JojoM 295750 20437451
CSU_Dynasty 262015 21828122
Fisherman 232181 18939229
ctoks 218866 17622052
glinscott 201989 13780820
tvijlbrief 201204 15337115
velislav 188630 14348485
gvreuls 187164 15149976
bking_US 180289 11876016
nordlandia 172076 13467830
leszek 157152 11443978
Thanar 148021 12365359
spams 141975 10319326
drabel 138073 11121749
vdv 137850 9394330
mgrabiak 133578 10454324
TueRens 132485 10878471
bcross 129683 11557084
marrco 126078 9356740
sqrt2 125830 9724586
robal 122873 9593418
vdbergh 120766 8926915
malala 115926 8002293
CoffeeOne 114241 5004100
dsmith 113189 7570238
BrunoBanani 104644 7436849
Data 92328 8220352
mhoram 89333 6695109
davar 87924 7009424
xoto 81094 6869316
ElbertoOne 80899 7023771
grandphish2 78067 6160199
brabos 77212 6186135
psk 75733 5984901
BRAVONE 73875 5054681
sunu 70771 5597972
sterni1971 70605 5590573
MaZePallas 66886 5188978
Vizvezdenec 63708 4967313
nssy 63462 5259388
jromang 61634 4940891
teddybaer 61231 5407666
Pking_cda 60099 5293873
solarlight 57469 5028306
dv8silencer 56913 3883992
tinker 54936 4086118
renouve 49732 3501516
Freja 49543 3733019
robnjr 46972 4053117
rap 46563 3219146
Bobo1239 46036 3817196
ttruscott 45304 3649765
racerschmacer 44881 3975413
finfish 44764 3370515
eva42 41783 3599691
biffhero 40263 3111352
bigpen0r 39817 3291647
mhunt 38871 2691355
ronaldjerum 38820 3240695
Antihistamine 38785 2761312
pb00067 38038 3086320
speedycpu 37591 3003273
rkl 37207 3289580
VoyagerOne 37050 3441673
jbwiebe 35320 2805433
cuistot 34191 2146279
homyur 33927 2850481
manap 32873 2327384
gri 32538 2515779
oryx 31267 2899051
EthanOConnor 30959 2090311
SC 30832 2730764
csnodgrass 29505 2688994
jmdana 29458 2205261
strelock 28219 2067805
jkiiski 27832 1904470
Pyafue 27533 1902349
Garf 27515 2747562
eastorwest 27421 2317535
slakovv 26903 2021889
Prcuvu 24835 2170122
anst 24714 2190091
hyperbolic.tom 24319 2017394
Patrick_G 23687 1801617
Sharaf_DG 22896 1786697
nabildanial 22195 1519409
chriswk 21931 1868317
achambord 21665 1767323
Zirie 20887 1472937
team-oh 20217 1636708
Isidor 20096 1680691
ncfish1 19931 1520927
nesoneg 19875 1463031
Spprtr 19853 1548165
JanErik 19849 1703875
agg177 19478 1395014
SFTUser 19231 1567999
xor12 19017 1680165
sg4032 18431 1641865
rstoesser 18118 1293588
MazeOfGalious 17917 1629593
j3corre 17743 941444
cisco2015 17725 1690126
ianh2105 17706 1632562
dex 17678 1467203
jundery 17194 1115855
iisiraider 17019 1101015
horst.prack 17012 1465656
Adrian.Schmidt123 16563 1281436
purplefishies 16342 1092533
wei 16274 1745989
ville 16144 1384026
eudhan 15712 1283717
OuaisBla 15581 972000
DragonLord 15559 1162790
dju 14716 875569
chris 14479 1487385
0xB00B1ES 14079 1001120
OssumOpossum 13776 1007129
enedene 13460 905279
bpfliegel 13346 884523
Ente 13198 1156722
IgorLeMasson 13087 1147232
jpulman 13000 870599
ako027ako 12775 1173203
Nikolay.IT 12352 1068349
Andrew Grant 12327 895539
joster 12008 950160
AdrianSA 11996 804972
Nesa92 11455 1111993
fatmurphy 11345 853210
Dark_wizzie 11108 1007152
modolief 10869 896470
mschmidt 10757 803401
infinity 10594 727027
mabichito 10524 749391
Thomas A. Anderson 10474 732094
thijsk 10431 719357
Flopzee 10339 894821
crocogoat 10104 1013854
SapphireBrand 10104 969604
stocky 10017 699440

75
appveyor.yml Normal file
View File

@@ -0,0 +1,75 @@
version: 1.0.{build}
clone_depth: 50
branches:
only:
- master
- nnue-player-wip
# Operating system (build VM template)
os: Visual Studio 2019
# Build platform, i.e. x86, x64, AnyCPU. This setting is optional.
platform:
- x86
- x64
# build Configuration, i.e. Debug, Release, etc.
configuration:
- Debug
- Release
matrix:
# The build fail immediately once one of the job fails
fast_finish: true
# Scripts that are called at very beginning, before repo cloning
init:
- cmake --version
- msbuild /version
before_build:
- ps: |
# Get sources
$src = get-childitem -Path *.cpp -Recurse | select -ExpandProperty FullName
$src = $src -join ' '
$src = $src.Replace("\", "/")
# Build CMakeLists.txt
$t = 'cmake_minimum_required(VERSION 3.17)',
'project(Stockfish)',
'set(CMAKE_CXX_STANDARD 17)',
'set(CMAKE_CXX_STANDARD_REQUIRED ON)',
'set (CMAKE_CXX_EXTENSIONS OFF)',
'set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_SOURCE_DIR}/src)',
'set(source_files', $src, ')',
'add_executable(stockfish ${source_files})'
# Write CMakeLists.txt withouth BOM
$MyPath = (Get-Item -Path "." -Verbose).FullName + '\CMakeLists.txt'
$Utf8NoBomEncoding = New-Object System.Text.UTF8Encoding $False
[System.IO.File]::WriteAllLines($MyPath, $t, $Utf8NoBomEncoding)
# Obtain bench reference from git log
$b = git log HEAD | sls "\b[Bb]ench[ :]+[0-9]{7}" | select -first 1
$bench = $b -match '\D+(\d+)' | % { $matches[1] }
Write-Host "Reference bench:" $bench
$g = "Visual Studio 16 2019"
If (${env:PLATFORM} -eq 'x64') { $a = "x64" }
If (${env:PLATFORM} -eq 'x86') { $a = "Win32" }
cmake -G "${g}" -A ${a} .
Write-Host "Generated files for: " $g $a
build_script:
- cmake --build . --config %CONFIGURATION% -- /verbosity:minimal
before_test:
- cd src/%CONFIGURATION%
- stockfish bench 2> out.txt >NUL
- ps: |
# Verify bench number
$s = (gc "./out.txt" | out-string)
$r = ($s -match 'Nodes searched \D+(\d+)' | % { $matches[1] })
Write-Host "Engine bench:" $r
Write-Host "Reference bench:" $bench
If ($r -ne $bench) { exit 1 }

View File

@@ -1 +0,0 @@
*.sh text eol=lf

View File

@@ -1,159 +0,0 @@
#!/bin/sh
#
# Returns properties of the native system.
# best architecture as supported by the CPU
# filename of the best binary uploaded as an artifact during CI
#
# Check if all the given flags are present in the CPU flags list
check_flags() {
for flag; do
printf '%s\n' "$flags" | grep -q -w "$flag" || return 1
done
}
# Set the CPU flags list
# remove underscores and points from flags, e.g. gcc uses avx512vnni, while some cpuinfo can have avx512_vnni, some systems use sse4_1 others sse4.1
get_flags() {
flags=$(awk '/^flags[ \t]*:|^Features[ \t]*:/{gsub(/^flags[ \t]*:[ \t]*|^Features[ \t]*:[ \t]*|[_.]/, ""); line=$0} END{print line}' /proc/cpuinfo)
}
# Check for gcc march "znver1" or "znver2" https://en.wikichip.org/wiki/amd/cpuid
check_znver_1_2() {
vendor_id=$(awk '/^vendor_id/{print $3; exit}' /proc/cpuinfo)
cpu_family=$(awk '/^cpu family/{print $4; exit}' /proc/cpuinfo)
[ "$vendor_id" = "AuthenticAMD" ] && [ "$cpu_family" = "23" ] && znver_1_2=true
}
# Set the file CPU loongarch64 architecture
set_arch_loongarch64() {
if check_flags 'lasx'; then
true_arch='loongarch64-lasx'
elif check_flags 'lsx'; then
true_arch='lonngarch64-lsx'
else
true_arch='loongarch64'
fi
}
# Set the file CPU x86_64 architecture
set_arch_x86_64() {
if check_flags 'avx512vnni' 'avx512dq' 'avx512f' 'avx512bw' 'avx512vl'; then
true_arch='x86-64-vnni256'
elif check_flags 'avx512f' 'avx512bw'; then
true_arch='x86-64-avx512'
elif [ -z "${znver_1_2+1}" ] && check_flags 'bmi2'; then
true_arch='x86-64-bmi2'
elif check_flags 'avx2'; then
true_arch='x86-64-avx2'
elif check_flags 'sse41' && check_flags 'popcnt'; then
true_arch='x86-64-sse41-popcnt'
else
true_arch='x86-64'
fi
}
set_arch_ppc_64() {
if $(grep -q -w "altivec" /proc/cpuinfo); then
power=$(grep -oP -m 1 'cpu\t+: POWER\K\d+' /proc/cpuinfo)
if [ "0$power" -gt 7 ]; then
# VSX started with POWER8
true_arch='ppc-64-vsx'
else
true_arch='ppc-64-altivec'
fi
else
true_arch='ppc-64'
fi
}
# Check the system type
uname_s=$(uname -s)
uname_m=$(uname -m)
case $uname_s in
'Darwin') # Mac OSX system
case $uname_m in
'arm64')
true_arch='apple-silicon'
file_arch='m1-apple-silicon'
;;
'x86_64')
flags=$(sysctl -n machdep.cpu.features machdep.cpu.leaf7_features | tr '\n' ' ' | tr '[:upper:]' '[:lower:]' | tr -d '_.')
set_arch_x86_64
if [ "$true_arch" = 'x86-64-vnni256' ] || [ "$true_arch" = 'x86-64-avx512' ]; then
file_arch='x86-64-bmi2'
fi
;;
esac
file_os='macos'
file_ext='tar'
;;
'Linux') # Linux system
get_flags
case $uname_m in
'x86_64')
file_os='ubuntu'
check_znver_1_2
set_arch_x86_64
;;
'i686')
file_os='ubuntu'
true_arch='x86-32'
;;
'ppc64'*)
file_os='ubuntu'
set_arch_ppc_64
;;
'aarch64')
file_os='android'
true_arch='armv8'
if check_flags 'asimddp'; then
true_arch="$true_arch-dotprod"
fi
;;
'armv7'*)
file_os='android'
true_arch='armv7'
if check_flags 'neon'; then
true_arch="$true_arch-neon"
fi
;;
'loongarch64'*)
file_os='linux'
set_arch_loongarch64
;;
*) # Unsupported machine type, exit with error
printf 'Unsupported machine type: %s\n' "$uname_m"
exit 1
;;
esac
file_ext='tar'
;;
'MINGW'*'ARM64'*) # Windows ARM64 system with POSIX compatibility layer
# TODO: older chips might be armv8, but we have no good way to detect, /proc/cpuinfo shows x86 info
file_os='windows'
true_arch='armv8-dotprod'
file_ext='zip'
;;
'CYGWIN'*|'MINGW'*|'MSYS'*) # Windows x86_64system with POSIX compatibility layer
get_flags
check_znver_1_2
set_arch_x86_64
file_os='windows'
file_ext='zip'
;;
*)
# Unknown system type, exit with error
printf 'Unsupported system type: %s\n' "$uname_s"
exit 1
;;
esac
if [ -z "$file_arch" ]; then
file_arch=$true_arch
fi
file_name="stockfish-$file_os-$file_arch.$file_ext"
printf '%s %s\n' "$true_arch" "$file_name"

View File

@@ -1,76 +0,0 @@
#!/bin/sh
wget_or_curl=$( (command -v wget > /dev/null 2>&1 && echo "wget -qO-") || \
(command -v curl > /dev/null 2>&1 && echo "curl -skL"))
sha256sum=$( (command -v shasum > /dev/null 2>&1 && echo "shasum -a 256") || \
(command -v sha256sum > /dev/null 2>&1 && echo "sha256sum"))
if [ -z "$sha256sum" ]; then
>&2 echo "sha256sum not found, NNUE files will be assumed valid."
fi
get_nnue_filename() {
grep "$1" evaluate.h | grep "#define" | sed "s/.*\(nn-[a-z0-9]\{12\}.nnue\).*/\1/"
}
validate_network() {
# If no sha256sum command is available, assume the file is always valid.
if [ -n "$sha256sum" ] && [ -f "$1" ]; then
if [ "$1" != "nn-$($sha256sum "$1" | cut -c 1-12).nnue" ]; then
rm -f "$1"
return 1
fi
fi
}
fetch_network() {
_filename="$(get_nnue_filename "$1")"
if [ -z "$_filename" ]; then
>&2 echo "NNUE file name not found for: $1"
return 1
fi
if [ -f "$_filename" ]; then
if validate_network "$_filename"; then
echo "Existing $_filename validated, skipping download"
return
else
echo "Removing invalid NNUE file: $_filename"
fi
fi
if [ -z "$wget_or_curl" ]; then
>&2 printf "%s\n" "Neither wget or curl is installed." \
"Install one of these tools to download NNUE files automatically."
exit 1
fi
for url in \
"https://tests.stockfishchess.org/api/nn/$_filename" \
"https://github.com/official-stockfish/networks/raw/master/$_filename"; do
echo "Downloading from $url ..."
if $wget_or_curl "$url" > "$_filename"; then
if validate_network "$_filename"; then
echo "Successfully validated $_filename"
else
echo "Downloaded $_filename is invalid"
continue
fi
else
echo "Failed to download from $url"
fi
if [ -f "$_filename" ]; then
return
fi
done
# Download was not successful in the loop, return false.
>&2 echo "Failed to download $_filename"
return 1
}
fetch_network EvalFileDefaultNameBig && \
fetch_network EvalFileDefaultNameSmall

File diff suppressed because it is too large Load Diff

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -16,18 +16,18 @@
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include "benchmark.h"
#include "numa.h"
#include <cstdlib>
#include <fstream>
#include <iostream>
#include <istream>
#include <vector>
#include "position.h"
using namespace std;
namespace {
// clang-format off
const std::vector<std::string> Defaults = {
const vector<string> Defaults = {
"setoption name UCI_Chess960 value false",
"rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1",
"r3k2r/p1ppqpb1/bn2pnp1/3PN3/1p2P3/2N2Q1p/PPPBBPPP/R3K2R w KQkq - 0 10",
@@ -87,426 +87,73 @@ const std::vector<std::string> Defaults = {
// Chess 960
"setoption name UCI_Chess960 value true",
"bbqnnrkr/pppppppp/8/8/8/8/PPPPPPPP/BBQNNRKR w HFhf - 0 1 moves g2g3 d7d5 d2d4 c8h3 c1g5 e8d6 g5e7 f7f6",
"nqbnrkrb/pppppppp/8/8/8/8/PPPPPPPP/NQBNRKRB w KQkq - 0 1",
"setoption name UCI_Chess960 value false"
};
// clang-format on
// clang-format off
// human-randomly picked 5 games with <60 moves from
// https://tests.stockfishchess.org/tests/view/665c71f9fd45fb0f907c21e0
// only moves for one side
const std::vector<std::vector<std::string>> BenchmarkPositions = {
{
"rnbq1k1r/ppp1bppp/4pn2/8/2B5/2NP1N2/PPP2PPP/R1BQR1K1 b - - 2 8",
"rnbq1k1r/pp2bppp/4pn2/2p5/2B2B2/2NP1N2/PPP2PPP/R2QR1K1 b - - 1 9",
"r1bq1k1r/pp2bppp/2n1pn2/2p5/2B1NB2/3P1N2/PPP2PPP/R2QR1K1 b - - 3 10",
"r1bq1k1r/pp2bppp/2n1p3/2p5/2B1PB2/5N2/PPP2PPP/R2QR1K1 b - - 0 11",
"r1b2k1r/pp2bppp/2n1p3/2p5/2B1PB2/5N2/PPP2PPP/3RR1K1 b - - 0 12",
"r1b1k2r/pp2bppp/2n1p3/2p5/2B1PB2/2P2N2/PP3PPP/3RR1K1 b - - 0 13",
"r1b1k2r/1p2bppp/p1n1p3/2p5/4PB2/2P2N2/PP2BPPP/3RR1K1 b - - 1 14",
"r1b1k2r/4bppp/p1n1p3/1pp5/P3PB2/2P2N2/1P2BPPP/3RR1K1 b - - 0 15",
"r1b1k2r/4bppp/p1n1p3/1P6/2p1PB2/2P2N2/1P2BPPP/3RR1K1 b - - 0 16",
"r1b1k2r/4bppp/2n1p3/1p6/2p1PB2/1PP2N2/4BPPP/3RR1K1 b - - 0 17",
"r3k2r/3bbppp/2n1p3/1p6/2P1PB2/2P2N2/4BPPP/3RR1K1 b - - 0 18",
"r3k2r/3bbppp/2n1p3/8/1pP1P3/2P2N2/3BBPPP/3RR1K1 b - - 1 19",
"1r2k2r/3bbppp/2n1p3/8/1pPNP3/2P5/3BBPPP/3RR1K1 b - - 3 20",
"1r2k2r/3bbppp/2n1p3/8/2PNP3/2B5/4BPPP/3RR1K1 b - - 0 21",
"1r2k2r/3bb1pp/2n1pp2/1N6/2P1P3/2B5/4BPPP/3RR1K1 b - - 1 22",
"1r2k2r/3b2pp/2n1pp2/1N6/1BP1P3/8/4BPPP/3RR1K1 b - - 0 23",
"1r2k2r/3b2pp/4pp2/1N6/1nP1P3/8/3RBPPP/4R1K1 b - - 1 24",
"1r5r/3bk1pp/4pp2/1N6/1nP1PP2/8/3RB1PP/4R1K1 b - - 0 25",
"1r5r/3bk1pp/2n1pp2/1N6/2P1PP2/8/3RBKPP/4R3 b - - 2 26",
"1r5r/3bk1pp/2n2p2/1N2p3/2P1PP2/6P1/3RBK1P/4R3 b - - 0 27",
"1r1r4/3bk1pp/2n2p2/1N2p3/2P1PP2/6P1/3RBK1P/R7 b - - 2 28",
"1r1r4/N3k1pp/2n1bp2/4p3/2P1PP2/6P1/3RBK1P/R7 b - - 4 29",
"1r1r4/3bk1pp/2N2p2/4p3/2P1PP2/6P1/3RBK1P/R7 b - - 0 30",
"1r1R4/4k1pp/2b2p2/4p3/2P1PP2/6P1/4BK1P/R7 b - - 0 31",
"3r4/4k1pp/2b2p2/4P3/2P1P3/6P1/4BK1P/R7 b - - 0 32",
"3r4/R3k1pp/2b5/4p3/2P1P3/6P1/4BK1P/8 b - - 1 33",
"8/3rk1pp/2b5/R3p3/2P1P3/6P1/4BK1P/8 b - - 3 34",
"8/3r2pp/2bk4/R1P1p3/4P3/6P1/4BK1P/8 b - - 0 35",
"8/2kr2pp/2b5/R1P1p3/4P3/4K1P1/4B2P/8 b - - 2 36",
"1k6/3r2pp/2b5/RBP1p3/4P3/4K1P1/7P/8 b - - 4 37",
"8/1k1r2pp/2b5/R1P1p3/4P3/3BK1P1/7P/8 b - - 6 38",
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"2r1q1k1/2Rn2p1/3rpp1p/1p6/1P2P3/5N1P/Q4PP1/R5K1 w - - 1 41",
"1r2q1k1/1R1n2p1/3rpp1p/1p6/1P2P3/5N1P/Q4PP1/R5K1 w - - 3 42",
"2r1q1k1/2Rn2p1/3rpp1p/1p6/1P2P3/5N1P/Q4PP1/R5K1 w - - 5 43",
"1r2q1k1/1R1n2p1/3rpp1p/1p6/1P2P3/5N1P/Q4PP1/R5K1 w - - 7 44",
"1rq3k1/R2n2p1/3rpp1p/1p6/1P2P3/5N1P/Q4PP1/R5K1 w - - 9 45",
"2q3k1/Rr1n2p1/3rpp1p/1p6/1P2P3/5N1P/4QPP1/R5K1 w - - 11 46",
"Rrq3k1/3n2p1/3rpp1p/1p6/1P2P3/5N1P/4QPP1/R5K1 w - - 13 47",
},
{
"rn1qkb1r/1pp2ppp/p4p2/3p1b2/5P2/1P2PN2/P1PP2PP/RN1QKB1R b KQkq - 1 6",
"r2qkb1r/1pp2ppp/p1n2p2/3p1b2/3P1P2/1P2PN2/P1P3PP/RN1QKB1R b KQkq - 0 7",
"r2qkb1r/1pp2ppp/p4p2/3p1b2/1n1P1P2/1P1BPN2/P1P3PP/RN1QK2R b KQkq - 2 8",
"r2qkb1r/1pp2ppp/p4p2/3p1b2/3P1P2/1P1PPN2/P5PP/RN1QK2R b KQkq - 0 9",
"r2qk2r/1pp2ppp/p2b1p2/3p1b2/3P1P2/1PNPPN2/P5PP/R2QK2R b KQkq - 2 10",
"r2qk2r/1p3ppp/p1pb1p2/3p1b2/3P1P2/1PNPPN2/P5PP/R2Q1RK1 b kq - 1 11",
"r2q1rk1/1p3ppp/p1pb1p2/3p1b2/3P1P2/1PNPPN2/P2Q2PP/R4RK1 b - - 3 12",
"r2qr1k1/1p3ppp/p1pb1p2/3p1b2/3P1P2/1P1PPN2/P2QN1PP/R4RK1 b - - 5 13",
"r3r1k1/1p3ppp/pqpb1p2/3p1b2/3P1P2/1P1PPNN1/P2Q2PP/R4RK1 b - - 7 14",
"r3r1k1/1p3ppp/pqp2p2/3p1b2/1b1P1P2/1P1PPNN1/P1Q3PP/R4RK1 b - - 9 15",
"r3r1k1/1p1b1ppp/pqp2p2/3p4/1b1P1P2/1P1PPNN1/P4QPP/R4RK1 b - - 11 16",
"2r1r1k1/1p1b1ppp/pqp2p2/3p4/1b1PPP2/1P1P1NN1/P4QPP/R4RK1 b - - 0 17",
"2r1r1k1/1p1b1ppp/pq3p2/2pp4/1b1PPP2/PP1P1NN1/5QPP/R4RK1 b - - 0 18",
"2r1r1k1/1p1b1ppp/pq3p2/2Pp4/4PP2/PPbP1NN1/5QPP/R4RK1 b - - 0 19",
"2r1r1k1/1p1b1ppp/p4p2/2Pp4/4PP2/PqbP1NN1/5QPP/RR4K1 b - - 1 20",
"2r1r1k1/1p1b1ppp/p4p2/2Pp4/q3PP2/P1bP1NN1/R4QPP/1R4K1 b - - 3 21",
"2r1r1k1/1p3ppp/p4p2/1bPP4/q4P2/P1bP1NN1/R4QPP/1R4K1 b - - 0 22",
"2r1r1k1/1p3ppp/p4p2/2PP4/q4P2/P1bb1NN1/R4QPP/2R3K1 b - - 1 23",
"2r1r1k1/1p3ppp/p2P1p2/2P5/2q2P2/P1bb1NN1/R4QPP/2R3K1 b - - 0 24",
"2rr2k1/1p3ppp/p2P1p2/2P5/2q2P2/P1bb1NN1/R4QPP/2R4K b - - 2 25",
"2rr2k1/1p3ppp/p2P1p2/2Q5/5P2/P1bb1NN1/R5PP/2R4K b - - 0 26",
"3r2k1/1p3ppp/p2P1p2/2r5/5P2/P1bb1N2/R3N1PP/2R4K b - - 1 27",
"3r2k1/1p3ppp/p2P1p2/2r5/5P2/P1b2N2/4R1PP/2R4K b - - 0 28",
"3r2k1/1p3ppp/p2P1p2/2r5/1b3P2/P4N2/4R1PP/3R3K b - - 2 29",
"3r2k1/1p2Rppp/p2P1p2/b1r5/5P2/P4N2/6PP/3R3K b - - 4 30",
"3r2k1/1R3ppp/p1rP1p2/b7/5P2/P4N2/6PP/3R3K b - - 0 31",
"3r2k1/1R3ppp/p2R1p2/b7/5P2/P4N2/6PP/7K b - - 0 32",
"6k1/1R3ppp/p2r1p2/b7/5P2/P4NP1/7P/7K b - - 0 33",
"6k1/1R3p1p/p2r1pp1/b7/5P1P/P4NP1/8/7K b - - 0 34",
"6k1/3R1p1p/pr3pp1/b7/5P1P/P4NP1/8/7K b - - 2 35",
"6k1/5p2/pr3pp1/b2R3p/5P1P/P4NP1/8/7K b - - 1 36",
"6k1/5p2/pr3pp1/7p/5P1P/P1bR1NP1/8/7K b - - 3 37",
"6k1/5p2/p1r2pp1/7p/5P1P/P1bR1NP1/6K1/8 b - - 5 38",
"6k1/5p2/p1r2pp1/b2R3p/5P1P/P4NP1/6K1/8 b - - 7 39",
"6k1/5p2/p4pp1/b2R3p/5P1P/P4NPK/2r5/8 b - - 9 40",
"6k1/2b2p2/p4pp1/7p/5P1P/P2R1NPK/2r5/8 b - - 11 41",
"6k1/2b2p2/5pp1/p6p/3N1P1P/P2R2PK/2r5/8 b - - 1 42",
"6k1/2b2p2/5pp1/p6p/3N1P1P/P1R3PK/r7/8 b - - 3 43",
"6k1/5p2/1b3pp1/p6p/5P1P/P1R3PK/r1N5/8 b - - 5 44",
"8/5pk1/1bR2pp1/p6p/5P1P/P5PK/r1N5/8 b - - 7 45",
"3b4/5pk1/2R2pp1/p4P1p/7P/P5PK/r1N5/8 b - - 0 46",
"8/4bpk1/2R2pp1/p4P1p/6PP/P6K/r1N5/8 b - - 0 47",
"8/5pk1/2R2pP1/p6p/6PP/b6K/r1N5/8 b - - 0 48",
"8/6k1/2R2pp1/p6P/7P/b6K/r1N5/8 b - - 0 49",
"8/6k1/2R2p2/p6p/7P/b5K1/r1N5/8 b - - 1 50",
"8/8/2R2pk1/p6p/7P/b4K2/r1N5/8 b - - 3 51",
"8/8/2R2pk1/p6p/7P/4NK2/rb6/8 b - - 5 52",
"2R5/8/5pk1/7p/p6P/4NK2/rb6/8 b - - 1 53",
"6R1/8/5pk1/7p/p6P/4NK2/1b6/r7 b - - 3 54",
"R7/5k2/5p2/7p/p6P/4NK2/1b6/r7 b - - 5 55",
"R7/5k2/5p2/7p/7P/p3N3/1b2K3/r7 b - - 1 56",
"8/R4k2/5p2/7p/7P/p3N3/1b2K3/7r b - - 3 57",
"8/8/5pk1/7p/R6P/p3N3/1b2K3/7r b - - 5 58",
"8/8/5pk1/7p/R6P/p7/4K3/2bN3r b - - 7 59",
"8/8/5pk1/7p/R6P/p7/4KN1r/2b5 b - - 9 60",
"8/8/5pk1/7p/R6P/p3K3/1b3N1r/8 b - - 11 61",
"8/8/R4pk1/7p/7P/p1b1K3/5N1r/8 b - - 13 62",
"8/8/5pk1/7p/7P/2b1K3/R4N1r/8 b - - 0 63",
"8/8/5pk1/7p/3K3P/8/R4N1r/4b3 b - - 2 64",
}
};
// clang-format on
} // namespace
} // namespace
/// setup_bench() builds a list of UCI commands to be run by bench. There
/// are five parameters: TT size in MB, number of search threads that
/// should be used, the limit value spent for each position, a file name
/// where to look for positions in FEN format and the type of the limit:
/// depth, perft, nodes and movetime (in millisecs).
///
/// bench -> search default positions up to depth 13
/// bench 64 1 15 -> search default positions up to depth 15 (TT = 64MB)
/// bench 64 4 5000 current movetime -> search current position with 4 threads for 5 sec
/// bench 64 1 100000 default nodes -> search default positions for 100K nodes each
/// bench 16 1 5 default perft -> run a perft 5 on default positions
namespace Stockfish::Benchmark {
vector<string> setup_bench(const Position& current, istream& is) {
// Builds a list of UCI commands to be run by bench. There
// are five parameters: TT size in MB, number of search threads that
// should be used, the limit value spent for each position, a file name
// where to look for positions in FEN format, and the type of the limit:
// depth, perft, nodes and movetime (in milliseconds). Examples:
//
// bench : search default positions up to depth 13
// bench 64 1 15 : search default positions up to depth 15 (TT = 64MB)
// bench 64 1 100000 default nodes : search default positions for 100K nodes each
// bench 64 4 5000 current movetime : search current position with 4 threads for 5 sec
// bench 16 1 5 blah perft : run a perft 5 on positions in file "blah"
std::vector<std::string> setup_bench(const std::string& currentFen, std::istream& is) {
vector<string> fens, list;
string go, token;
std::vector<std::string> fens, list;
std::string go, token;
// Assign default values to missing arguments
string ttSize = (is >> token) ? token : "16";
string threads = (is >> token) ? token : "1";
string limit = (is >> token) ? token : "13";
string fenFile = (is >> token) ? token : "default";
string limitType = (is >> token) ? token : "depth";
// Assign default values to missing arguments
std::string ttSize = (is >> token) ? token : "16";
std::string threads = (is >> token) ? token : "1";
std::string limit = (is >> token) ? token : "13";
std::string fenFile = (is >> token) ? token : "default";
std::string limitType = (is >> token) ? token : "depth";
go = limitType == "eval" ? "eval" : "go " + limitType + " " + limit;
go = limitType == "eval" ? "eval" : "go " + limitType + " " + limit;
if (fenFile == "default")
fens = Defaults;
if (fenFile == "default")
fens = Defaults;
else if (fenFile == "current")
fens.push_back(current.fen());
else if (fenFile == "current")
fens.push_back(currentFen);
else
{
string fen;
ifstream file(fenFile);
else
{
std::string fen;
std::ifstream file(fenFile);
if (!file.is_open())
{
cerr << "Unable to open file " << fenFile << endl;
exit(EXIT_FAILURE);
}
if (!file.is_open())
{
std::cerr << "Unable to open file " << fenFile << std::endl;
exit(EXIT_FAILURE);
}
while (getline(file, fen))
if (!fen.empty())
fens.push_back(fen);
while (getline(file, fen))
if (!fen.empty())
fens.push_back(fen);
file.close();
}
file.close();
}
list.emplace_back("setoption name Threads value " + threads);
list.emplace_back("setoption name Hash value " + ttSize);
list.emplace_back("ucinewgame");
list.emplace_back("setoption name Threads value " + threads);
list.emplace_back("setoption name Hash value " + ttSize);
list.emplace_back("ucinewgame");
for (const string& fen : fens)
if (fen.find("setoption") != string::npos)
list.emplace_back(fen);
else
{
list.emplace_back("position fen " + fen);
list.emplace_back(go);
}
for (const std::string& fen : fens)
if (fen.find("setoption") != std::string::npos)
list.emplace_back(fen);
else
{
list.emplace_back("position fen " + fen);
list.emplace_back(go);
}
return list;
return list;
}
BenchmarkSetup setup_benchmark(std::istream& is) {
// TT_SIZE_PER_THREAD is chosen such that roughly half of the hash is used all positions
// for the current sequence have been searched.
static constexpr int TT_SIZE_PER_THREAD = 128;
static constexpr int DEFAULT_DURATION_S = 150;
BenchmarkSetup setup{};
// Assign default values to missing arguments
int desiredTimeS;
if (!(is >> setup.threads))
setup.threads = get_hardware_concurrency();
else
setup.originalInvocation += std::to_string(setup.threads);
if (!(is >> setup.ttSize))
setup.ttSize = TT_SIZE_PER_THREAD * setup.threads;
else
setup.originalInvocation += " " + std::to_string(setup.ttSize);
if (!(is >> desiredTimeS))
desiredTimeS = DEFAULT_DURATION_S;
else
setup.originalInvocation += " " + std::to_string(desiredTimeS);
setup.filledInvocation += std::to_string(setup.threads) + " " + std::to_string(setup.ttSize)
+ " " + std::to_string(desiredTimeS);
auto getCorrectedTime = [&](int ply) {
// time per move is fit roughly based on LTC games
// seconds = 50/{ply+15}
// ms = 50000/{ply+15}
// with this fit 10th move gets 2000ms
// adjust for desired 10th move time
return 50000.0 / (static_cast<double>(ply) + 15.0);
};
float totalTime = 0;
for (const auto& game : BenchmarkPositions)
{
setup.commands.emplace_back("ucinewgame");
int ply = 1;
for (int i = 0; i < static_cast<int>(game.size()); ++i)
{
const float correctedTime = getCorrectedTime(ply);
totalTime += correctedTime;
ply += 1;
}
}
float timeScaleFactor = static_cast<float>(desiredTimeS * 1000) / totalTime;
for (const auto& game : BenchmarkPositions)
{
setup.commands.emplace_back("ucinewgame");
int ply = 1;
for (const std::string& fen : game)
{
setup.commands.emplace_back("position fen " + fen);
const int correctedTime = static_cast<int>(getCorrectedTime(ply) * timeScaleFactor);
setup.commands.emplace_back("go movetime " + std::to_string(correctedTime));
ply += 1;
}
}
return setup;
}
} // namespace Stockfish

170
src/bitbase.cpp Normal file
View File

@@ -0,0 +1,170 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include <cassert>
#include <vector>
#include <bitset>
#include "bitboard.h"
#include "types.h"
namespace {
// There are 24 possible pawn squares: files A to D and ranks from 2 to 7.
// Positions with the pawn on files E to H will be mirrored before probing.
constexpr unsigned MAX_INDEX = 2*24*64*64; // stm * psq * wksq * bksq = 196608
std::bitset<MAX_INDEX> KPKBitbase;
// A KPK bitbase index is an integer in [0, IndexMax] range
//
// Information is mapped in a way that minimizes the number of iterations:
//
// bit 0- 5: white king square (from SQ_A1 to SQ_H8)
// bit 6-11: black king square (from SQ_A1 to SQ_H8)
// bit 12: side to move (WHITE or BLACK)
// bit 13-14: white pawn file (from FILE_A to FILE_D)
// bit 15-17: white pawn RANK_7 - rank (from RANK_7 - RANK_7 to RANK_7 - RANK_2)
unsigned index(Color stm, Square bksq, Square wksq, Square psq) {
return int(wksq) | (bksq << 6) | (stm << 12) | (file_of(psq) << 13) | ((RANK_7 - rank_of(psq)) << 15);
}
enum Result {
INVALID = 0,
UNKNOWN = 1,
DRAW = 2,
WIN = 4
};
Result& operator|=(Result& r, Result v) { return r = Result(r | v); }
struct KPKPosition {
KPKPosition() = default;
explicit KPKPosition(unsigned idx);
operator Result() const { return result; }
Result classify(const std::vector<KPKPosition>& db);
Color stm;
Square ksq[COLOR_NB], psq;
Result result;
};
} // namespace
bool Bitbases::probe(Square wksq, Square wpsq, Square bksq, Color stm) {
assert(file_of(wpsq) <= FILE_D);
return KPKBitbase[index(stm, bksq, wksq, wpsq)];
}
void Bitbases::init() {
std::vector<KPKPosition> db(MAX_INDEX);
unsigned idx, repeat = 1;
// Initialize db with known win / draw positions
for (idx = 0; idx < MAX_INDEX; ++idx)
db[idx] = KPKPosition(idx);
// Iterate through the positions until none of the unknown positions can be
// changed to either wins or draws (15 cycles needed).
while (repeat)
for (repeat = idx = 0; idx < MAX_INDEX; ++idx)
repeat |= (db[idx] == UNKNOWN && db[idx].classify(db) != UNKNOWN);
// Fill the bitbase with the decisive results
for (idx = 0; idx < MAX_INDEX; ++idx)
if (db[idx] == WIN)
KPKBitbase.set(idx);
}
namespace {
KPKPosition::KPKPosition(unsigned idx) {
ksq[WHITE] = Square((idx >> 0) & 0x3F);
ksq[BLACK] = Square((idx >> 6) & 0x3F);
stm = Color ((idx >> 12) & 0x01);
psq = make_square(File((idx >> 13) & 0x3), Rank(RANK_7 - ((idx >> 15) & 0x7)));
// Invalid if two pieces are on the same square or if a king can be captured
if ( distance(ksq[WHITE], ksq[BLACK]) <= 1
|| ksq[WHITE] == psq
|| ksq[BLACK] == psq
|| (stm == WHITE && (pawn_attacks_bb(WHITE, psq) & ksq[BLACK])))
result = INVALID;
// Win if the pawn can be promoted without getting captured
else if ( stm == WHITE
&& rank_of(psq) == RANK_7
&& ksq[WHITE] != psq + NORTH
&& ( distance(ksq[BLACK], psq + NORTH) > 1
|| (distance(ksq[WHITE], psq + NORTH) == 1)))
result = WIN;
// Draw if it is stalemate or the black king can capture the pawn
else if ( stm == BLACK
&& ( !(attacks_bb<KING>(ksq[BLACK]) & ~(attacks_bb<KING>(ksq[WHITE]) | pawn_attacks_bb(WHITE, psq)))
|| (attacks_bb<KING>(ksq[BLACK]) & ~attacks_bb<KING>(ksq[WHITE]) & psq)))
result = DRAW;
// Position will be classified later
else
result = UNKNOWN;
}
Result KPKPosition::classify(const std::vector<KPKPosition>& db) {
// White to move: If one move leads to a position classified as WIN, the result
// of the current position is WIN. If all moves lead to positions classified
// as DRAW, the current position is classified as DRAW, otherwise the current
// position is classified as UNKNOWN.
//
// Black to move: If one move leads to a position classified as DRAW, the result
// of the current position is DRAW. If all moves lead to positions classified
// as WIN, the position is classified as WIN, otherwise the current position is
// classified as UNKNOWN.
const Result Good = (stm == WHITE ? WIN : DRAW);
const Result Bad = (stm == WHITE ? DRAW : WIN);
Result r = INVALID;
Bitboard b = attacks_bb<KING>(ksq[stm]);
while (b)
r |= stm == WHITE ? db[index(BLACK, ksq[BLACK] , pop_lsb(&b), psq)]
: db[index(WHITE, pop_lsb(&b), ksq[WHITE], psq)];
if (stm == WHITE)
{
if (rank_of(psq) < RANK_7) // Single push
r |= db[index(BLACK, ksq[BLACK], ksq[WHITE], psq + NORTH)];
if ( rank_of(psq) == RANK_2 // Double push
&& psq + NORTH != ksq[WHITE]
&& psq + NORTH != ksq[BLACK])
r |= db[index(BLACK, ksq[BLACK], ksq[WHITE], psq + NORTH + NORTH)];
}
return result = r & Good ? Good : r & UNKNOWN ? UNKNOWN : Bad;
}
} // namespace

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -16,171 +16,148 @@
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include "bitboard.h"
#include <algorithm>
#include <bitset>
#include <initializer_list>
#include "bitboard.h"
#include "misc.h"
namespace Stockfish {
uint8_t PopCnt16[1 << 16];
uint8_t SquareDistance[SQUARE_NB][SQUARE_NB];
Bitboard SquareBB[SQUARE_NB];
Bitboard LineBB[SQUARE_NB][SQUARE_NB];
Bitboard BetweenBB[SQUARE_NB][SQUARE_NB];
Bitboard PseudoAttacks[PIECE_TYPE_NB][SQUARE_NB];
Bitboard PawnAttacks[COLOR_NB][SQUARE_NB];
alignas(64) Magic Magics[SQUARE_NB][2];
Magic RookMagics[SQUARE_NB];
Magic BishopMagics[SQUARE_NB];
namespace {
Bitboard RookTable[0x19000]; // To store rook attacks
Bitboard BishopTable[0x1480]; // To store bishop attacks
Bitboard RookTable[0x19000]; // To store rook attacks
Bitboard BishopTable[0x1480]; // To store bishop attacks
void init_magics(PieceType pt, Bitboard table[], Magic magics[][2]);
// Returns the bitboard of target square for the given step
// from the given square. If the step is off the board, returns empty bitboard.
Bitboard safe_destination(Square s, int step) {
Square to = Square(s + step);
return is_ok(to) && distance(s, to) <= 2 ? square_bb(to) : Bitboard(0);
}
}
// Returns an ASCII representation of a bitboard suitable
// to be printed to standard output. Useful for debugging.
std::string Bitboards::pretty(Bitboard b) {
std::string s = "+---+---+---+---+---+---+---+---+\n";
for (Rank r = RANK_8; r >= RANK_1; --r)
{
for (File f = FILE_A; f <= FILE_H; ++f)
s += b & make_square(f, r) ? "| X " : "| ";
s += "| " + std::to_string(1 + r) + "\n+---+---+---+---+---+---+---+---+\n";
}
s += " a b c d e f g h\n";
return s;
void init_magics(PieceType pt, Bitboard table[], Magic magics[]);
}
// Initializes various bitboard tables. It is called at
// startup and relies on global objects to be already zero-initialized.
/// Bitboards::pretty() returns an ASCII representation of a bitboard suitable
/// to be printed to standard output. Useful for debugging.
const std::string Bitboards::pretty(Bitboard b) {
std::string s = "+---+---+---+---+---+---+---+---+\n";
for (Rank r = RANK_8; r >= RANK_1; --r)
{
for (File f = FILE_A; f <= FILE_H; ++f)
s += b & make_square(f, r) ? "| X " : "| ";
s += "| " + std::to_string(1 + r) + "\n+---+---+---+---+---+---+---+---+\n";
}
s += " a b c d e f g h\n";
return s;
}
/// Bitboards::init() initializes various bitboard tables. It is called at
/// startup and relies on global objects to be already zero-initialized.
void Bitboards::init() {
for (unsigned i = 0; i < (1 << 16); ++i)
PopCnt16[i] = uint8_t(std::bitset<16>(i).count());
for (unsigned i = 0; i < (1 << 16); ++i)
PopCnt16[i] = uint8_t(std::bitset<16>(i).count());
for (Square s1 = SQ_A1; s1 <= SQ_H8; ++s1)
for (Square s2 = SQ_A1; s2 <= SQ_H8; ++s2)
SquareDistance[s1][s2] = std::max(distance<File>(s1, s2), distance<Rank>(s1, s2));
for (Square s = SQ_A1; s <= SQ_H8; ++s)
SquareBB[s] = (1ULL << s);
init_magics(ROOK, RookTable, Magics);
init_magics(BISHOP, BishopTable, Magics);
for (Square s1 = SQ_A1; s1 <= SQ_H8; ++s1)
for (Square s2 = SQ_A1; s2 <= SQ_H8; ++s2)
SquareDistance[s1][s2] = std::max(distance<File>(s1, s2), distance<Rank>(s1, s2));
for (Square s1 = SQ_A1; s1 <= SQ_H8; ++s1)
{
PseudoAttacks[WHITE][s1] = pawn_attacks_bb<WHITE>(square_bb(s1));
PseudoAttacks[BLACK][s1] = pawn_attacks_bb<BLACK>(square_bb(s1));
init_magics(ROOK, RookTable, RookMagics);
init_magics(BISHOP, BishopTable, BishopMagics);
for (int step : {-9, -8, -7, -1, 1, 7, 8, 9})
PseudoAttacks[KING][s1] |= safe_destination(s1, step);
for (Square s1 = SQ_A1; s1 <= SQ_H8; ++s1)
{
PawnAttacks[WHITE][s1] = pawn_attacks_bb<WHITE>(square_bb(s1));
PawnAttacks[BLACK][s1] = pawn_attacks_bb<BLACK>(square_bb(s1));
for (int step : {-17, -15, -10, -6, 6, 10, 15, 17})
PseudoAttacks[KNIGHT][s1] |= safe_destination(s1, step);
for (int step : {-9, -8, -7, -1, 1, 7, 8, 9} )
PseudoAttacks[KING][s1] |= safe_destination(s1, step);
PseudoAttacks[QUEEN][s1] = PseudoAttacks[BISHOP][s1] = attacks_bb<BISHOP>(s1, 0);
PseudoAttacks[QUEEN][s1] |= PseudoAttacks[ROOK][s1] = attacks_bb<ROOK>(s1, 0);
for (int step : {-17, -15, -10, -6, 6, 10, 15, 17} )
PseudoAttacks[KNIGHT][s1] |= safe_destination(s1, step);
for (PieceType pt : {BISHOP, ROOK})
for (Square s2 = SQ_A1; s2 <= SQ_H8; ++s2)
{
if (PseudoAttacks[pt][s1] & s2)
{
LineBB[s1][s2] = (attacks_bb(pt, s1, 0) & attacks_bb(pt, s2, 0)) | s1 | s2;
BetweenBB[s1][s2] =
(attacks_bb(pt, s1, square_bb(s2)) & attacks_bb(pt, s2, square_bb(s1)));
}
BetweenBB[s1][s2] |= s2;
}
}
PseudoAttacks[QUEEN][s1] = PseudoAttacks[BISHOP][s1] = attacks_bb<BISHOP>(s1, 0);
PseudoAttacks[QUEEN][s1] |= PseudoAttacks[ ROOK][s1] = attacks_bb< ROOK>(s1, 0);
for (PieceType pt : { BISHOP, ROOK })
for (Square s2 = SQ_A1; s2 <= SQ_H8; ++s2)
if (PseudoAttacks[pt][s1] & s2)
LineBB[s1][s2] = (attacks_bb(pt, s1, 0) & attacks_bb(pt, s2, 0)) | s1 | s2;
}
}
namespace {
Bitboard sliding_attack(PieceType pt, Square sq, Bitboard occupied) {
Bitboard sliding_attack(PieceType pt, Square sq, Bitboard occupied) {
Bitboard attacks = 0;
Direction RookDirections[4] = {NORTH, SOUTH, EAST, WEST};
Bitboard attacks = 0;
Direction RookDirections[4] = {NORTH, SOUTH, EAST, WEST};
Direction BishopDirections[4] = {NORTH_EAST, SOUTH_EAST, SOUTH_WEST, NORTH_WEST};
for (Direction d : (pt == ROOK ? RookDirections : BishopDirections))
for(Direction d : (pt == ROOK ? RookDirections : BishopDirections))
{
Square s = sq;
while (safe_destination(s, d))
{
while(safe_destination(s, d) && !(occupied & s))
attacks |= (s += d);
if (occupied & s)
{
break;
}
}
}
return attacks;
}
}
// Computes all rook and bishop attacks at startup. Magic
// bitboards are used to look up attacks of sliding pieces. As a reference see
// https://www.chessprogramming.org/Magic_Bitboards. In particular, here we use
// the so called "fancy" approach.
void init_magics(PieceType pt, Bitboard table[], Magic magics[][2]) {
// init_magics() computes all rook and bishop attacks at startup. Magic
// bitboards are used to look up attacks of sliding pieces. As a reference see
// www.chessprogramming.org/Magic_Bitboards. In particular, here we use the so
// called "fancy" approach.
void init_magics(PieceType pt, Bitboard table[], Magic magics[]) {
#ifndef USE_PEXT
// Optimal PRNG seeds to pick the correct magics in the shortest time
int seeds[][RANK_NB] = {{8977, 44560, 54343, 38998, 5731, 95205, 104912, 17020},
{728, 10316, 55013, 32803, 12281, 15100, 16645, 255}};
int seeds[][RANK_NB] = { { 8977, 44560, 54343, 38998, 5731, 95205, 104912, 17020 },
{ 728, 10316, 55013, 32803, 12281, 15100, 16645, 255 } };
Bitboard occupancy[4096];
int epoch[4096] = {}, cnt = 0;
#endif
Bitboard reference[4096];
int size = 0;
Bitboard occupancy[4096], reference[4096], edges, b;
int epoch[4096] = {}, cnt = 0, size = 0;
for (Square s = SQ_A1; s <= SQ_H8; ++s)
{
// Board edges are not considered in the relevant occupancies
Bitboard edges = ((Rank1BB | Rank8BB) & ~rank_bb(s)) | ((FileABB | FileHBB) & ~file_bb(s));
edges = ((Rank1BB | Rank8BB) & ~rank_bb(s)) | ((FileABB | FileHBB) & ~file_bb(s));
// Given a square 's', the mask is the bitboard of sliding attacks from
// 's' computed on an empty board. The index must be big enough to contain
// all the attacks for each possible subset of the mask and so is 2 power
// the number of 1s of the mask. Hence we deduce the size of the shift to
// apply to the 64 or 32 bits word to get the index.
Magic& m = magics[s][pt - BISHOP];
m.mask = sliding_attack(pt, s, 0) & ~edges;
#ifndef USE_PEXT
Magic& m = magics[s];
m.mask = sliding_attack(pt, s, 0) & ~edges;
m.shift = (Is64Bit ? 64 : 32) - popcount(m.mask);
#endif
// Set the offset for the attacks table of the square. We have individual
// table sizes for each square with "Fancy Magic Bitboards".
m.attacks = s == SQ_A1 ? table : magics[s - 1][pt - BISHOP].attacks + size;
size = 0;
m.attacks = s == SQ_A1 ? table : magics[s - 1].attacks + size;
// Use Carry-Rippler trick to enumerate all subsets of masks[s] and
// store the corresponding sliding attack bitboard in reference[].
Bitboard b = 0;
do
{
#ifndef USE_PEXT
b = size = 0;
do {
occupancy[size] = b;
#endif
reference[size] = sliding_attack(pt, s, b);
if (HasPext)
@@ -190,14 +167,16 @@ void init_magics(PieceType pt, Bitboard table[], Magic magics[][2]) {
b = (b - m.mask) & m.mask;
} while (b);
#ifndef USE_PEXT
if (HasPext)
continue;
PRNG rng(seeds[Is64Bit][rank_of(s)]);
// Find a magic for square 's' picking up an (almost) random number
// until we find the one that passes the verification test.
for (int i = 0; i < size;)
for (int i = 0; i < size; )
{
for (m.magic = 0; popcount((m.magic * m.mask) >> 56) < 6;)
for (m.magic = 0; popcount((m.magic * m.mask) >> 56) < 6; )
m.magic = rng.sparse_rand<Bitboard>();
// A good magic must map every possible occupancy to an index that
@@ -212,16 +191,13 @@ void init_magics(PieceType pt, Bitboard table[], Magic magics[][2]) {
if (epoch[idx] < cnt)
{
epoch[idx] = cnt;
epoch[idx] = cnt;
m.attacks[idx] = reference[i];
}
else if (m.attacks[idx] != reference[i])
break;
}
}
#endif
}
}
}
}
} // namespace Stockfish

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -19,24 +19,26 @@
#ifndef BITBOARD_H_INCLUDED
#define BITBOARD_H_INCLUDED
#include <algorithm>
#include <cassert>
#include <cmath>
#include <cstring>
#include <cstdint>
#include <cstdlib>
#include <string>
#include "types.h"
namespace Stockfish {
namespace Bitbases {
void init();
bool probe(Square wksq, Square wpsq, Square bksq, Color us);
}
namespace Bitboards {
void init();
std::string pretty(Bitboard b);
void init();
const std::string pretty(Bitboard b);
} // namespace Stockfish::Bitboards
}
constexpr Bitboard AllSquares = ~Bitboard(0);
constexpr Bitboard DarkSquares = 0xAA55AA55AA55AA55ULL;
constexpr Bitboard FileABB = 0x0101010101010101ULL;
constexpr Bitboard FileBBB = FileABB << 1;
@@ -56,313 +58,386 @@ constexpr Bitboard Rank6BB = Rank1BB << (8 * 5);
constexpr Bitboard Rank7BB = Rank1BB << (8 * 6);
constexpr Bitboard Rank8BB = Rank1BB << (8 * 7);
constexpr Bitboard QueenSide = FileABB | FileBBB | FileCBB | FileDBB;
constexpr Bitboard CenterFiles = FileCBB | FileDBB | FileEBB | FileFBB;
constexpr Bitboard KingSide = FileEBB | FileFBB | FileGBB | FileHBB;
constexpr Bitboard Center = (FileDBB | FileEBB) & (Rank4BB | Rank5BB);
constexpr Bitboard KingFlank[FILE_NB] = {
QueenSide ^ FileDBB, QueenSide, QueenSide,
CenterFiles, CenterFiles,
KingSide, KingSide, KingSide ^ FileEBB
};
extern uint8_t PopCnt16[1 << 16];
extern uint8_t SquareDistance[SQUARE_NB][SQUARE_NB];
extern Bitboard BetweenBB[SQUARE_NB][SQUARE_NB];
extern Bitboard SquareBB[SQUARE_NB];
extern Bitboard LineBB[SQUARE_NB][SQUARE_NB];
extern Bitboard PseudoAttacks[PIECE_TYPE_NB][SQUARE_NB];
extern Bitboard PawnAttacks[COLOR_NB][SQUARE_NB];
// Magic holds all magic bitboards relevant data for a single square
/// Magic holds all magic bitboards relevant data for a single square
struct Magic {
Bitboard mask;
Bitboard* attacks;
#ifndef USE_PEXT
Bitboard magic;
unsigned shift;
#endif
Bitboard mask;
Bitboard magic;
Bitboard* attacks;
unsigned shift;
// Compute the attack's index using the 'magic bitboards' approach
unsigned index(Bitboard occupied) const {
// Compute the attack's index using the 'magic bitboards' approach
unsigned index(Bitboard occupied) const {
#ifdef USE_PEXT
if (HasPext)
return unsigned(pext(occupied, mask));
#else
if (Is64Bit)
return unsigned(((occupied & mask) * magic) >> shift);
unsigned lo = unsigned(occupied) & unsigned(mask);
unsigned hi = unsigned(occupied >> 32) & unsigned(mask >> 32);
return (lo * unsigned(magic) ^ hi * unsigned(magic >> 32)) >> shift;
#endif
}
if (Is64Bit)
return unsigned(((occupied & mask) * magic) >> shift);
Bitboard attacks_bb(Bitboard occupied) const { return attacks[index(occupied)]; }
unsigned lo = unsigned(occupied) & unsigned(mask);
unsigned hi = unsigned(occupied >> 32) & unsigned(mask >> 32);
return (lo * unsigned(magic) ^ hi * unsigned(magic >> 32)) >> shift;
}
};
extern Magic Magics[SQUARE_NB][2];
extern Magic RookMagics[SQUARE_NB];
extern Magic BishopMagics[SQUARE_NB];
constexpr Bitboard square_bb(Square s) {
assert(is_ok(s));
return (1ULL << s);
inline Bitboard square_bb(Square s) {
assert(is_ok(s));
return SquareBB[s];
}
// Overloads of bitwise operators between a Bitboard and a Square for testing
// whether a given bit is set in a bitboard, and for setting and clearing bits.
/// Overloads of bitwise operators between a Bitboard and a Square for testing
/// whether a given bit is set in a bitboard, and for setting and clearing bits.
constexpr Bitboard operator&(Bitboard b, Square s) { return b & square_bb(s); }
constexpr Bitboard operator|(Bitboard b, Square s) { return b | square_bb(s); }
constexpr Bitboard operator^(Bitboard b, Square s) { return b ^ square_bb(s); }
constexpr Bitboard& operator|=(Bitboard& b, Square s) { return b |= square_bb(s); }
constexpr Bitboard& operator^=(Bitboard& b, Square s) { return b ^= square_bb(s); }
inline Bitboard operator&( Bitboard b, Square s) { return b & square_bb(s); }
inline Bitboard operator|( Bitboard b, Square s) { return b | square_bb(s); }
inline Bitboard operator^( Bitboard b, Square s) { return b ^ square_bb(s); }
inline Bitboard& operator|=(Bitboard& b, Square s) { return b |= square_bb(s); }
inline Bitboard& operator^=(Bitboard& b, Square s) { return b ^= square_bb(s); }
constexpr Bitboard operator&(Square s, Bitboard b) { return b & s; }
constexpr Bitboard operator|(Square s, Bitboard b) { return b | s; }
constexpr Bitboard operator^(Square s, Bitboard b) { return b ^ s; }
inline Bitboard operator&(Square s, Bitboard b) { return b & s; }
inline Bitboard operator|(Square s, Bitboard b) { return b | s; }
inline Bitboard operator^(Square s, Bitboard b) { return b ^ s; }
constexpr Bitboard operator|(Square s1, Square s2) { return square_bb(s1) | s2; }
inline Bitboard operator|(Square s1, Square s2) { return square_bb(s1) | s2; }
constexpr bool more_than_one(Bitboard b) { return b & (b - 1); }
constexpr bool more_than_one(Bitboard b) {
return b & (b - 1);
}
// rank_bb() and file_bb() return a bitboard representing all the squares on
// the given file or rank.
constexpr Bitboard rank_bb(Rank r) { return Rank1BB << (8 * r); }
constexpr Bitboard rank_bb(Square s) { return rank_bb(rank_of(s)); }
constexpr Bitboard file_bb(File f) { return FileABB << f; }
constexpr Bitboard file_bb(Square s) { return file_bb(file_of(s)); }
constexpr bool opposite_colors(Square s1, Square s2) {
return (s1 + rank_of(s1) + s2 + rank_of(s2)) & 1;
}
// Moves a bitboard one or two steps as specified by the direction D
/// rank_bb() and file_bb() return a bitboard representing all the squares on
/// the given file or rank.
constexpr Bitboard rank_bb(Rank r) {
return Rank1BB << (8 * r);
}
constexpr Bitboard rank_bb(Square s) {
return rank_bb(rank_of(s));
}
constexpr Bitboard file_bb(File f) {
return FileABB << f;
}
constexpr Bitboard file_bb(Square s) {
return file_bb(file_of(s));
}
/// shift() moves a bitboard one or two steps as specified by the direction D
template<Direction D>
constexpr Bitboard shift(Bitboard b) {
return D == NORTH ? b << 8
: D == SOUTH ? b >> 8
: D == NORTH + NORTH ? b << 16
: D == SOUTH + SOUTH ? b >> 16
: D == EAST ? (b & ~FileHBB) << 1
: D == WEST ? (b & ~FileABB) >> 1
: D == NORTH_EAST ? (b & ~FileHBB) << 9
: D == NORTH_WEST ? (b & ~FileABB) << 7
: D == SOUTH_EAST ? (b & ~FileHBB) >> 7
: D == SOUTH_WEST ? (b & ~FileABB) >> 9
: 0;
return D == NORTH ? b << 8 : D == SOUTH ? b >> 8
: D == NORTH+NORTH? b <<16 : D == SOUTH+SOUTH? b >>16
: D == EAST ? (b & ~FileHBB) << 1 : D == WEST ? (b & ~FileABB) >> 1
: D == NORTH_EAST ? (b & ~FileHBB) << 9 : D == NORTH_WEST ? (b & ~FileABB) << 7
: D == SOUTH_EAST ? (b & ~FileHBB) >> 7 : D == SOUTH_WEST ? (b & ~FileABB) >> 9
: 0;
}
// Returns the squares attacked by pawns of the given color
// from the squares in the given bitboard.
/// pawn_attacks_bb() returns the squares attacked by pawns of the given color
/// from the squares in the given bitboard.
template<Color C>
constexpr Bitboard pawn_attacks_bb(Bitboard b) {
return C == WHITE ? shift<NORTH_WEST>(b) | shift<NORTH_EAST>(b)
: shift<SOUTH_WEST>(b) | shift<SOUTH_EAST>(b);
return C == WHITE ? shift<NORTH_WEST>(b) | shift<NORTH_EAST>(b)
: shift<SOUTH_WEST>(b) | shift<SOUTH_EAST>(b);
}
inline Bitboard pawn_attacks_bb(Color c, Square s) {
assert(is_ok(s));
return PawnAttacks[c][s];
}
// Returns a bitboard representing an entire line (from board edge
// to board edge) that intersects the two given squares. If the given squares
// are not on a same file/rank/diagonal, the function returns 0. For instance,
// line_bb(SQ_C4, SQ_F7) will return a bitboard with the A2-G8 diagonal.
/// pawn_double_attacks_bb() returns the squares doubly attacked by pawns of the
/// given color from the squares in the given bitboard.
template<Color C>
constexpr Bitboard pawn_double_attacks_bb(Bitboard b) {
return C == WHITE ? shift<NORTH_WEST>(b) & shift<NORTH_EAST>(b)
: shift<SOUTH_WEST>(b) & shift<SOUTH_EAST>(b);
}
/// adjacent_files_bb() returns a bitboard representing all the squares on the
/// adjacent files of a given square.
constexpr Bitboard adjacent_files_bb(Square s) {
return shift<EAST>(file_bb(s)) | shift<WEST>(file_bb(s));
}
/// line_bb() returns a bitboard representing an entire line (from board edge
/// to board edge) that intersects the two given squares. If the given squares
/// are not on a same file/rank/diagonal, the function returns 0. For instance,
/// line_bb(SQ_C4, SQ_F7) will return a bitboard with the A2-G8 diagonal.
inline Bitboard line_bb(Square s1, Square s2) {
assert(is_ok(s1) && is_ok(s2));
return LineBB[s1][s2];
assert(is_ok(s1) && is_ok(s2));
return LineBB[s1][s2];
}
// Returns a bitboard representing the squares in the semi-open
// segment between the squares s1 and s2 (excluding s1 but including s2). If the
// given squares are not on a same file/rank/diagonal, it returns s2. For instance,
// between_bb(SQ_C4, SQ_F7) will return a bitboard with squares D5, E6 and F7, but
// between_bb(SQ_E6, SQ_F8) will return a bitboard with the square F8. This trick
// allows to generate non-king evasion moves faster: the defending piece must either
// interpose itself to cover the check or capture the checking piece.
/// between_bb() returns a bitboard representing squares that are linearly
/// between the two given squares (excluding the given squares). If the given
/// squares are not on a same file/rank/diagonal, we return 0. For instance,
/// between_bb(SQ_C4, SQ_F7) will return a bitboard with squares D5 and E6.
inline Bitboard between_bb(Square s1, Square s2) {
assert(is_ok(s1) && is_ok(s2));
return BetweenBB[s1][s2];
Bitboard b = line_bb(s1, s2) & ((AllSquares << s1) ^ (AllSquares << s2));
return b & (b - 1); //exclude lsb
}
// Returns true if the squares s1, s2 and s3 are aligned either on a
// straight or on a diagonal line.
inline bool aligned(Square s1, Square s2, Square s3) { return line_bb(s1, s2) & s3; }
/// forward_ranks_bb() returns a bitboard representing the squares on the ranks
/// in front of the given one, from the point of view of the given color. For instance,
/// forward_ranks_bb(BLACK, SQ_D3) will return the 16 squares on ranks 1 and 2.
// distance() functions return the distance between x and y, defined as the
// number of steps for a king in x to reach y.
template<typename T1 = Square>
inline int distance(Square x, Square y);
template<>
inline int distance<File>(Square x, Square y) {
return std::abs(file_of(x) - file_of(y));
constexpr Bitboard forward_ranks_bb(Color c, Square s) {
return c == WHITE ? ~Rank1BB << 8 * relative_rank(WHITE, s)
: ~Rank8BB >> 8 * relative_rank(BLACK, s);
}
template<>
inline int distance<Rank>(Square x, Square y) {
return std::abs(rank_of(x) - rank_of(y));
/// forward_file_bb() returns a bitboard representing all the squares along the
/// line in front of the given one, from the point of view of the given color.
constexpr Bitboard forward_file_bb(Color c, Square s) {
return forward_ranks_bb(c, s) & file_bb(s);
}
template<>
inline int distance<Square>(Square x, Square y) {
return SquareDistance[x][y];
/// pawn_attack_span() returns a bitboard representing all the squares that can
/// be attacked by a pawn of the given color when it moves along its file, starting
/// from the given square.
constexpr Bitboard pawn_attack_span(Color c, Square s) {
return forward_ranks_bb(c, s) & adjacent_files_bb(s);
}
/// passed_pawn_span() returns a bitboard which can be used to test if a pawn of
/// the given color and on the given square is a passed pawn.
constexpr Bitboard passed_pawn_span(Color c, Square s) {
return pawn_attack_span(c, s) | forward_file_bb(c, s);
}
/// aligned() returns true if the squares s1, s2 and s3 are aligned either on a
/// straight or on a diagonal line.
inline bool aligned(Square s1, Square s2, Square s3) {
return line_bb(s1, s2) & s3;
}
/// distance() functions return the distance between x and y, defined as the
/// number of steps for a king in x to reach y.
template<typename T1 = Square> inline int distance(Square x, Square y);
template<> inline int distance<File>(Square x, Square y) { return std::abs(file_of(x) - file_of(y)); }
template<> inline int distance<Rank>(Square x, Square y) { return std::abs(rank_of(x) - rank_of(y)); }
template<> inline int distance<Square>(Square x, Square y) { return SquareDistance[x][y]; }
inline int edge_distance(File f) { return std::min(f, File(FILE_H - f)); }
inline int edge_distance(Rank r) { return std::min(r, Rank(RANK_8 - r)); }
// Returns the pseudo attacks of the given piece type
// assuming an empty board.
template<PieceType Pt>
inline Bitboard attacks_bb(Square s, Color c = COLOR_NB) {
assert((Pt != PAWN || c < COLOR_NB) && (is_ok(s)));
return Pt == PAWN ? PseudoAttacks[c][s] : PseudoAttacks[Pt][s];
/// safe_destination() returns the bitboard of target square for the given step
/// from the given square. If the step is off the board, returns empty bitboard.
inline Bitboard safe_destination(Square s, int step)
{
Square to = Square(s + step);
return is_ok(to) && distance(s, to) <= 2 ? square_bb(to) : Bitboard(0);
}
// Returns the attacks by the given piece
// assuming the board is occupied according to the passed Bitboard.
// Sliding piece attacks do not continue passed an occupied square.
/// attacks_bb(Square) returns the pseudo attacks of the give piece type
/// assuming an empty board.
template<PieceType Pt>
inline Bitboard attacks_bb(Square s) {
assert((Pt != PAWN) && (is_ok(s)));
return PseudoAttacks[Pt][s];
}
/// attacks_bb(Square, Bitboard) returns the attacks by the given piece
/// assuming the board is occupied according to the passed Bitboard.
/// Sliding piece attacks do not continue passed an occupied square.
template<PieceType Pt>
inline Bitboard attacks_bb(Square s, Bitboard occupied) {
assert((Pt != PAWN) && (is_ok(s)));
assert((Pt != PAWN) && (is_ok(s)));
switch (Pt)
{
case BISHOP :
case ROOK :
return Magics[s][Pt - BISHOP].attacks_bb(occupied);
case QUEEN :
return attacks_bb<BISHOP>(s, occupied) | attacks_bb<ROOK>(s, occupied);
default :
return PseudoAttacks[Pt][s];
}
switch (Pt)
{
case BISHOP: return BishopMagics[s].attacks[BishopMagics[s].index(occupied)];
case ROOK : return RookMagics[s].attacks[ RookMagics[s].index(occupied)];
case QUEEN : return attacks_bb<BISHOP>(s, occupied) | attacks_bb<ROOK>(s, occupied);
default : return PseudoAttacks[Pt][s];
}
}
// Returns the attacks by the given piece
// assuming the board is occupied according to the passed Bitboard.
// Sliding piece attacks do not continue passed an occupied square.
inline Bitboard attacks_bb(PieceType pt, Square s, Bitboard occupied) {
assert((pt != PAWN) && (is_ok(s)));
assert((pt != PAWN) && (is_ok(s)));
switch (pt)
{
case BISHOP :
return attacks_bb<BISHOP>(s, occupied);
case ROOK :
return attacks_bb<ROOK>(s, occupied);
case QUEEN :
return attacks_bb<BISHOP>(s, occupied) | attacks_bb<ROOK>(s, occupied);
default :
return PseudoAttacks[pt][s];
}
switch (pt)
{
case BISHOP: return attacks_bb<BISHOP>(s, occupied);
case ROOK : return attacks_bb< ROOK>(s, occupied);
case QUEEN : return attacks_bb<BISHOP>(s, occupied) | attacks_bb<ROOK>(s, occupied);
default : return PseudoAttacks[pt][s];
}
}
// Counts the number of non-zero bits in a bitboard.
/// popcount() counts the number of non-zero bits in a bitboard
inline int popcount(Bitboard b) {
#ifndef USE_POPCNT
std::uint16_t indices[4];
std::memcpy(indices, &b, sizeof(b));
return PopCnt16[indices[0]] + PopCnt16[indices[1]] + PopCnt16[indices[2]]
+ PopCnt16[indices[3]];
union { Bitboard bb; uint16_t u[4]; } v = { b };
return PopCnt16[v.u[0]] + PopCnt16[v.u[1]] + PopCnt16[v.u[2]] + PopCnt16[v.u[3]];
#elif defined(_MSC_VER)
#elif defined(_MSC_VER) || defined(__INTEL_COMPILER)
return int(_mm_popcnt_u64(b));
return (int)_mm_popcnt_u64(b);
#else // Assumed gcc or compatible compiler
#else // Assumed gcc or compatible compiler
return __builtin_popcountll(b);
return __builtin_popcountll(b);
#endif
}
// Returns the least significant bit in a non-zero bitboard.
/// lsb() and msb() return the least/most significant bit in a non-zero bitboard
#if defined(__GNUC__) // GCC, Clang, ICC
inline Square lsb(Bitboard b) {
assert(b);
#if defined(__GNUC__) // GCC, Clang, ICX
return Square(__builtin_ctzll(b));
#elif defined(_MSC_VER)
#ifdef _WIN64 // MSVC, WIN64
unsigned long idx;
_BitScanForward64(&idx, b);
return Square(idx);
#else // MSVC, WIN32
unsigned long idx;
if (b & 0xffffffff)
{
_BitScanForward(&idx, int32_t(b));
return Square(idx);
}
else
{
_BitScanForward(&idx, int32_t(b >> 32));
return Square(idx + 32);
}
#endif
#else // Compiler is neither GCC nor MSVC compatible
#error "Compiler not supported."
#endif
assert(b);
return Square(__builtin_ctzll(b));
}
// Returns the most significant bit in a non-zero bitboard.
inline Square msb(Bitboard b) {
assert(b);
assert(b);
return Square(63 ^ __builtin_clzll(b));
}
#if defined(__GNUC__) // GCC, Clang, ICX
#elif defined(_MSC_VER) // MSVC
return Square(63 ^ __builtin_clzll(b));
#ifdef _WIN64 // MSVC, WIN64
#elif defined(_MSC_VER)
#ifdef _WIN64 // MSVC, WIN64
inline Square lsb(Bitboard b) {
assert(b);
unsigned long idx;
_BitScanForward64(&idx, b);
return (Square) idx;
}
unsigned long idx;
_BitScanReverse64(&idx, b);
return Square(idx);
inline Square msb(Bitboard b) {
assert(b);
unsigned long idx;
_BitScanReverse64(&idx, b);
return (Square) idx;
}
#else // MSVC, WIN32
#else // MSVC, WIN32
unsigned long idx;
inline Square lsb(Bitboard b) {
assert(b);
unsigned long idx;
if (b & 0xffffffff) {
_BitScanForward(&idx, int32_t(b));
return Square(idx);
} else {
_BitScanForward(&idx, int32_t(b >> 32));
return Square(idx + 32);
}
}
inline Square msb(Bitboard b) {
assert(b);
unsigned long idx;
if (b >> 32) {
_BitScanReverse(&idx, int32_t(b >> 32));
return Square(idx + 32);
} else {
_BitScanReverse(&idx, int32_t(b));
return Square(idx);
}
}
if (b >> 32)
{
_BitScanReverse(&idx, int32_t(b >> 32));
return Square(idx + 32);
}
else
{
_BitScanReverse(&idx, int32_t(b));
return Square(idx);
}
#endif
#else // Compiler is neither GCC nor MSVC compatible
#error "Compiler not supported."
#endif
#else // Compiler is neither GCC nor MSVC compatible
#error "Compiler not supported."
#endif
/// pop_lsb() finds and clears the least significant bit in a non-zero bitboard
inline Square pop_lsb(Bitboard* b) {
assert(*b);
const Square s = lsb(*b);
*b &= *b - 1;
return s;
}
// Returns the bitboard of the least significant
// square of a non-zero bitboard. It is equivalent to square_bb(lsb(bb)).
inline Bitboard least_significant_square_bb(Bitboard b) {
assert(b);
return b & -b;
/// frontmost_sq() returns the most advanced square for the given color,
/// requires a non-zero bitboard.
inline Square frontmost_sq(Color c, Bitboard b) {
assert(b);
return c == WHITE ? msb(b) : lsb(b);
}
// Finds and clears the least significant bit in a non-zero bitboard.
inline Square pop_lsb(Bitboard& b) {
assert(b);
const Square s = lsb(b);
b &= b - 1;
return s;
}
} // namespace Stockfish
#endif // #ifndef BITBOARD_H_INCLUDED
#endif // #ifndef BITBOARD_H_INCLUDED

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/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include <cassert>
#include "bitboard.h"
#include "endgame.h"
#include "movegen.h"
namespace {
// Used to drive the king towards the edge of the board
// in KX vs K and KQ vs KR endgames.
// Values range from 27 (center squares) to 90 (in the corners)
inline int push_to_edge(Square s) {
int rd = edge_distance(rank_of(s)), fd = edge_distance(file_of(s));
return 90 - (7 * fd * fd / 2 + 7 * rd * rd / 2);
}
// Used to drive the king towards A1H8 corners in KBN vs K endgames.
// Values range from 0 on A8H1 diagonal to 7 in A1H8 corners
inline int push_to_corner(Square s) {
return abs(7 - rank_of(s) - file_of(s));
}
// Drive a piece close to or away from another piece
inline int push_close(Square s1, Square s2) { return 140 - 20 * distance(s1, s2); }
inline int push_away(Square s1, Square s2) { return 120 - push_close(s1, s2); }
#ifndef NDEBUG
bool verify_material(const Position& pos, Color c, Value npm, int pawnsCnt) {
return pos.non_pawn_material(c) == npm && pos.count<PAWN>(c) == pawnsCnt;
}
#endif
// Map the square as if strongSide is white and strongSide's only pawn
// is on the left half of the board.
Square normalize(const Position& pos, Color strongSide, Square sq) {
assert(pos.count<PAWN>(strongSide) == 1);
if (file_of(pos.square<PAWN>(strongSide)) >= FILE_E)
sq = flip_file(sq);
return strongSide == WHITE ? sq : flip_rank(sq);
}
} // namespace
namespace Endgames {
std::pair<Map<Value>, Map<ScaleFactor>> maps;
void init() {
add<KPK>("KPK");
add<KNNK>("KNNK");
add<KBNK>("KBNK");
add<KRKP>("KRKP");
add<KRKB>("KRKB");
add<KRKN>("KRKN");
add<KQKP>("KQKP");
add<KQKR>("KQKR");
add<KNNKP>("KNNKP");
add<KRPKR>("KRPKR");
add<KRPKB>("KRPKB");
add<KBPKB>("KBPKB");
add<KBPKN>("KBPKN");
add<KBPPKB>("KBPPKB");
add<KRPPKRP>("KRPPKRP");
}
}
/// Mate with KX vs K. This function is used to evaluate positions with
/// king and plenty of material vs a lone king. It simply gives the
/// attacking side a bonus for driving the defending king towards the edge
/// of the board, and for keeping the distance between the two kings small.
template<>
Value Endgame<KXK>::operator()(const Position& pos) const {
assert(verify_material(pos, weakSide, VALUE_ZERO, 0));
assert(!pos.checkers()); // Eval is never called when in check
// Stalemate detection with lone king
if (pos.side_to_move() == weakSide && !MoveList<LEGAL>(pos).size())
return VALUE_DRAW;
Square strongKing = pos.square<KING>(strongSide);
Square weakKing = pos.square<KING>(weakSide);
Value result = pos.non_pawn_material(strongSide)
+ pos.count<PAWN>(strongSide) * PawnValueEg
+ push_to_edge(weakKing)
+ push_close(strongKing, weakKing);
if ( pos.count<QUEEN>(strongSide)
|| pos.count<ROOK>(strongSide)
||(pos.count<BISHOP>(strongSide) && pos.count<KNIGHT>(strongSide))
|| ( (pos.pieces(strongSide, BISHOP) & ~DarkSquares)
&& (pos.pieces(strongSide, BISHOP) & DarkSquares)))
result = std::min(result + VALUE_KNOWN_WIN, VALUE_TB_WIN_IN_MAX_PLY - 1);
return strongSide == pos.side_to_move() ? result : -result;
}
/// Mate with KBN vs K. This is similar to KX vs K, but we have to drive the
/// defending king towards a corner square that our bishop attacks.
template<>
Value Endgame<KBNK>::operator()(const Position& pos) const {
assert(verify_material(pos, strongSide, KnightValueMg + BishopValueMg, 0));
assert(verify_material(pos, weakSide, VALUE_ZERO, 0));
Square strongKing = pos.square<KING>(strongSide);
Square strongBishop = pos.square<BISHOP>(strongSide);
Square weakKing = pos.square<KING>(weakSide);
// If our bishop does not attack A1/H8, we flip the enemy king square
// to drive to opposite corners (A8/H1).
Value result = (VALUE_KNOWN_WIN + 3520)
+ push_close(strongKing, weakKing)
+ 420 * push_to_corner(opposite_colors(strongBishop, SQ_A1) ? flip_file(weakKing) : weakKing);
assert(abs(result) < VALUE_TB_WIN_IN_MAX_PLY);
return strongSide == pos.side_to_move() ? result : -result;
}
/// KP vs K. This endgame is evaluated with the help of a bitbase
template<>
Value Endgame<KPK>::operator()(const Position& pos) const {
assert(verify_material(pos, strongSide, VALUE_ZERO, 1));
assert(verify_material(pos, weakSide, VALUE_ZERO, 0));
// Assume strongSide is white and the pawn is on files A-D
Square strongKing = normalize(pos, strongSide, pos.square<KING>(strongSide));
Square strongPawn = normalize(pos, strongSide, pos.square<PAWN>(strongSide));
Square weakKing = normalize(pos, strongSide, pos.square<KING>(weakSide));
Color us = strongSide == pos.side_to_move() ? WHITE : BLACK;
if (!Bitbases::probe(strongKing, strongPawn, weakKing, us))
return VALUE_DRAW;
Value result = VALUE_KNOWN_WIN + PawnValueEg + Value(rank_of(strongPawn));
return strongSide == pos.side_to_move() ? result : -result;
}
/// KR vs KP. This is a somewhat tricky endgame to evaluate precisely without
/// a bitbase. The function below returns drawish scores when the pawn is
/// far advanced with support of the king, while the attacking king is far
/// away.
template<>
Value Endgame<KRKP>::operator()(const Position& pos) const {
assert(verify_material(pos, strongSide, RookValueMg, 0));
assert(verify_material(pos, weakSide, VALUE_ZERO, 1));
Square strongKing = pos.square<KING>(strongSide);
Square weakKing = pos.square<KING>(weakSide);
Square strongRook = pos.square<ROOK>(strongSide);
Square weakPawn = pos.square<PAWN>(weakSide);
Square queeningSquare = make_square(file_of(weakPawn), relative_rank(weakSide, RANK_8));
Value result;
// If the stronger side's king is in front of the pawn, it's a win
if (forward_file_bb(strongSide, strongKing) & weakPawn)
result = RookValueEg - distance(strongKing, weakPawn);
// If the weaker side's king is too far from the pawn and the rook,
// it's a win.
else if ( distance(weakKing, weakPawn) >= 3 + (pos.side_to_move() == weakSide)
&& distance(weakKing, strongRook) >= 3)
result = RookValueEg - distance(strongKing, weakPawn);
// If the pawn is far advanced and supported by the defending king,
// the position is drawish
else if ( relative_rank(strongSide, weakKing) <= RANK_3
&& distance(weakKing, weakPawn) == 1
&& relative_rank(strongSide, strongKing) >= RANK_4
&& distance(strongKing, weakPawn) > 2 + (pos.side_to_move() == strongSide))
result = Value(80) - 8 * distance(strongKing, weakPawn);
else
result = Value(200) - 8 * ( distance(strongKing, weakPawn + pawn_push(weakSide))
- distance(weakKing, weakPawn + pawn_push(weakSide))
- distance(weakPawn, queeningSquare));
return strongSide == pos.side_to_move() ? result : -result;
}
/// KR vs KB. This is very simple, and always returns drawish scores. The
/// score is slightly bigger when the defending king is close to the edge.
template<>
Value Endgame<KRKB>::operator()(const Position& pos) const {
assert(verify_material(pos, strongSide, RookValueMg, 0));
assert(verify_material(pos, weakSide, BishopValueMg, 0));
Value result = Value(push_to_edge(pos.square<KING>(weakSide)));
return strongSide == pos.side_to_move() ? result : -result;
}
/// KR vs KN. The attacking side has slightly better winning chances than
/// in KR vs KB, particularly if the king and the knight are far apart.
template<>
Value Endgame<KRKN>::operator()(const Position& pos) const {
assert(verify_material(pos, strongSide, RookValueMg, 0));
assert(verify_material(pos, weakSide, KnightValueMg, 0));
Square weakKing = pos.square<KING>(weakSide);
Square weakKnight = pos.square<KNIGHT>(weakSide);
Value result = Value(push_to_edge(weakKing) + push_away(weakKing, weakKnight));
return strongSide == pos.side_to_move() ? result : -result;
}
/// KQ vs KP. In general, this is a win for the stronger side, but there are a
/// few important exceptions. A pawn on 7th rank and on the A,C,F or H files
/// with a king positioned next to it can be a draw, so in that case, we only
/// use the distance between the kings.
template<>
Value Endgame<KQKP>::operator()(const Position& pos) const {
assert(verify_material(pos, strongSide, QueenValueMg, 0));
assert(verify_material(pos, weakSide, VALUE_ZERO, 1));
Square strongKing = pos.square<KING>(strongSide);
Square weakKing = pos.square<KING>(weakSide);
Square weakPawn = pos.square<PAWN>(weakSide);
Value result = Value(push_close(strongKing, weakKing));
if ( relative_rank(weakSide, weakPawn) != RANK_7
|| distance(weakKing, weakPawn) != 1
|| ((FileBBB | FileDBB | FileEBB | FileGBB) & weakPawn))
result += QueenValueEg - PawnValueEg;
return strongSide == pos.side_to_move() ? result : -result;
}
/// KQ vs KR. This is almost identical to KX vs K: we give the attacking
/// king a bonus for having the kings close together, and for forcing the
/// defending king towards the edge. If we also take care to avoid null move for
/// the defending side in the search, this is usually sufficient to win KQ vs KR.
template<>
Value Endgame<KQKR>::operator()(const Position& pos) const {
assert(verify_material(pos, strongSide, QueenValueMg, 0));
assert(verify_material(pos, weakSide, RookValueMg, 0));
Square strongKing = pos.square<KING>(strongSide);
Square weakKing = pos.square<KING>(weakSide);
Value result = QueenValueEg
- RookValueEg
+ push_to_edge(weakKing)
+ push_close(strongKing, weakKing);
return strongSide == pos.side_to_move() ? result : -result;
}
/// KNN vs KP. Very drawish, but there are some mate opportunities if we can
/// press the weakSide King to a corner before the pawn advances too much.
template<>
Value Endgame<KNNKP>::operator()(const Position& pos) const {
assert(verify_material(pos, strongSide, 2 * KnightValueMg, 0));
assert(verify_material(pos, weakSide, VALUE_ZERO, 1));
Square weakKing = pos.square<KING>(weakSide);
Square weakPawn = pos.square<PAWN>(weakSide);
Value result = PawnValueEg
+ 2 * push_to_edge(weakKing)
- 10 * relative_rank(weakSide, weakPawn);
return strongSide == pos.side_to_move() ? result : -result;
}
/// Some cases of trivial draws
template<> Value Endgame<KNNK>::operator()(const Position&) const { return VALUE_DRAW; }
/// KB and one or more pawns vs K. It checks for draws with rook pawns and
/// a bishop of the wrong color. If such a draw is detected, SCALE_FACTOR_DRAW
/// is returned. If not, the return value is SCALE_FACTOR_NONE, i.e. no scaling
/// will be used.
template<>
ScaleFactor Endgame<KBPsK>::operator()(const Position& pos) const {
assert(pos.non_pawn_material(strongSide) == BishopValueMg);
assert(pos.count<PAWN>(strongSide) >= 1);
// No assertions about the material of weakSide, because we want draws to
// be detected even when the weaker side has some pawns.
Bitboard strongPawns = pos.pieces(strongSide, PAWN);
Bitboard allPawns = pos.pieces(PAWN);
Square strongBishop = pos.square<BISHOP>(strongSide);
Square weakKing = pos.square<KING>(weakSide);
Square strongKing = pos.square<KING>(strongSide);
// All strongSide pawns are on a single rook file?
if (!(strongPawns & ~FileABB) || !(strongPawns & ~FileHBB))
{
Square queeningSquare = relative_square(strongSide, make_square(file_of(lsb(strongPawns)), RANK_8));
if ( opposite_colors(queeningSquare, strongBishop)
&& distance(queeningSquare, weakKing) <= 1)
return SCALE_FACTOR_DRAW;
}
// If all the pawns are on the same B or G file, then it's potentially a draw
if ((!(allPawns & ~FileBBB) || !(allPawns & ~FileGBB))
&& pos.non_pawn_material(weakSide) == 0
&& pos.count<PAWN>(weakSide) >= 1)
{
// Get the least advanced weakSide pawn
Square weakPawn = frontmost_sq(strongSide, pos.pieces(weakSide, PAWN));
// There's potential for a draw if our pawn is blocked on the 7th rank,
// the bishop cannot attack it or they only have one pawn left.
if ( relative_rank(strongSide, weakPawn) == RANK_7
&& (strongPawns & (weakPawn + pawn_push(weakSide)))
&& (opposite_colors(strongBishop, weakPawn) || !more_than_one(strongPawns)))
{
int strongKingDist = distance(weakPawn, strongKing);
int weakKingDist = distance(weakPawn, weakKing);
// It's a draw if the weak king is on its back two ranks, within 2
// squares of the blocking pawn and the strong king is not
// closer. (I think this rule only fails in practically
// unreachable positions such as 5k1K/6p1/6P1/8/8/3B4/8/8 w
// and positions where qsearch will immediately correct the
// problem such as 8/4k1p1/6P1/1K6/3B4/8/8/8 w).
if ( relative_rank(strongSide, weakKing) >= RANK_7
&& weakKingDist <= 2
&& weakKingDist <= strongKingDist)
return SCALE_FACTOR_DRAW;
}
}
return SCALE_FACTOR_NONE;
}
/// KQ vs KR and one or more pawns. It tests for fortress draws with a rook on
/// the third rank defended by a pawn.
template<>
ScaleFactor Endgame<KQKRPs>::operator()(const Position& pos) const {
assert(verify_material(pos, strongSide, QueenValueMg, 0));
assert(pos.count<ROOK>(weakSide) == 1);
assert(pos.count<PAWN>(weakSide) >= 1);
Square strongKing = pos.square<KING>(strongSide);
Square weakKing = pos.square<KING>(weakSide);
Square weakRook = pos.square<ROOK>(weakSide);
if ( relative_rank(weakSide, weakKing) <= RANK_2
&& relative_rank(weakSide, strongKing) >= RANK_4
&& relative_rank(weakSide, weakRook) == RANK_3
&& ( pos.pieces(weakSide, PAWN)
& attacks_bb<KING>(weakKing)
& pawn_attacks_bb(strongSide, weakRook)))
return SCALE_FACTOR_DRAW;
return SCALE_FACTOR_NONE;
}
/// KRP vs KR. This function knows a handful of the most important classes of
/// drawn positions, but is far from perfect. It would probably be a good idea
/// to add more knowledge in the future.
///
/// It would also be nice to rewrite the actual code for this function,
/// which is mostly copied from Glaurung 1.x, and isn't very pretty.
template<>
ScaleFactor Endgame<KRPKR>::operator()(const Position& pos) const {
assert(verify_material(pos, strongSide, RookValueMg, 1));
assert(verify_material(pos, weakSide, RookValueMg, 0));
// Assume strongSide is white and the pawn is on files A-D
Square strongKing = normalize(pos, strongSide, pos.square<KING>(strongSide));
Square strongRook = normalize(pos, strongSide, pos.square<ROOK>(strongSide));
Square strongPawn = normalize(pos, strongSide, pos.square<PAWN>(strongSide));
Square weakKing = normalize(pos, strongSide, pos.square<KING>(weakSide));
Square weakRook = normalize(pos, strongSide, pos.square<ROOK>(weakSide));
File pawnFile = file_of(strongPawn);
Rank pawnRank = rank_of(strongPawn);
Square queeningSquare = make_square(pawnFile, RANK_8);
int tempo = (pos.side_to_move() == strongSide);
// If the pawn is not too far advanced and the defending king defends the
// queening square, use the third-rank defence.
if ( pawnRank <= RANK_5
&& distance(weakKing, queeningSquare) <= 1
&& strongKing <= SQ_H5
&& (rank_of(weakRook) == RANK_6 || (pawnRank <= RANK_3 && rank_of(strongRook) != RANK_6)))
return SCALE_FACTOR_DRAW;
// The defending side saves a draw by checking from behind in case the pawn
// has advanced to the 6th rank with the king behind.
if ( pawnRank == RANK_6
&& distance(weakKing, queeningSquare) <= 1
&& rank_of(strongKing) + tempo <= RANK_6
&& (rank_of(weakRook) == RANK_1 || (!tempo && distance<File>(weakRook, strongPawn) >= 3)))
return SCALE_FACTOR_DRAW;
if ( pawnRank >= RANK_6
&& weakKing == queeningSquare
&& rank_of(weakRook) == RANK_1
&& (!tempo || distance(strongKing, strongPawn) >= 2))
return SCALE_FACTOR_DRAW;
// White pawn on a7 and rook on a8 is a draw if black's king is on g7 or h7
// and the black rook is behind the pawn.
if ( strongPawn == SQ_A7
&& strongRook == SQ_A8
&& (weakKing == SQ_H7 || weakKing == SQ_G7)
&& file_of(weakRook) == FILE_A
&& (rank_of(weakRook) <= RANK_3 || file_of(strongKing) >= FILE_D || rank_of(strongKing) <= RANK_5))
return SCALE_FACTOR_DRAW;
// If the defending king blocks the pawn and the attacking king is too far
// away, it's a draw.
if ( pawnRank <= RANK_5
&& weakKing == strongPawn + NORTH
&& distance(strongKing, strongPawn) - tempo >= 2
&& distance(strongKing, weakRook) - tempo >= 2)
return SCALE_FACTOR_DRAW;
// Pawn on the 7th rank supported by the rook from behind usually wins if the
// attacking king is closer to the queening square than the defending king,
// and the defending king cannot gain tempi by threatening the attacking rook.
if ( pawnRank == RANK_7
&& pawnFile != FILE_A
&& file_of(strongRook) == pawnFile
&& strongRook != queeningSquare
&& (distance(strongKing, queeningSquare) < distance(weakKing, queeningSquare) - 2 + tempo)
&& (distance(strongKing, queeningSquare) < distance(weakKing, strongRook) + tempo))
return ScaleFactor(SCALE_FACTOR_MAX - 2 * distance(strongKing, queeningSquare));
// Similar to the above, but with the pawn further back
if ( pawnFile != FILE_A
&& file_of(strongRook) == pawnFile
&& strongRook < strongPawn
&& (distance(strongKing, queeningSquare) < distance(weakKing, queeningSquare) - 2 + tempo)
&& (distance(strongKing, strongPawn + NORTH) < distance(weakKing, strongPawn + NORTH) - 2 + tempo)
&& ( distance(weakKing, strongRook) + tempo >= 3
|| ( distance(strongKing, queeningSquare) < distance(weakKing, strongRook) + tempo
&& (distance(strongKing, strongPawn + NORTH) < distance(weakKing, strongPawn) + tempo))))
return ScaleFactor( SCALE_FACTOR_MAX
- 8 * distance(strongPawn, queeningSquare)
- 2 * distance(strongKing, queeningSquare));
// If the pawn is not far advanced and the defending king is somewhere in
// the pawn's path, it's probably a draw.
if (pawnRank <= RANK_4 && weakKing > strongPawn)
{
if (file_of(weakKing) == file_of(strongPawn))
return ScaleFactor(10);
if ( distance<File>(weakKing, strongPawn) == 1
&& distance(strongKing, weakKing) > 2)
return ScaleFactor(24 - 2 * distance(strongKing, weakKing));
}
return SCALE_FACTOR_NONE;
}
template<>
ScaleFactor Endgame<KRPKB>::operator()(const Position& pos) const {
assert(verify_material(pos, strongSide, RookValueMg, 1));
assert(verify_material(pos, weakSide, BishopValueMg, 0));
// Test for a rook pawn
if (pos.pieces(PAWN) & (FileABB | FileHBB))
{
Square weakKing = pos.square<KING>(weakSide);
Square weakBishop = pos.square<BISHOP>(weakSide);
Square strongKing = pos.square<KING>(strongSide);
Square strongPawn = pos.square<PAWN>(strongSide);
Rank pawnRank = relative_rank(strongSide, strongPawn);
Direction push = pawn_push(strongSide);
// If the pawn is on the 5th rank and the pawn (currently) is on
// the same color square as the bishop then there is a chance of
// a fortress. Depending on the king position give a moderate
// reduction or a stronger one if the defending king is near the
// corner but not trapped there.
if (pawnRank == RANK_5 && !opposite_colors(weakBishop, strongPawn))
{
int d = distance(strongPawn + 3 * push, weakKing);
if (d <= 2 && !(d == 0 && weakKing == strongKing + 2 * push))
return ScaleFactor(24);
else
return ScaleFactor(48);
}
// When the pawn has moved to the 6th rank we can be fairly sure
// it's drawn if the bishop attacks the square in front of the
// pawn from a reasonable distance and the defending king is near
// the corner
if ( pawnRank == RANK_6
&& distance(strongPawn + 2 * push, weakKing) <= 1
&& (attacks_bb<BISHOP>(weakBishop) & (strongPawn + push))
&& distance<File>(weakBishop, strongPawn) >= 2)
return ScaleFactor(8);
}
return SCALE_FACTOR_NONE;
}
/// KRPP vs KRP. There is just a single rule: if the stronger side has no passed
/// pawns and the defending king is actively placed, the position is drawish.
template<>
ScaleFactor Endgame<KRPPKRP>::operator()(const Position& pos) const {
assert(verify_material(pos, strongSide, RookValueMg, 2));
assert(verify_material(pos, weakSide, RookValueMg, 1));
Square strongPawn1 = pos.squares<PAWN>(strongSide)[0];
Square strongPawn2 = pos.squares<PAWN>(strongSide)[1];
Square weakKing = pos.square<KING>(weakSide);
// Does the stronger side have a passed pawn?
if (pos.pawn_passed(strongSide, strongPawn1) || pos.pawn_passed(strongSide, strongPawn2))
return SCALE_FACTOR_NONE;
Rank pawnRank = std::max(relative_rank(strongSide, strongPawn1), relative_rank(strongSide, strongPawn2));
if ( distance<File>(weakKing, strongPawn1) <= 1
&& distance<File>(weakKing, strongPawn2) <= 1
&& relative_rank(strongSide, weakKing) > pawnRank)
{
assert(pawnRank > RANK_1 && pawnRank < RANK_7);
return ScaleFactor(7 * pawnRank);
}
return SCALE_FACTOR_NONE;
}
/// K and two or more pawns vs K. There is just a single rule here: if all pawns
/// are on the same rook file and are blocked by the defending king, it's a draw.
template<>
ScaleFactor Endgame<KPsK>::operator()(const Position& pos) const {
assert(pos.non_pawn_material(strongSide) == VALUE_ZERO);
assert(pos.count<PAWN>(strongSide) >= 2);
assert(verify_material(pos, weakSide, VALUE_ZERO, 0));
Square weakKing = pos.square<KING>(weakSide);
Bitboard strongPawns = pos.pieces(strongSide, PAWN);
// If all pawns are ahead of the king on a single rook file, it's a draw.
if ( !(strongPawns & ~(FileABB | FileHBB))
&& !(strongPawns & ~passed_pawn_span(weakSide, weakKing)))
return SCALE_FACTOR_DRAW;
return SCALE_FACTOR_NONE;
}
/// KBP vs KB. There are two rules: if the defending king is somewhere along the
/// path of the pawn, and the square of the king is not of the same color as the
/// stronger side's bishop, it's a draw. If the two bishops have opposite color,
/// it's almost always a draw.
template<>
ScaleFactor Endgame<KBPKB>::operator()(const Position& pos) const {
assert(verify_material(pos, strongSide, BishopValueMg, 1));
assert(verify_material(pos, weakSide, BishopValueMg, 0));
Square strongPawn = pos.square<PAWN>(strongSide);
Square strongBishop = pos.square<BISHOP>(strongSide);
Square weakBishop = pos.square<BISHOP>(weakSide);
Square weakKing = pos.square<KING>(weakSide);
// Case 1: Defending king blocks the pawn, and cannot be driven away
if ( (forward_file_bb(strongSide, strongPawn) & weakKing)
&& ( opposite_colors(weakKing, strongBishop)
|| relative_rank(strongSide, weakKing) <= RANK_6))
return SCALE_FACTOR_DRAW;
// Case 2: Opposite colored bishops
if (opposite_colors(strongBishop, weakBishop))
return SCALE_FACTOR_DRAW;
return SCALE_FACTOR_NONE;
}
/// KBPP vs KB. It detects a few basic draws with opposite-colored bishops
template<>
ScaleFactor Endgame<KBPPKB>::operator()(const Position& pos) const {
assert(verify_material(pos, strongSide, BishopValueMg, 2));
assert(verify_material(pos, weakSide, BishopValueMg, 0));
Square strongBishop = pos.square<BISHOP>(strongSide);
Square weakBishop = pos.square<BISHOP>(weakSide);
if (!opposite_colors(strongBishop, weakBishop))
return SCALE_FACTOR_NONE;
Square weakKing = pos.square<KING>(weakSide);
Square strongPawn1 = pos.squares<PAWN>(strongSide)[0];
Square strongPawn2 = pos.squares<PAWN>(strongSide)[1];
Square blockSq1, blockSq2;
if (relative_rank(strongSide, strongPawn1) > relative_rank(strongSide, strongPawn2))
{
blockSq1 = strongPawn1 + pawn_push(strongSide);
blockSq2 = make_square(file_of(strongPawn2), rank_of(strongPawn1));
}
else
{
blockSq1 = strongPawn2 + pawn_push(strongSide);
blockSq2 = make_square(file_of(strongPawn1), rank_of(strongPawn2));
}
switch (distance<File>(strongPawn1, strongPawn2))
{
case 0:
// Both pawns are on the same file. It's an easy draw if the defender firmly
// controls some square in the frontmost pawn's path.
if ( file_of(weakKing) == file_of(blockSq1)
&& relative_rank(strongSide, weakKing) >= relative_rank(strongSide, blockSq1)
&& opposite_colors(weakKing, strongBishop))
return SCALE_FACTOR_DRAW;
else
return SCALE_FACTOR_NONE;
case 1:
// Pawns on adjacent files. It's a draw if the defender firmly controls the
// square in front of the frontmost pawn's path, and the square diagonally
// behind this square on the file of the other pawn.
if ( weakKing == blockSq1
&& opposite_colors(weakKing, strongBishop)
&& ( weakBishop == blockSq2
|| (attacks_bb<BISHOP>(blockSq2, pos.pieces()) & pos.pieces(weakSide, BISHOP))
|| distance<Rank>(strongPawn1, strongPawn2) >= 2))
return SCALE_FACTOR_DRAW;
else if ( weakKing == blockSq2
&& opposite_colors(weakKing, strongBishop)
&& ( weakBishop == blockSq1
|| (attacks_bb<BISHOP>(blockSq1, pos.pieces()) & pos.pieces(weakSide, BISHOP))))
return SCALE_FACTOR_DRAW;
else
return SCALE_FACTOR_NONE;
default:
// The pawns are not on the same file or adjacent files. No scaling.
return SCALE_FACTOR_NONE;
}
}
/// KBP vs KN. There is a single rule: if the defending king is somewhere along
/// the path of the pawn, and the square of the king is not of the same color as
/// the stronger side's bishop, it's a draw.
template<>
ScaleFactor Endgame<KBPKN>::operator()(const Position& pos) const {
assert(verify_material(pos, strongSide, BishopValueMg, 1));
assert(verify_material(pos, weakSide, KnightValueMg, 0));
Square strongPawn = pos.square<PAWN>(strongSide);
Square strongBishop = pos.square<BISHOP>(strongSide);
Square weakKing = pos.square<KING>(weakSide);
if ( file_of(weakKing) == file_of(strongPawn)
&& relative_rank(strongSide, strongPawn) < relative_rank(strongSide, weakKing)
&& ( opposite_colors(weakKing, strongBishop)
|| relative_rank(strongSide, weakKing) <= RANK_6))
return SCALE_FACTOR_DRAW;
return SCALE_FACTOR_NONE;
}
/// KP vs KP. This is done by removing the weakest side's pawn and probing the
/// KP vs K bitbase: if the weakest side has a draw without the pawn, it probably
/// has at least a draw with the pawn as well. The exception is when the stronger
/// side's pawn is far advanced and not on a rook file; in this case it is often
/// possible to win (e.g. 8/4k3/3p4/3P4/6K1/8/8/8 w - - 0 1).
template<>
ScaleFactor Endgame<KPKP>::operator()(const Position& pos) const {
assert(verify_material(pos, strongSide, VALUE_ZERO, 1));
assert(verify_material(pos, weakSide, VALUE_ZERO, 1));
// Assume strongSide is white and the pawn is on files A-D
Square strongKing = normalize(pos, strongSide, pos.square<KING>(strongSide));
Square weakKing = normalize(pos, strongSide, pos.square<KING>(weakSide));
Square strongPawn = normalize(pos, strongSide, pos.square<PAWN>(strongSide));
Color us = strongSide == pos.side_to_move() ? WHITE : BLACK;
// If the pawn has advanced to the fifth rank or further, and is not a
// rook pawn, it's too dangerous to assume that it's at least a draw.
if (rank_of(strongPawn) >= RANK_5 && file_of(strongPawn) != FILE_A)
return SCALE_FACTOR_NONE;
// Probe the KPK bitbase with the weakest side's pawn removed. If it's a draw,
// it's probably at least a draw even with the pawn.
return Bitbases::probe(strongKing, strongPawn, weakKing, us) ? SCALE_FACTOR_NONE : SCALE_FACTOR_DRAW;
}

123
src/endgame.h Normal file
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/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef ENDGAME_H_INCLUDED
#define ENDGAME_H_INCLUDED
#include <memory>
#include <string>
#include <type_traits>
#include <unordered_map>
#include <utility>
#include "position.h"
#include "types.h"
/// EndgameCode lists all supported endgame functions by corresponding codes
enum EndgameCode {
EVALUATION_FUNCTIONS,
KNNK, // KNN vs K
KNNKP, // KNN vs KP
KXK, // Generic "mate lone king" eval
KBNK, // KBN vs K
KPK, // KP vs K
KRKP, // KR vs KP
KRKB, // KR vs KB
KRKN, // KR vs KN
KQKP, // KQ vs KP
KQKR, // KQ vs KR
SCALING_FUNCTIONS,
KBPsK, // KB and pawns vs K
KQKRPs, // KQ vs KR and pawns
KRPKR, // KRP vs KR
KRPKB, // KRP vs KB
KRPPKRP, // KRPP vs KRP
KPsK, // K and pawns vs K
KBPKB, // KBP vs KB
KBPPKB, // KBPP vs KB
KBPKN, // KBP vs KN
KPKP // KP vs KP
};
/// Endgame functions can be of two types depending on whether they return a
/// Value or a ScaleFactor.
template<EndgameCode E> using
eg_type = typename std::conditional<(E < SCALING_FUNCTIONS), Value, ScaleFactor>::type;
/// Base and derived functors for endgame evaluation and scaling functions
template<typename T>
struct EndgameBase {
explicit EndgameBase(Color c) : strongSide(c), weakSide(~c) {}
virtual ~EndgameBase() = default;
virtual T operator()(const Position&) const = 0;
const Color strongSide, weakSide;
};
template<EndgameCode E, typename T = eg_type<E>>
struct Endgame : public EndgameBase<T> {
explicit Endgame(Color c) : EndgameBase<T>(c) {}
T operator()(const Position&) const override;
};
/// The Endgames namespace handles the pointers to endgame evaluation and scaling
/// base objects in two std::map. We use polymorphism to invoke the actual
/// endgame function by calling its virtual operator().
namespace Endgames {
template<typename T> using Ptr = std::unique_ptr<EndgameBase<T>>;
template<typename T> using Map = std::unordered_map<Key, Ptr<T>>;
extern std::pair<Map<Value>, Map<ScaleFactor>> maps;
void init();
template<typename T>
Map<T>& map() {
return std::get<std::is_same<T, ScaleFactor>::value>(maps);
}
template<EndgameCode E, typename T = eg_type<E>>
void add(const std::string& code) {
StateInfo st;
map<T>()[Position().set(code, WHITE, &st).material_key()] = Ptr<T>(new Endgame<E>(WHITE));
map<T>()[Position().set(code, BLACK, &st).material_key()] = Ptr<T>(new Endgame<E>(BLACK));
}
template<typename T>
const EndgameBase<T>* probe(Key key) {
auto it = map<T>().find(key);
return it != map<T>().end() ? it->second.get() : nullptr;
}
}
#endif // #ifndef ENDGAME_H_INCLUDED

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@@ -1,372 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include "engine.h"
#include <algorithm>
#include <cassert>
#include <deque>
#include <iosfwd>
#include <memory>
#include <ostream>
#include <sstream>
#include <string_view>
#include <utility>
#include <vector>
#include "evaluate.h"
#include "misc.h"
#include "nnue/network.h"
#include "nnue/nnue_common.h"
#include "numa.h"
#include "perft.h"
#include "position.h"
#include "search.h"
#include "syzygy/tbprobe.h"
#include "types.h"
#include "uci.h"
#include "ucioption.h"
namespace Stockfish {
namespace NN = Eval::NNUE;
constexpr auto StartFEN = "rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1";
constexpr int MaxHashMB = Is64Bit ? 33554432 : 2048;
int MaxThreads = std::max(1024, 4 * int(get_hardware_concurrency()));
Engine::Engine(std::optional<std::string> path) :
binaryDirectory(path ? CommandLine::get_binary_directory(*path) : ""),
numaContext(NumaConfig::from_system()),
states(new std::deque<StateInfo>(1)),
threads(),
networks(
numaContext,
NN::Networks(
NN::NetworkBig({EvalFileDefaultNameBig, "None", ""}, NN::EmbeddedNNUEType::BIG),
NN::NetworkSmall({EvalFileDefaultNameSmall, "None", ""}, NN::EmbeddedNNUEType::SMALL))) {
pos.set(StartFEN, false, &states->back());
options.add( //
"Debug Log File", Option("", [](const Option& o) {
start_logger(o);
return std::nullopt;
}));
options.add( //
"NumaPolicy", Option("auto", [this](const Option& o) {
set_numa_config_from_option(o);
return numa_config_information_as_string() + "\n"
+ thread_allocation_information_as_string();
}));
options.add( //
"Threads", Option(1, 1, MaxThreads, [this](const Option&) {
resize_threads();
return thread_allocation_information_as_string();
}));
options.add( //
"Hash", Option(16, 1, MaxHashMB, [this](const Option& o) {
set_tt_size(o);
return std::nullopt;
}));
options.add( //
"Clear Hash", Option([this](const Option&) {
search_clear();
return std::nullopt;
}));
options.add( //
"Ponder", Option(false));
options.add( //
"MultiPV", Option(1, 1, MAX_MOVES));
options.add("Skill Level", Option(20, 0, 20));
options.add("Move Overhead", Option(10, 0, 5000));
options.add("nodestime", Option(0, 0, 10000));
options.add("UCI_Chess960", Option(false));
options.add("UCI_LimitStrength", Option(false));
options.add("UCI_Elo",
Option(Stockfish::Search::Skill::LowestElo, Stockfish::Search::Skill::LowestElo,
Stockfish::Search::Skill::HighestElo));
options.add("UCI_ShowWDL", Option(false));
options.add( //
"SyzygyPath", Option("", [](const Option& o) {
Tablebases::init(o);
return std::nullopt;
}));
options.add("SyzygyProbeDepth", Option(1, 1, 100));
options.add("Syzygy50MoveRule", Option(true));
options.add("SyzygyProbeLimit", Option(7, 0, 7));
options.add( //
"EvalFile", Option(EvalFileDefaultNameBig, [this](const Option& o) {
load_big_network(o);
return std::nullopt;
}));
options.add( //
"EvalFileSmall", Option(EvalFileDefaultNameSmall, [this](const Option& o) {
load_small_network(o);
return std::nullopt;
}));
load_networks();
resize_threads();
}
std::uint64_t Engine::perft(const std::string& fen, Depth depth, bool isChess960) {
verify_networks();
return Benchmark::perft(fen, depth, isChess960);
}
void Engine::go(Search::LimitsType& limits) {
assert(limits.perft == 0);
verify_networks();
threads.start_thinking(options, pos, states, limits);
}
void Engine::stop() { threads.stop = true; }
void Engine::search_clear() {
wait_for_search_finished();
tt.clear(threads);
threads.clear();
// @TODO wont work with multiple instances
Tablebases::init(options["SyzygyPath"]); // Free mapped files
}
void Engine::set_on_update_no_moves(std::function<void(const Engine::InfoShort&)>&& f) {
updateContext.onUpdateNoMoves = std::move(f);
}
void Engine::set_on_update_full(std::function<void(const Engine::InfoFull&)>&& f) {
updateContext.onUpdateFull = std::move(f);
}
void Engine::set_on_iter(std::function<void(const Engine::InfoIter&)>&& f) {
updateContext.onIter = std::move(f);
}
void Engine::set_on_bestmove(std::function<void(std::string_view, std::string_view)>&& f) {
updateContext.onBestmove = std::move(f);
}
void Engine::set_on_verify_networks(std::function<void(std::string_view)>&& f) {
onVerifyNetworks = std::move(f);
}
void Engine::wait_for_search_finished() { threads.main_thread()->wait_for_search_finished(); }
void Engine::set_position(const std::string& fen, const std::vector<std::string>& moves) {
// Drop the old state and create a new one
states = StateListPtr(new std::deque<StateInfo>(1));
pos.set(fen, options["UCI_Chess960"], &states->back());
for (const auto& move : moves)
{
auto m = UCIEngine::to_move(pos, move);
if (m == Move::none())
break;
states->emplace_back();
pos.do_move(m, states->back());
}
}
// modifiers
void Engine::set_numa_config_from_option(const std::string& o) {
if (o == "auto" || o == "system")
{
numaContext.set_numa_config(NumaConfig::from_system());
}
else if (o == "hardware")
{
// Don't respect affinity set in the system.
numaContext.set_numa_config(NumaConfig::from_system(false));
}
else if (o == "none")
{
numaContext.set_numa_config(NumaConfig{});
}
else
{
numaContext.set_numa_config(NumaConfig::from_string(o));
}
// Force reallocation of threads in case affinities need to change.
resize_threads();
threads.ensure_network_replicated();
}
void Engine::resize_threads() {
threads.wait_for_search_finished();
threads.set(numaContext.get_numa_config(), {options, threads, tt, networks}, updateContext);
// Reallocate the hash with the new threadpool size
set_tt_size(options["Hash"]);
threads.ensure_network_replicated();
}
void Engine::set_tt_size(size_t mb) {
wait_for_search_finished();
tt.resize(mb, threads);
}
void Engine::set_ponderhit(bool b) { threads.main_manager()->ponder = b; }
// network related
void Engine::verify_networks() const {
networks->big.verify(options["EvalFile"], onVerifyNetworks);
networks->small.verify(options["EvalFileSmall"], onVerifyNetworks);
}
void Engine::load_networks() {
networks.modify_and_replicate([this](NN::Networks& networks_) {
networks_.big.load(binaryDirectory, options["EvalFile"]);
networks_.small.load(binaryDirectory, options["EvalFileSmall"]);
});
threads.clear();
threads.ensure_network_replicated();
}
void Engine::load_big_network(const std::string& file) {
networks.modify_and_replicate(
[this, &file](NN::Networks& networks_) { networks_.big.load(binaryDirectory, file); });
threads.clear();
threads.ensure_network_replicated();
}
void Engine::load_small_network(const std::string& file) {
networks.modify_and_replicate(
[this, &file](NN::Networks& networks_) { networks_.small.load(binaryDirectory, file); });
threads.clear();
threads.ensure_network_replicated();
}
void Engine::save_network(const std::pair<std::optional<std::string>, std::string> files[2]) {
networks.modify_and_replicate([&files](NN::Networks& networks_) {
networks_.big.save(files[0].first);
networks_.small.save(files[1].first);
});
}
// utility functions
void Engine::trace_eval() const {
StateListPtr trace_states(new std::deque<StateInfo>(1));
Position p;
p.set(pos.fen(), options["UCI_Chess960"], &trace_states->back());
verify_networks();
sync_cout << "\n" << Eval::trace(p, *networks) << sync_endl;
}
const OptionsMap& Engine::get_options() const { return options; }
OptionsMap& Engine::get_options() { return options; }
std::string Engine::fen() const { return pos.fen(); }
void Engine::flip() { pos.flip(); }
std::string Engine::visualize() const {
std::stringstream ss;
ss << pos;
return ss.str();
}
int Engine::get_hashfull(int maxAge) const { return tt.hashfull(maxAge); }
std::vector<std::pair<size_t, size_t>> Engine::get_bound_thread_count_by_numa_node() const {
auto counts = threads.get_bound_thread_count_by_numa_node();
const NumaConfig& cfg = numaContext.get_numa_config();
std::vector<std::pair<size_t, size_t>> ratios;
NumaIndex n = 0;
for (; n < counts.size(); ++n)
ratios.emplace_back(counts[n], cfg.num_cpus_in_numa_node(n));
if (!counts.empty())
for (; n < cfg.num_numa_nodes(); ++n)
ratios.emplace_back(0, cfg.num_cpus_in_numa_node(n));
return ratios;
}
std::string Engine::get_numa_config_as_string() const {
return numaContext.get_numa_config().to_string();
}
std::string Engine::numa_config_information_as_string() const {
auto cfgStr = get_numa_config_as_string();
return "Available processors: " + cfgStr;
}
std::string Engine::thread_binding_information_as_string() const {
auto boundThreadsByNode = get_bound_thread_count_by_numa_node();
std::stringstream ss;
if (boundThreadsByNode.empty())
return ss.str();
bool isFirst = true;
for (auto&& [current, total] : boundThreadsByNode)
{
if (!isFirst)
ss << ":";
ss << current << "/" << total;
isFirst = false;
}
return ss.str();
}
std::string Engine::thread_allocation_information_as_string() const {
std::stringstream ss;
size_t threadsSize = threads.size();
ss << "Using " << threadsSize << (threadsSize > 1 ? " threads" : " thread");
auto boundThreadsByNodeStr = thread_binding_information_as_string();
if (boundThreadsByNodeStr.empty())
return ss.str();
ss << " with NUMA node thread binding: ";
ss << boundThreadsByNodeStr;
return ss.str();
}
}

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@@ -1,130 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef ENGINE_H_INCLUDED
#define ENGINE_H_INCLUDED
#include <cstddef>
#include <cstdint>
#include <functional>
#include <optional>
#include <string>
#include <string_view>
#include <utility>
#include <vector>
#include "nnue/network.h"
#include "numa.h"
#include "position.h"
#include "search.h"
#include "syzygy/tbprobe.h" // for Stockfish::Depth
#include "thread.h"
#include "tt.h"
#include "ucioption.h"
namespace Stockfish {
class Engine {
public:
using InfoShort = Search::InfoShort;
using InfoFull = Search::InfoFull;
using InfoIter = Search::InfoIteration;
Engine(std::optional<std::string> path = std::nullopt);
// Cannot be movable due to components holding backreferences to fields
Engine(const Engine&) = delete;
Engine(Engine&&) = delete;
Engine& operator=(const Engine&) = delete;
Engine& operator=(Engine&&) = delete;
~Engine() { wait_for_search_finished(); }
std::uint64_t perft(const std::string& fen, Depth depth, bool isChess960);
// non blocking call to start searching
void go(Search::LimitsType&);
// non blocking call to stop searching
void stop();
// blocking call to wait for search to finish
void wait_for_search_finished();
// set a new position, moves are in UCI format
void set_position(const std::string& fen, const std::vector<std::string>& moves);
// modifiers
void set_numa_config_from_option(const std::string& o);
void resize_threads();
void set_tt_size(size_t mb);
void set_ponderhit(bool);
void search_clear();
void set_on_update_no_moves(std::function<void(const InfoShort&)>&&);
void set_on_update_full(std::function<void(const InfoFull&)>&&);
void set_on_iter(std::function<void(const InfoIter&)>&&);
void set_on_bestmove(std::function<void(std::string_view, std::string_view)>&&);
void set_on_verify_networks(std::function<void(std::string_view)>&&);
// network related
void verify_networks() const;
void load_networks();
void load_big_network(const std::string& file);
void load_small_network(const std::string& file);
void save_network(const std::pair<std::optional<std::string>, std::string> files[2]);
// utility functions
void trace_eval() const;
const OptionsMap& get_options() const;
OptionsMap& get_options();
int get_hashfull(int maxAge = 0) const;
std::string fen() const;
void flip();
std::string visualize() const;
std::vector<std::pair<size_t, size_t>> get_bound_thread_count_by_numa_node() const;
std::string get_numa_config_as_string() const;
std::string numa_config_information_as_string() const;
std::string thread_allocation_information_as_string() const;
std::string thread_binding_information_as_string() const;
private:
const std::string binaryDirectory;
NumaReplicationContext numaContext;
Position pos;
StateListPtr states;
OptionsMap options;
ThreadPool threads;
TranspositionTable tt;
LazyNumaReplicated<Eval::NNUE::Networks> networks;
Search::SearchManager::UpdateContext updateContext;
std::function<void(std::string_view)> onVerifyNetworks;
};
} // namespace Stockfish
#endif // #ifndef ENGINE_H_INCLUDED

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@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -23,36 +23,27 @@
#include "types.h"
namespace Stockfish {
class Position;
namespace Eval {
// The default net name MUST follow the format nn-[SHA256 first 12 digits].nnue
// for the build process (profile-build and fishtest) to work. Do not change the
// name of the macro or the location where this macro is defined, as it is used
// in the Makefile/Fishtest.
#define EvalFileDefaultNameBig "nn-1c0000000000.nnue"
#define EvalFileDefaultNameSmall "nn-37f18f62d772.nnue"
std::string trace(const Position& pos);
Value evaluate(const Position& pos);
namespace NNUE {
struct Networks;
struct AccumulatorCaches;
class AccumulatorStack;
}
extern bool useNNUE;
extern std::string eval_file_loaded;
void init_NNUE();
void verify_NNUE();
std::string trace(Position& pos, const Eval::NNUE::Networks& networks);
namespace NNUE {
int simple_eval(const Position& pos);
bool use_smallnet(const Position& pos);
Value evaluate(const NNUE::Networks& networks,
const Position& pos,
Eval::NNUE::AccumulatorStack& accumulators,
Eval::NNUE::AccumulatorCaches& caches,
int optimism);
} // namespace Eval
Value evaluate(const Position& pos);
Value compute_eval(const Position& pos);
void update_eval(const Position& pos);
bool load_eval_file(const std::string& evalFile);
} // namespace Stockfish
} // namespace NNUE
#endif // #ifndef EVALUATE_H_INCLUDED
} // namespace Eval
#endif // #ifndef EVALUATE_H_INCLUDED

View File

@@ -1,173 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef HISTORY_H_INCLUDED
#define HISTORY_H_INCLUDED
#include <algorithm>
#include <array>
#include <cassert>
#include <cmath>
#include <cstdint>
#include <cstdlib>
#include <limits>
#include <type_traits> // IWYU pragma: keep
#include "misc.h"
#include "position.h"
namespace Stockfish {
constexpr int PAWN_HISTORY_SIZE = 512; // has to be a power of 2
constexpr int CORRECTION_HISTORY_SIZE = 32768; // has to be a power of 2
constexpr int CORRECTION_HISTORY_LIMIT = 1024;
constexpr int LOW_PLY_HISTORY_SIZE = 5;
static_assert((PAWN_HISTORY_SIZE & (PAWN_HISTORY_SIZE - 1)) == 0,
"PAWN_HISTORY_SIZE has to be a power of 2");
static_assert((CORRECTION_HISTORY_SIZE & (CORRECTION_HISTORY_SIZE - 1)) == 0,
"CORRECTION_HISTORY_SIZE has to be a power of 2");
enum PawnHistoryType {
Normal,
Correction
};
template<PawnHistoryType T = Normal>
inline int pawn_structure_index(const Position& pos) {
return pos.pawn_key() & ((T == Normal ? PAWN_HISTORY_SIZE : CORRECTION_HISTORY_SIZE) - 1);
}
inline int minor_piece_index(const Position& pos) {
return pos.minor_piece_key() & (CORRECTION_HISTORY_SIZE - 1);
}
template<Color c>
inline int non_pawn_index(const Position& pos) {
return pos.non_pawn_key(c) & (CORRECTION_HISTORY_SIZE - 1);
}
// StatsEntry is the container of various numerical statistics. We use a class
// instead of a naked value to directly call history update operator<<() on
// the entry. The first template parameter T is the base type of the array,
// and the second template parameter D limits the range of updates in [-D, D]
// when we update values with the << operator
template<typename T, int D>
class StatsEntry {
static_assert(std::is_arithmetic_v<T>, "Not an arithmetic type");
static_assert(D <= std::numeric_limits<T>::max(), "D overflows T");
T entry;
public:
StatsEntry& operator=(const T& v) {
entry = v;
return *this;
}
operator const T&() const { return entry; }
void operator<<(int bonus) {
// Make sure that bonus is in range [-D, D]
int clampedBonus = std::clamp(bonus, -D, D);
entry += clampedBonus - entry * std::abs(clampedBonus) / D;
assert(std::abs(entry) <= D);
}
};
enum StatsType {
NoCaptures,
Captures
};
template<typename T, int D, std::size_t... Sizes>
using Stats = MultiArray<StatsEntry<T, D>, Sizes...>;
// ButterflyHistory records how often quiet moves have been successful or unsuccessful
// during the current search, and is used for reduction and move ordering decisions.
// It uses 2 tables (one for each color) indexed by the move's from and to squares,
// see https://www.chessprogramming.org/Butterfly_Boards (~11 elo)
using ButterflyHistory = Stats<std::int16_t, 7183, COLOR_NB, int(SQUARE_NB) * int(SQUARE_NB)>;
// LowPlyHistory is adressed by play and move's from and to squares, used
// to improve move ordering near the root
using LowPlyHistory =
Stats<std::int16_t, 7183, LOW_PLY_HISTORY_SIZE, int(SQUARE_NB) * int(SQUARE_NB)>;
// CapturePieceToHistory is addressed by a move's [piece][to][captured piece type]
using CapturePieceToHistory = Stats<std::int16_t, 10692, PIECE_NB, SQUARE_NB, PIECE_TYPE_NB>;
// PieceToHistory is like ButterflyHistory but is addressed by a move's [piece][to]
using PieceToHistory = Stats<std::int16_t, 30000, PIECE_NB, SQUARE_NB>;
// ContinuationHistory is the combined history of a given pair of moves, usually
// the current one given a previous one. The nested history table is based on
// PieceToHistory instead of ButterflyBoards.
// (~63 elo)
using ContinuationHistory = MultiArray<PieceToHistory, PIECE_NB, SQUARE_NB>;
// PawnHistory is addressed by the pawn structure and a move's [piece][to]
using PawnHistory = Stats<std::int16_t, 8192, PAWN_HISTORY_SIZE, PIECE_NB, SQUARE_NB>;
// Correction histories record differences between the static evaluation of
// positions and their search score. It is used to improve the static evaluation
// used by some search heuristics.
// see https://www.chessprogramming.org/Static_Evaluation_Correction_History
enum CorrHistType {
Pawn, // By color and pawn structure
Minor, // By color and positions of minor pieces (Knight, Bishop)
NonPawn, // By non-pawn material positions and color
PieceTo, // By [piece][to] move
Continuation, // Combined history of move pairs
};
namespace Detail {
template<CorrHistType>
struct CorrHistTypedef {
using type = Stats<std::int16_t, CORRECTION_HISTORY_LIMIT, CORRECTION_HISTORY_SIZE, COLOR_NB>;
};
template<>
struct CorrHistTypedef<PieceTo> {
using type = Stats<std::int16_t, CORRECTION_HISTORY_LIMIT, PIECE_NB, SQUARE_NB>;
};
template<>
struct CorrHistTypedef<Continuation> {
using type = MultiArray<CorrHistTypedef<PieceTo>::type, PIECE_NB, SQUARE_NB>;
};
template<>
struct CorrHistTypedef<NonPawn> {
using type =
Stats<std::int16_t, CORRECTION_HISTORY_LIMIT, CORRECTION_HISTORY_SIZE, COLOR_NB, COLOR_NB>;
};
}
template<CorrHistType T>
using CorrectionHistory = typename Detail::CorrHistTypedef<T>::type;
using TTMoveHistory = StatsEntry<std::int16_t, 8192>;
} // namespace Stockfish
#endif // #ifndef HISTORY_H_INCLUDED

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@@ -1,26 +0,0 @@
The file "incbin.h" is free and unencumbered software released into
the public domain by Dale Weiler, see:
<https://github.com/graphitemaster/incbin>
Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any
means.
In jurisdictions that recognize copyright laws, the author or authors
of this software dedicate any and all copyright interest in the
software to the public domain. We make this dedication for the benefit
of the public at large and to the detriment of our heirs and
successors. We intend this dedication to be an overt act of
relinquishment in perpetuity of all present and future rights to this
software under copyright law.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR
OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
OTHER DEALINGS IN THE SOFTWARE.
For more information, please refer to <http://unlicense.org/>

View File

@@ -1,476 +0,0 @@
/**
* @file incbin.h
* @author Dale Weiler
* @brief Utility for including binary files
*
* Facilities for including binary files into the current translation unit and
* making use from them externally in other translation units.
*/
#ifndef INCBIN_HDR
#define INCBIN_HDR
#include <limits.h>
#if defined(__AVX512BW__) || \
defined(__AVX512CD__) || \
defined(__AVX512DQ__) || \
defined(__AVX512ER__) || \
defined(__AVX512PF__) || \
defined(__AVX512VL__) || \
defined(__AVX512F__)
# define INCBIN_ALIGNMENT_INDEX 6
#elif defined(__AVX__) || \
defined(__AVX2__)
# define INCBIN_ALIGNMENT_INDEX 5
#elif defined(__SSE__) || \
defined(__SSE2__) || \
defined(__SSE3__) || \
defined(__SSSE3__) || \
defined(__SSE4_1__) || \
defined(__SSE4_2__) || \
defined(__neon__) || \
defined(__ARM_NEON) || \
defined(__ALTIVEC__)
# define INCBIN_ALIGNMENT_INDEX 4
#elif ULONG_MAX != 0xffffffffu
# define INCBIN_ALIGNMENT_INDEX 3
# else
# define INCBIN_ALIGNMENT_INDEX 2
#endif
/* Lookup table of (1 << n) where `n' is `INCBIN_ALIGNMENT_INDEX' */
#define INCBIN_ALIGN_SHIFT_0 1
#define INCBIN_ALIGN_SHIFT_1 2
#define INCBIN_ALIGN_SHIFT_2 4
#define INCBIN_ALIGN_SHIFT_3 8
#define INCBIN_ALIGN_SHIFT_4 16
#define INCBIN_ALIGN_SHIFT_5 32
#define INCBIN_ALIGN_SHIFT_6 64
/* Actual alignment value */
#define INCBIN_ALIGNMENT \
INCBIN_CONCATENATE( \
INCBIN_CONCATENATE(INCBIN_ALIGN_SHIFT, _), \
INCBIN_ALIGNMENT_INDEX)
/* Stringize */
#define INCBIN_STR(X) \
#X
#define INCBIN_STRINGIZE(X) \
INCBIN_STR(X)
/* Concatenate */
#define INCBIN_CAT(X, Y) \
X ## Y
#define INCBIN_CONCATENATE(X, Y) \
INCBIN_CAT(X, Y)
/* Deferred macro expansion */
#define INCBIN_EVAL(X) \
X
#define INCBIN_INVOKE(N, ...) \
INCBIN_EVAL(N(__VA_ARGS__))
/* Variable argument count for overloading by arity */
#define INCBIN_VA_ARG_COUNTER(_1, _2, _3, N, ...) N
#define INCBIN_VA_ARGC(...) INCBIN_VA_ARG_COUNTER(__VA_ARGS__, 3, 2, 1, 0)
/* Green Hills uses a different directive for including binary data */
#if defined(__ghs__)
# if (__ghs_asm == 2)
# define INCBIN_MACRO ".file"
/* Or consider the ".myrawdata" entry in the ld file */
# else
# define INCBIN_MACRO "\tINCBIN"
# endif
#else
# define INCBIN_MACRO ".incbin"
#endif
#ifndef _MSC_VER
# define INCBIN_ALIGN \
__attribute__((aligned(INCBIN_ALIGNMENT)))
#else
# define INCBIN_ALIGN __declspec(align(INCBIN_ALIGNMENT))
#endif
#if defined(__arm__) || /* GNU C and RealView */ \
defined(__arm) || /* Diab */ \
defined(_ARM) /* ImageCraft */
# define INCBIN_ARM
#endif
#ifdef __GNUC__
/* Utilize .balign where supported */
# define INCBIN_ALIGN_HOST ".balign " INCBIN_STRINGIZE(INCBIN_ALIGNMENT) "\n"
# define INCBIN_ALIGN_BYTE ".balign 1\n"
#elif defined(INCBIN_ARM)
/*
* On arm assemblers, the alignment value is calculated as (1 << n) where `n' is
* the shift count. This is the value passed to `.align'
*/
# define INCBIN_ALIGN_HOST ".align " INCBIN_STRINGIZE(INCBIN_ALIGNMENT_INDEX) "\n"
# define INCBIN_ALIGN_BYTE ".align 0\n"
#else
/* We assume other inline assembler's treat `.align' as `.balign' */
# define INCBIN_ALIGN_HOST ".align " INCBIN_STRINGIZE(INCBIN_ALIGNMENT) "\n"
# define INCBIN_ALIGN_BYTE ".align 1\n"
#endif
/* INCBIN_CONST is used by incbin.c generated files */
#if defined(__cplusplus)
# define INCBIN_EXTERNAL extern "C"
# define INCBIN_CONST extern const
#else
# define INCBIN_EXTERNAL extern
# define INCBIN_CONST const
#endif
/**
* @brief Optionally override the linker section into which size and data is
* emitted.
*
* @warning If you use this facility, you might have to deal with
* platform-specific linker output section naming on your own.
*/
#if !defined(INCBIN_OUTPUT_SECTION)
# if defined(__APPLE__)
# define INCBIN_OUTPUT_SECTION ".const_data"
# else
# define INCBIN_OUTPUT_SECTION ".rodata"
# endif
#endif
/**
* @brief Optionally override the linker section into which data is emitted.
*
* @warning If you use this facility, you might have to deal with
* platform-specific linker output section naming on your own.
*/
#if !defined(INCBIN_OUTPUT_DATA_SECTION)
# define INCBIN_OUTPUT_DATA_SECTION INCBIN_OUTPUT_SECTION
#endif
/**
* @brief Optionally override the linker section into which size is emitted.
*
* @warning If you use this facility, you might have to deal with
* platform-specific linker output section naming on your own.
*
* @note This is useful for Harvard architectures where program memory cannot
* be directly read from the program without special instructions. With this you
* can chose to put the size variable in RAM rather than ROM.
*/
#if !defined(INCBIN_OUTPUT_SIZE_SECTION)
# define INCBIN_OUTPUT_SIZE_SECTION INCBIN_OUTPUT_SECTION
#endif
#if defined(__APPLE__)
# include "TargetConditionals.h"
# if defined(TARGET_OS_IPHONE) && !defined(INCBIN_SILENCE_BITCODE_WARNING)
# warning "incbin is incompatible with bitcode. Using the library will break upload to App Store if you have bitcode enabled. Add `#define INCBIN_SILENCE_BITCODE_WARNING` before including this header to silence this warning."
# endif
/* The directives are different for Apple branded compilers */
# define INCBIN_SECTION INCBIN_OUTPUT_SECTION "\n"
# define INCBIN_GLOBAL(NAME) ".globl " INCBIN_MANGLE INCBIN_STRINGIZE(INCBIN_PREFIX) #NAME "\n"
# define INCBIN_INT ".long "
# define INCBIN_MANGLE "_"
# define INCBIN_BYTE ".byte "
# define INCBIN_TYPE(...)
#else
# define INCBIN_SECTION ".section " INCBIN_OUTPUT_SECTION "\n"
# define INCBIN_GLOBAL(NAME) ".global " INCBIN_STRINGIZE(INCBIN_PREFIX) #NAME "\n"
# if defined(__ghs__)
# define INCBIN_INT ".word "
# else
# define INCBIN_INT ".int "
# endif
# if defined(__USER_LABEL_PREFIX__)
# define INCBIN_MANGLE INCBIN_STRINGIZE(__USER_LABEL_PREFIX__)
# else
# define INCBIN_MANGLE ""
# endif
# if defined(INCBIN_ARM)
/* On arm assemblers, `@' is used as a line comment token */
# define INCBIN_TYPE(NAME) ".type " INCBIN_STRINGIZE(INCBIN_PREFIX) #NAME ", %object\n"
# elif defined(__MINGW32__) || defined(__MINGW64__)
/* Mingw doesn't support this directive either */
# define INCBIN_TYPE(NAME)
# else
/* It's safe to use `@' on other architectures */
# define INCBIN_TYPE(NAME) ".type " INCBIN_STRINGIZE(INCBIN_PREFIX) #NAME ", @object\n"
# endif
# define INCBIN_BYTE ".byte "
#endif
/* List of style types used for symbol names */
#define INCBIN_STYLE_CAMEL 0
#define INCBIN_STYLE_SNAKE 1
/**
* @brief Specify the prefix to use for symbol names.
*
* @note By default this is "g".
*
* @code
* #define INCBIN_PREFIX incbin
* #include "incbin.h"
* INCBIN(Foo, "foo.txt");
*
* // Now you have the following symbols instead:
* // const unsigned char incbinFoo<data>[];
* // const unsigned char *const incbinFoo<end>;
* // const unsigned int incbinFoo<size>;
* @endcode
*/
#if !defined(INCBIN_PREFIX)
# define INCBIN_PREFIX g
#endif
/**
* @brief Specify the style used for symbol names.
*
* Possible options are
* - INCBIN_STYLE_CAMEL "CamelCase"
* - INCBIN_STYLE_SNAKE "snake_case"
*
* @note By default this is INCBIN_STYLE_CAMEL
*
* @code
* #define INCBIN_STYLE INCBIN_STYLE_SNAKE
* #include "incbin.h"
* INCBIN(foo, "foo.txt");
*
* // Now you have the following symbols:
* // const unsigned char <prefix>foo_data[];
* // const unsigned char *const <prefix>foo_end;
* // const unsigned int <prefix>foo_size;
* @endcode
*/
#if !defined(INCBIN_STYLE)
# define INCBIN_STYLE INCBIN_STYLE_CAMEL
#endif
/* Style lookup tables */
#define INCBIN_STYLE_0_DATA Data
#define INCBIN_STYLE_0_END End
#define INCBIN_STYLE_0_SIZE Size
#define INCBIN_STYLE_1_DATA _data
#define INCBIN_STYLE_1_END _end
#define INCBIN_STYLE_1_SIZE _size
/* Style lookup: returning identifier */
#define INCBIN_STYLE_IDENT(TYPE) \
INCBIN_CONCATENATE( \
INCBIN_STYLE_, \
INCBIN_CONCATENATE( \
INCBIN_EVAL(INCBIN_STYLE), \
INCBIN_CONCATENATE(_, TYPE)))
/* Style lookup: returning string literal */
#define INCBIN_STYLE_STRING(TYPE) \
INCBIN_STRINGIZE( \
INCBIN_STYLE_IDENT(TYPE)) \
/* Generate the global labels by indirectly invoking the macro with our style
* type and concatenating the name against them. */
#define INCBIN_GLOBAL_LABELS(NAME, TYPE) \
INCBIN_INVOKE( \
INCBIN_GLOBAL, \
INCBIN_CONCATENATE( \
NAME, \
INCBIN_INVOKE( \
INCBIN_STYLE_IDENT, \
TYPE))) \
INCBIN_INVOKE( \
INCBIN_TYPE, \
INCBIN_CONCATENATE( \
NAME, \
INCBIN_INVOKE( \
INCBIN_STYLE_IDENT, \
TYPE)))
/**
* @brief Externally reference binary data included in another translation unit.
*
* Produces three external symbols that reference the binary data included in
* another translation unit.
*
* The symbol names are a concatenation of `INCBIN_PREFIX' before *NAME*; with
* "Data", as well as "End" and "Size" after. An example is provided below.
*
* @param TYPE Optional array type. Omitting this picks a default of `unsigned char`.
* @param NAME The name given for the binary data
*
* @code
* INCBIN_EXTERN(Foo);
*
* // Now you have the following symbols:
* // extern const unsigned char <prefix>Foo<data>[];
* // extern const unsigned char *const <prefix>Foo<end>;
* // extern const unsigned int <prefix>Foo<size>;
* @endcode
*
* You may specify a custom optional data type as well as the first argument.
* @code
* INCBIN_EXTERN(custom_type, Foo);
*
* // Now you have the following symbols:
* // extern const custom_type <prefix>Foo<data>[];
* // extern const custom_type *const <prefix>Foo<end>;
* // extern const unsigned int <prefix>Foo<size>;
* @endcode
*/
#define INCBIN_EXTERN(...) \
INCBIN_CONCATENATE(INCBIN_EXTERN_, INCBIN_VA_ARGC(__VA_ARGS__))(__VA_ARGS__)
#define INCBIN_EXTERN_1(NAME, ...) \
INCBIN_EXTERN_2(unsigned char, NAME)
#define INCBIN_EXTERN_2(TYPE, NAME) \
INCBIN_EXTERNAL const INCBIN_ALIGN TYPE \
INCBIN_CONCATENATE( \
INCBIN_CONCATENATE(INCBIN_PREFIX, NAME), \
INCBIN_STYLE_IDENT(DATA))[]; \
INCBIN_EXTERNAL const INCBIN_ALIGN TYPE *const \
INCBIN_CONCATENATE( \
INCBIN_CONCATENATE(INCBIN_PREFIX, NAME), \
INCBIN_STYLE_IDENT(END)); \
INCBIN_EXTERNAL const unsigned int \
INCBIN_CONCATENATE( \
INCBIN_CONCATENATE(INCBIN_PREFIX, NAME), \
INCBIN_STYLE_IDENT(SIZE))
/**
* @brief Externally reference textual data included in another translation unit.
*
* Produces three external symbols that reference the textual data included in
* another translation unit.
*
* The symbol names are a concatenation of `INCBIN_PREFIX' before *NAME*; with
* "Data", as well as "End" and "Size" after. An example is provided below.
*
* @param NAME The name given for the textual data
*
* @code
* INCBIN_EXTERN(Foo);
*
* // Now you have the following symbols:
* // extern const char <prefix>Foo<data>[];
* // extern const char *const <prefix>Foo<end>;
* // extern const unsigned int <prefix>Foo<size>;
* @endcode
*/
#define INCTXT_EXTERN(NAME) \
INCBIN_EXTERN_2(char, NAME)
/**
* @brief Include a binary file into the current translation unit.
*
* Includes a binary file into the current translation unit, producing three symbols
* for objects that encode the data and size respectively.
*
* The symbol names are a concatenation of `INCBIN_PREFIX' before *NAME*; with
* "Data", as well as "End" and "Size" after. An example is provided below.
*
* @param TYPE Optional array type. Omitting this picks a default of `unsigned char`.
* @param NAME The name to associate with this binary data (as an identifier.)
* @param FILENAME The file to include (as a string literal.)
*
* @code
* INCBIN(Icon, "icon.png");
*
* // Now you have the following symbols:
* // const unsigned char <prefix>Icon<data>[];
* // const unsigned char *const <prefix>Icon<end>;
* // const unsigned int <prefix>Icon<size>;
* @endcode
*
* You may specify a custom optional data type as well as the first argument.
* These macros are specialized by arity.
* @code
* INCBIN(custom_type, Icon, "icon.png");
*
* // Now you have the following symbols:
* // const custom_type <prefix>Icon<data>[];
* // const custom_type *const <prefix>Icon<end>;
* // const unsigned int <prefix>Icon<size>;
* @endcode
*
* @warning This must be used in global scope
* @warning The identifiers may be different if INCBIN_STYLE is not default
*
* To externally reference the data included by this in another translation unit
* please @see INCBIN_EXTERN.
*/
#ifdef _MSC_VER
# define INCBIN(NAME, FILENAME) \
INCBIN_EXTERN(NAME)
#else
# define INCBIN(...) \
INCBIN_CONCATENATE(INCBIN_, INCBIN_VA_ARGC(__VA_ARGS__))(__VA_ARGS__)
# if defined(__GNUC__)
# define INCBIN_1(...) _Pragma("GCC error \"Single argument INCBIN not allowed\"")
# elif defined(__clang__)
# define INCBIN_1(...) _Pragma("clang error \"Single argument INCBIN not allowed\"")
# else
# define INCBIN_1(...) /* Cannot do anything here */
# endif
# define INCBIN_2(NAME, FILENAME) \
INCBIN_3(unsigned char, NAME, FILENAME)
# define INCBIN_3(TYPE, NAME, FILENAME) INCBIN_COMMON(TYPE, NAME, FILENAME, /* No terminator for binary data */)
# define INCBIN_COMMON(TYPE, NAME, FILENAME, TERMINATOR) \
__asm__(INCBIN_SECTION \
INCBIN_GLOBAL_LABELS(NAME, DATA) \
INCBIN_ALIGN_HOST \
INCBIN_MANGLE INCBIN_STRINGIZE(INCBIN_PREFIX) #NAME INCBIN_STYLE_STRING(DATA) ":\n" \
INCBIN_MACRO " \"" FILENAME "\"\n" \
TERMINATOR \
INCBIN_GLOBAL_LABELS(NAME, END) \
INCBIN_ALIGN_BYTE \
INCBIN_MANGLE INCBIN_STRINGIZE(INCBIN_PREFIX) #NAME INCBIN_STYLE_STRING(END) ":\n" \
INCBIN_BYTE "1\n" \
INCBIN_GLOBAL_LABELS(NAME, SIZE) \
INCBIN_ALIGN_HOST \
INCBIN_MANGLE INCBIN_STRINGIZE(INCBIN_PREFIX) #NAME INCBIN_STYLE_STRING(SIZE) ":\n" \
INCBIN_INT INCBIN_MANGLE INCBIN_STRINGIZE(INCBIN_PREFIX) #NAME INCBIN_STYLE_STRING(END) " - " \
INCBIN_MANGLE INCBIN_STRINGIZE(INCBIN_PREFIX) #NAME INCBIN_STYLE_STRING(DATA) "\n" \
INCBIN_ALIGN_HOST \
".text\n" \
); \
INCBIN_EXTERN(TYPE, NAME)
#endif
/**
* @brief Include a textual file into the current translation unit.
*
* This behaves the same as INCBIN except it produces char compatible arrays
* and implicitly adds a null-terminator byte, thus the size of data included
* by this is one byte larger than that of INCBIN.
*
* Includes a textual file into the current translation unit, producing three
* symbols for objects that encode the data and size respectively.
*
* The symbol names are a concatenation of `INCBIN_PREFIX' before *NAME*; with
* "Data", as well as "End" and "Size" after. An example is provided below.
*
* @param NAME The name to associate with this binary data (as an identifier.)
* @param FILENAME The file to include (as a string literal.)
*
* @code
* INCTXT(Readme, "readme.txt");
*
* // Now you have the following symbols:
* // const char <prefix>Readme<data>[];
* // const char *const <prefix>Readme<end>;
* // const unsigned int <prefix>Readme<size>;
* @endcode
*
* @warning This must be used in global scope
* @warning The identifiers may be different if INCBIN_STYLE is not default
*
* To externally reference the data included by this in another translation unit
* please @see INCBIN_EXTERN.
*/
#if defined(_MSC_VER)
# define INCTXT(NAME, FILENAME) \
INCBIN_EXTERN(NAME)
#else
# define INCTXT(NAME, FILENAME) \
INCBIN_COMMON(char, NAME, FILENAME, INCBIN_BYTE "0\n")
#endif
#endif

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -19,26 +19,35 @@
#include <iostream>
#include "bitboard.h"
#include "misc.h"
#include "endgame.h"
#include "position.h"
#include "types.h"
#include "search.h"
#include "thread.h"
#include "tt.h"
#include "uci.h"
#include "tune.h"
#include "syzygy/tbprobe.h"
using namespace Stockfish;
namespace PSQT {
void init();
}
int main(int argc, char* argv[]) {
std::cout << engine_info() << std::endl;
std::cout << engine_info() << std::endl;
Bitboards::init();
Position::init();
UCI::init(Options);
Tune::init();
PSQT::init();
Bitboards::init();
Position::init();
Bitbases::init();
Endgames::init();
Threads.set(size_t(Options["Threads"]));
Search::clear(); // After threads are up
Eval::init_NNUE();
UCIEngine uci(argc, argv);
UCI::loop(argc, argv);
Tune::init(uci.engine_options());
uci.loop();
return 0;
Threads.set(0);
return 0;
}

220
src/material.cpp Normal file
View File

@@ -0,0 +1,220 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include <cassert>
#include <cstring> // For std::memset
#include "material.h"
#include "thread.h"
using namespace std;
namespace {
// Polynomial material imbalance parameters
constexpr int QuadraticOurs[][PIECE_TYPE_NB] = {
// OUR PIECES
// pair pawn knight bishop rook queen
{1438 }, // Bishop pair
{ 40, 38 }, // Pawn
{ 32, 255, -62 }, // Knight OUR PIECES
{ 0, 104, 4, 0 }, // Bishop
{ -26, -2, 47, 105, -208 }, // Rook
{-189, 24, 117, 133, -134, -6 } // Queen
};
constexpr int QuadraticTheirs[][PIECE_TYPE_NB] = {
// THEIR PIECES
// pair pawn knight bishop rook queen
{ }, // Bishop pair
{ 36, }, // Pawn
{ 9, 63, }, // Knight OUR PIECES
{ 59, 65, 42, }, // Bishop
{ 46, 39, 24, -24, }, // Rook
{ 97, 100, -42, 137, 268, } // Queen
};
// Endgame evaluation and scaling functions are accessed directly and not through
// the function maps because they correspond to more than one material hash key.
Endgame<KXK> EvaluateKXK[] = { Endgame<KXK>(WHITE), Endgame<KXK>(BLACK) };
Endgame<KBPsK> ScaleKBPsK[] = { Endgame<KBPsK>(WHITE), Endgame<KBPsK>(BLACK) };
Endgame<KQKRPs> ScaleKQKRPs[] = { Endgame<KQKRPs>(WHITE), Endgame<KQKRPs>(BLACK) };
Endgame<KPsK> ScaleKPsK[] = { Endgame<KPsK>(WHITE), Endgame<KPsK>(BLACK) };
Endgame<KPKP> ScaleKPKP[] = { Endgame<KPKP>(WHITE), Endgame<KPKP>(BLACK) };
// Helper used to detect a given material distribution
bool is_KXK(const Position& pos, Color us) {
return !more_than_one(pos.pieces(~us))
&& pos.non_pawn_material(us) >= RookValueMg;
}
bool is_KBPsK(const Position& pos, Color us) {
return pos.non_pawn_material(us) == BishopValueMg
&& pos.count<PAWN >(us) >= 1;
}
bool is_KQKRPs(const Position& pos, Color us) {
return !pos.count<PAWN>(us)
&& pos.non_pawn_material(us) == QueenValueMg
&& pos.count<ROOK>(~us) == 1
&& pos.count<PAWN>(~us) >= 1;
}
/// imbalance() calculates the imbalance by comparing the piece count of each
/// piece type for both colors.
template<Color Us>
int imbalance(const int pieceCount[][PIECE_TYPE_NB]) {
constexpr Color Them = ~Us;
int bonus = 0;
// Second-degree polynomial material imbalance, by Tord Romstad
for (int pt1 = NO_PIECE_TYPE; pt1 <= QUEEN; ++pt1)
{
if (!pieceCount[Us][pt1])
continue;
int v = QuadraticOurs[pt1][pt1] * pieceCount[Us][pt1];
for (int pt2 = NO_PIECE_TYPE; pt2 < pt1; ++pt2)
v += QuadraticOurs[pt1][pt2] * pieceCount[Us][pt2]
+ QuadraticTheirs[pt1][pt2] * pieceCount[Them][pt2];
bonus += pieceCount[Us][pt1] * v;
}
return bonus;
}
} // namespace
namespace Material {
/// Material::probe() looks up the current position's material configuration in
/// the material hash table. It returns a pointer to the Entry if the position
/// is found. Otherwise a new Entry is computed and stored there, so we don't
/// have to recompute all when the same material configuration occurs again.
Entry* probe(const Position& pos) {
Key key = pos.material_key();
Entry* e = pos.this_thread()->materialTable[key];
if (e->key == key)
return e;
std::memset(e, 0, sizeof(Entry));
e->key = key;
e->factor[WHITE] = e->factor[BLACK] = (uint8_t)SCALE_FACTOR_NORMAL;
Value npm_w = pos.non_pawn_material(WHITE);
Value npm_b = pos.non_pawn_material(BLACK);
Value npm = Utility::clamp(npm_w + npm_b, EndgameLimit, MidgameLimit);
// Map total non-pawn material into [PHASE_ENDGAME, PHASE_MIDGAME]
e->gamePhase = Phase(((npm - EndgameLimit) * PHASE_MIDGAME) / (MidgameLimit - EndgameLimit));
// Let's look if we have a specialized evaluation function for this particular
// material configuration. Firstly we look for a fixed configuration one, then
// for a generic one if the previous search failed.
if ((e->evaluationFunction = Endgames::probe<Value>(key)) != nullptr)
return e;
for (Color c : { WHITE, BLACK })
if (is_KXK(pos, c))
{
e->evaluationFunction = &EvaluateKXK[c];
return e;
}
// OK, we didn't find any special evaluation function for the current material
// configuration. Is there a suitable specialized scaling function?
const auto* sf = Endgames::probe<ScaleFactor>(key);
if (sf)
{
e->scalingFunction[sf->strongSide] = sf; // Only strong color assigned
return e;
}
// We didn't find any specialized scaling function, so fall back on generic
// ones that refer to more than one material distribution. Note that in this
// case we don't return after setting the function.
for (Color c : { WHITE, BLACK })
{
if (is_KBPsK(pos, c))
e->scalingFunction[c] = &ScaleKBPsK[c];
else if (is_KQKRPs(pos, c))
e->scalingFunction[c] = &ScaleKQKRPs[c];
}
if (npm_w + npm_b == VALUE_ZERO && pos.pieces(PAWN)) // Only pawns on the board
{
if (!pos.count<PAWN>(BLACK))
{
assert(pos.count<PAWN>(WHITE) >= 2);
e->scalingFunction[WHITE] = &ScaleKPsK[WHITE];
}
else if (!pos.count<PAWN>(WHITE))
{
assert(pos.count<PAWN>(BLACK) >= 2);
e->scalingFunction[BLACK] = &ScaleKPsK[BLACK];
}
else if (pos.count<PAWN>(WHITE) == 1 && pos.count<PAWN>(BLACK) == 1)
{
// This is a special case because we set scaling functions
// for both colors instead of only one.
e->scalingFunction[WHITE] = &ScaleKPKP[WHITE];
e->scalingFunction[BLACK] = &ScaleKPKP[BLACK];
}
}
// Zero or just one pawn makes it difficult to win, even with a small material
// advantage. This catches some trivial draws like KK, KBK and KNK and gives a
// drawish scale factor for cases such as KRKBP and KmmKm (except for KBBKN).
if (!pos.count<PAWN>(WHITE) && npm_w - npm_b <= BishopValueMg)
e->factor[WHITE] = uint8_t(npm_w < RookValueMg ? SCALE_FACTOR_DRAW :
npm_b <= BishopValueMg ? 4 : 14);
if (!pos.count<PAWN>(BLACK) && npm_b - npm_w <= BishopValueMg)
e->factor[BLACK] = uint8_t(npm_b < RookValueMg ? SCALE_FACTOR_DRAW :
npm_w <= BishopValueMg ? 4 : 14);
// Evaluate the material imbalance. We use PIECE_TYPE_NONE as a place holder
// for the bishop pair "extended piece", which allows us to be more flexible
// in defining bishop pair bonuses.
const int pieceCount[COLOR_NB][PIECE_TYPE_NB] = {
{ pos.count<BISHOP>(WHITE) > 1, pos.count<PAWN>(WHITE), pos.count<KNIGHT>(WHITE),
pos.count<BISHOP>(WHITE) , pos.count<ROOK>(WHITE), pos.count<QUEEN >(WHITE) },
{ pos.count<BISHOP>(BLACK) > 1, pos.count<PAWN>(BLACK), pos.count<KNIGHT>(BLACK),
pos.count<BISHOP>(BLACK) , pos.count<ROOK>(BLACK), pos.count<QUEEN >(BLACK) } };
e->value = int16_t((imbalance<WHITE>(pieceCount) - imbalance<BLACK>(pieceCount)) / 16);
return e;
}
} // namespace Material

71
src/material.h Normal file
View File

@@ -0,0 +1,71 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef MATERIAL_H_INCLUDED
#define MATERIAL_H_INCLUDED
#include "endgame.h"
#include "misc.h"
#include "position.h"
#include "types.h"
namespace Material {
/// Material::Entry contains various information about a material configuration.
/// It contains a material imbalance evaluation, a function pointer to a special
/// endgame evaluation function (which in most cases is NULL, meaning that the
/// standard evaluation function will be used), and scale factors.
///
/// The scale factors are used to scale the evaluation score up or down. For
/// instance, in KRB vs KR endgames, the score is scaled down by a factor of 4,
/// which will result in scores of absolute value less than one pawn.
struct Entry {
Score imbalance() const { return make_score(value, value); }
Phase game_phase() const { return gamePhase; }
bool specialized_eval_exists() const { return evaluationFunction != nullptr; }
Value evaluate(const Position& pos) const { return (*evaluationFunction)(pos); }
// scale_factor() takes a position and a color as input and returns a scale factor
// for the given color. We have to provide the position in addition to the color
// because the scale factor may also be a function which should be applied to
// the position. For instance, in KBP vs K endgames, the scaling function looks
// for rook pawns and wrong-colored bishops.
ScaleFactor scale_factor(const Position& pos, Color c) const {
ScaleFactor sf = scalingFunction[c] ? (*scalingFunction[c])(pos)
: SCALE_FACTOR_NONE;
return sf != SCALE_FACTOR_NONE ? sf : ScaleFactor(factor[c]);
}
Key key;
const EndgameBase<Value>* evaluationFunction;
const EndgameBase<ScaleFactor>* scalingFunction[COLOR_NB]; // Could be one for each
// side (e.g. KPKP, KBPsK)
int16_t value;
uint8_t factor[COLOR_NB];
Phase gamePhase;
};
typedef HashTable<Entry, 8192> Table;
Entry* probe(const Position& pos);
} // namespace Material
#endif // #ifndef MATERIAL_H_INCLUDED

View File

@@ -1,268 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include "memory.h"
#include <cstdlib>
#if __has_include("features.h")
#include <features.h>
#endif
#if defined(__linux__) && !defined(__ANDROID__)
#include <sys/mman.h>
#endif
#if defined(__APPLE__) || defined(__ANDROID__) || defined(__OpenBSD__) \
|| (defined(__GLIBCXX__) && !defined(_GLIBCXX_HAVE_ALIGNED_ALLOC) && !defined(_WIN32)) \
|| defined(__e2k__)
#define POSIXALIGNEDALLOC
#include <stdlib.h>
#endif
#ifdef _WIN32
#if _WIN32_WINNT < 0x0601
#undef _WIN32_WINNT
#define _WIN32_WINNT 0x0601 // Force to include needed API prototypes
#endif
#ifndef NOMINMAX
#define NOMINMAX
#endif
#include <ios> // std::hex, std::dec
#include <iostream> // std::cerr
#include <ostream> // std::endl
#include <windows.h>
// The needed Windows API for processor groups could be missed from old Windows
// versions, so instead of calling them directly (forcing the linker to resolve
// the calls at compile time), try to load them at runtime. To do this we need
// first to define the corresponding function pointers.
extern "C" {
using OpenProcessToken_t = bool (*)(HANDLE, DWORD, PHANDLE);
using LookupPrivilegeValueA_t = bool (*)(LPCSTR, LPCSTR, PLUID);
using AdjustTokenPrivileges_t =
bool (*)(HANDLE, BOOL, PTOKEN_PRIVILEGES, DWORD, PTOKEN_PRIVILEGES, PDWORD);
}
#endif
namespace Stockfish {
// Wrappers for systems where the c++17 implementation does not guarantee the
// availability of aligned_alloc(). Memory allocated with std_aligned_alloc()
// must be freed with std_aligned_free().
void* std_aligned_alloc(size_t alignment, size_t size) {
#if defined(_ISOC11_SOURCE)
return aligned_alloc(alignment, size);
#elif defined(POSIXALIGNEDALLOC)
void* mem = nullptr;
posix_memalign(&mem, alignment, size);
return mem;
#elif defined(_WIN32) && !defined(_M_ARM) && !defined(_M_ARM64)
return _mm_malloc(size, alignment);
#elif defined(_WIN32)
return _aligned_malloc(size, alignment);
#else
return std::aligned_alloc(alignment, size);
#endif
}
void std_aligned_free(void* ptr) {
#if defined(POSIXALIGNEDALLOC)
free(ptr);
#elif defined(_WIN32) && !defined(_M_ARM) && !defined(_M_ARM64)
_mm_free(ptr);
#elif defined(_WIN32)
_aligned_free(ptr);
#else
free(ptr);
#endif
}
// aligned_large_pages_alloc() will return suitably aligned memory,
// if possible using large pages.
#if defined(_WIN32)
static void* aligned_large_pages_alloc_windows([[maybe_unused]] size_t allocSize) {
#if !defined(_WIN64)
return nullptr;
#else
HANDLE hProcessToken{};
LUID luid{};
void* mem = nullptr;
const size_t largePageSize = GetLargePageMinimum();
if (!largePageSize)
return nullptr;
// Dynamically link OpenProcessToken, LookupPrivilegeValue and AdjustTokenPrivileges
HMODULE hAdvapi32 = GetModuleHandle(TEXT("advapi32.dll"));
if (!hAdvapi32)
hAdvapi32 = LoadLibrary(TEXT("advapi32.dll"));
auto OpenProcessToken_f =
OpenProcessToken_t((void (*)()) GetProcAddress(hAdvapi32, "OpenProcessToken"));
if (!OpenProcessToken_f)
return nullptr;
auto LookupPrivilegeValueA_f =
LookupPrivilegeValueA_t((void (*)()) GetProcAddress(hAdvapi32, "LookupPrivilegeValueA"));
if (!LookupPrivilegeValueA_f)
return nullptr;
auto AdjustTokenPrivileges_f =
AdjustTokenPrivileges_t((void (*)()) GetProcAddress(hAdvapi32, "AdjustTokenPrivileges"));
if (!AdjustTokenPrivileges_f)
return nullptr;
// We need SeLockMemoryPrivilege, so try to enable it for the process
if (!OpenProcessToken_f( // OpenProcessToken()
GetCurrentProcess(), TOKEN_ADJUST_PRIVILEGES | TOKEN_QUERY, &hProcessToken))
return nullptr;
if (LookupPrivilegeValueA_f(nullptr, "SeLockMemoryPrivilege", &luid))
{
TOKEN_PRIVILEGES tp{};
TOKEN_PRIVILEGES prevTp{};
DWORD prevTpLen = 0;
tp.PrivilegeCount = 1;
tp.Privileges[0].Luid = luid;
tp.Privileges[0].Attributes = SE_PRIVILEGE_ENABLED;
// Try to enable SeLockMemoryPrivilege. Note that even if AdjustTokenPrivileges()
// succeeds, we still need to query GetLastError() to ensure that the privileges
// were actually obtained.
if (AdjustTokenPrivileges_f(hProcessToken, FALSE, &tp, sizeof(TOKEN_PRIVILEGES), &prevTp,
&prevTpLen)
&& GetLastError() == ERROR_SUCCESS)
{
// Round up size to full pages and allocate
allocSize = (allocSize + largePageSize - 1) & ~size_t(largePageSize - 1);
mem = VirtualAlloc(nullptr, allocSize, MEM_RESERVE | MEM_COMMIT | MEM_LARGE_PAGES,
PAGE_READWRITE);
// Privilege no longer needed, restore previous state
AdjustTokenPrivileges_f(hProcessToken, FALSE, &prevTp, 0, nullptr, nullptr);
}
}
CloseHandle(hProcessToken);
return mem;
#endif
}
void* aligned_large_pages_alloc(size_t allocSize) {
// Try to allocate large pages
void* mem = aligned_large_pages_alloc_windows(allocSize);
// Fall back to regular, page-aligned, allocation if necessary
if (!mem)
mem = VirtualAlloc(nullptr, allocSize, MEM_RESERVE | MEM_COMMIT, PAGE_READWRITE);
return mem;
}
#else
void* aligned_large_pages_alloc(size_t allocSize) {
#if defined(__linux__)
constexpr size_t alignment = 2 * 1024 * 1024; // 2MB page size assumed
#else
constexpr size_t alignment = 4096; // small page size assumed
#endif
// Round up to multiples of alignment
size_t size = ((allocSize + alignment - 1) / alignment) * alignment;
void* mem = std_aligned_alloc(alignment, size);
#if defined(MADV_HUGEPAGE)
madvise(mem, size, MADV_HUGEPAGE);
#endif
return mem;
}
#endif
bool has_large_pages() {
#if defined(_WIN32)
constexpr size_t page_size = 2 * 1024 * 1024; // 2MB page size assumed
void* mem = aligned_large_pages_alloc_windows(page_size);
if (mem == nullptr)
{
return false;
}
else
{
aligned_large_pages_free(mem);
return true;
}
#elif defined(__linux__)
#if defined(MADV_HUGEPAGE)
return true;
#else
return false;
#endif
#else
return false;
#endif
}
// aligned_large_pages_free() will free the previously memory allocated
// by aligned_large_pages_alloc(). The effect is a nop if mem == nullptr.
#if defined(_WIN32)
void aligned_large_pages_free(void* mem) {
if (mem && !VirtualFree(mem, 0, MEM_RELEASE))
{
DWORD err = GetLastError();
std::cerr << "Failed to free large page memory. Error code: 0x" << std::hex << err
<< std::dec << std::endl;
exit(EXIT_FAILURE);
}
}
#else
void aligned_large_pages_free(void* mem) { std_aligned_free(mem); }
#endif
} // namespace Stockfish

View File

@@ -1,217 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef MEMORY_H_INCLUDED
#define MEMORY_H_INCLUDED
#include <algorithm>
#include <cstddef>
#include <cstdint>
#include <memory>
#include <new>
#include <type_traits>
#include <utility>
#include "types.h"
namespace Stockfish {
void* std_aligned_alloc(size_t alignment, size_t size);
void std_aligned_free(void* ptr);
// Memory aligned by page size, min alignment: 4096 bytes
void* aligned_large_pages_alloc(size_t size);
void aligned_large_pages_free(void* mem);
bool has_large_pages();
// Frees memory which was placed there with placement new.
// Works for both single objects and arrays of unknown bound.
template<typename T, typename FREE_FUNC>
void memory_deleter(T* ptr, FREE_FUNC free_func) {
if (!ptr)
return;
// Explicitly needed to call the destructor
if constexpr (!std::is_trivially_destructible_v<T>)
ptr->~T();
free_func(ptr);
}
// Frees memory which was placed there with placement new.
// Works for both single objects and arrays of unknown bound.
template<typename T, typename FREE_FUNC>
void memory_deleter_array(T* ptr, FREE_FUNC free_func) {
if (!ptr)
return;
// Move back on the pointer to where the size is allocated
const size_t array_offset = std::max(sizeof(size_t), alignof(T));
char* raw_memory = reinterpret_cast<char*>(ptr) - array_offset;
if constexpr (!std::is_trivially_destructible_v<T>)
{
const size_t size = *reinterpret_cast<size_t*>(raw_memory);
// Explicitly call the destructor for each element in reverse order
for (size_t i = size; i-- > 0;)
ptr[i].~T();
}
free_func(raw_memory);
}
// Allocates memory for a single object and places it there with placement new
template<typename T, typename ALLOC_FUNC, typename... Args>
inline std::enable_if_t<!std::is_array_v<T>, T*> memory_allocator(ALLOC_FUNC alloc_func,
Args&&... args) {
void* raw_memory = alloc_func(sizeof(T));
ASSERT_ALIGNED(raw_memory, alignof(T));
return new (raw_memory) T(std::forward<Args>(args)...);
}
// Allocates memory for an array of unknown bound and places it there with placement new
template<typename T, typename ALLOC_FUNC>
inline std::enable_if_t<std::is_array_v<T>, std::remove_extent_t<T>*>
memory_allocator(ALLOC_FUNC alloc_func, size_t num) {
using ElementType = std::remove_extent_t<T>;
const size_t array_offset = std::max(sizeof(size_t), alignof(ElementType));
// Save the array size in the memory location
char* raw_memory =
reinterpret_cast<char*>(alloc_func(array_offset + num * sizeof(ElementType)));
ASSERT_ALIGNED(raw_memory, alignof(T));
new (raw_memory) size_t(num);
for (size_t i = 0; i < num; ++i)
new (raw_memory + array_offset + i * sizeof(ElementType)) ElementType();
// Need to return the pointer at the start of the array so that
// the indexing in unique_ptr<T[]> works.
return reinterpret_cast<ElementType*>(raw_memory + array_offset);
}
//
//
// aligned large page unique ptr
//
//
template<typename T>
struct LargePageDeleter {
void operator()(T* ptr) const { return memory_deleter<T>(ptr, aligned_large_pages_free); }
};
template<typename T>
struct LargePageArrayDeleter {
void operator()(T* ptr) const { return memory_deleter_array<T>(ptr, aligned_large_pages_free); }
};
template<typename T>
using LargePagePtr =
std::conditional_t<std::is_array_v<T>,
std::unique_ptr<T, LargePageArrayDeleter<std::remove_extent_t<T>>>,
std::unique_ptr<T, LargePageDeleter<T>>>;
// make_unique_large_page for single objects
template<typename T, typename... Args>
std::enable_if_t<!std::is_array_v<T>, LargePagePtr<T>> make_unique_large_page(Args&&... args) {
static_assert(alignof(T) <= 4096,
"aligned_large_pages_alloc() may fail for such a big alignment requirement of T");
T* obj = memory_allocator<T>(aligned_large_pages_alloc, std::forward<Args>(args)...);
return LargePagePtr<T>(obj);
}
// make_unique_large_page for arrays of unknown bound
template<typename T>
std::enable_if_t<std::is_array_v<T>, LargePagePtr<T>> make_unique_large_page(size_t num) {
using ElementType = std::remove_extent_t<T>;
static_assert(alignof(ElementType) <= 4096,
"aligned_large_pages_alloc() may fail for such a big alignment requirement of T");
ElementType* memory = memory_allocator<T>(aligned_large_pages_alloc, num);
return LargePagePtr<T>(memory);
}
//
//
// aligned unique ptr
//
//
template<typename T>
struct AlignedDeleter {
void operator()(T* ptr) const { return memory_deleter<T>(ptr, std_aligned_free); }
};
template<typename T>
struct AlignedArrayDeleter {
void operator()(T* ptr) const { return memory_deleter_array<T>(ptr, std_aligned_free); }
};
template<typename T>
using AlignedPtr =
std::conditional_t<std::is_array_v<T>,
std::unique_ptr<T, AlignedArrayDeleter<std::remove_extent_t<T>>>,
std::unique_ptr<T, AlignedDeleter<T>>>;
// make_unique_aligned for single objects
template<typename T, typename... Args>
std::enable_if_t<!std::is_array_v<T>, AlignedPtr<T>> make_unique_aligned(Args&&... args) {
const auto func = [](size_t size) { return std_aligned_alloc(alignof(T), size); };
T* obj = memory_allocator<T>(func, std::forward<Args>(args)...);
return AlignedPtr<T>(obj);
}
// make_unique_aligned for arrays of unknown bound
template<typename T>
std::enable_if_t<std::is_array_v<T>, AlignedPtr<T>> make_unique_aligned(size_t num) {
using ElementType = std::remove_extent_t<T>;
const auto func = [](size_t size) { return std_aligned_alloc(alignof(ElementType), size); };
ElementType* memory = memory_allocator<T>(func, num);
return AlignedPtr<T>(memory);
}
// Get the first aligned element of an array.
// ptr must point to an array of size at least `sizeof(T) * N + alignment` bytes,
// where N is the number of elements in the array.
template<uintptr_t Alignment, typename T>
T* align_ptr_up(T* ptr) {
static_assert(alignof(T) < Alignment);
const uintptr_t ptrint = reinterpret_cast<uintptr_t>(reinterpret_cast<char*>(ptr));
return reinterpret_cast<T*>(
reinterpret_cast<char*>((ptrint + (Alignment - 1)) / Alignment * Alignment));
}
} // namespace Stockfish
#endif // #ifndef MEMORY_H_INCLUDED

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -16,509 +16,558 @@
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include "misc.h"
#ifdef _WIN32
#if _WIN32_WINNT < 0x0601
#undef _WIN32_WINNT
#define _WIN32_WINNT 0x0601 // Force to include needed API prototypes
#endif
#ifndef NOMINMAX
#define NOMINMAX
#endif
#include <windows.h>
// The needed Windows API for processor groups could be missed from old Windows
// versions, so instead of calling them directly (forcing the linker to resolve
// the calls at compile time), try to load them at runtime. To do this we need
// first to define the corresponding function pointers.
extern "C" {
typedef bool(*fun1_t)(LOGICAL_PROCESSOR_RELATIONSHIP,
PSYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX, PDWORD);
typedef bool(*fun2_t)(USHORT, PGROUP_AFFINITY);
typedef bool(*fun3_t)(HANDLE, CONST GROUP_AFFINITY*, PGROUP_AFFINITY);
}
#endif
#include <array>
#include <atomic>
#include <cassert>
#include <cctype>
#include <cmath>
#include <cstdlib>
#include <fstream>
#include <iomanip>
#include <iostream>
#include <iterator>
#include <limits>
#include <mutex>
#include <sstream>
#include <string_view>
#include <vector>
#include <cstdlib>
#include "types.h"
#if defined(__linux__) && !defined(__ANDROID__)
#include <stdlib.h>
#include <sys/mman.h>
#endif
namespace Stockfish {
#include "misc.h"
#include "thread.h"
using namespace std;
namespace {
// Version number or dev.
constexpr std::string_view version = "dev";
/// Version number. If Version is left empty, then compile date in the format
/// DD-MM-YY and show in engine_info.
const string Version = "";
// Our fancy logging facility. The trick here is to replace cin.rdbuf() and
// cout.rdbuf() with two Tie objects that tie cin and cout to a file stream. We
// can toggle the logging of std::cout and std:cin at runtime whilst preserving
// usual I/O functionality, all without changing a single line of code!
// Idea from http://groups.google.com/group/comp.lang.c++/msg/1d941c0f26ea0d81
/// Our fancy logging facility. The trick here is to replace cin.rdbuf() and
/// cout.rdbuf() with two Tie objects that tie cin and cout to a file stream. We
/// can toggle the logging of std::cout and std:cin at runtime whilst preserving
/// usual I/O functionality, all without changing a single line of code!
/// Idea from http://groups.google.com/group/comp.lang.c++/msg/1d941c0f26ea0d81
struct Tie: public std::streambuf { // MSVC requires split streambuf for cin and cout
struct Tie: public streambuf { // MSVC requires split streambuf for cin and cout
Tie(std::streambuf* b, std::streambuf* l) :
buf(b),
logBuf(l) {}
Tie(streambuf* b, streambuf* l) : buf(b), logBuf(l) {}
int sync() override { return logBuf->pubsync(), buf->pubsync(); }
int overflow(int c) override { return log(buf->sputc(char(c)), "<< "); }
int underflow() override { return buf->sgetc(); }
int uflow() override { return log(buf->sbumpc(), ">> "); }
int sync() override { return logBuf->pubsync(), buf->pubsync(); }
int overflow(int c) override { return log(buf->sputc((char)c), "<< "); }
int underflow() override { return buf->sgetc(); }
int uflow() override { return log(buf->sbumpc(), ">> "); }
std::streambuf *buf, *logBuf;
streambuf *buf, *logBuf;
int log(int c, const char* prefix) {
int log(int c, const char* prefix) {
static int last = '\n'; // Single log file
static int last = '\n'; // Single log file
if (last == '\n')
logBuf->sputn(prefix, 3);
if (last == '\n')
logBuf->sputn(prefix, 3);
return last = logBuf->sputc(char(c));
}
return last = logBuf->sputc((char)c);
}
};
class Logger {
Logger() :
in(std::cin.rdbuf(), file.rdbuf()),
out(std::cout.rdbuf(), file.rdbuf()) {}
~Logger() { start(""); }
Logger() : in(cin.rdbuf(), file.rdbuf()), out(cout.rdbuf(), file.rdbuf()) {}
~Logger() { start(""); }
std::ofstream file;
Tie in, out;
ofstream file;
Tie in, out;
public:
static void start(const std::string& fname) {
public:
static void start(const std::string& fname) {
static Logger l;
static Logger l;
if (l.file.is_open())
{
std::cout.rdbuf(l.out.buf);
std::cin.rdbuf(l.in.buf);
l.file.close();
}
if (!fname.empty())
{
l.file.open(fname, std::ifstream::out);
if (!l.file.is_open())
{
std::cerr << "Unable to open debug log file " << fname << std::endl;
exit(EXIT_FAILURE);
}
std::cin.rdbuf(&l.in);
std::cout.rdbuf(&l.out);
}
}
};
} // namespace
// Returns the full name of the current Stockfish version.
//
// For local dev compiles we try to append the commit SHA and
// commit date from git. If that fails only the local compilation
// date is set and "nogit" is specified:
// Stockfish dev-YYYYMMDD-SHA
// or
// Stockfish dev-YYYYMMDD-nogit
//
// For releases (non-dev builds) we only include the version number:
// Stockfish version
std::string engine_version_info() {
std::stringstream ss;
ss << "Stockfish " << version << std::setfill('0');
if constexpr (version == "dev")
if (!fname.empty() && !l.file.is_open())
{
ss << "-";
#ifdef GIT_DATE
ss << stringify(GIT_DATE);
#else
constexpr std::string_view months("Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec");
l.file.open(fname, ifstream::out);
std::string month, day, year;
std::stringstream date(__DATE__); // From compiler, format is "Sep 21 2008"
if (!l.file.is_open())
{
cerr << "Unable to open debug log file " << fname << endl;
exit(EXIT_FAILURE);
}
date >> month >> day >> year;
ss << year << std::setw(2) << std::setfill('0') << (1 + months.find(month) / 4)
<< std::setw(2) << std::setfill('0') << day;
#endif
ss << "-";
#ifdef GIT_SHA
ss << stringify(GIT_SHA);
#else
ss << "nogit";
#endif
cin.rdbuf(&l.in);
cout.rdbuf(&l.out);
}
else if (fname.empty() && l.file.is_open())
{
cout.rdbuf(l.out.buf);
cin.rdbuf(l.in.buf);
l.file.close();
}
}
};
return ss.str();
}
} // namespace
std::string engine_info(bool to_uci) {
return engine_version_info() + (to_uci ? "\nid author " : " by ")
+ "the Stockfish developers (see AUTHORS file)";
/// engine_info() returns the full name of the current Stockfish version. This
/// will be either "Stockfish <Tag> DD-MM-YY" (where DD-MM-YY is the date when
/// the program was compiled) or "Stockfish <Version>", depending on whether
/// Version is empty.
const string engine_info(bool to_uci) {
const string months("Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec");
string month, day, year;
stringstream ss, date(__DATE__); // From compiler, format is "Sep 21 2008"
ss << "Stockfish " << Version << setfill('0');
if (Version.empty())
{
date >> month >> day >> year;
ss << setw(2) << day << setw(2) << (1 + months.find(month) / 4) << year.substr(2);
}
ss << (to_uci ? "\nid author ": " by ")
<< "the Stockfish developers (see AUTHORS file)";
return ss.str();
}
// Returns a string trying to describe the compiler we use
std::string compiler_info() {
/// compiler_info() returns a string trying to describe the compiler we use
#define make_version_string(major, minor, patch) \
stringify(major) "." stringify(minor) "." stringify(patch)
const std::string compiler_info() {
// Predefined macros hell:
//
// __GNUC__ Compiler is GCC, Clang or ICX
// __clang__ Compiler is Clang or ICX
// __INTEL_LLVM_COMPILER Compiler is ICX
// _MSC_VER Compiler is MSVC
// _WIN32 Building on Windows (any)
// _WIN64 Building on Windows 64 bit
#define stringify2(x) #x
#define stringify(x) stringify2(x)
#define make_version_string(major, minor, patch) stringify(major) "." stringify(minor) "." stringify(patch)
std::string compiler = "\nCompiled by : ";
/// Predefined macros hell:
///
/// __GNUC__ Compiler is gcc, Clang or Intel on Linux
/// __INTEL_COMPILER Compiler is Intel
/// _MSC_VER Compiler is MSVC or Intel on Windows
/// _WIN32 Building on Windows (any)
/// _WIN64 Building on Windows 64 bit
#if defined(__INTEL_LLVM_COMPILER)
compiler += "ICX ";
compiler += stringify(__INTEL_LLVM_COMPILER);
#elif defined(__clang__)
compiler += "clang++ ";
compiler += make_version_string(__clang_major__, __clang_minor__, __clang_patchlevel__);
#elif _MSC_VER
compiler += "MSVC ";
compiler += "(version ";
compiler += stringify(_MSC_FULL_VER) "." stringify(_MSC_BUILD);
compiler += ")";
#elif defined(__e2k__) && defined(__LCC__)
#define dot_ver2(n) \
compiler += char('.'); \
compiler += char('0' + (n) / 10); \
compiler += char('0' + (n) % 10);
std::string compiler = "\nCompiled by ";
compiler += "MCST LCC ";
compiler += "(version ";
compiler += std::to_string(__LCC__ / 100);
dot_ver2(__LCC__ % 100) dot_ver2(__LCC_MINOR__) compiler += ")";
#elif __GNUC__
compiler += "g++ (GNUC) ";
compiler += make_version_string(__GNUC__, __GNUC_MINOR__, __GNUC_PATCHLEVEL__);
#else
compiler += "Unknown compiler ";
compiler += "(unknown version)";
#endif
#ifdef __clang__
compiler += "clang++ ";
compiler += make_version_string(__clang_major__, __clang_minor__, __clang_patchlevel__);
#elif __INTEL_COMPILER
compiler += "Intel compiler ";
compiler += "(version ";
compiler += stringify(__INTEL_COMPILER) " update " stringify(__INTEL_COMPILER_UPDATE);
compiler += ")";
#elif _MSC_VER
compiler += "MSVC ";
compiler += "(version ";
compiler += stringify(_MSC_FULL_VER) "." stringify(_MSC_BUILD);
compiler += ")";
#elif __GNUC__
compiler += "g++ (GNUC) ";
compiler += make_version_string(__GNUC__, __GNUC_MINOR__, __GNUC_PATCHLEVEL__);
#else
compiler += "Unknown compiler ";
compiler += "(unknown version)";
#endif
#if defined(__APPLE__)
compiler += " on Apple";
#elif defined(__CYGWIN__)
compiler += " on Cygwin";
#elif defined(__MINGW64__)
compiler += " on MinGW64";
#elif defined(__MINGW32__)
compiler += " on MinGW32";
#elif defined(__ANDROID__)
compiler += " on Android";
#elif defined(__linux__)
compiler += " on Linux";
#elif defined(_WIN64)
compiler += " on Microsoft Windows 64-bit";
#elif defined(_WIN32)
compiler += " on Microsoft Windows 32-bit";
#else
compiler += " on unknown system";
#endif
#if defined(__APPLE__)
compiler += " on Apple";
#elif defined(__CYGWIN__)
compiler += " on Cygwin";
#elif defined(__MINGW64__)
compiler += " on MinGW64";
#elif defined(__MINGW32__)
compiler += " on MinGW32";
#elif defined(__ANDROID__)
compiler += " on Android";
#elif defined(__linux__)
compiler += " on Linux";
#elif defined(_WIN64)
compiler += " on Microsoft Windows 64-bit";
#elif defined(_WIN32)
compiler += " on Microsoft Windows 32-bit";
#else
compiler += " on unknown system";
#endif
compiler += "\nCompilation architecture : ";
#if defined(ARCH)
compiler += stringify(ARCH);
#else
compiler += "(undefined architecture)";
#endif
compiler += "\nCompilation settings : ";
compiler += (Is64Bit ? "64bit" : "32bit");
#if defined(USE_VNNI)
compiler += " VNNI";
#endif
#if defined(USE_AVX512)
compiler += "\nCompilation settings include: ";
compiler += (Is64Bit ? " 64bit" : " 32bit");
#if defined(USE_AVX512)
compiler += " AVX512";
#endif
compiler += (HasPext ? " BMI2" : "");
#if defined(USE_AVX2)
#endif
#if defined(USE_AVX2)
compiler += " AVX2";
#endif
#if defined(USE_SSE41)
#endif
#if defined(USE_SSE42)
compiler += " SSE42";
#endif
#if defined(USE_SSE41)
compiler += " SSE41";
#endif
#if defined(USE_SSSE3)
#endif
#if defined(USE_SSSE3)
compiler += " SSSE3";
#endif
#if defined(USE_SSE2)
compiler += " SSE2";
#endif
#endif
#if defined(USE_SSE3)
compiler += " SSE3";
#endif
compiler += (HasPext ? " BMI2" : "");
compiler += (HasPopCnt ? " POPCNT" : "");
#if defined(USE_NEON_DOTPROD)
compiler += " NEON_DOTPROD";
#elif defined(USE_NEON)
compiler += " NEON";
#endif
#if !defined(NDEBUG)
#if !defined(NDEBUG)
compiler += " DEBUG";
#endif
#endif
compiler += "\nCompiler __VERSION__ macro : ";
#ifdef __VERSION__
compiler += __VERSION__;
#else
compiler += "(undefined macro)";
#endif
compiler += "\n__VERSION__ macro expands to: ";
#ifdef __VERSION__
compiler += __VERSION__;
#else
compiler += "(undefined macro)";
#endif
compiler += "\n";
compiler += "\n";
return compiler;
return compiler;
}
// Debug functions used mainly to collect run-time statistics
constexpr int MaxDebugSlots = 32;
/// Debug functions used mainly to collect run-time statistics
static std::atomic<int64_t> hits[2], means[2];
namespace {
template<size_t N>
struct DebugInfo {
std::array<std::atomic<int64_t>, N> data = {0};
[[nodiscard]] constexpr std::atomic<int64_t>& operator[](size_t index) {
assert(index < N);
return data[index];
}
constexpr DebugInfo& operator=(const DebugInfo& other) {
for (size_t i = 0; i < N; i++)
data[i].store(other.data[i].load());
return *this;
}
};
struct DebugExtremes: public DebugInfo<3> {
DebugExtremes() {
data[1] = std::numeric_limits<int64_t>::min();
data[2] = std::numeric_limits<int64_t>::max();
}
};
std::array<DebugInfo<2>, MaxDebugSlots> hit;
std::array<DebugInfo<2>, MaxDebugSlots> mean;
std::array<DebugInfo<3>, MaxDebugSlots> stdev;
std::array<DebugInfo<6>, MaxDebugSlots> correl;
std::array<DebugExtremes, MaxDebugSlots> extremes;
} // namespace
void dbg_hit_on(bool cond, int slot) {
++hit.at(slot)[0];
if (cond)
++hit.at(slot)[1];
}
void dbg_mean_of(int64_t value, int slot) {
++mean.at(slot)[0];
mean.at(slot)[1] += value;
}
void dbg_stdev_of(int64_t value, int slot) {
++stdev.at(slot)[0];
stdev.at(slot)[1] += value;
stdev.at(slot)[2] += value * value;
}
void dbg_extremes_of(int64_t value, int slot) {
++extremes.at(slot)[0];
int64_t current_max = extremes.at(slot)[1].load();
while (current_max < value && !extremes.at(slot)[1].compare_exchange_weak(current_max, value))
{}
int64_t current_min = extremes.at(slot)[2].load();
while (current_min > value && !extremes.at(slot)[2].compare_exchange_weak(current_min, value))
{}
}
void dbg_correl_of(int64_t value1, int64_t value2, int slot) {
++correl.at(slot)[0];
correl.at(slot)[1] += value1;
correl.at(slot)[2] += value1 * value1;
correl.at(slot)[3] += value2;
correl.at(slot)[4] += value2 * value2;
correl.at(slot)[5] += value1 * value2;
}
void dbg_hit_on(bool b) { ++hits[0]; if (b) ++hits[1]; }
void dbg_hit_on(bool c, bool b) { if (c) dbg_hit_on(b); }
void dbg_mean_of(int v) { ++means[0]; means[1] += v; }
void dbg_print() {
int64_t n;
auto E = [&n](int64_t x) { return double(x) / n; };
auto sqr = [](double x) { return x * x; };
if (hits[0])
cerr << "Total " << hits[0] << " Hits " << hits[1]
<< " hit rate (%) " << 100 * hits[1] / hits[0] << endl;
for (int i = 0; i < MaxDebugSlots; ++i)
if ((n = hit[i][0]))
std::cerr << "Hit #" << i << ": Total " << n << " Hits " << hit[i][1]
<< " Hit Rate (%) " << 100.0 * E(hit[i][1]) << std::endl;
for (int i = 0; i < MaxDebugSlots; ++i)
if ((n = mean[i][0]))
{
std::cerr << "Mean #" << i << ": Total " << n << " Mean " << E(mean[i][1]) << std::endl;
}
for (int i = 0; i < MaxDebugSlots; ++i)
if ((n = stdev[i][0]))
{
double r = sqrt(E(stdev[i][2]) - sqr(E(stdev[i][1])));
std::cerr << "Stdev #" << i << ": Total " << n << " Stdev " << r << std::endl;
}
for (int i = 0; i < MaxDebugSlots; ++i)
if ((n = extremes[i][0]))
{
std::cerr << "Extremity #" << i << ": Total " << n << " Min " << extremes[i][2]
<< " Max " << extremes[i][1] << std::endl;
}
for (int i = 0; i < MaxDebugSlots; ++i)
if ((n = correl[i][0]))
{
double r = (E(correl[i][5]) - E(correl[i][1]) * E(correl[i][3]))
/ (sqrt(E(correl[i][2]) - sqr(E(correl[i][1])))
* sqrt(E(correl[i][4]) - sqr(E(correl[i][3]))));
std::cerr << "Correl. #" << i << ": Total " << n << " Coefficient " << r << std::endl;
}
if (means[0])
cerr << "Total " << means[0] << " Mean "
<< (double)means[1] / means[0] << endl;
}
void dbg_clear() {
hit.fill({});
mean.fill({});
stdev.fill({});
correl.fill({});
extremes.fill({});
}
// Used to serialize access to std::cout
// to avoid multiple threads writing at the same time.
/// Used to serialize access to std::cout to avoid multiple threads writing at
/// the same time.
std::ostream& operator<<(std::ostream& os, SyncCout sc) {
static std::mutex m;
static std::mutex m;
if (sc == IO_LOCK)
m.lock();
if (sc == IO_LOCK)
m.lock();
if (sc == IO_UNLOCK)
m.unlock();
if (sc == IO_UNLOCK)
m.unlock();
return os;
return os;
}
void sync_cout_start() { std::cout << IO_LOCK; }
void sync_cout_end() { std::cout << IO_UNLOCK; }
// Trampoline helper to avoid moving Logger to misc.h
/// Trampoline helper to avoid moving Logger to misc.h
void start_logger(const std::string& fname) { Logger::start(fname); }
/// prefetch() preloads the given address in L1/L2 cache. This is a non-blocking
/// function that doesn't stall the CPU waiting for data to be loaded from memory,
/// which can be quite slow.
#ifdef NO_PREFETCH
void prefetch(const void*) {}
void prefetch(void*) {}
#else
void prefetch(const void* addr) {
void prefetch(void* addr) {
#if defined(_MSC_VER)
_mm_prefetch((char const*) addr, _MM_HINT_T0);
#else
__builtin_prefetch(addr);
#endif
# if defined(__INTEL_COMPILER)
// This hack prevents prefetches from being optimized away by
// Intel compiler. Both MSVC and gcc seem not be affected by this.
__asm__ ("");
# endif
# if defined(__INTEL_COMPILER) || defined(_MSC_VER)
_mm_prefetch((char*)addr, _MM_HINT_T0);
# else
__builtin_prefetch(addr);
# endif
}
#endif
#ifdef _WIN32
#include <direct.h>
#define GETCWD _getcwd
/// Wrappers for systems where the c++17 implementation doesn't guarantee the availability of aligned_alloc.
/// Memory allocated with std_aligned_alloc must be freed with std_aligned_free.
///
void* std_aligned_alloc(size_t alignment, size_t size) {
#if defined(__APPLE__)
return aligned_alloc(alignment, size);
#elif defined(_WIN32)
return _mm_malloc(size, alignment);
#else
#include <unistd.h>
#define GETCWD getcwd
return std::aligned_alloc(alignment, size);
#endif
}
void std_aligned_free(void* ptr) {
#if defined(__APPLE__)
free(ptr);
#elif defined(_WIN32)
_mm_free(ptr);
#else
free(ptr);
#endif
}
/// aligned_ttmem_alloc() will return suitably aligned memory, and if possible use large pages.
/// The returned pointer is the aligned one, while the mem argument is the one that needs
/// to be passed to free. With c++17 some of this functionality could be simplified.
#if defined(__linux__) && !defined(__ANDROID__)
void* aligned_ttmem_alloc(size_t allocSize, void*& mem) {
constexpr size_t alignment = 2 * 1024 * 1024; // assumed 2MB page sizes
size_t size = ((allocSize + alignment - 1) / alignment) * alignment; // multiple of alignment
if (posix_memalign(&mem, alignment, size))
mem = nullptr;
madvise(mem, allocSize, MADV_HUGEPAGE);
return mem;
}
#elif defined(_WIN64)
static void* aligned_ttmem_alloc_large_pages(size_t allocSize) {
HANDLE hProcessToken { };
LUID luid { };
void* mem = nullptr;
const size_t largePageSize = GetLargePageMinimum();
if (!largePageSize)
return nullptr;
// We need SeLockMemoryPrivilege, so try to enable it for the process
if (!OpenProcessToken(GetCurrentProcess(), TOKEN_ADJUST_PRIVILEGES | TOKEN_QUERY, &hProcessToken))
return nullptr;
if (LookupPrivilegeValue(NULL, SE_LOCK_MEMORY_NAME, &luid))
{
TOKEN_PRIVILEGES tp { };
TOKEN_PRIVILEGES prevTp { };
DWORD prevTpLen = 0;
tp.PrivilegeCount = 1;
tp.Privileges[0].Luid = luid;
tp.Privileges[0].Attributes = SE_PRIVILEGE_ENABLED;
// Try to enable SeLockMemoryPrivilege. Note that even if AdjustTokenPrivileges() succeeds,
// we still need to query GetLastError() to ensure that the privileges were actually obtained.
if (AdjustTokenPrivileges(
hProcessToken, FALSE, &tp, sizeof(TOKEN_PRIVILEGES), &prevTp, &prevTpLen) &&
GetLastError() == ERROR_SUCCESS)
{
// Round up size to full pages and allocate
allocSize = (allocSize + largePageSize - 1) & ~size_t(largePageSize - 1);
mem = VirtualAlloc(
NULL, allocSize, MEM_RESERVE | MEM_COMMIT | MEM_LARGE_PAGES, PAGE_READWRITE);
// Privilege no longer needed, restore previous state
AdjustTokenPrivileges(hProcessToken, FALSE, &prevTp, 0, NULL, NULL);
}
}
CloseHandle(hProcessToken);
return mem;
}
void* aligned_ttmem_alloc(size_t allocSize, void*& mem) {
static bool firstCall = true;
// Try to allocate large pages
mem = aligned_ttmem_alloc_large_pages(allocSize);
// Suppress info strings on the first call. The first call occurs before 'uci'
// is received and in that case this output confuses some GUIs.
if (!firstCall)
{
if (mem)
sync_cout << "info string Hash table allocation: Windows large pages used." << sync_endl;
else
sync_cout << "info string Hash table allocation: Windows large pages not used." << sync_endl;
}
firstCall = false;
// Fall back to regular, page aligned, allocation if necessary
if (!mem)
mem = VirtualAlloc(NULL, allocSize, MEM_RESERVE | MEM_COMMIT, PAGE_READWRITE);
return mem;
}
#else
void* aligned_ttmem_alloc(size_t allocSize, void*& mem) {
constexpr size_t alignment = 64; // assumed cache line size
size_t size = allocSize + alignment - 1; // allocate some extra space
mem = malloc(size);
void* ret = reinterpret_cast<void*>((uintptr_t(mem) + alignment - 1) & ~uintptr_t(alignment - 1));
return ret;
}
#endif
size_t str_to_size_t(const std::string& s) {
unsigned long long value = std::stoull(s);
if (value > std::numeric_limits<size_t>::max())
std::exit(EXIT_FAILURE);
return static_cast<size_t>(value);
/// aligned_ttmem_free() will free the previously allocated ttmem
#if defined(_WIN64)
void aligned_ttmem_free(void* mem) {
if (mem && !VirtualFree(mem, 0, MEM_RELEASE))
{
DWORD err = GetLastError();
std::cerr << "Failed to free transposition table. Error code: 0x" <<
std::hex << err << std::dec << std::endl;
exit(EXIT_FAILURE);
}
}
std::optional<std::string> read_file_to_string(const std::string& path) {
std::ifstream f(path, std::ios_base::binary);
if (!f)
return std::nullopt;
return std::string(std::istreambuf_iterator<char>(f), std::istreambuf_iterator<char>());
}
void remove_whitespace(std::string& s) {
s.erase(std::remove_if(s.begin(), s.end(), [](char c) { return std::isspace(c); }), s.end());
}
bool is_whitespace(std::string_view s) {
return std::all_of(s.begin(), s.end(), [](char c) { return std::isspace(c); });
}
std::string CommandLine::get_binary_directory(std::string argv0) {
std::string pathSeparator;
#ifdef _WIN32
pathSeparator = "\\";
#ifdef _MSC_VER
// Under windows argv[0] may not have the extension. Also _get_pgmptr() had
// issues in some Windows 10 versions, so check returned values carefully.
char* pgmptr = nullptr;
if (!_get_pgmptr(&pgmptr) && pgmptr != nullptr && *pgmptr)
argv0 = pgmptr;
#endif
#else
pathSeparator = "/";
void aligned_ttmem_free(void *mem) {
free(mem);
}
#endif
// Extract the working directory
auto workingDirectory = CommandLine::get_working_directory();
// Extract the binary directory path from argv0
auto binaryDirectory = argv0;
size_t pos = binaryDirectory.find_last_of("\\/");
if (pos == std::string::npos)
binaryDirectory = "." + pathSeparator;
else
binaryDirectory.resize(pos + 1);
namespace WinProcGroup {
// Pattern replacement: "./" at the start of path is replaced by the working directory
if (binaryDirectory.find("." + pathSeparator) == 0)
binaryDirectory.replace(0, 1, workingDirectory);
#ifndef _WIN32
return binaryDirectory;
}
void bindThisThread(size_t) {}
std::string CommandLine::get_working_directory() {
std::string workingDirectory = "";
char buff[40000];
char* cwd = GETCWD(buff, 40000);
if (cwd)
workingDirectory = cwd;
#else
return workingDirectory;
/// best_group() retrieves logical processor information using Windows specific
/// API and returns the best group id for the thread with index idx. Original
/// code from Texel by Peter Österlund.
int best_group(size_t idx) {
int threads = 0;
int nodes = 0;
int cores = 0;
DWORD returnLength = 0;
DWORD byteOffset = 0;
// Early exit if the needed API is not available at runtime
HMODULE k32 = GetModuleHandle("Kernel32.dll");
auto fun1 = (fun1_t)(void(*)())GetProcAddress(k32, "GetLogicalProcessorInformationEx");
if (!fun1)
return -1;
// First call to get returnLength. We expect it to fail due to null buffer
if (fun1(RelationAll, nullptr, &returnLength))
return -1;
// Once we know returnLength, allocate the buffer
SYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX *buffer, *ptr;
ptr = buffer = (SYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX*)malloc(returnLength);
// Second call, now we expect to succeed
if (!fun1(RelationAll, buffer, &returnLength))
{
free(buffer);
return -1;
}
while (byteOffset < returnLength)
{
if (ptr->Relationship == RelationNumaNode)
nodes++;
else if (ptr->Relationship == RelationProcessorCore)
{
cores++;
threads += (ptr->Processor.Flags == LTP_PC_SMT) ? 2 : 1;
}
assert(ptr->Size);
byteOffset += ptr->Size;
ptr = (SYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX*)(((char*)ptr) + ptr->Size);
}
free(buffer);
std::vector<int> groups;
// Run as many threads as possible on the same node until core limit is
// reached, then move on filling the next node.
for (int n = 0; n < nodes; n++)
for (int i = 0; i < cores / nodes; i++)
groups.push_back(n);
// In case a core has more than one logical processor (we assume 2) and we
// have still threads to allocate, then spread them evenly across available
// nodes.
for (int t = 0; t < threads - cores; t++)
groups.push_back(t % nodes);
// If we still have more threads than the total number of logical processors
// then return -1 and let the OS to decide what to do.
return idx < groups.size() ? groups[idx] : -1;
}
} // namespace Stockfish
/// bindThisThread() set the group affinity of the current thread
void bindThisThread(size_t idx) {
// Use only local variables to be thread-safe
int group = best_group(idx);
if (group == -1)
return;
// Early exit if the needed API are not available at runtime
HMODULE k32 = GetModuleHandle("Kernel32.dll");
auto fun2 = (fun2_t)(void(*)())GetProcAddress(k32, "GetNumaNodeProcessorMaskEx");
auto fun3 = (fun3_t)(void(*)())GetProcAddress(k32, "SetThreadGroupAffinity");
if (!fun2 || !fun3)
return;
GROUP_AFFINITY affinity;
if (fun2(group, &affinity))
fun3(GetCurrentThread(), &affinity, nullptr);
}
#endif
} // namespace WinProcGroup

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -19,320 +19,119 @@
#ifndef MISC_H_INCLUDED
#define MISC_H_INCLUDED
#include <algorithm>
#include <array>
#include <cassert>
#include <chrono>
#include <cstddef>
#include <cstdint>
#include <cstdio>
#include <iosfwd>
#include <optional>
#include <ostream>
#include <string>
#include <string_view>
#include <vector>
#define stringify2(x) #x
#define stringify(x) stringify2(x)
namespace Stockfish {
std::string engine_version_info();
std::string engine_info(bool to_uci = false);
std::string compiler_info();
// Preloads the given address in L1/L2 cache. This is a non-blocking
// function that doesn't stall the CPU waiting for data to be loaded from memory,
// which can be quite slow.
void prefetch(const void* addr);
#include "types.h"
const std::string engine_info(bool to_uci = false);
const std::string compiler_info();
void prefetch(void* addr);
void start_logger(const std::string& fname);
void* std_aligned_alloc(size_t alignment, size_t size);
void std_aligned_free(void* ptr);
void* aligned_ttmem_alloc(size_t size, void*& mem);
void aligned_ttmem_free(void* mem); // nop if mem == nullptr
size_t str_to_size_t(const std::string& s);
#if defined(__linux__)
struct PipeDeleter {
void operator()(FILE* file) const {
if (file != nullptr)
{
pclose(file);
}
}
};
#endif
// Reads the file as bytes.
// Returns std::nullopt if the file does not exist.
std::optional<std::string> read_file_to_string(const std::string& path);
void dbg_hit_on(bool cond, int slot = 0);
void dbg_mean_of(int64_t value, int slot = 0);
void dbg_stdev_of(int64_t value, int slot = 0);
void dbg_extremes_of(int64_t value, int slot = 0);
void dbg_correl_of(int64_t value1, int64_t value2, int slot = 0);
void dbg_hit_on(bool b);
void dbg_hit_on(bool c, bool b);
void dbg_mean_of(int v);
void dbg_print();
void dbg_clear();
using TimePoint = std::chrono::milliseconds::rep; // A value in milliseconds
typedef std::chrono::milliseconds::rep TimePoint; // A value in milliseconds
static_assert(sizeof(TimePoint) == sizeof(int64_t), "TimePoint should be 64 bits");
inline TimePoint now() {
return std::chrono::duration_cast<std::chrono::milliseconds>(
std::chrono::steady_clock::now().time_since_epoch())
.count();
return std::chrono::duration_cast<std::chrono::milliseconds>
(std::chrono::steady_clock::now().time_since_epoch()).count();
}
inline std::vector<std::string_view> split(std::string_view s, std::string_view delimiter) {
std::vector<std::string_view> res;
template<class Entry, int Size>
struct HashTable {
Entry* operator[](Key key) { return &table[(uint32_t)key & (Size - 1)]; }
if (s.empty())
return res;
size_t begin = 0;
for (;;)
{
const size_t end = s.find(delimiter, begin);
if (end == std::string::npos)
break;
res.emplace_back(s.substr(begin, end - begin));
begin = end + delimiter.size();
}
res.emplace_back(s.substr(begin));
return res;
}
void remove_whitespace(std::string& s);
bool is_whitespace(std::string_view s);
enum SyncCout {
IO_LOCK,
IO_UNLOCK
private:
std::vector<Entry> table = std::vector<Entry>(Size); // Allocate on the heap
};
enum SyncCout { IO_LOCK, IO_UNLOCK };
std::ostream& operator<<(std::ostream&, SyncCout);
#define sync_cout std::cout << IO_LOCK
#define sync_endl std::endl << IO_UNLOCK
void sync_cout_start();
void sync_cout_end();
namespace Utility {
// True if and only if the binary is compiled on a little-endian machine
static inline const std::uint16_t Le = 1;
static inline const bool IsLittleEndian = *reinterpret_cast<const char*>(&Le) == 1;
template<typename T, std::size_t MaxSize>
class ValueList {
public:
std::size_t size() const { return size_; }
void push_back(const T& value) { values_[size_++] = value; }
const T* begin() const { return values_; }
const T* end() const { return values_ + size_; }
const T& operator[](int index) const { return values_[index]; }
private:
T values_[MaxSize];
std::size_t size_ = 0;
};
template<typename T, std::size_t Size, std::size_t... Sizes>
class MultiArray;
namespace Detail {
template<typename T, std::size_t Size, std::size_t... Sizes>
struct MultiArrayHelper {
using ChildType = MultiArray<T, Sizes...>;
};
template<typename T, std::size_t Size>
struct MultiArrayHelper<T, Size> {
using ChildType = T;
};
template<typename To, typename From>
constexpr bool is_strictly_assignable_v =
std::is_assignable_v<To&, From> && (std::is_same_v<To, From> || !std::is_convertible_v<From, To>);
/// Clamp a value between lo and hi. Available in c++17.
template<class T> constexpr const T& clamp(const T& v, const T& lo, const T& hi) {
return v < lo ? lo : v > hi ? hi : v;
}
}
// MultiArray is a generic N-dimensional array.
// The template parameters (Size and Sizes) encode the dimensions of the array.
template<typename T, std::size_t Size, std::size_t... Sizes>
class MultiArray {
using ChildType = typename Detail::MultiArrayHelper<T, Size, Sizes...>::ChildType;
using ArrayType = std::array<ChildType, Size>;
ArrayType data_;
public:
using value_type = typename ArrayType::value_type;
using size_type = typename ArrayType::size_type;
using difference_type = typename ArrayType::difference_type;
using reference = typename ArrayType::reference;
using const_reference = typename ArrayType::const_reference;
using pointer = typename ArrayType::pointer;
using const_pointer = typename ArrayType::const_pointer;
using iterator = typename ArrayType::iterator;
using const_iterator = typename ArrayType::const_iterator;
using reverse_iterator = typename ArrayType::reverse_iterator;
using const_reverse_iterator = typename ArrayType::const_reverse_iterator;
constexpr auto& at(size_type index) noexcept { return data_.at(index); }
constexpr const auto& at(size_type index) const noexcept { return data_.at(index); }
constexpr auto& operator[](size_type index) noexcept { return data_[index]; }
constexpr const auto& operator[](size_type index) const noexcept { return data_[index]; }
constexpr auto& front() noexcept { return data_.front(); }
constexpr const auto& front() const noexcept { return data_.front(); }
constexpr auto& back() noexcept { return data_.back(); }
constexpr const auto& back() const noexcept { return data_.back(); }
auto* data() { return data_.data(); }
const auto* data() const { return data_.data(); }
constexpr auto begin() noexcept { return data_.begin(); }
constexpr auto end() noexcept { return data_.end(); }
constexpr auto begin() const noexcept { return data_.begin(); }
constexpr auto end() const noexcept { return data_.end(); }
constexpr auto cbegin() const noexcept { return data_.cbegin(); }
constexpr auto cend() const noexcept { return data_.cend(); }
constexpr auto rbegin() noexcept { return data_.rbegin(); }
constexpr auto rend() noexcept { return data_.rend(); }
constexpr auto rbegin() const noexcept { return data_.rbegin(); }
constexpr auto rend() const noexcept { return data_.rend(); }
constexpr auto crbegin() const noexcept { return data_.crbegin(); }
constexpr auto crend() const noexcept { return data_.crend(); }
constexpr bool empty() const noexcept { return data_.empty(); }
constexpr size_type size() const noexcept { return data_.size(); }
constexpr size_type max_size() const noexcept { return data_.max_size(); }
template<typename U>
void fill(const U& v) {
static_assert(Detail::is_strictly_assignable_v<T, U>,
"Cannot assign fill value to entry type");
for (auto& ele : data_)
{
if constexpr (sizeof...(Sizes) == 0)
ele = v;
else
ele.fill(v);
}
}
constexpr void swap(MultiArray<T, Size, Sizes...>& other) noexcept { data_.swap(other.data_); }
};
// xorshift64star Pseudo-Random Number Generator
// This class is based on original code written and dedicated
// to the public domain by Sebastiano Vigna (2014).
// It has the following characteristics:
//
// - Outputs 64-bit numbers
// - Passes Dieharder and SmallCrush test batteries
// - Does not require warm-up, no zeroland to escape
// - Internal state is a single 64-bit integer
// - Period is 2^64 - 1
// - Speed: 1.60 ns/call (Core i7 @3.40GHz)
//
// For further analysis see
// <http://vigna.di.unimi.it/ftp/papers/xorshift.pdf>
/// xorshift64star Pseudo-Random Number Generator
/// This class is based on original code written and dedicated
/// to the public domain by Sebastiano Vigna (2014).
/// It has the following characteristics:
///
/// - Outputs 64-bit numbers
/// - Passes Dieharder and SmallCrush test batteries
/// - Does not require warm-up, no zeroland to escape
/// - Internal state is a single 64-bit integer
/// - Period is 2^64 - 1
/// - Speed: 1.60 ns/call (Core i7 @3.40GHz)
///
/// For further analysis see
/// <http://vigna.di.unimi.it/ftp/papers/xorshift.pdf>
class PRNG {
uint64_t s;
uint64_t s;
uint64_t rand64() {
uint64_t rand64() {
s ^= s >> 12, s ^= s << 25, s ^= s >> 27;
return s * 2685821657736338717LL;
}
s ^= s >> 12, s ^= s << 25, s ^= s >> 27;
return s * 2685821657736338717LL;
}
public:
PRNG(uint64_t seed) :
s(seed) {
assert(seed);
}
public:
PRNG(uint64_t seed) : s(seed) { assert(seed); }
template<typename T>
T rand() {
return T(rand64());
}
template<typename T> T rand() { return T(rand64()); }
// Special generator used to fast init magic numbers.
// Output values only have 1/8th of their bits set on average.
template<typename T>
T sparse_rand() {
return T(rand64() & rand64() & rand64());
}
/// Special generator used to fast init magic numbers.
/// Output values only have 1/8th of their bits set on average.
template<typename T> T sparse_rand()
{ return T(rand64() & rand64() & rand64()); }
};
inline uint64_t mul_hi64(uint64_t a, uint64_t b) {
#if defined(__GNUC__) && defined(IS_64BIT)
__extension__ using uint128 = unsigned __int128;
return (uint128(a) * uint128(b)) >> 64;
__extension__ typedef unsigned __int128 uint128;
return ((uint128)a * (uint128)b) >> 64;
#else
uint64_t aL = uint32_t(a), aH = a >> 32;
uint64_t bL = uint32_t(b), bH = b >> 32;
uint64_t aL = (uint32_t)a, aH = a >> 32;
uint64_t bL = (uint32_t)b, bH = b >> 32;
uint64_t c1 = (aL * bL) >> 32;
uint64_t c2 = aH * bL + c1;
uint64_t c3 = aL * bH + uint32_t(c2);
uint64_t c3 = aL * bH + (uint32_t)c2;
return aH * bH + (c2 >> 32) + (c3 >> 32);
#endif
}
/// Under Windows it is not possible for a process to run on more than one
/// logical processor group. This usually means to be limited to use max 64
/// cores. To overcome this, some special platform specific API should be
/// called to set group affinity for each thread. Original code from Texel by
/// Peter Österlund.
struct CommandLine {
public:
CommandLine(int _argc, char** _argv) :
argc(_argc),
argv(_argv) {}
static std::string get_binary_directory(std::string argv0);
static std::string get_working_directory();
int argc;
char** argv;
};
namespace Utility {
template<typename T, typename Predicate>
void move_to_front(std::vector<T>& vec, Predicate pred) {
auto it = std::find_if(vec.begin(), vec.end(), pred);
if (it != vec.end())
{
std::rotate(vec.begin(), it, it + 1);
}
}
namespace WinProcGroup {
void bindThisThread(size_t idx);
}
#if defined(__GNUC__) && !defined(__clang__)
#if __GNUC__ >= 13
#define sf_assume(cond) __attribute__((assume(cond)))
#else
#define sf_assume(cond) \
do \
{ \
if (!(cond)) \
__builtin_unreachable(); \
} while (0)
#endif
#else
// do nothing for other compilers
#define sf_assume(cond)
#endif
} // namespace Stockfish
#endif // #ifndef MISC_H_INCLUDED
#endif // #ifndef MISC_H_INCLUDED

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -16,241 +16,352 @@
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include "movegen.h"
#include <cassert>
#include <initializer_list>
#include "bitboard.h"
#include "movegen.h"
#include "position.h"
namespace Stockfish {
namespace {
template<GenType Type, Direction D, bool Enemy>
ExtMove* make_promotions(ExtMove* moveList, [[maybe_unused]] Square to) {
template<GenType Type, Direction D>
ExtMove* make_promotions(ExtMove* moveList, Square to, Square ksq) {
constexpr bool all = Type == EVASIONS || Type == NON_EVASIONS;
if constexpr (Type == CAPTURES || all)
*moveList++ = Move::make<PROMOTION>(to - D, to, QUEEN);
if constexpr ((Type == CAPTURES && Enemy) || (Type == QUIETS && !Enemy) || all)
if (Type == CAPTURES || Type == EVASIONS || Type == NON_EVASIONS)
{
*moveList++ = Move::make<PROMOTION>(to - D, to, ROOK);
*moveList++ = Move::make<PROMOTION>(to - D, to, BISHOP);
*moveList++ = Move::make<PROMOTION>(to - D, to, KNIGHT);
*moveList++ = make<PROMOTION>(to - D, to, QUEEN);
if (attacks_bb<KNIGHT>(to) & ksq)
*moveList++ = make<PROMOTION>(to - D, to, KNIGHT);
}
if (Type == QUIETS || Type == EVASIONS || Type == NON_EVASIONS)
{
*moveList++ = make<PROMOTION>(to - D, to, ROOK);
*moveList++ = make<PROMOTION>(to - D, to, BISHOP);
if (!(attacks_bb<KNIGHT>(to) & ksq))
*moveList++ = make<PROMOTION>(to - D, to, KNIGHT);
}
return moveList;
}
}
template<Color Us, GenType Type>
ExtMove* generate_pawn_moves(const Position& pos, ExtMove* moveList, Bitboard target) {
template<Color Us, GenType Type>
ExtMove* generate_pawn_moves(const Position& pos, ExtMove* moveList, Bitboard target) {
constexpr Color Them = ~Us;
constexpr Bitboard TRank7BB = (Us == WHITE ? Rank7BB : Rank2BB);
constexpr Bitboard TRank3BB = (Us == WHITE ? Rank3BB : Rank6BB);
constexpr Bitboard TRank7BB = (Us == WHITE ? Rank7BB : Rank2BB);
constexpr Bitboard TRank3BB = (Us == WHITE ? Rank3BB : Rank6BB);
constexpr Direction Up = pawn_push(Us);
constexpr Direction UpRight = (Us == WHITE ? NORTH_EAST : SOUTH_WEST);
constexpr Direction UpLeft = (Us == WHITE ? NORTH_WEST : SOUTH_EAST);
const Bitboard emptySquares = ~pos.pieces();
const Bitboard enemies = Type == EVASIONS ? pos.checkers() : pos.pieces(Them);
const Square ksq = pos.square<KING>(Them);
Bitboard emptySquares;
Bitboard pawnsOn7 = pos.pieces(Us, PAWN) & TRank7BB;
Bitboard pawnsOn7 = pos.pieces(Us, PAWN) & TRank7BB;
Bitboard pawnsNotOn7 = pos.pieces(Us, PAWN) & ~TRank7BB;
Bitboard enemies = (Type == EVASIONS ? pos.pieces(Them) & target:
Type == CAPTURES ? target : pos.pieces(Them));
// Single and double pawn pushes, no promotions
if constexpr (Type != CAPTURES)
if (Type != CAPTURES)
{
Bitboard b1 = shift<Up>(pawnsNotOn7) & emptySquares;
emptySquares = (Type == QUIETS || Type == QUIET_CHECKS ? target : ~pos.pieces());
Bitboard b1 = shift<Up>(pawnsNotOn7) & emptySquares;
Bitboard b2 = shift<Up>(b1 & TRank3BB) & emptySquares;
if constexpr (Type == EVASIONS) // Consider only blocking squares
if (Type == EVASIONS) // Consider only blocking squares
{
b1 &= target;
b2 &= target;
}
if (Type == QUIET_CHECKS)
{
b1 &= pawn_attacks_bb(Them, ksq);
b2 &= pawn_attacks_bb(Them, ksq);
// Add pawn pushes which give discovered check. This is possible only
// if the pawn is not on the same file as the enemy king, because we
// don't generate captures. Note that a possible discovery check
// promotion has been already generated amongst the captures.
Bitboard dcCandidateQuiets = pos.blockers_for_king(Them) & pawnsNotOn7;
if (dcCandidateQuiets)
{
Bitboard dc1 = shift<Up>(dcCandidateQuiets) & emptySquares & ~file_bb(ksq);
Bitboard dc2 = shift<Up>(dc1 & TRank3BB) & emptySquares;
b1 |= dc1;
b2 |= dc2;
}
}
while (b1)
{
Square to = pop_lsb(b1);
*moveList++ = Move(to - Up, to);
Square to = pop_lsb(&b1);
*moveList++ = make_move(to - Up, to);
}
while (b2)
{
Square to = pop_lsb(b2);
*moveList++ = Move(to - Up - Up, to);
Square to = pop_lsb(&b2);
*moveList++ = make_move(to - Up - Up, to);
}
}
// Promotions and underpromotions
if (pawnsOn7)
{
Bitboard b1 = shift<UpRight>(pawnsOn7) & enemies;
Bitboard b2 = shift<UpLeft>(pawnsOn7) & enemies;
Bitboard b3 = shift<Up>(pawnsOn7) & emptySquares;
if (Type == CAPTURES)
emptySquares = ~pos.pieces();
if constexpr (Type == EVASIONS)
b3 &= target;
if (Type == EVASIONS)
emptySquares &= target;
Bitboard b1 = shift<UpRight>(pawnsOn7) & enemies;
Bitboard b2 = shift<UpLeft >(pawnsOn7) & enemies;
Bitboard b3 = shift<Up >(pawnsOn7) & emptySquares;
while (b1)
moveList = make_promotions<Type, UpRight, true>(moveList, pop_lsb(b1));
moveList = make_promotions<Type, UpRight>(moveList, pop_lsb(&b1), ksq);
while (b2)
moveList = make_promotions<Type, UpLeft, true>(moveList, pop_lsb(b2));
moveList = make_promotions<Type, UpLeft >(moveList, pop_lsb(&b2), ksq);
while (b3)
moveList = make_promotions<Type, Up, false>(moveList, pop_lsb(b3));
moveList = make_promotions<Type, Up >(moveList, pop_lsb(&b3), ksq);
}
// Standard and en passant captures
if constexpr (Type == CAPTURES || Type == EVASIONS || Type == NON_EVASIONS)
// Standard and en-passant captures
if (Type == CAPTURES || Type == EVASIONS || Type == NON_EVASIONS)
{
Bitboard b1 = shift<UpRight>(pawnsNotOn7) & enemies;
Bitboard b2 = shift<UpLeft>(pawnsNotOn7) & enemies;
Bitboard b2 = shift<UpLeft >(pawnsNotOn7) & enemies;
while (b1)
{
Square to = pop_lsb(b1);
*moveList++ = Move(to - UpRight, to);
Square to = pop_lsb(&b1);
*moveList++ = make_move(to - UpRight, to);
}
while (b2)
{
Square to = pop_lsb(b2);
*moveList++ = Move(to - UpLeft, to);
Square to = pop_lsb(&b2);
*moveList++ = make_move(to - UpLeft, to);
}
if (pos.ep_square() != SQ_NONE)
{
assert(rank_of(pos.ep_square()) == relative_rank(Us, RANK_6));
// An en passant capture cannot resolve a discovered check
if (Type == EVASIONS && (target & (pos.ep_square() + Up)))
// An en passant capture can be an evasion only if the checking piece
// is the double pushed pawn and so is in the target. Otherwise this
// is a discovery check and we are forced to do otherwise.
if (Type == EVASIONS && !(target & (pos.ep_square() - Up)))
return moveList;
b1 = pawnsNotOn7 & attacks_bb<PAWN>(pos.ep_square(), Them);
b1 = pawnsNotOn7 & pawn_attacks_bb(Them, pos.ep_square());
assert(b1);
while (b1)
*moveList++ = Move::make<EN_PASSANT>(pop_lsb(b1), pos.ep_square());
*moveList++ = make<ENPASSANT>(pop_lsb(&b1), pos.ep_square());
}
}
return moveList;
}
}
template<Color Us, PieceType Pt>
ExtMove* generate_moves(const Position& pos, ExtMove* moveList, Bitboard target) {
template<Color Us, PieceType Pt, bool Checks>
ExtMove* generate_moves(const Position& pos, ExtMove* moveList, Bitboard target) {
static_assert(Pt != KING && Pt != PAWN, "Unsupported piece type in generate_moves()");
Bitboard bb = pos.pieces(Us, Pt);
const Square* pl = pos.squares<Pt>(Us);
while (bb)
for (Square from = *pl; from != SQ_NONE; from = *++pl)
{
Square from = pop_lsb(bb);
Bitboard b = attacks_bb<Pt>(from, pos.pieces()) & target;
if (Checks)
{
if ( (Pt == BISHOP || Pt == ROOK || Pt == QUEEN)
&& !(attacks_bb<Pt>(from) & target & pos.check_squares(Pt)))
continue;
if (pos.blockers_for_king(~Us) & from)
continue;
}
Bitboard b = attacks_bb<Pt>(from, pos.pieces()) & target;
if (Checks)
b &= pos.check_squares(Pt);
while (b)
*moveList++ = Move(from, pop_lsb(b));
*moveList++ = make_move(from, pop_lsb(&b));
}
return moveList;
}
}
template<Color Us, GenType Type>
ExtMove* generate_all(const Position& pos, ExtMove* moveList) {
template<Color Us, GenType Type>
ExtMove* generate_all(const Position& pos, ExtMove* moveList) {
constexpr bool Checks = Type == QUIET_CHECKS; // Reduce template instantations
Bitboard target;
static_assert(Type != LEGAL, "Unsupported type in generate_all()");
const Square ksq = pos.square<KING>(Us);
Bitboard target;
// Skip generating non-king moves when in double check
if (Type != EVASIONS || !more_than_one(pos.checkers()))
switch (Type)
{
target = Type == EVASIONS ? between_bb(ksq, lsb(pos.checkers()))
: Type == NON_EVASIONS ? ~pos.pieces(Us)
: Type == CAPTURES ? pos.pieces(~Us)
: ~pos.pieces(); // QUIETS
moveList = generate_pawn_moves<Us, Type>(pos, moveList, target);
moveList = generate_moves<Us, KNIGHT>(pos, moveList, target);
moveList = generate_moves<Us, BISHOP>(pos, moveList, target);
moveList = generate_moves<Us, ROOK>(pos, moveList, target);
moveList = generate_moves<Us, QUEEN>(pos, moveList, target);
case CAPTURES:
target = pos.pieces(~Us);
break;
case QUIETS:
case QUIET_CHECKS:
target = ~pos.pieces();
break;
case EVASIONS:
{
Square checksq = lsb(pos.checkers());
target = between_bb(pos.square<KING>(Us), checksq) | checksq;
break;
}
case NON_EVASIONS:
target = ~pos.pieces(Us);
break;
default:
static_assert(true, "Unsupported type in generate_all()");
}
Bitboard b = attacks_bb<KING>(ksq) & (Type == EVASIONS ? ~pos.pieces(Us) : target);
moveList = generate_pawn_moves<Us, Type>(pos, moveList, target);
moveList = generate_moves<Us, KNIGHT, Checks>(pos, moveList, target);
moveList = generate_moves<Us, BISHOP, Checks>(pos, moveList, target);
moveList = generate_moves<Us, ROOK, Checks>(pos, moveList, target);
moveList = generate_moves<Us, QUEEN, Checks>(pos, moveList, target);
while (b)
*moveList++ = Move(ksq, pop_lsb(b));
if (Type != QUIET_CHECKS && Type != EVASIONS)
{
Square ksq = pos.square<KING>(Us);
Bitboard b = attacks_bb<KING>(ksq) & target;
while (b)
*moveList++ = make_move(ksq, pop_lsb(&b));
if ((Type == QUIETS || Type == NON_EVASIONS) && pos.can_castle(Us & ANY_CASTLING))
for (CastlingRights cr : {Us & KING_SIDE, Us & QUEEN_SIDE})
if (!pos.castling_impeded(cr) && pos.can_castle(cr))
*moveList++ = Move::make<CASTLING>(ksq, pos.castling_rook_square(cr));
if ((Type != CAPTURES) && pos.can_castle(Us & ANY_CASTLING))
for(CastlingRights cr : { Us & KING_SIDE, Us & QUEEN_SIDE } )
if (!pos.castling_impeded(cr) && pos.can_castle(cr))
*moveList++ = make<CASTLING>(ksq, pos.castling_rook_square(cr));
}
return moveList;
}
}
} // namespace
} // namespace
// <CAPTURES> Generates all pseudo-legal captures plus queen promotions
// <QUIETS> Generates all pseudo-legal non-captures and underpromotions
// <EVASIONS> Generates all pseudo-legal check evasions
// <NON_EVASIONS> Generates all pseudo-legal captures and non-captures
//
// Returns a pointer to the end of the move list.
/// <CAPTURES> Generates all pseudo-legal captures plus queen and checking knight promotions
/// <QUIETS> Generates all pseudo-legal non-captures and underpromotions(except checking knight)
/// <NON_EVASIONS> Generates all pseudo-legal captures and non-captures
///
/// Returns a pointer to the end of the move list.
template<GenType Type>
ExtMove* generate(const Position& pos, ExtMove* moveList) {
static_assert(Type != LEGAL, "Unsupported type in generate()");
assert((Type == EVASIONS) == bool(pos.checkers()));
static_assert(Type == CAPTURES || Type == QUIETS || Type == NON_EVASIONS, "Unsupported type in generate()");
assert(!pos.checkers());
Color us = pos.side_to_move();
Color us = pos.side_to_move();
return us == WHITE ? generate_all<WHITE, Type>(pos, moveList)
: generate_all<BLACK, Type>(pos, moveList);
return us == WHITE ? generate_all<WHITE, Type>(pos, moveList)
: generate_all<BLACK, Type>(pos, moveList);
}
// Explicit template instantiations
template ExtMove* generate<CAPTURES>(const Position&, ExtMove*);
template ExtMove* generate<QUIETS>(const Position&, ExtMove*);
template ExtMove* generate<EVASIONS>(const Position&, ExtMove*);
template ExtMove* generate<NON_EVASIONS>(const Position&, ExtMove*);
// generate<LEGAL> generates all the legal moves in the given position
/// generate<QUIET_CHECKS> generates all pseudo-legal non-captures.
/// Returns a pointer to the end of the move list.
template<>
ExtMove* generate<QUIET_CHECKS>(const Position& pos, ExtMove* moveList) {
assert(!pos.checkers());
Color us = pos.side_to_move();
Bitboard dc = pos.blockers_for_king(~us) & pos.pieces(us) & ~pos.pieces(PAWN);
while (dc)
{
Square from = pop_lsb(&dc);
PieceType pt = type_of(pos.piece_on(from));
Bitboard b = attacks_bb(pt, from, pos.pieces()) & ~pos.pieces();
if (pt == KING)
b &= ~attacks_bb<QUEEN>(pos.square<KING>(~us));
while (b)
*moveList++ = make_move(from, pop_lsb(&b));
}
return us == WHITE ? generate_all<WHITE, QUIET_CHECKS>(pos, moveList)
: generate_all<BLACK, QUIET_CHECKS>(pos, moveList);
}
/// generate<EVASIONS> generates all pseudo-legal check evasions when the side
/// to move is in check. Returns a pointer to the end of the move list.
template<>
ExtMove* generate<EVASIONS>(const Position& pos, ExtMove* moveList) {
assert(pos.checkers());
Color us = pos.side_to_move();
Square ksq = pos.square<KING>(us);
Bitboard sliderAttacks = 0;
Bitboard sliders = pos.checkers() & ~pos.pieces(KNIGHT, PAWN);
// Find all the squares attacked by slider checkers. We will remove them from
// the king evasions in order to skip known illegal moves, which avoids any
// useless legality checks later on.
while (sliders)
sliderAttacks |= line_bb(ksq, pop_lsb(&sliders)) & ~pos.checkers();
// Generate evasions for king, capture and non capture moves
Bitboard b = attacks_bb<KING>(ksq) & ~pos.pieces(us) & ~sliderAttacks;
while (b)
*moveList++ = make_move(ksq, pop_lsb(&b));
if (more_than_one(pos.checkers()))
return moveList; // Double check, only a king move can save the day
// Generate blocking evasions or captures of the checking piece
return us == WHITE ? generate_all<WHITE, EVASIONS>(pos, moveList)
: generate_all<BLACK, EVASIONS>(pos, moveList);
}
/// generate<LEGAL> generates all the legal moves in the given position
template<>
ExtMove* generate<LEGAL>(const Position& pos, ExtMove* moveList) {
Color us = pos.side_to_move();
Bitboard pinned = pos.blockers_for_king(us) & pos.pieces(us);
Square ksq = pos.square<KING>(us);
ExtMove* cur = moveList;
Color us = pos.side_to_move();
Bitboard pinned = pos.blockers_for_king(us) & pos.pieces(us);
Square ksq = pos.square<KING>(us);
ExtMove* cur = moveList;
moveList =
pos.checkers() ? generate<EVASIONS>(pos, moveList) : generate<NON_EVASIONS>(pos, moveList);
while (cur != moveList)
if (((pinned & cur->from_sq()) || cur->from_sq() == ksq || cur->type_of() == EN_PASSANT)
&& !pos.legal(*cur))
*cur = *(--moveList);
else
++cur;
moveList = pos.checkers() ? generate<EVASIONS >(pos, moveList)
: generate<NON_EVASIONS>(pos, moveList);
while (cur != moveList)
if ( (pinned || from_sq(*cur) == ksq || type_of(*cur) == ENPASSANT)
&& !pos.legal(*cur))
*cur = (--moveList)->move;
else
++cur;
return moveList;
return moveList;
}
} // namespace Stockfish

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -19,55 +19,55 @@
#ifndef MOVEGEN_H_INCLUDED
#define MOVEGEN_H_INCLUDED
#include <algorithm> // IWYU pragma: keep
#include <cstddef>
#include <algorithm>
#include "types.h"
namespace Stockfish {
class Position;
enum GenType {
CAPTURES,
QUIETS,
EVASIONS,
NON_EVASIONS,
LEGAL
CAPTURES,
QUIETS,
QUIET_CHECKS,
EVASIONS,
NON_EVASIONS,
LEGAL
};
struct ExtMove: public Move {
int value;
struct ExtMove {
Move move;
int value;
void operator=(Move m) { data = m.raw(); }
operator Move() const { return move; }
void operator=(Move m) { move = m; }
// Inhibit unwanted implicit conversions to Move
// with an ambiguity that yields to a compile error.
operator float() const = delete;
// Inhibit unwanted implicit conversions to Move
// with an ambiguity that yields to a compile error.
operator float() const = delete;
};
inline bool operator<(const ExtMove& f, const ExtMove& s) { return f.value < s.value; }
inline bool operator<(const ExtMove& f, const ExtMove& s) {
return f.value < s.value;
}
template<GenType>
ExtMove* generate(const Position& pos, ExtMove* moveList);
// The MoveList struct wraps the generate() function and returns a convenient
// list of moves. Using MoveList is sometimes preferable to directly calling
// the lower level generate() function.
/// The MoveList struct is a simple wrapper around generate(). It sometimes comes
/// in handy to use this class instead of the low level generate() function.
template<GenType T>
struct MoveList {
explicit MoveList(const Position& pos) :
last(generate<T>(pos, moveList)) {}
const ExtMove* begin() const { return moveList; }
const ExtMove* end() const { return last; }
size_t size() const { return last - moveList; }
bool contains(Move move) const { return std::find(begin(), end(), move) != end(); }
explicit MoveList(const Position& pos) : last(generate<T>(pos, moveList)) {}
const ExtMove* begin() const { return moveList; }
const ExtMove* end() const { return last; }
size_t size() const { return last - moveList; }
bool contains(Move move) const {
return std::find(begin(), end(), move) != end();
}
private:
ExtMove moveList[MAX_MOVES], *last;
private:
ExtMove moveList[MAX_MOVES], *last;
};
} // namespace Stockfish
#endif // #ifndef MOVEGEN_H_INCLUDED
#endif // #ifndef MOVEGEN_H_INCLUDED

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -16,308 +16,249 @@
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include "movepick.h"
#include <cassert>
#include <limits>
#include <utility>
#include "bitboard.h"
#include "misc.h"
#include "position.h"
namespace Stockfish {
#include "movepick.h"
namespace {
enum Stages {
// generate main search moves
MAIN_TT,
CAPTURE_INIT,
GOOD_CAPTURE,
QUIET_INIT,
GOOD_QUIET,
BAD_CAPTURE,
BAD_QUIET,
enum Stages {
MAIN_TT, CAPTURE_INIT, GOOD_CAPTURE, REFUTATION, QUIET_INIT, QUIET, BAD_CAPTURE,
EVASION_TT, EVASION_INIT, EVASION,
PROBCUT_TT, PROBCUT_INIT, PROBCUT,
QSEARCH_TT, QCAPTURE_INIT, QCAPTURE, QCHECK_INIT, QCHECK
};
// generate evasion moves
EVASION_TT,
EVASION_INIT,
EVASION,
// generate probcut moves
PROBCUT_TT,
PROBCUT_INIT,
PROBCUT,
// generate qsearch moves
QSEARCH_TT,
QCAPTURE_INIT,
QCAPTURE
};
// Sort moves in descending order up to and including a given limit.
// The order of moves smaller than the limit is left unspecified.
void partial_insertion_sort(ExtMove* begin, ExtMove* end, int limit) {
// partial_insertion_sort() sorts moves in descending order up to and including
// a given limit. The order of moves smaller than the limit is left unspecified.
void partial_insertion_sort(ExtMove* begin, ExtMove* end, int limit) {
for (ExtMove *sortedEnd = begin, *p = begin + 1; p < end; ++p)
if (p->value >= limit)
{
ExtMove tmp = *p, *q;
*p = *++sortedEnd;
*p = *++sortedEnd;
for (q = sortedEnd; q != begin && *(q - 1) < tmp; --q)
*q = *(q - 1);
*q = tmp;
}
}
} // namespace
/// Constructors of the MovePicker class. As arguments we pass information
/// to help it to return the (presumably) good moves first, to decide which
/// moves to return (in the quiescence search, for instance, we only want to
/// search captures, promotions, and some checks) and how important good move
/// ordering is at the current node.
/// MovePicker constructor for the main search
MovePicker::MovePicker(const Position& p, Move ttm, Depth d, const ButterflyHistory* mh, const LowPlyHistory* lp,
const CapturePieceToHistory* cph, const PieceToHistory** ch, Move cm, const Move* killers, int pl)
: pos(p), mainHistory(mh), lowPlyHistory(lp), captureHistory(cph), continuationHistory(ch),
ttMove(ttm), refutations{{killers[0], 0}, {killers[1], 0}, {cm, 0}}, depth(d), ply(pl) {
assert(d > 0);
stage = (pos.checkers() ? EVASION_TT : MAIN_TT) +
!(ttm && pos.pseudo_legal(ttm));
}
} // namespace
/// MovePicker constructor for quiescence search
MovePicker::MovePicker(const Position& p, Move ttm, Depth d, const ButterflyHistory* mh,
const CapturePieceToHistory* cph, const PieceToHistory** ch, Square rs)
: pos(p), mainHistory(mh), captureHistory(cph), continuationHistory(ch), ttMove(ttm), recaptureSquare(rs), depth(d) {
assert(d <= 0);
// Constructors of the MovePicker class. As arguments, we pass information
// to decide which class of moves to emit, to help sorting the (presumably)
// good moves first, and how important move ordering is at the current node.
// MovePicker constructor for the main search and for the quiescence search
MovePicker::MovePicker(const Position& p,
Move ttm,
Depth d,
const ButterflyHistory* mh,
const LowPlyHistory* lph,
const CapturePieceToHistory* cph,
const PieceToHistory** ch,
const PawnHistory* ph,
int pl) :
pos(p),
mainHistory(mh),
lowPlyHistory(lph),
captureHistory(cph),
continuationHistory(ch),
pawnHistory(ph),
ttMove(ttm),
depth(d),
ply(pl) {
if (pos.checkers())
stage = EVASION_TT + !(ttm && pos.pseudo_legal(ttm));
else
stage = (depth > 0 ? MAIN_TT : QSEARCH_TT) + !(ttm && pos.pseudo_legal(ttm));
stage = (pos.checkers() ? EVASION_TT : QSEARCH_TT) +
!(ttm && (depth > DEPTH_QS_RECAPTURES || to_sq(ttm) == recaptureSquare)
&& pos.pseudo_legal(ttm));
}
// MovePicker constructor for ProbCut: we generate captures with Static Exchange
// Evaluation (SEE) greater than or equal to the given threshold.
MovePicker::MovePicker(const Position& p, Move ttm, int th, const CapturePieceToHistory* cph) :
pos(p),
captureHistory(cph),
ttMove(ttm),
threshold(th) {
assert(!pos.checkers());
/// MovePicker constructor for ProbCut: we generate captures with SEE greater
/// than or equal to the given threshold.
MovePicker::MovePicker(const Position& p, Move ttm, Value th, const CapturePieceToHistory* cph)
: pos(p), captureHistory(cph), ttMove(ttm), threshold(th) {
stage = PROBCUT_TT
+ !(ttm && pos.capture_stage(ttm) && pos.pseudo_legal(ttm) && pos.see_ge(ttm, threshold));
assert(!pos.checkers());
stage = PROBCUT_TT + !(ttm && pos.capture(ttm)
&& pos.pseudo_legal(ttm)
&& pos.see_ge(ttm, threshold));
}
// Assigns a numerical value to each move in a list, used for sorting.
// Captures are ordered by Most Valuable Victim (MVV), preferring captures
// with a good history. Quiets moves are ordered using the history tables.
/// MovePicker::score() assigns a numerical value to each move in a list, used
/// for sorting. Captures are ordered by Most Valuable Victim (MVV), preferring
/// captures with a good history. Quiets moves are ordered using the histories.
template<GenType Type>
void MovePicker::score() {
static_assert(Type == CAPTURES || Type == QUIETS || Type == EVASIONS, "Wrong type");
static_assert(Type == CAPTURES || Type == QUIETS || Type == EVASIONS, "Wrong type");
Color us = pos.side_to_move();
for (auto& m : *this)
if (Type == CAPTURES)
m.value = int(PieceValue[MG][pos.piece_on(to_sq(m))]) * 6
+ (*captureHistory)[pos.moved_piece(m)][to_sq(m)][type_of(pos.piece_on(to_sq(m)))];
[[maybe_unused]] Bitboard threatByLesser[QUEEN + 1];
if constexpr (Type == QUIETS)
{
threatByLesser[KNIGHT] = threatByLesser[BISHOP] = pos.attacks_by<PAWN>(~us);
threatByLesser[ROOK] =
pos.attacks_by<KNIGHT>(~us) | pos.attacks_by<BISHOP>(~us) | threatByLesser[KNIGHT];
threatByLesser[QUEEN] = pos.attacks_by<ROOK>(~us) | threatByLesser[ROOK];
}
else if (Type == QUIETS)
m.value = (*mainHistory)[pos.side_to_move()][from_to(m)]
+ 2 * (*continuationHistory[0])[pos.moved_piece(m)][to_sq(m)]
+ 2 * (*continuationHistory[1])[pos.moved_piece(m)][to_sq(m)]
+ 2 * (*continuationHistory[3])[pos.moved_piece(m)][to_sq(m)]
+ (*continuationHistory[5])[pos.moved_piece(m)][to_sq(m)]
+ (ply < MAX_LPH ? std::min(4, depth / 3) * (*lowPlyHistory)[ply][from_to(m)] : 0);
for (auto& m : *this)
{
const Square from = m.from_sq();
const Square to = m.to_sq();
const Piece pc = pos.moved_piece(m);
const PieceType pt = type_of(pc);
const Piece capturedPiece = pos.piece_on(to);
if constexpr (Type == CAPTURES)
m.value = (*captureHistory)[pc][to][type_of(capturedPiece)]
+ 7 * int(PieceValue[capturedPiece]) + 1024 * bool(pos.check_squares(pt) & to);
else if constexpr (Type == QUIETS)
{
// histories
m.value = 2 * (*mainHistory)[us][m.from_to()];
m.value += 2 * (*pawnHistory)[pawn_structure_index(pos)][pc][to];
m.value += (*continuationHistory[0])[pc][to];
m.value += (*continuationHistory[1])[pc][to];
m.value += (*continuationHistory[2])[pc][to];
m.value += (*continuationHistory[3])[pc][to];
m.value += (*continuationHistory[5])[pc][to];
// bonus for checks
m.value += (bool(pos.check_squares(pt) & to) && pos.see_ge(m, -75)) * 16384;
// penalty for moving to a square threatened by a lesser piece
// or bonus for escaping an attack by a lesser piece.
if (KNIGHT <= pt && pt <= QUEEN)
{
static constexpr int bonus[QUEEN + 1] = {0, 0, 144, 144, 256, 517};
int v = threatByLesser[pt] & to ? -95 : 100 * bool(threatByLesser[pt] & from);
m.value += bonus[pt] * v;
}
if (ply < LOW_PLY_HISTORY_SIZE)
m.value += 8 * (*lowPlyHistory)[ply][m.from_to()] / (1 + ply);
}
else // Type == EVASIONS
{
if (pos.capture_stage(m))
m.value = PieceValue[capturedPiece] + (1 << 28);
else
{
m.value = (*mainHistory)[us][m.from_to()] + (*continuationHistory[0])[pc][to];
if (ply < LOW_PLY_HISTORY_SIZE)
m.value += 2 * (*lowPlyHistory)[ply][m.from_to()] / (1 + ply);
}
}
}
else // Type == EVASIONS
{
if (pos.capture(m))
m.value = PieceValue[MG][pos.piece_on(to_sq(m))]
- Value(type_of(pos.moved_piece(m)));
else
m.value = (*mainHistory)[pos.side_to_move()][from_to(m)]
+ (*continuationHistory[0])[pos.moved_piece(m)][to_sq(m)]
- (1 << 28);
}
}
// Returns the next move satisfying a predicate function.
// This never returns the TT move, as it was emitted before.
template<typename Pred>
/// MovePicker::select() returns the next move satisfying a predicate function.
/// It never returns the TT move.
template<MovePicker::PickType T, typename Pred>
Move MovePicker::select(Pred filter) {
for (; cur < endCur; ++cur)
if (*cur != ttMove && filter())
return *cur++;
while (cur < endMoves)
{
if (T == Best)
std::swap(*cur, *std::max_element(cur, endMoves));
return Move::none();
if (*cur != ttMove && filter())
return *cur++;
cur++;
}
return MOVE_NONE;
}
// This is the most important method of the MovePicker class. We emit one
// new pseudo-legal move on every call until there are no more moves left,
// picking the move with the highest score from a list of generated moves.
Move MovePicker::next_move() {
/// MovePicker::next_move() is the most important method of the MovePicker class. It
/// returns a new pseudo legal move every time it is called until there are no more
/// moves left, picking the move with the highest score from a list of generated moves.
Move MovePicker::next_move(bool skipQuiets) {
constexpr int goodQuietThreshold = -14000;
top:
switch (stage)
{
switch (stage) {
case MAIN_TT :
case EVASION_TT :
case QSEARCH_TT :
case PROBCUT_TT :
++stage;
return ttMove;
case MAIN_TT:
case EVASION_TT:
case QSEARCH_TT:
case PROBCUT_TT:
++stage;
return ttMove;
case CAPTURE_INIT :
case PROBCUT_INIT :
case QCAPTURE_INIT :
cur = endBadCaptures = moves;
endCur = endCaptures = generate<CAPTURES>(pos, cur);
case CAPTURE_INIT:
case PROBCUT_INIT:
case QCAPTURE_INIT:
cur = endBadCaptures = moves;
endMoves = generate<CAPTURES>(pos, cur);
score<CAPTURES>();
partial_insertion_sort(cur, endCur, std::numeric_limits<int>::min());
++stage;
goto top;
score<CAPTURES>();
++stage;
goto top;
case GOOD_CAPTURE :
if (select([&]() {
if (pos.see_ge(*cur, -cur->value / 18))
return true;
std::swap(*endBadCaptures++, *cur);
return false;
}))
return *(cur - 1);
case GOOD_CAPTURE:
if (select<Best>([&](){
return pos.see_ge(*cur, Value(-69 * cur->value / 1024)) ?
// Move losing capture to endBadCaptures to be tried later
true : (*endBadCaptures++ = *cur, false); }))
return *(cur - 1);
++stage;
[[fallthrough]];
// Prepare the pointers to loop over the refutations array
cur = std::begin(refutations);
endMoves = std::end(refutations);
case QUIET_INIT :
if (!skipQuiets)
{
endCur = endGenerated = generate<QUIETS>(pos, cur);
// If the countermove is the same as a killer, skip it
if ( refutations[0].move == refutations[2].move
|| refutations[1].move == refutations[2].move)
--endMoves;
score<QUIETS>();
partial_insertion_sort(cur, endCur, -3560 * depth);
}
++stage;
/* fallthrough */
++stage;
[[fallthrough]];
case REFUTATION:
if (select<Next>([&](){ return *cur != MOVE_NONE
&& !pos.capture(*cur)
&& pos.pseudo_legal(*cur); }))
return *(cur - 1);
++stage;
/* fallthrough */
case GOOD_QUIET :
if (!skipQuiets && select([&]() { return cur->value > goodQuietThreshold; }))
return *(cur - 1);
case QUIET_INIT:
if (!skipQuiets)
{
cur = endBadCaptures;
endMoves = generate<QUIETS>(pos, cur);
// Prepare the pointers to loop over the bad captures
cur = moves;
endCur = endBadCaptures;
score<QUIETS>();
partial_insertion_sort(cur, endMoves, -3000 * depth);
}
++stage;
[[fallthrough]];
++stage;
/* fallthrough */
case BAD_CAPTURE :
if (select([]() { return true; }))
return *(cur - 1);
case QUIET:
if ( !skipQuiets
&& select<Next>([&](){return *cur != refutations[0].move
&& *cur != refutations[1].move
&& *cur != refutations[2].move;}))
return *(cur - 1);
// Prepare the pointers to loop over quiets again
cur = endCaptures;
endCur = endGenerated;
// Prepare the pointers to loop over the bad captures
cur = moves;
endMoves = endBadCaptures;
++stage;
[[fallthrough]];
++stage;
/* fallthrough */
case BAD_QUIET :
if (!skipQuiets)
return select([&]() { return cur->value <= goodQuietThreshold; });
case BAD_CAPTURE:
return select<Next>([](){ return true; });
return Move::none();
case EVASION_INIT:
cur = moves;
endMoves = generate<EVASIONS>(pos, cur);
case EVASION_INIT :
cur = moves;
endCur = endGenerated = generate<EVASIONS>(pos, cur);
score<EVASIONS>();
++stage;
/* fallthrough */
score<EVASIONS>();
partial_insertion_sort(cur, endCur, std::numeric_limits<int>::min());
++stage;
[[fallthrough]];
case EVASION:
return select<Best>([](){ return true; });
case EVASION :
case QCAPTURE :
return select([]() { return true; });
case PROBCUT:
return select<Best>([&](){ return pos.see_ge(*cur, threshold); });
case PROBCUT :
return select([&]() { return pos.see_ge(*cur, threshold); });
}
case QCAPTURE:
if (select<Best>([&](){ return depth > DEPTH_QS_RECAPTURES
|| to_sq(*cur) == recaptureSquare; }))
return *(cur - 1);
assert(false);
return Move::none(); // Silence warning
// If we did not find any move and we do not try checks, we have finished
if (depth != DEPTH_QS_CHECKS)
return MOVE_NONE;
++stage;
/* fallthrough */
case QCHECK_INIT:
cur = moves;
endMoves = generate<QUIET_CHECKS>(pos, cur);
++stage;
/* fallthrough */
case QCHECK:
return select<Next>([](){ return true; });
}
assert(false);
return MOVE_NONE; // Silence warning
}
void MovePicker::skip_quiet_moves() { skipQuiets = true; }
// this function must be called after all quiet moves and captures have been generated
bool MovePicker::can_move_king_or_pawn() const {
// SEE negative captures shouldn't be returned in GOOD_CAPTURE stage
assert(stage > GOOD_CAPTURE && stage != EVASION_INIT);
for (const ExtMove* m = moves; m < endGenerated; ++m)
{
PieceType movedPieceType = type_of(pos.moved_piece(*m));
if ((movedPieceType == PAWN || movedPieceType == KING) && pos.legal(*m))
return true;
}
return false;
}
} // namespace Stockfish

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -19,63 +19,141 @@
#ifndef MOVEPICK_H_INCLUDED
#define MOVEPICK_H_INCLUDED
#include "history.h"
#include <array>
#include <limits>
#include <type_traits>
#include "movegen.h"
#include "position.h"
#include "types.h"
namespace Stockfish {
/// StatsEntry stores the stat table value. It is usually a number but could
/// be a move or even a nested history. We use a class instead of naked value
/// to directly call history update operator<<() on the entry so to use stats
/// tables at caller sites as simple multi-dim arrays.
template<typename T, int D>
class StatsEntry {
class Position;
T entry;
// The MovePicker class is used to pick one pseudo-legal move at a time from the
// current position. The most important method is next_move(), which emits one
// new pseudo-legal move on every call, until there are no moves left, when
// Move::none() is returned. In order to improve the efficiency of the alpha-beta
// algorithm, MovePicker attempts to return the moves which are most likely to get
// a cut-off first.
class MovePicker {
public:
void operator=(const T& v) { entry = v; }
T* operator&() { return &entry; }
T* operator->() { return &entry; }
operator const T&() const { return entry; }
public:
MovePicker(const MovePicker&) = delete;
MovePicker& operator=(const MovePicker&) = delete;
MovePicker(const Position&,
Move,
Depth,
const ButterflyHistory*,
const LowPlyHistory*,
const CapturePieceToHistory*,
const PieceToHistory**,
const PawnHistory*,
int);
MovePicker(const Position&, Move, int, const CapturePieceToHistory*);
Move next_move();
void skip_quiet_moves();
bool can_move_king_or_pawn() const;
void operator<<(int bonus) {
assert(abs(bonus) <= D); // Ensure range is [-D, D]
static_assert(D <= std::numeric_limits<T>::max(), "D overflows T");
private:
template<typename Pred>
Move select(Pred);
template<GenType>
void score();
ExtMove* begin() { return cur; }
ExtMove* end() { return endCur; }
entry += bonus - entry * abs(bonus) / D;
const Position& pos;
const ButterflyHistory* mainHistory;
const LowPlyHistory* lowPlyHistory;
const CapturePieceToHistory* captureHistory;
const PieceToHistory** continuationHistory;
const PawnHistory* pawnHistory;
Move ttMove;
ExtMove * cur, *endCur, *endBadCaptures, *endCaptures, *endGenerated;
int stage;
int threshold;
Depth depth;
int ply;
bool skipQuiets = false;
ExtMove moves[MAX_MOVES];
assert(abs(entry) <= D);
}
};
} // namespace Stockfish
/// Stats is a generic N-dimensional array used to store various statistics.
/// The first template parameter T is the base type of the array, the second
/// template parameter D limits the range of updates in [-D, D] when we update
/// values with the << operator, while the last parameters (Size and Sizes)
/// encode the dimensions of the array.
template <typename T, int D, int Size, int... Sizes>
struct Stats : public std::array<Stats<T, D, Sizes...>, Size>
{
typedef Stats<T, D, Size, Sizes...> stats;
#endif // #ifndef MOVEPICK_H_INCLUDED
void fill(const T& v) {
// For standard-layout 'this' points to first struct member
assert(std::is_standard_layout<stats>::value);
typedef StatsEntry<T, D> entry;
entry* p = reinterpret_cast<entry*>(this);
std::fill(p, p + sizeof(*this) / sizeof(entry), v);
}
};
template <typename T, int D, int Size>
struct Stats<T, D, Size> : public std::array<StatsEntry<T, D>, Size> {};
/// In stats table, D=0 means that the template parameter is not used
enum StatsParams { NOT_USED = 0 };
enum StatsType { NoCaptures, Captures };
/// ButterflyHistory records how often quiet moves have been successful or
/// unsuccessful during the current search, and is used for reduction and move
/// ordering decisions. It uses 2 tables (one for each color) indexed by
/// the move's from and to squares, see www.chessprogramming.org/Butterfly_Boards
typedef Stats<int16_t, 10692, COLOR_NB, int(SQUARE_NB) * int(SQUARE_NB)> ButterflyHistory;
/// At higher depths LowPlyHistory records successful quiet moves near the root and quiet
/// moves which are/were in the PV (ttPv)
/// It is cleared with each new search and filled during iterative deepening
constexpr int MAX_LPH = 4;
typedef Stats<int16_t, 10692, MAX_LPH, int(SQUARE_NB) * int(SQUARE_NB)> LowPlyHistory;
/// CounterMoveHistory stores counter moves indexed by [piece][to] of the previous
/// move, see www.chessprogramming.org/Countermove_Heuristic
typedef Stats<Move, NOT_USED, PIECE_NB, SQUARE_NB> CounterMoveHistory;
/// CapturePieceToHistory is addressed by a move's [piece][to][captured piece type]
typedef Stats<int16_t, 10692, PIECE_NB, SQUARE_NB, PIECE_TYPE_NB> CapturePieceToHistory;
/// PieceToHistory is like ButterflyHistory but is addressed by a move's [piece][to]
typedef Stats<int16_t, 29952, PIECE_NB, SQUARE_NB> PieceToHistory;
/// ContinuationHistory is the combined history of a given pair of moves, usually
/// the current one given a previous one. The nested history table is based on
/// PieceToHistory instead of ButterflyBoards.
typedef Stats<PieceToHistory, NOT_USED, PIECE_NB, SQUARE_NB> ContinuationHistory;
/// MovePicker class is used to pick one pseudo legal move at a time from the
/// current position. The most important method is next_move(), which returns a
/// new pseudo legal move each time it is called, until there are no moves left,
/// when MOVE_NONE is returned. In order to improve the efficiency of the alpha
/// beta algorithm, MovePicker attempts to return the moves which are most likely
/// to get a cut-off first.
class MovePicker {
enum PickType { Next, Best };
public:
MovePicker(const MovePicker&) = delete;
MovePicker& operator=(const MovePicker&) = delete;
MovePicker(const Position&, Move, Value, const CapturePieceToHistory*);
MovePicker(const Position&, Move, Depth, const ButterflyHistory*,
const CapturePieceToHistory*,
const PieceToHistory**,
Square);
MovePicker(const Position&, Move, Depth, const ButterflyHistory*,
const LowPlyHistory*,
const CapturePieceToHistory*,
const PieceToHistory**,
Move,
const Move*,
int);
Move next_move(bool skipQuiets = false);
private:
template<PickType T, typename Pred> Move select(Pred);
template<GenType> void score();
ExtMove* begin() { return cur; }
ExtMove* end() { return endMoves; }
const Position& pos;
const ButterflyHistory* mainHistory;
const LowPlyHistory* lowPlyHistory;
const CapturePieceToHistory* captureHistory;
const PieceToHistory** continuationHistory;
Move ttMove;
ExtMove refutations[3], *cur, *endMoves, *endBadCaptures;
int stage;
Square recaptureSquare;
Value threshold;
Depth depth;
int ply;
ExtMove moves[MAX_MOVES];
};
#endif // #ifndef MOVEPICK_H_INCLUDED

View File

@@ -0,0 +1,54 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
// Definition of input features and network structure used in NNUE evaluation function
#ifndef NNUE_HALFKP_256X2_32_32_H_INCLUDED
#define NNUE_HALFKP_256X2_32_32_H_INCLUDED
#include "../features/feature_set.h"
#include "../features/half_kp.h"
#include "../layers/input_slice.h"
#include "../layers/affine_transform.h"
#include "../layers/clipped_relu.h"
namespace Eval::NNUE {
// Input features used in evaluation function
using RawFeatures = Features::FeatureSet<
Features::HalfKP<Features::Side::kFriend>>;
// Number of input feature dimensions after conversion
constexpr IndexType kTransformedFeatureDimensions = 256;
namespace Layers {
// Define network structure
using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
using OutputLayer = AffineTransform<HiddenLayer2, 1>;
} // namespace Layers
using Network = Layers::OutputLayer;
} // namespace Eval::NNUE
#endif // #ifndef NNUE_HALFKP_256X2_32_32_H_INCLUDED

178
src/nnue/evaluate_nnue.cpp Normal file
View File

@@ -0,0 +1,178 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
// Code for calculating NNUE evaluation function
#include <fstream>
#include <iostream>
#include <set>
#include "../evaluate.h"
#include "../position.h"
#include "../misc.h"
#include "../uci.h"
#include "evaluate_nnue.h"
ExtPieceSquare kpp_board_index[PIECE_NB] = {
// convention: W - us, B - them
// viewed from other side, W and B are reversed
{ PS_NONE, PS_NONE },
{ PS_W_PAWN, PS_B_PAWN },
{ PS_W_KNIGHT, PS_B_KNIGHT },
{ PS_W_BISHOP, PS_B_BISHOP },
{ PS_W_ROOK, PS_B_ROOK },
{ PS_W_QUEEN, PS_B_QUEEN },
{ PS_W_KING, PS_B_KING },
{ PS_NONE, PS_NONE },
{ PS_NONE, PS_NONE },
{ PS_B_PAWN, PS_W_PAWN },
{ PS_B_KNIGHT, PS_W_KNIGHT },
{ PS_B_BISHOP, PS_W_BISHOP },
{ PS_B_ROOK, PS_W_ROOK },
{ PS_B_QUEEN, PS_W_QUEEN },
{ PS_B_KING, PS_W_KING },
{ PS_NONE, PS_NONE }
};
namespace Eval::NNUE {
// Input feature converter
AlignedPtr<FeatureTransformer> feature_transformer;
// Evaluation function
AlignedPtr<Network> network;
// Evaluation function file name
std::string fileName;
namespace Detail {
// Initialize the evaluation function parameters
template <typename T>
void Initialize(AlignedPtr<T>& pointer) {
pointer.reset(reinterpret_cast<T*>(std_aligned_alloc(alignof(T), sizeof(T))));
std::memset(pointer.get(), 0, sizeof(T));
}
// Read evaluation function parameters
template <typename T>
bool ReadParameters(std::istream& stream, const AlignedPtr<T>& pointer) {
std::uint32_t header;
stream.read(reinterpret_cast<char*>(&header), sizeof(header));
if (!stream || header != T::GetHashValue()) return false;
return pointer->ReadParameters(stream);
}
} // namespace Detail
// Initialize the evaluation function parameters
void Initialize() {
Detail::Initialize(feature_transformer);
Detail::Initialize(network);
}
// Read network header
bool ReadHeader(std::istream& stream,
std::uint32_t* hash_value, std::string* architecture) {
std::uint32_t version, size;
stream.read(reinterpret_cast<char*>(&version), sizeof(version));
stream.read(reinterpret_cast<char*>(hash_value), sizeof(*hash_value));
stream.read(reinterpret_cast<char*>(&size), sizeof(size));
if (!stream || version != kVersion) return false;
architecture->resize(size);
stream.read(&(*architecture)[0], size);
return !stream.fail();
}
// Read network parameters
bool ReadParameters(std::istream& stream) {
std::uint32_t hash_value;
std::string architecture;
if (!ReadHeader(stream, &hash_value, &architecture)) return false;
if (hash_value != kHashValue) return false;
if (!Detail::ReadParameters(stream, feature_transformer)) return false;
if (!Detail::ReadParameters(stream, network)) return false;
return stream && stream.peek() == std::ios::traits_type::eof();
}
// Proceed with the difference calculation if possible
static void UpdateAccumulatorIfPossible(const Position& pos) {
feature_transformer->UpdateAccumulatorIfPossible(pos);
}
// Calculate the evaluation value
static Value ComputeScore(const Position& pos, bool refresh) {
auto& accumulator = pos.state()->accumulator;
if (!refresh && accumulator.computed_score) {
return accumulator.score;
}
alignas(kCacheLineSize) TransformedFeatureType
transformed_features[FeatureTransformer::kBufferSize];
feature_transformer->Transform(pos, transformed_features, refresh);
alignas(kCacheLineSize) char buffer[Network::kBufferSize];
const auto output = network->Propagate(transformed_features, buffer);
auto score = static_cast<Value>(output[0] / FV_SCALE);
accumulator.score = score;
accumulator.computed_score = true;
return accumulator.score;
}
// Load the evaluation function file
bool load_eval_file(const std::string& evalFile) {
Initialize();
fileName = evalFile;
std::ifstream stream(evalFile, std::ios::binary);
const bool result = ReadParameters(stream);
return result;
}
// Evaluation function. Perform differential calculation.
Value evaluate(const Position& pos) {
Value v = ComputeScore(pos, false);
v = Utility::clamp(v, VALUE_TB_LOSS_IN_MAX_PLY + 1, VALUE_TB_WIN_IN_MAX_PLY - 1);
return v;
}
// Evaluation function. Perform full calculation.
Value compute_eval(const Position& pos) {
return ComputeScore(pos, true);
}
// Proceed with the difference calculation if possible
void update_eval(const Position& pos) {
UpdateAccumulatorIfPossible(pos);
}
} // namespace Eval::NNUE

48
src/nnue/evaluate_nnue.h Normal file
View File

@@ -0,0 +1,48 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
// header used in NNUE evaluation function
#ifndef NNUE_EVALUATE_NNUE_H_INCLUDED
#define NNUE_EVALUATE_NNUE_H_INCLUDED
#include "nnue_feature_transformer.h"
#include <memory>
namespace Eval::NNUE {
// Hash value of evaluation function structure
constexpr std::uint32_t kHashValue =
FeatureTransformer::GetHashValue() ^ Network::GetHashValue();
// Deleter for automating release of memory area
template <typename T>
struct AlignedDeleter {
void operator()(T* ptr) const {
ptr->~T();
std_aligned_free(ptr);
}
};
template <typename T>
using AlignedPtr = std::unique_ptr<T, AlignedDeleter<T>>;
} // namespace Eval::NNUE
#endif // #ifndef NNUE_EVALUATE_NNUE_H_INCLUDED

View File

@@ -0,0 +1,135 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
// A class template that represents the input feature set of the NNUE evaluation function
#ifndef NNUE_FEATURE_SET_H_INCLUDED
#define NNUE_FEATURE_SET_H_INCLUDED
#include "features_common.h"
#include <array>
namespace Eval::NNUE::Features {
// Class template that represents a list of values
template <typename T, T... Values>
struct CompileTimeList;
template <typename T, T First, T... Remaining>
struct CompileTimeList<T, First, Remaining...> {
static constexpr bool Contains(T value) {
return value == First || CompileTimeList<T, Remaining...>::Contains(value);
}
static constexpr std::array<T, sizeof...(Remaining) + 1>
kValues = {{First, Remaining...}};
};
// Base class of feature set
template <typename Derived>
class FeatureSetBase {
public:
// Get a list of indices for active features
template <typename IndexListType>
static void AppendActiveIndices(
const Position& pos, TriggerEvent trigger, IndexListType active[2]) {
for (Color perspective : { WHITE, BLACK }) {
Derived::CollectActiveIndices(
pos, trigger, perspective, &active[perspective]);
}
}
// Get a list of indices for recently changed features
template <typename PositionType, typename IndexListType>
static void AppendChangedIndices(
const PositionType& pos, TriggerEvent trigger,
IndexListType removed[2], IndexListType added[2], bool reset[2]) {
const auto& dp = pos.state()->dirtyPiece;
if (dp.dirty_num == 0) return;
for (Color perspective : { WHITE, BLACK }) {
reset[perspective] = false;
switch (trigger) {
case TriggerEvent::kFriendKingMoved:
reset[perspective] =
dp.pieceId[0] == PIECE_ID_KING + perspective;
break;
default:
assert(false);
break;
}
if (reset[perspective]) {
Derived::CollectActiveIndices(
pos, trigger, perspective, &added[perspective]);
} else {
Derived::CollectChangedIndices(
pos, trigger, perspective,
&removed[perspective], &added[perspective]);
}
}
}
};
// Class template that represents the feature set
template <typename FeatureType>
class FeatureSet<FeatureType> : public FeatureSetBase<FeatureSet<FeatureType>> {
public:
// Hash value embedded in the evaluation file
static constexpr std::uint32_t kHashValue = FeatureType::kHashValue;
// Number of feature dimensions
static constexpr IndexType kDimensions = FeatureType::kDimensions;
// Maximum number of simultaneously active features
static constexpr IndexType kMaxActiveDimensions =
FeatureType::kMaxActiveDimensions;
// Trigger for full calculation instead of difference calculation
using SortedTriggerSet =
CompileTimeList<TriggerEvent, FeatureType::kRefreshTrigger>;
static constexpr auto kRefreshTriggers = SortedTriggerSet::kValues;
private:
// Get a list of indices for active features
static void CollectActiveIndices(
const Position& pos, const TriggerEvent trigger, const Color perspective,
IndexList* const active) {
if (FeatureType::kRefreshTrigger == trigger) {
FeatureType::AppendActiveIndices(pos, perspective, active);
}
}
// Get a list of indices for recently changed features
static void CollectChangedIndices(
const Position& pos, const TriggerEvent trigger, const Color perspective,
IndexList* const removed, IndexList* const added) {
if (FeatureType::kRefreshTrigger == trigger) {
FeatureType::AppendChangedIndices(pos, perspective, removed, added);
}
}
// Make the base class and the class template that recursively uses itself a friend
friend class FeatureSetBase<FeatureSet>;
template <typename... FeatureTypes>
friend class FeatureSet;
};
} // namespace Eval::NNUE::Features
#endif // #ifndef NNUE_FEATURE_SET_H_INCLUDED

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -16,27 +16,30 @@
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef BENCHMARK_H_INCLUDED
#define BENCHMARK_H_INCLUDED
//Common header of input features of NNUE evaluation function
#include <iosfwd>
#include <string>
#include <vector>
#ifndef NNUE_FEATURES_COMMON_H_INCLUDED
#define NNUE_FEATURES_COMMON_H_INCLUDED
namespace Stockfish::Benchmark {
#include "../../evaluate.h"
#include "../nnue_common.h"
std::vector<std::string> setup_bench(const std::string&, std::istream&);
namespace Eval::NNUE::Features {
struct BenchmarkSetup {
int ttSize;
int threads;
std::vector<std::string> commands;
std::string originalInvocation;
std::string filledInvocation;
};
class IndexList;
BenchmarkSetup setup_benchmark(std::istream&);
template <typename... FeatureTypes>
class FeatureSet;
} // namespace Stockfish
// Trigger to perform full calculations instead of difference only
enum class TriggerEvent {
kFriendKingMoved // calculate full evaluation when own king moves
};
#endif // #ifndef BENCHMARK_H_INCLUDED
enum class Side {
kFriend // side to move
};
} // namespace Eval::NNUE::Features
#endif // #ifndef NNUE_FEATURES_COMMON_H_INCLUDED

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@@ -1,86 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
//Definition of input features HalfKAv2_hm of NNUE evaluation function
#include "half_ka_v2_hm.h"
#include "../../bitboard.h"
#include "../../position.h"
#include "../../types.h"
#include "../nnue_common.h"
namespace Stockfish::Eval::NNUE::Features {
// Index of a feature for a given king position and another piece on some square
template<Color Perspective>
inline IndexType HalfKAv2_hm::make_index(Square s, Piece pc, Square ksq) {
return IndexType((int(s) ^ OrientTBL[Perspective][ksq]) + PieceSquareIndex[Perspective][pc]
+ KingBuckets[Perspective][ksq]);
}
// Get a list of indices for active features
template<Color Perspective>
void HalfKAv2_hm::append_active_indices(const Position& pos, IndexList& active) {
Square ksq = pos.square<KING>(Perspective);
Bitboard bb = pos.pieces();
while (bb)
{
Square s = pop_lsb(bb);
active.push_back(make_index<Perspective>(s, pos.piece_on(s), ksq));
}
}
// Explicit template instantiations
template void HalfKAv2_hm::append_active_indices<WHITE>(const Position& pos, IndexList& active);
template void HalfKAv2_hm::append_active_indices<BLACK>(const Position& pos, IndexList& active);
template IndexType HalfKAv2_hm::make_index<WHITE>(Square s, Piece pc, Square ksq);
template IndexType HalfKAv2_hm::make_index<BLACK>(Square s, Piece pc, Square ksq);
// Get a list of indices for recently changed features
template<Color Perspective>
void HalfKAv2_hm::append_changed_indices(Square ksq,
const DirtyPiece& dp,
IndexList& removed,
IndexList& added) {
removed.push_back(make_index<Perspective>(dp.from, dp.pc, ksq));
if (dp.to != SQ_NONE)
added.push_back(make_index<Perspective>(dp.to, dp.pc, ksq));
if (dp.remove_sq != SQ_NONE)
removed.push_back(make_index<Perspective>(dp.remove_sq, dp.remove_pc, ksq));
if (dp.add_sq != SQ_NONE)
added.push_back(make_index<Perspective>(dp.add_sq, dp.add_pc, ksq));
}
// Explicit template instantiations
template void HalfKAv2_hm::append_changed_indices<WHITE>(Square ksq,
const DirtyPiece& dp,
IndexList& removed,
IndexList& added);
template void HalfKAv2_hm::append_changed_indices<BLACK>(Square ksq,
const DirtyPiece& dp,
IndexList& removed,
IndexList& added);
bool HalfKAv2_hm::requires_refresh(const DirtyPiece& dirtyPiece, Color perspective) {
return dirtyPiece.pc == make_piece(perspective, KING);
}
} // namespace Stockfish::Eval::NNUE::Features

View File

@@ -1,144 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
//Definition of input features HalfKP of NNUE evaluation function
#ifndef NNUE_FEATURES_HALF_KA_V2_HM_H_INCLUDED
#define NNUE_FEATURES_HALF_KA_V2_HM_H_INCLUDED
#include <cstdint>
#include "../../misc.h"
#include "../../types.h"
#include "../nnue_common.h"
namespace Stockfish {
class Position;
}
namespace Stockfish::Eval::NNUE::Features {
// Feature HalfKAv2_hm: Combination of the position of own king and the
// position of pieces. Position mirrored such that king is always on e..h files.
class HalfKAv2_hm {
// Unique number for each piece type on each square
enum {
PS_NONE = 0,
PS_W_PAWN = 0,
PS_B_PAWN = 1 * SQUARE_NB,
PS_W_KNIGHT = 2 * SQUARE_NB,
PS_B_KNIGHT = 3 * SQUARE_NB,
PS_W_BISHOP = 4 * SQUARE_NB,
PS_B_BISHOP = 5 * SQUARE_NB,
PS_W_ROOK = 6 * SQUARE_NB,
PS_B_ROOK = 7 * SQUARE_NB,
PS_W_QUEEN = 8 * SQUARE_NB,
PS_B_QUEEN = 9 * SQUARE_NB,
PS_KING = 10 * SQUARE_NB,
PS_NB = 11 * SQUARE_NB
};
static constexpr IndexType PieceSquareIndex[COLOR_NB][PIECE_NB] = {
// Convention: W - us, B - them
// Viewed from other side, W and B are reversed
{PS_NONE, PS_W_PAWN, PS_W_KNIGHT, PS_W_BISHOP, PS_W_ROOK, PS_W_QUEEN, PS_KING, PS_NONE,
PS_NONE, PS_B_PAWN, PS_B_KNIGHT, PS_B_BISHOP, PS_B_ROOK, PS_B_QUEEN, PS_KING, PS_NONE},
{PS_NONE, PS_B_PAWN, PS_B_KNIGHT, PS_B_BISHOP, PS_B_ROOK, PS_B_QUEEN, PS_KING, PS_NONE,
PS_NONE, PS_W_PAWN, PS_W_KNIGHT, PS_W_BISHOP, PS_W_ROOK, PS_W_QUEEN, PS_KING, PS_NONE}};
public:
// Feature name
static constexpr const char* Name = "HalfKAv2_hm(Friend)";
// Hash value embedded in the evaluation file
static constexpr std::uint32_t HashValue = 0x7f234cb8u;
// Number of feature dimensions
static constexpr IndexType Dimensions =
static_cast<IndexType>(SQUARE_NB) * static_cast<IndexType>(PS_NB) / 2;
#define B(v) (v * PS_NB)
// clang-format off
static constexpr int KingBuckets[COLOR_NB][SQUARE_NB] = {
{ B(28), B(29), B(30), B(31), B(31), B(30), B(29), B(28),
B(24), B(25), B(26), B(27), B(27), B(26), B(25), B(24),
B(20), B(21), B(22), B(23), B(23), B(22), B(21), B(20),
B(16), B(17), B(18), B(19), B(19), B(18), B(17), B(16),
B(12), B(13), B(14), B(15), B(15), B(14), B(13), B(12),
B( 8), B( 9), B(10), B(11), B(11), B(10), B( 9), B( 8),
B( 4), B( 5), B( 6), B( 7), B( 7), B( 6), B( 5), B( 4),
B( 0), B( 1), B( 2), B( 3), B( 3), B( 2), B( 1), B( 0) },
{ B( 0), B( 1), B( 2), B( 3), B( 3), B( 2), B( 1), B( 0),
B( 4), B( 5), B( 6), B( 7), B( 7), B( 6), B( 5), B( 4),
B( 8), B( 9), B(10), B(11), B(11), B(10), B( 9), B( 8),
B(12), B(13), B(14), B(15), B(15), B(14), B(13), B(12),
B(16), B(17), B(18), B(19), B(19), B(18), B(17), B(16),
B(20), B(21), B(22), B(23), B(23), B(22), B(21), B(20),
B(24), B(25), B(26), B(27), B(27), B(26), B(25), B(24),
B(28), B(29), B(30), B(31), B(31), B(30), B(29), B(28) }
};
// clang-format on
#undef B
// clang-format off
// Orient a square according to perspective (rotates by 180 for black)
static constexpr int OrientTBL[COLOR_NB][SQUARE_NB] = {
{ SQ_H1, SQ_H1, SQ_H1, SQ_H1, SQ_A1, SQ_A1, SQ_A1, SQ_A1,
SQ_H1, SQ_H1, SQ_H1, SQ_H1, SQ_A1, SQ_A1, SQ_A1, SQ_A1,
SQ_H1, SQ_H1, SQ_H1, SQ_H1, SQ_A1, SQ_A1, SQ_A1, SQ_A1,
SQ_H1, SQ_H1, SQ_H1, SQ_H1, SQ_A1, SQ_A1, SQ_A1, SQ_A1,
SQ_H1, SQ_H1, SQ_H1, SQ_H1, SQ_A1, SQ_A1, SQ_A1, SQ_A1,
SQ_H1, SQ_H1, SQ_H1, SQ_H1, SQ_A1, SQ_A1, SQ_A1, SQ_A1,
SQ_H1, SQ_H1, SQ_H1, SQ_H1, SQ_A1, SQ_A1, SQ_A1, SQ_A1,
SQ_H1, SQ_H1, SQ_H1, SQ_H1, SQ_A1, SQ_A1, SQ_A1, SQ_A1 },
{ SQ_H8, SQ_H8, SQ_H8, SQ_H8, SQ_A8, SQ_A8, SQ_A8, SQ_A8,
SQ_H8, SQ_H8, SQ_H8, SQ_H8, SQ_A8, SQ_A8, SQ_A8, SQ_A8,
SQ_H8, SQ_H8, SQ_H8, SQ_H8, SQ_A8, SQ_A8, SQ_A8, SQ_A8,
SQ_H8, SQ_H8, SQ_H8, SQ_H8, SQ_A8, SQ_A8, SQ_A8, SQ_A8,
SQ_H8, SQ_H8, SQ_H8, SQ_H8, SQ_A8, SQ_A8, SQ_A8, SQ_A8,
SQ_H8, SQ_H8, SQ_H8, SQ_H8, SQ_A8, SQ_A8, SQ_A8, SQ_A8,
SQ_H8, SQ_H8, SQ_H8, SQ_H8, SQ_A8, SQ_A8, SQ_A8, SQ_A8,
SQ_H8, SQ_H8, SQ_H8, SQ_H8, SQ_A8, SQ_A8, SQ_A8, SQ_A8 }
};
// clang-format on
// Maximum number of simultaneously active features.
static constexpr IndexType MaxActiveDimensions = 32;
using IndexList = ValueList<IndexType, MaxActiveDimensions>;
// Index of a feature for a given king position and another piece on some square
template<Color Perspective>
static IndexType make_index(Square s, Piece pc, Square ksq);
// Get a list of indices for active features
template<Color Perspective>
static void append_active_indices(const Position& pos, IndexList& active);
// Get a list of indices for recently changed features
template<Color Perspective>
static void
append_changed_indices(Square ksq, const DirtyPiece& dp, IndexList& removed, IndexList& added);
// Returns whether the change stored in this DirtyPiece means
// that a full accumulator refresh is required.
static bool requires_refresh(const DirtyPiece& dirtyPiece, Color perspective);
};
} // namespace Stockfish::Eval::NNUE::Features
#endif // #ifndef NNUE_FEATURES_HALF_KA_V2_HM_H_INCLUDED

View File

@@ -0,0 +1,92 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
//Definition of input features HalfKP of NNUE evaluation function
#include "half_kp.h"
#include "index_list.h"
namespace Eval::NNUE::Features {
// Find the index of the feature quantity from the king position and PieceSquare
template <Side AssociatedKing>
inline IndexType HalfKP<AssociatedKing>::MakeIndex(Square sq_k, PieceSquare p) {
return static_cast<IndexType>(PS_END) * static_cast<IndexType>(sq_k) + p;
}
// Get pieces information
template <Side AssociatedKing>
inline void HalfKP<AssociatedKing>::GetPieces(
const Position& pos, Color perspective,
PieceSquare** pieces, Square* sq_target_k) {
*pieces = (perspective == BLACK) ?
pos.eval_list()->piece_list_fb() :
pos.eval_list()->piece_list_fw();
const PieceId target = (AssociatedKing == Side::kFriend) ?
static_cast<PieceId>(PIECE_ID_KING + perspective) :
static_cast<PieceId>(PIECE_ID_KING + ~perspective);
*sq_target_k = static_cast<Square>(((*pieces)[target] - PS_W_KING) % SQUARE_NB);
}
// Get a list of indices for active features
template <Side AssociatedKing>
void HalfKP<AssociatedKing>::AppendActiveIndices(
const Position& pos, Color perspective, IndexList* active) {
// Do nothing if array size is small to avoid compiler warning
if (RawFeatures::kMaxActiveDimensions < kMaxActiveDimensions) return;
PieceSquare* pieces;
Square sq_target_k;
GetPieces(pos, perspective, &pieces, &sq_target_k);
for (PieceId i = PIECE_ID_ZERO; i < PIECE_ID_KING; ++i) {
if (pieces[i] != PS_NONE) {
active->push_back(MakeIndex(sq_target_k, pieces[i]));
}
}
}
// Get a list of indices for recently changed features
template <Side AssociatedKing>
void HalfKP<AssociatedKing>::AppendChangedIndices(
const Position& pos, Color perspective,
IndexList* removed, IndexList* added) {
PieceSquare* pieces;
Square sq_target_k;
GetPieces(pos, perspective, &pieces, &sq_target_k);
const auto& dp = pos.state()->dirtyPiece;
for (int i = 0; i < dp.dirty_num; ++i) {
if (dp.pieceId[i] >= PIECE_ID_KING) continue;
const auto old_p = static_cast<PieceSquare>(
dp.old_piece[i].from[perspective]);
if (old_p != PS_NONE) {
removed->push_back(MakeIndex(sq_target_k, old_p));
}
const auto new_p = static_cast<PieceSquare>(
dp.new_piece[i].from[perspective]);
if (new_p != PS_NONE) {
added->push_back(MakeIndex(sq_target_k, new_p));
}
}
}
template class HalfKP<Side::kFriend>;
} // namespace Eval::NNUE::Features

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@@ -0,0 +1,67 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
//Definition of input features HalfKP of NNUE evaluation function
#ifndef NNUE_FEATURES_HALF_KP_H_INCLUDED
#define NNUE_FEATURES_HALF_KP_H_INCLUDED
#include "../../evaluate.h"
#include "features_common.h"
namespace Eval::NNUE::Features {
// Feature HalfKP: Combination of the position of own king
// and the position of pieces other than kings
template <Side AssociatedKing>
class HalfKP {
public:
// Feature name
static constexpr const char* kName = "HalfKP(Friend)";
// Hash value embedded in the evaluation file
static constexpr std::uint32_t kHashValue =
0x5D69D5B9u ^ (AssociatedKing == Side::kFriend);
// Number of feature dimensions
static constexpr IndexType kDimensions =
static_cast<IndexType>(SQUARE_NB) * static_cast<IndexType>(PS_END);
// Maximum number of simultaneously active features
static constexpr IndexType kMaxActiveDimensions = PIECE_ID_KING;
// Trigger for full calculation instead of difference calculation
static constexpr TriggerEvent kRefreshTrigger = TriggerEvent::kFriendKingMoved;
// Get a list of indices for active features
static void AppendActiveIndices(const Position& pos, Color perspective,
IndexList* active);
// Get a list of indices for recently changed features
static void AppendChangedIndices(const Position& pos, Color perspective,
IndexList* removed, IndexList* added);
// Index of a feature for a given king position and another piece on some square
static IndexType MakeIndex(Square sq_k, PieceSquare p);
private:
// Get pieces information
static void GetPieces(const Position& pos, Color perspective,
PieceSquare** pieces, Square* sq_target_k);
};
} // namespace Eval::NNUE::Features
#endif // #ifndef NNUE_FEATURES_HALF_KP_H_INCLUDED

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@@ -0,0 +1,64 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
// Definition of index list of input features
#ifndef NNUE_FEATURES_INDEX_LIST_H_INCLUDED
#define NNUE_FEATURES_INDEX_LIST_H_INCLUDED
#include "../../position.h"
#include "../nnue_architecture.h"
namespace Eval::NNUE::Features {
// Class template used for feature index list
template <typename T, std::size_t MaxSize>
class ValueList {
public:
std::size_t size() const { return size_; }
void resize(std::size_t size) { size_ = size; }
void push_back(const T& value) { values_[size_++] = value; }
T& operator[](std::size_t index) { return values_[index]; }
T* begin() { return values_; }
T* end() { return values_ + size_; }
const T& operator[](std::size_t index) const { return values_[index]; }
const T* begin() const { return values_; }
const T* end() const { return values_ + size_; }
void swap(ValueList& other) {
const std::size_t max_size = std::max(size_, other.size_);
for (std::size_t i = 0; i < max_size; ++i) {
std::swap(values_[i], other.values_[i]);
}
std::swap(size_, other.size_);
}
private:
T values_[MaxSize];
std::size_t size_ = 0;
};
//Type of feature index list
class IndexList
: public ValueList<IndexType, RawFeatures::kMaxActiveDimensions> {
};
} // namespace Eval::NNUE::Features
#endif // NNUE_FEATURES_INDEX_LIST_H_INCLUDED

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -21,282 +21,195 @@
#ifndef NNUE_LAYERS_AFFINE_TRANSFORM_H_INCLUDED
#define NNUE_LAYERS_AFFINE_TRANSFORM_H_INCLUDED
#include <cstdint>
#include <iostream>
#include "../nnue_common.h"
#include "../simd.h"
/*
This file contains the definition for a fully connected layer (aka affine transform).
namespace Eval::NNUE::Layers {
- expected use-case is for when PaddedInputDimensions == 32 and InputDimensions <= 32.
- that's why AVX512 is hard to implement
- expected use-case is small layers
- inputs are processed in chunks of 4, weights are respectively transposed
- accumulation happens directly to int32s
*/
namespace Stockfish::Eval::NNUE::Layers {
#if defined(USE_SSSE3) || defined(USE_NEON_DOTPROD)
#define ENABLE_SEQ_OPT
#endif
// Fallback implementation for older/other architectures.
// Requires the input to be padded to at least 16 values.
#ifndef ENABLE_SEQ_OPT
template<IndexType InputDimensions, IndexType PaddedInputDimensions, IndexType OutputDimensions>
static void affine_transform_non_ssse3(std::int32_t* output,
const std::int8_t* weights,
const std::int32_t* biases,
const std::uint8_t* input) {
#if defined(USE_SSE2) || defined(USE_NEON)
#if defined(USE_SSE2)
// At least a multiple of 16, with SSE2.
constexpr IndexType NumChunks = ceil_to_multiple<IndexType>(InputDimensions, 16) / 16;
const __m128i Zeros = _mm_setzero_si128();
const auto inputVector = reinterpret_cast<const __m128i*>(input);
#elif defined(USE_NEON)
constexpr IndexType NumChunks = ceil_to_multiple<IndexType>(InputDimensions, 16) / 16;
const auto inputVector = reinterpret_cast<const int8x8_t*>(input);
#endif
for (IndexType i = 0; i < OutputDimensions; ++i)
{
const IndexType offset = i * PaddedInputDimensions;
#if defined(USE_SSE2)
__m128i sumLo = _mm_cvtsi32_si128(biases[i]);
__m128i sumHi = Zeros;
const auto row = reinterpret_cast<const __m128i*>(&weights[offset]);
for (IndexType j = 0; j < NumChunks; ++j)
{
__m128i row_j = _mm_load_si128(&row[j]);
__m128i input_j = _mm_load_si128(&inputVector[j]);
__m128i extendedRowLo = _mm_srai_epi16(_mm_unpacklo_epi8(row_j, row_j), 8);
__m128i extendedRowHi = _mm_srai_epi16(_mm_unpackhi_epi8(row_j, row_j), 8);
__m128i extendedInputLo = _mm_unpacklo_epi8(input_j, Zeros);
__m128i extendedInputHi = _mm_unpackhi_epi8(input_j, Zeros);
__m128i productLo = _mm_madd_epi16(extendedRowLo, extendedInputLo);
__m128i productHi = _mm_madd_epi16(extendedRowHi, extendedInputHi);
sumLo = _mm_add_epi32(sumLo, productLo);
sumHi = _mm_add_epi32(sumHi, productHi);
}
__m128i sum = _mm_add_epi32(sumLo, sumHi);
__m128i sumHigh_64 = _mm_shuffle_epi32(sum, _MM_SHUFFLE(1, 0, 3, 2));
sum = _mm_add_epi32(sum, sumHigh_64);
__m128i sum_second_32 = _mm_shufflelo_epi16(sum, _MM_SHUFFLE(1, 0, 3, 2));
sum = _mm_add_epi32(sum, sum_second_32);
output[i] = _mm_cvtsi128_si32(sum);
#elif defined(USE_NEON)
int32x4_t sum = {biases[i]};
const auto row = reinterpret_cast<const int8x8_t*>(&weights[offset]);
for (IndexType j = 0; j < NumChunks; ++j)
{
int16x8_t product = vmull_s8(inputVector[j * 2], row[j * 2]);
product = vmlal_s8(product, inputVector[j * 2 + 1], row[j * 2 + 1]);
sum = vpadalq_s16(sum, product);
}
output[i] = SIMD::neon_m128_reduce_add_epi32(sum);
#endif
}
#else
std::memcpy(output, biases, sizeof(std::int32_t) * OutputDimensions);
// Traverse weights in transpose order to take advantage of input sparsity
for (IndexType i = 0; i < InputDimensions; ++i)
if (input[i])
{
const std::int8_t* w = &weights[i];
const int in = input[i];
for (IndexType j = 0; j < OutputDimensions; ++j)
output[j] += w[j * PaddedInputDimensions] * in;
}
#endif
}
#endif // !ENABLE_SEQ_OPT
template<IndexType InDims, IndexType OutDims>
class AffineTransform {
// Affine transformation layer
template <typename PreviousLayer, IndexType OutputDimensions>
class AffineTransform {
public:
// Input/output type
using InputType = std::uint8_t;
using InputType = typename PreviousLayer::OutputType;
using OutputType = std::int32_t;
static_assert(std::is_same<InputType, std::uint8_t>::value, "");
// Number of input/output dimensions
static constexpr IndexType InputDimensions = InDims;
static constexpr IndexType OutputDimensions = OutDims;
static constexpr IndexType kInputDimensions =
PreviousLayer::kOutputDimensions;
static constexpr IndexType kOutputDimensions = OutputDimensions;
static constexpr IndexType kPaddedInputDimensions =
CeilToMultiple<IndexType>(kInputDimensions, kMaxSimdWidth);
static constexpr IndexType PaddedInputDimensions =
ceil_to_multiple<IndexType>(InputDimensions, MaxSimdWidth);
static constexpr IndexType PaddedOutputDimensions =
ceil_to_multiple<IndexType>(OutputDimensions, MaxSimdWidth);
// Size of forward propagation buffer used in this layer
static constexpr std::size_t kSelfBufferSize =
CeilToMultiple(kOutputDimensions * sizeof(OutputType), kCacheLineSize);
using OutputBuffer = OutputType[PaddedOutputDimensions];
// Size of the forward propagation buffer used from the input layer to this layer
static constexpr std::size_t kBufferSize =
PreviousLayer::kBufferSize + kSelfBufferSize;
// Hash value embedded in the evaluation file
static constexpr std::uint32_t get_hash_value(std::uint32_t prevHash) {
std::uint32_t hashValue = 0xCC03DAE4u;
hashValue += OutputDimensions;
hashValue ^= prevHash >> 1;
hashValue ^= prevHash << 31;
return hashValue;
static constexpr std::uint32_t GetHashValue() {
std::uint32_t hash_value = 0xCC03DAE4u;
hash_value += kOutputDimensions;
hash_value ^= PreviousLayer::GetHashValue() >> 1;
hash_value ^= PreviousLayer::GetHashValue() << 31;
return hash_value;
}
static constexpr IndexType get_weight_index_scrambled(IndexType i) {
return (i / 4) % (PaddedInputDimensions / 4) * OutputDimensions * 4
+ i / PaddedInputDimensions * 4 + i % 4;
// Read network parameters
bool ReadParameters(std::istream& stream) {
if (!previous_layer_.ReadParameters(stream)) return false;
stream.read(reinterpret_cast<char*>(biases_),
kOutputDimensions * sizeof(BiasType));
stream.read(reinterpret_cast<char*>(weights_),
kOutputDimensions * kPaddedInputDimensions *
sizeof(WeightType));
return !stream.fail();
}
static constexpr IndexType get_weight_index(IndexType i) {
#ifdef ENABLE_SEQ_OPT
return get_weight_index_scrambled(i);
#else
return i;
#endif
}
// Read network parameters
bool read_parameters(std::istream& stream) {
read_little_endian<BiasType>(stream, biases, OutputDimensions);
for (IndexType i = 0; i < OutputDimensions * PaddedInputDimensions; ++i)
weights[get_weight_index(i)] = read_little_endian<WeightType>(stream);
return !stream.fail();
}
// Write network parameters
bool write_parameters(std::ostream& stream) const {
write_little_endian<BiasType>(stream, biases, OutputDimensions);
for (IndexType i = 0; i < OutputDimensions * PaddedInputDimensions; ++i)
write_little_endian<WeightType>(stream, weights[get_weight_index(i)]);
return !stream.fail();
}
// Forward propagation
void propagate(const InputType* input, OutputType* output) const {
const OutputType* Propagate(
const TransformedFeatureType* transformed_features, char* buffer) const {
const auto input = previous_layer_.Propagate(
transformed_features, buffer + kSelfBufferSize);
const auto output = reinterpret_cast<OutputType*>(buffer);
#ifdef ENABLE_SEQ_OPT
#if defined(USE_AVX512)
constexpr IndexType kNumChunks = kPaddedInputDimensions / (kSimdWidth * 2);
const __m512i kOnes = _mm512_set1_epi16(1);
const auto input_vector = reinterpret_cast<const __m512i*>(input);
if constexpr (OutputDimensions > 1)
{
#if defined(USE_AVX512)
using vec_t = __m512i;
#define vec_set_32 _mm512_set1_epi32
#define vec_add_dpbusd_32 SIMD::m512_add_dpbusd_epi32
#elif defined(USE_AVX2)
using vec_t = __m256i;
#define vec_set_32 _mm256_set1_epi32
#define vec_add_dpbusd_32 SIMD::m256_add_dpbusd_epi32
#elif defined(USE_SSSE3)
using vec_t = __m128i;
#define vec_set_32 _mm_set1_epi32
#define vec_add_dpbusd_32 SIMD::m128_add_dpbusd_epi32
#elif defined(USE_NEON_DOTPROD)
using vec_t = int32x4_t;
#define vec_set_32 vdupq_n_s32
#define vec_add_dpbusd_32(acc, a, b) \
SIMD::dotprod_m128_add_dpbusd_epi32(acc, vreinterpretq_s8_s32(a), \
vreinterpretq_s8_s32(b))
#endif
#elif defined(USE_AVX2)
constexpr IndexType kNumChunks = kPaddedInputDimensions / kSimdWidth;
const __m256i kOnes = _mm256_set1_epi16(1);
const auto input_vector = reinterpret_cast<const __m256i*>(input);
static constexpr IndexType OutputSimdWidth = sizeof(vec_t) / sizeof(OutputType);
#elif defined(USE_SSSE3)
constexpr IndexType kNumChunks = kPaddedInputDimensions / kSimdWidth;
const __m128i kOnes = _mm_set1_epi16(1);
const auto input_vector = reinterpret_cast<const __m128i*>(input);
static_assert(OutputDimensions % OutputSimdWidth == 0);
#elif defined(USE_NEON)
constexpr IndexType kNumChunks = kPaddedInputDimensions / kSimdWidth;
const auto input_vector = reinterpret_cast<const int8x8_t*>(input);
#endif
constexpr IndexType NumChunks = ceil_to_multiple<IndexType>(InputDimensions, 8) / 4;
constexpr IndexType NumRegs = OutputDimensions / OutputSimdWidth;
for (IndexType i = 0; i < kOutputDimensions; ++i) {
const IndexType offset = i * kPaddedInputDimensions;
const auto input32 = reinterpret_cast<const std::int32_t*>(input);
const vec_t* biasvec = reinterpret_cast<const vec_t*>(biases);
vec_t acc[NumRegs];
for (IndexType k = 0; k < NumRegs; ++k)
acc[k] = biasvec[k];
#if defined(USE_AVX512)
__m512i sum = _mm512_setzero_si512();
const auto row = reinterpret_cast<const __m512i*>(&weights_[offset]);
for (IndexType j = 0; j < kNumChunks; ++j) {
for (IndexType i = 0; i < NumChunks; ++i)
{
const vec_t in0 = vec_set_32(input32[i]);
const auto col0 =
reinterpret_cast<const vec_t*>(&weights[i * OutputDimensions * 4]);
#if defined(__MINGW32__) || defined(__MINGW64__)
__m512i product = _mm512_maddubs_epi16(_mm512_loadu_si512(&input_vector[j]), _mm512_load_si512(&row[j]));
#else
__m512i product = _mm512_maddubs_epi16(_mm512_load_si512(&input_vector[j]), _mm512_load_si512(&row[j]));
#endif
for (IndexType k = 0; k < NumRegs; ++k)
vec_add_dpbusd_32(acc[k], in0, col0[k]);
}
vec_t* outptr = reinterpret_cast<vec_t*>(output);
for (IndexType k = 0; k < NumRegs; ++k)
outptr[k] = acc[k];
#undef vec_set_32
#undef vec_add_dpbusd_32
product = _mm512_madd_epi16(product, kOnes);
sum = _mm512_add_epi32(sum, product);
}
else if constexpr (OutputDimensions == 1)
output[i] = _mm512_reduce_add_epi32(sum) + biases_[i];
// Note: Changing kMaxSimdWidth from 32 to 64 breaks loading existing networks.
// As a result kPaddedInputDimensions may not be an even multiple of 64(512bit)
// and we have to do one more 256bit chunk.
if (kPaddedInputDimensions != kNumChunks * kSimdWidth * 2)
{
// We cannot use AVX512 for the last layer because there are only 32 inputs
// and the buffer is not padded to 64 elements.
#if defined(USE_AVX2)
using vec_t = __m256i;
#define vec_setzero() _mm256_setzero_si256()
#define vec_add_dpbusd_32 SIMD::m256_add_dpbusd_epi32
#define vec_hadd SIMD::m256_hadd
#elif defined(USE_SSSE3)
using vec_t = __m128i;
#define vec_setzero() _mm_setzero_si128()
#define vec_add_dpbusd_32 SIMD::m128_add_dpbusd_epi32
#define vec_hadd SIMD::m128_hadd
#elif defined(USE_NEON_DOTPROD)
using vec_t = int32x4_t;
#define vec_setzero() vdupq_n_s32(0)
#define vec_add_dpbusd_32(acc, a, b) \
SIMD::dotprod_m128_add_dpbusd_epi32(acc, vreinterpretq_s8_s32(a), \
vreinterpretq_s8_s32(b))
#define vec_hadd SIMD::neon_m128_hadd
#endif
const auto iv_256 = reinterpret_cast<const __m256i*>(input);
const auto row_256 = reinterpret_cast<const __m256i*>(&weights_[offset]);
int j = kNumChunks * 2;
const auto inputVector = reinterpret_cast<const vec_t*>(input);
#if defined(__MINGW32__) || defined(__MINGW64__) // See HACK comment below in AVX2.
__m256i sum256 = _mm256_maddubs_epi16(_mm256_loadu_si256(&iv_256[j]), _mm256_load_si256(&row_256[j]));
#else
__m256i sum256 = _mm256_maddubs_epi16(_mm256_load_si256(&iv_256[j]), _mm256_load_si256(&row_256[j]));
#endif
static constexpr IndexType InputSimdWidth = sizeof(vec_t) / sizeof(InputType);
static_assert(PaddedInputDimensions % InputSimdWidth == 0);
constexpr IndexType NumChunks = PaddedInputDimensions / InputSimdWidth;
vec_t sum0 = vec_setzero();
const auto row0 = reinterpret_cast<const vec_t*>(&weights[0]);
for (int j = 0; j < int(NumChunks); ++j)
{
const vec_t in = inputVector[j];
vec_add_dpbusd_32(sum0, in, row0[j]);
}
output[0] = vec_hadd(sum0, biases[0]);
#undef vec_setzero
#undef vec_add_dpbusd_32
#undef vec_hadd
sum256 = _mm256_madd_epi16(sum256, _mm256_set1_epi16(1));
sum256 = _mm256_hadd_epi32(sum256, sum256);
sum256 = _mm256_hadd_epi32(sum256, sum256);
const __m128i lo = _mm256_extracti128_si256(sum256, 0);
const __m128i hi = _mm256_extracti128_si256(sum256, 1);
output[i] += _mm_cvtsi128_si32(lo) + _mm_cvtsi128_si32(hi);
}
#else
// Use old implementation for the other architectures.
affine_transform_non_ssse3<InputDimensions, PaddedInputDimensions, OutputDimensions>(
output, weights, biases, input);
#endif
#elif defined(USE_AVX2)
__m256i sum = _mm256_setzero_si256();
const auto row = reinterpret_cast<const __m256i*>(&weights_[offset]);
for (IndexType j = 0; j < kNumChunks; ++j) {
__m256i product = _mm256_maddubs_epi16(
#if defined(__MINGW32__) || defined(__MINGW64__)
// HACK: Use _mm256_loadu_si256() instead of _mm256_load_si256. Because the binary
// compiled with g++ in MSYS2 crashes here because the output memory is not aligned
// even though alignas is specified.
_mm256_loadu_si256
#else
_mm256_load_si256
#endif
(&input_vector[j]), _mm256_load_si256(&row[j]));
product = _mm256_madd_epi16(product, kOnes);
sum = _mm256_add_epi32(sum, product);
}
sum = _mm256_hadd_epi32(sum, sum);
sum = _mm256_hadd_epi32(sum, sum);
const __m128i lo = _mm256_extracti128_si256(sum, 0);
const __m128i hi = _mm256_extracti128_si256(sum, 1);
output[i] = _mm_cvtsi128_si32(lo) + _mm_cvtsi128_si32(hi) + biases_[i];
#elif defined(USE_SSSE3)
__m128i sum = _mm_cvtsi32_si128(biases_[i]);
const auto row = reinterpret_cast<const __m128i*>(&weights_[offset]);
for (IndexType j = 0; j < kNumChunks; ++j) {
__m128i product = _mm_maddubs_epi16(
_mm_load_si128(&input_vector[j]), _mm_load_si128(&row[j]));
product = _mm_madd_epi16(product, kOnes);
sum = _mm_add_epi32(sum, product);
}
sum = _mm_hadd_epi32(sum, sum);
sum = _mm_hadd_epi32(sum, sum);
output[i] = _mm_cvtsi128_si32(sum);
#elif defined(USE_NEON)
int32x4_t sum = {biases_[i]};
const auto row = reinterpret_cast<const int8x8_t*>(&weights_[offset]);
for (IndexType j = 0; j < kNumChunks; ++j) {
int16x8_t product = vmull_s8(input_vector[j * 2], row[j * 2]);
product = vmlal_s8(product, input_vector[j * 2 + 1], row[j * 2 + 1]);
sum = vpadalq_s16(sum, product);
}
output[i] = sum[0] + sum[1] + sum[2] + sum[3];
#else
OutputType sum = biases_[i];
for (IndexType j = 0; j < kInputDimensions; ++j) {
sum += weights_[offset + j] * input[j];
}
output[i] = sum;
#endif
}
return output;
}
private:
using BiasType = OutputType;
using BiasType = OutputType;
using WeightType = std::int8_t;
alignas(CacheLineSize) BiasType biases[OutputDimensions];
alignas(CacheLineSize) WeightType weights[OutputDimensions * PaddedInputDimensions];
};
PreviousLayer previous_layer_;
} // namespace Stockfish::Eval::NNUE::Layers
alignas(kCacheLineSize) BiasType biases_[kOutputDimensions];
alignas(kCacheLineSize)
WeightType weights_[kOutputDimensions * kPaddedInputDimensions];
};
#endif // #ifndef NNUE_LAYERS_AFFINE_TRANSFORM_H_INCLUDED
} // namespace Eval::NNUE::Layers
#endif // #ifndef NNUE_LAYERS_AFFINE_TRANSFORM_H_INCLUDED

View File

@@ -1,292 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
// Definition of layer AffineTransformSparseInput of NNUE evaluation function
#ifndef NNUE_LAYERS_AFFINE_TRANSFORM_SPARSE_INPUT_H_INCLUDED
#define NNUE_LAYERS_AFFINE_TRANSFORM_SPARSE_INPUT_H_INCLUDED
#include <algorithm>
#include <cstdint>
#include <iostream>
#include "../../bitboard.h"
#include "../simd.h"
#include "../nnue_common.h"
/*
This file contains the definition for a fully connected layer (aka affine transform) with block sparse input.
*/
namespace Stockfish::Eval::NNUE::Layers {
#if (USE_SSSE3 | (USE_NEON >= 8))
static constexpr int lsb_index64[64] = {
0, 47, 1, 56, 48, 27, 2, 60, 57, 49, 41, 37, 28, 16, 3, 61, 54, 58, 35, 52, 50, 42,
21, 44, 38, 32, 29, 23, 17, 11, 4, 62, 46, 55, 26, 59, 40, 36, 15, 53, 34, 51, 20, 43,
31, 22, 10, 45, 25, 39, 14, 33, 19, 30, 9, 24, 13, 18, 8, 12, 7, 6, 5, 63};
constexpr int constexpr_lsb(uint64_t bb) {
assert(bb != 0);
constexpr uint64_t debruijn64 = 0x03F79D71B4CB0A89ULL;
return lsb_index64[((bb ^ (bb - 1)) * debruijn64) >> 58];
}
alignas(CacheLineSize) static constexpr struct OffsetIndices {
std::uint16_t offset_indices[256][8];
constexpr OffsetIndices() :
offset_indices() {
for (int i = 0; i < 256; ++i)
{
std::uint64_t j = i, k = 0;
while (j)
{
offset_indices[i][k++] = constexpr_lsb(j);
j &= j - 1;
}
while (k < 8)
offset_indices[i][k++] = 0;
}
}
} Lookup;
#if defined(__GNUC__) || defined(__clang__)
#define RESTRICT __restrict__
#elif defined(_MSC_VER)
#define RESTRICT __restrict
#else
#define RESTRICT
#endif
// Find indices of nonzero numbers in an int32_t array
template<const IndexType InputDimensions>
void find_nnz(const std::int32_t* RESTRICT input,
std::uint16_t* RESTRICT out,
IndexType& count_out) {
#ifdef USE_AVX512
constexpr IndexType SimdWidth = 16; // 512 bits / 32 bits
constexpr IndexType NumChunks = InputDimensions / SimdWidth;
const __m512i increment = _mm512_set1_epi32(SimdWidth);
__m512i base = _mm512_set_epi32(15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0);
IndexType count = 0;
for (IndexType i = 0; i < NumChunks; ++i)
{
const __m512i inputV = _mm512_load_si512(input + i * SimdWidth);
// Get a bitmask and gather non zero indices
const __mmask16 nnzMask = _mm512_test_epi32_mask(inputV, inputV);
const __m512i nnzV = _mm512_maskz_compress_epi32(nnzMask, base);
_mm512_mask_cvtepi32_storeu_epi16(out + count, 0xFFFF, nnzV);
count += popcount(nnzMask);
base = _mm512_add_epi32(base, increment);
}
count_out = count;
#else
using namespace SIMD;
constexpr IndexType InputSimdWidth = sizeof(vec_uint_t) / sizeof(std::int32_t);
// Inputs are processed InputSimdWidth at a time and outputs are processed 8 at a time so we process in chunks of max(InputSimdWidth, 8)
constexpr IndexType ChunkSize = std::max<IndexType>(InputSimdWidth, 8);
constexpr IndexType NumChunks = InputDimensions / ChunkSize;
constexpr IndexType InputsPerChunk = ChunkSize / InputSimdWidth;
constexpr IndexType OutputsPerChunk = ChunkSize / 8;
const auto inputVector = reinterpret_cast<const vec_uint_t*>(input);
IndexType count = 0;
vec128_t base = vec128_zero;
const vec128_t increment = vec128_set_16(8);
for (IndexType i = 0; i < NumChunks; ++i)
{
// bitmask of nonzero values in this chunk
unsigned nnz = 0;
for (IndexType j = 0; j < InputsPerChunk; ++j)
{
const vec_uint_t inputChunk = inputVector[i * InputsPerChunk + j];
nnz |= unsigned(vec_nnz(inputChunk)) << (j * InputSimdWidth);
}
for (IndexType j = 0; j < OutputsPerChunk; ++j)
{
const unsigned lookup = (nnz >> (j * 8)) & 0xFF;
const vec128_t offsets =
vec128_load(reinterpret_cast<const vec128_t*>(&Lookup.offset_indices[lookup]));
vec128_storeu(reinterpret_cast<vec128_t*>(out + count), vec128_add(base, offsets));
count += popcount(lookup);
base = vec128_add(base, increment);
}
}
count_out = count;
#endif
}
#endif
// Sparse input implementation
template<IndexType InDims, IndexType OutDims>
class AffineTransformSparseInput {
public:
// Input/output type
using InputType = std::uint8_t;
using OutputType = std::int32_t;
// Number of input/output dimensions
static constexpr IndexType InputDimensions = InDims;
static constexpr IndexType OutputDimensions = OutDims;
static_assert(OutputDimensions % 16 == 0,
"Only implemented for OutputDimensions divisible by 16.");
static constexpr IndexType PaddedInputDimensions =
ceil_to_multiple<IndexType>(InputDimensions, MaxSimdWidth);
static constexpr IndexType PaddedOutputDimensions =
ceil_to_multiple<IndexType>(OutputDimensions, MaxSimdWidth);
#if (USE_SSSE3 | (USE_NEON >= 8))
static constexpr IndexType ChunkSize = 4;
#else
static constexpr IndexType ChunkSize = 1;
#endif
using OutputBuffer = OutputType[PaddedOutputDimensions];
// Hash value embedded in the evaluation file
static constexpr std::uint32_t get_hash_value(std::uint32_t prevHash) {
std::uint32_t hashValue = 0xCC03DAE4u;
hashValue += OutputDimensions;
hashValue ^= prevHash >> 1;
hashValue ^= prevHash << 31;
return hashValue;
}
static constexpr IndexType get_weight_index_scrambled(IndexType i) {
return (i / ChunkSize) % (PaddedInputDimensions / ChunkSize) * OutputDimensions * ChunkSize
+ i / PaddedInputDimensions * ChunkSize + i % ChunkSize;
}
static constexpr IndexType get_weight_index(IndexType i) {
#if (USE_SSSE3 | (USE_NEON >= 8))
return get_weight_index_scrambled(i);
#else
return i;
#endif
}
// Read network parameters
bool read_parameters(std::istream& stream) {
read_little_endian<BiasType>(stream, biases, OutputDimensions);
for (IndexType i = 0; i < OutputDimensions * PaddedInputDimensions; ++i)
weights[get_weight_index(i)] = read_little_endian<WeightType>(stream);
return !stream.fail();
}
// Write network parameters
bool write_parameters(std::ostream& stream) const {
write_little_endian<BiasType>(stream, biases, OutputDimensions);
for (IndexType i = 0; i < OutputDimensions * PaddedInputDimensions; ++i)
write_little_endian<WeightType>(stream, weights[get_weight_index(i)]);
return !stream.fail();
}
// Forward propagation
void propagate(const InputType* input, OutputType* output) const {
#if (USE_SSSE3 | (USE_NEON >= 8))
#if defined(USE_AVX512)
using invec_t = __m512i;
using outvec_t = __m512i;
#define vec_set_32 _mm512_set1_epi32
#define vec_add_dpbusd_32 SIMD::m512_add_dpbusd_epi32
#elif defined(USE_AVX2)
using invec_t = __m256i;
using outvec_t = __m256i;
#define vec_set_32 _mm256_set1_epi32
#define vec_add_dpbusd_32 SIMD::m256_add_dpbusd_epi32
#elif defined(USE_SSSE3)
using invec_t = __m128i;
using outvec_t = __m128i;
#define vec_set_32 _mm_set1_epi32
#define vec_add_dpbusd_32 SIMD::m128_add_dpbusd_epi32
#elif defined(USE_NEON_DOTPROD)
using invec_t = int8x16_t;
using outvec_t = int32x4_t;
#define vec_set_32(a) vreinterpretq_s8_u32(vdupq_n_u32(a))
#define vec_add_dpbusd_32 SIMD::dotprod_m128_add_dpbusd_epi32
#elif defined(USE_NEON)
using invec_t = int8x16_t;
using outvec_t = int32x4_t;
#define vec_set_32(a) vreinterpretq_s8_u32(vdupq_n_u32(a))
#define vec_add_dpbusd_32 SIMD::neon_m128_add_dpbusd_epi32
#endif
static constexpr IndexType OutputSimdWidth = sizeof(outvec_t) / sizeof(OutputType);
constexpr IndexType NumChunks = ceil_to_multiple<IndexType>(InputDimensions, 8) / ChunkSize;
constexpr IndexType NumRegs = OutputDimensions / OutputSimdWidth;
std::uint16_t nnz[NumChunks];
IndexType count;
const auto input32 = reinterpret_cast<const std::int32_t*>(input);
// Find indices of nonzero 32-bit blocks
find_nnz<NumChunks>(input32, nnz, count);
const outvec_t* biasvec = reinterpret_cast<const outvec_t*>(biases);
outvec_t acc[NumRegs];
for (IndexType k = 0; k < NumRegs; ++k)
acc[k] = biasvec[k];
for (IndexType j = 0; j < count; ++j)
{
const auto i = nnz[j];
const invec_t in = vec_set_32(input32[i]);
const auto col =
reinterpret_cast<const invec_t*>(&weights[i * OutputDimensions * ChunkSize]);
for (IndexType k = 0; k < NumRegs; ++k)
vec_add_dpbusd_32(acc[k], in, col[k]);
}
outvec_t* outptr = reinterpret_cast<outvec_t*>(output);
for (IndexType k = 0; k < NumRegs; ++k)
outptr[k] = acc[k];
#undef vec_set_32
#undef vec_add_dpbusd_32
#else
// Use dense implementation for the other architectures.
affine_transform_non_ssse3<InputDimensions, PaddedInputDimensions, OutputDimensions>(
output, weights, biases, input);
#endif
}
private:
using BiasType = OutputType;
using WeightType = std::int8_t;
alignas(CacheLineSize) BiasType biases[OutputDimensions];
alignas(CacheLineSize) WeightType weights[OutputDimensions * PaddedInputDimensions];
};
} // namespace Stockfish::Eval::NNUE::Layers
#endif // #ifndef NNUE_LAYERS_AFFINE_TRANSFORM_SPARSE_INPUT_H_INCLUDED

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -21,144 +21,166 @@
#ifndef NNUE_LAYERS_CLIPPED_RELU_H_INCLUDED
#define NNUE_LAYERS_CLIPPED_RELU_H_INCLUDED
#include <algorithm>
#include <cstdint>
#include <iosfwd>
#include "../nnue_common.h"
namespace Stockfish::Eval::NNUE::Layers {
namespace Eval::NNUE::Layers {
// Clipped ReLU
template<IndexType InDims>
class ClippedReLU {
// Clipped ReLU
template <typename PreviousLayer>
class ClippedReLU {
public:
// Input/output type
using InputType = std::int32_t;
using InputType = typename PreviousLayer::OutputType;
using OutputType = std::uint8_t;
static_assert(std::is_same<InputType, std::int32_t>::value, "");
// Number of input/output dimensions
static constexpr IndexType InputDimensions = InDims;
static constexpr IndexType OutputDimensions = InputDimensions;
static constexpr IndexType PaddedOutputDimensions =
ceil_to_multiple<IndexType>(OutputDimensions, 32);
static constexpr IndexType kInputDimensions =
PreviousLayer::kOutputDimensions;
static constexpr IndexType kOutputDimensions = kInputDimensions;
using OutputBuffer = OutputType[PaddedOutputDimensions];
// Size of forward propagation buffer used in this layer
static constexpr std::size_t kSelfBufferSize =
CeilToMultiple(kOutputDimensions * sizeof(OutputType), kCacheLineSize);
// Size of the forward propagation buffer used from the input layer to this layer
static constexpr std::size_t kBufferSize =
PreviousLayer::kBufferSize + kSelfBufferSize;
// Hash value embedded in the evaluation file
static constexpr std::uint32_t get_hash_value(std::uint32_t prevHash) {
std::uint32_t hashValue = 0x538D24C7u;
hashValue += prevHash;
return hashValue;
static constexpr std::uint32_t GetHashValue() {
std::uint32_t hash_value = 0x538D24C7u;
hash_value += PreviousLayer::GetHashValue();
return hash_value;
}
// Read network parameters
bool read_parameters(std::istream&) { return true; }
// Write network parameters
bool write_parameters(std::ostream&) const { return true; }
bool ReadParameters(std::istream& stream) {
return previous_layer_.ReadParameters(stream);
}
// Forward propagation
void propagate(const InputType* input, OutputType* output) const {
const OutputType* Propagate(
const TransformedFeatureType* transformed_features, char* buffer) const {
const auto input = previous_layer_.Propagate(
transformed_features, buffer + kSelfBufferSize);
const auto output = reinterpret_cast<OutputType*>(buffer);
#if defined(USE_AVX2)
if constexpr (InputDimensions % SimdWidth == 0)
{
constexpr IndexType NumChunks = InputDimensions / SimdWidth;
const __m256i Offsets = _mm256_set_epi32(7, 3, 6, 2, 5, 1, 4, 0);
const auto in = reinterpret_cast<const __m256i*>(input);
const auto out = reinterpret_cast<__m256i*>(output);
for (IndexType i = 0; i < NumChunks; ++i)
{
const __m256i words0 =
_mm256_srli_epi16(_mm256_packus_epi32(_mm256_load_si256(&in[i * 4 + 0]),
_mm256_load_si256(&in[i * 4 + 1])),
WeightScaleBits);
const __m256i words1 =
_mm256_srli_epi16(_mm256_packus_epi32(_mm256_load_si256(&in[i * 4 + 2]),
_mm256_load_si256(&in[i * 4 + 3])),
WeightScaleBits);
_mm256_store_si256(&out[i], _mm256_permutevar8x32_epi32(
_mm256_packs_epi16(words0, words1), Offsets));
}
}
else
{
constexpr IndexType NumChunks = InputDimensions / (SimdWidth / 2);
const auto in = reinterpret_cast<const __m128i*>(input);
const auto out = reinterpret_cast<__m128i*>(output);
for (IndexType i = 0; i < NumChunks; ++i)
{
const __m128i words0 = _mm_srli_epi16(
_mm_packus_epi32(_mm_load_si128(&in[i * 4 + 0]), _mm_load_si128(&in[i * 4 + 1])),
WeightScaleBits);
const __m128i words1 = _mm_srli_epi16(
_mm_packus_epi32(_mm_load_si128(&in[i * 4 + 2]), _mm_load_si128(&in[i * 4 + 3])),
WeightScaleBits);
_mm_store_si128(&out[i], _mm_packs_epi16(words0, words1));
}
}
constexpr IndexType Start = InputDimensions % SimdWidth == 0
? InputDimensions / SimdWidth * SimdWidth
: InputDimensions / (SimdWidth / 2) * (SimdWidth / 2);
#if defined(USE_AVX2)
constexpr IndexType kNumChunks = kInputDimensions / kSimdWidth;
const __m256i kZero = _mm256_setzero_si256();
const __m256i kOffsets = _mm256_set_epi32(7, 3, 6, 2, 5, 1, 4, 0);
const auto in = reinterpret_cast<const __m256i*>(input);
const auto out = reinterpret_cast<__m256i*>(output);
for (IndexType i = 0; i < kNumChunks; ++i) {
const __m256i words0 = _mm256_srai_epi16(_mm256_packs_epi32(
#elif defined(USE_SSE2)
constexpr IndexType NumChunks = InputDimensions / SimdWidth;
#if defined(__MINGW32__) || defined(__MINGW64__)
// HACK: Use _mm256_loadu_si256() instead of _mm256_load_si256. Because the binary
// compiled with g++ in MSYS2 crashes here because the output memory is not aligned
// even though alignas is specified.
_mm256_loadu_si256
#else
_mm256_load_si256
#endif
#ifndef USE_SSE41
const __m128i k0x80s = _mm_set1_epi8(-128);
#endif
(&in[i * 4 + 0]),
const auto in = reinterpret_cast<const __m128i*>(input);
const auto out = reinterpret_cast<__m128i*>(output);
for (IndexType i = 0; i < NumChunks; ++i)
{
#if defined(USE_SSE41)
const __m128i words0 = _mm_srli_epi16(
_mm_packus_epi32(_mm_load_si128(&in[i * 4 + 0]), _mm_load_si128(&in[i * 4 + 1])),
WeightScaleBits);
const __m128i words1 = _mm_srli_epi16(
_mm_packus_epi32(_mm_load_si128(&in[i * 4 + 2]), _mm_load_si128(&in[i * 4 + 3])),
WeightScaleBits);
_mm_store_si128(&out[i], _mm_packs_epi16(words0, words1));
#else
const __m128i words0 = _mm_srai_epi16(
_mm_packs_epi32(_mm_load_si128(&in[i * 4 + 0]), _mm_load_si128(&in[i * 4 + 1])),
WeightScaleBits);
const __m128i words1 = _mm_srai_epi16(
_mm_packs_epi32(_mm_load_si128(&in[i * 4 + 2]), _mm_load_si128(&in[i * 4 + 3])),
WeightScaleBits);
const __m128i packedbytes = _mm_packs_epi16(words0, words1);
_mm_store_si128(&out[i], _mm_subs_epi8(_mm_adds_epi8(packedbytes, k0x80s), k0x80s));
#endif
}
constexpr IndexType Start = NumChunks * SimdWidth;
#if defined(__MINGW32__) || defined(__MINGW64__)
_mm256_loadu_si256
#else
_mm256_load_si256
#endif
#elif defined(USE_NEON)
constexpr IndexType NumChunks = InputDimensions / (SimdWidth / 2);
const int8x8_t Zero = {0};
const auto in = reinterpret_cast<const int32x4_t*>(input);
const auto out = reinterpret_cast<int8x8_t*>(output);
for (IndexType i = 0; i < NumChunks; ++i)
{
int16x8_t shifted;
const auto pack = reinterpret_cast<int16x4_t*>(&shifted);
pack[0] = vqshrn_n_s32(in[i * 2 + 0], WeightScaleBits);
pack[1] = vqshrn_n_s32(in[i * 2 + 1], WeightScaleBits);
out[i] = vmax_s8(vqmovn_s16(shifted), Zero);
}
constexpr IndexType Start = NumChunks * (SimdWidth / 2);
#else
constexpr IndexType Start = 0;
#endif
(&in[i * 4 + 1])), kWeightScaleBits);
const __m256i words1 = _mm256_srai_epi16(_mm256_packs_epi32(
for (IndexType i = Start; i < InputDimensions; ++i)
{
output[i] = static_cast<OutputType>(std::clamp(input[i] >> WeightScaleBits, 0, 127));
}
#if defined(__MINGW32__) || defined(__MINGW64__)
_mm256_loadu_si256
#else
_mm256_load_si256
#endif
(&in[i * 4 + 2]),
#if defined(__MINGW32__) || defined(__MINGW64__)
_mm256_loadu_si256
#else
_mm256_load_si256
#endif
(&in[i * 4 + 3])), kWeightScaleBits);
#if defined(__MINGW32__) || defined(__MINGW64__)
_mm256_storeu_si256
#else
_mm256_store_si256
#endif
(&out[i], _mm256_permutevar8x32_epi32(_mm256_max_epi8(
_mm256_packs_epi16(words0, words1), kZero), kOffsets));
}
constexpr IndexType kStart = kNumChunks * kSimdWidth;
#elif defined(USE_SSSE3)
constexpr IndexType kNumChunks = kInputDimensions / kSimdWidth;
#ifdef USE_SSE41
const __m128i kZero = _mm_setzero_si128();
#else
const __m128i k0x80s = _mm_set1_epi8(-128);
#endif
const auto in = reinterpret_cast<const __m128i*>(input);
const auto out = reinterpret_cast<__m128i*>(output);
for (IndexType i = 0; i < kNumChunks; ++i) {
const __m128i words0 = _mm_srai_epi16(_mm_packs_epi32(
_mm_load_si128(&in[i * 4 + 0]),
_mm_load_si128(&in[i * 4 + 1])), kWeightScaleBits);
const __m128i words1 = _mm_srai_epi16(_mm_packs_epi32(
_mm_load_si128(&in[i * 4 + 2]),
_mm_load_si128(&in[i * 4 + 3])), kWeightScaleBits);
const __m128i packedbytes = _mm_packs_epi16(words0, words1);
_mm_store_si128(&out[i],
#ifdef USE_SSE41
_mm_max_epi8(packedbytes, kZero)
#else
_mm_subs_epi8(_mm_adds_epi8(packedbytes, k0x80s), k0x80s)
#endif
);
}
constexpr IndexType kStart = kNumChunks * kSimdWidth;
#elif defined(USE_NEON)
constexpr IndexType kNumChunks = kInputDimensions / (kSimdWidth / 2);
const int8x8_t kZero = {0};
const auto in = reinterpret_cast<const int32x4_t*>(input);
const auto out = reinterpret_cast<int8x8_t*>(output);
for (IndexType i = 0; i < kNumChunks; ++i) {
int16x8_t shifted;
const auto pack = reinterpret_cast<int16x4_t*>(&shifted);
pack[0] = vqshrn_n_s32(in[i * 2 + 0], kWeightScaleBits);
pack[1] = vqshrn_n_s32(in[i * 2 + 1], kWeightScaleBits);
out[i] = vmax_s8(vqmovn_s16(shifted), kZero);
}
constexpr IndexType kStart = kNumChunks * (kSimdWidth / 2);
#else
constexpr IndexType kStart = 0;
#endif
for (IndexType i = kStart; i < kInputDimensions; ++i) {
output[i] = static_cast<OutputType>(
std::max(0, std::min(127, input[i] >> kWeightScaleBits)));
}
return output;
}
};
} // namespace Stockfish::Eval::NNUE::Layers
private:
PreviousLayer previous_layer_;
};
#endif // NNUE_LAYERS_CLIPPED_RELU_H_INCLUDED
} // namespace Eval::NNUE::Layers
#endif // NNUE_LAYERS_CLIPPED_RELU_H_INCLUDED

View File

@@ -0,0 +1,68 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
// NNUE evaluation function layer InputSlice definition
#ifndef NNUE_LAYERS_INPUT_SLICE_H_INCLUDED
#define NNUE_LAYERS_INPUT_SLICE_H_INCLUDED
#include "../nnue_common.h"
namespace Eval::NNUE::Layers {
// Input layer
template <IndexType OutputDimensions, IndexType Offset = 0>
class InputSlice {
public:
// Need to maintain alignment
static_assert(Offset % kMaxSimdWidth == 0, "");
// Output type
using OutputType = TransformedFeatureType;
// Output dimensionality
static constexpr IndexType kOutputDimensions = OutputDimensions;
// Size of forward propagation buffer used from the input layer to this layer
static constexpr std::size_t kBufferSize = 0;
// Hash value embedded in the evaluation file
static constexpr std::uint32_t GetHashValue() {
std::uint32_t hash_value = 0xEC42E90Du;
hash_value ^= kOutputDimensions ^ (Offset << 10);
return hash_value;
}
// Read network parameters
bool ReadParameters(std::istream& /*stream*/) {
return true;
}
// Forward propagation
const OutputType* Propagate(
const TransformedFeatureType* transformed_features,
char* /*buffer*/) const {
return transformed_features + Offset;
}
private:
};
} // namespace Layers
#endif // #ifndef NNUE_LAYERS_INPUT_SLICE_H_INCLUDED

View File

@@ -1,103 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
// Definition of layer ClippedReLU of NNUE evaluation function
#ifndef NNUE_LAYERS_SQR_CLIPPED_RELU_H_INCLUDED
#define NNUE_LAYERS_SQR_CLIPPED_RELU_H_INCLUDED
#include <algorithm>
#include <cstdint>
#include <iosfwd>
#include "../nnue_common.h"
namespace Stockfish::Eval::NNUE::Layers {
// Clipped ReLU
template<IndexType InDims>
class SqrClippedReLU {
public:
// Input/output type
using InputType = std::int32_t;
using OutputType = std::uint8_t;
// Number of input/output dimensions
static constexpr IndexType InputDimensions = InDims;
static constexpr IndexType OutputDimensions = InputDimensions;
static constexpr IndexType PaddedOutputDimensions =
ceil_to_multiple<IndexType>(OutputDimensions, 32);
using OutputBuffer = OutputType[PaddedOutputDimensions];
// Hash value embedded in the evaluation file
static constexpr std::uint32_t get_hash_value(std::uint32_t prevHash) {
std::uint32_t hashValue = 0x538D24C7u;
hashValue += prevHash;
return hashValue;
}
// Read network parameters
bool read_parameters(std::istream&) { return true; }
// Write network parameters
bool write_parameters(std::ostream&) const { return true; }
// Forward propagation
void propagate(const InputType* input, OutputType* output) const {
#if defined(USE_SSE2)
constexpr IndexType NumChunks = InputDimensions / 16;
static_assert(WeightScaleBits == 6);
const auto in = reinterpret_cast<const __m128i*>(input);
const auto out = reinterpret_cast<__m128i*>(output);
for (IndexType i = 0; i < NumChunks; ++i)
{
__m128i words0 =
_mm_packs_epi32(_mm_load_si128(&in[i * 4 + 0]), _mm_load_si128(&in[i * 4 + 1]));
__m128i words1 =
_mm_packs_epi32(_mm_load_si128(&in[i * 4 + 2]), _mm_load_si128(&in[i * 4 + 3]));
// We shift by WeightScaleBits * 2 = 12 and divide by 128
// which is an additional shift-right of 7, meaning 19 in total.
// MulHi strips the lower 16 bits so we need to shift out 3 more to match.
words0 = _mm_srli_epi16(_mm_mulhi_epi16(words0, words0), 3);
words1 = _mm_srli_epi16(_mm_mulhi_epi16(words1, words1), 3);
_mm_store_si128(&out[i], _mm_packs_epi16(words0, words1));
}
constexpr IndexType Start = NumChunks * 16;
#else
constexpr IndexType Start = 0;
#endif
for (IndexType i = Start; i < InputDimensions; ++i)
{
output[i] = static_cast<OutputType>(
// Really should be /127 but we need to make it fast so we right-shift
// by an extra 7 bits instead. Needs to be accounted for in the trainer.
std::min(127ll, ((long long) (input[i]) * input[i]) >> (2 * WeightScaleBits + 7)));
}
}
};
} // namespace Stockfish::Eval::NNUE::Layers
#endif // NNUE_LAYERS_SQR_CLIPPED_RELU_H_INCLUDED

View File

@@ -1,442 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include "network.h"
#include <cstdlib>
#include <fstream>
#include <iostream>
#include <memory>
#include <optional>
#include <type_traits>
#include <vector>
#define INCBIN_SILENCE_BITCODE_WARNING
#include "../incbin/incbin.h"
#include "../evaluate.h"
#include "../memory.h"
#include "../misc.h"
#include "../position.h"
#include "../types.h"
#include "nnue_architecture.h"
#include "nnue_common.h"
#include "nnue_misc.h"
// Macro to embed the default efficiently updatable neural network (NNUE) file
// data in the engine binary (using incbin.h, by Dale Weiler).
// This macro invocation will declare the following three variables
// const unsigned char gEmbeddedNNUEData[]; // a pointer to the embedded data
// const unsigned char *const gEmbeddedNNUEEnd; // a marker to the end
// const unsigned int gEmbeddedNNUESize; // the size of the embedded file
// Note that this does not work in Microsoft Visual Studio.
#if !defined(_MSC_VER) && !defined(NNUE_EMBEDDING_OFF)
INCBIN(EmbeddedNNUEBig, EvalFileDefaultNameBig);
INCBIN(EmbeddedNNUESmall, EvalFileDefaultNameSmall);
#else
const unsigned char gEmbeddedNNUEBigData[1] = {0x0};
const unsigned char* const gEmbeddedNNUEBigEnd = &gEmbeddedNNUEBigData[1];
const unsigned int gEmbeddedNNUEBigSize = 1;
const unsigned char gEmbeddedNNUESmallData[1] = {0x0};
const unsigned char* const gEmbeddedNNUESmallEnd = &gEmbeddedNNUESmallData[1];
const unsigned int gEmbeddedNNUESmallSize = 1;
#endif
namespace {
struct EmbeddedNNUE {
EmbeddedNNUE(const unsigned char* embeddedData,
const unsigned char* embeddedEnd,
const unsigned int embeddedSize) :
data(embeddedData),
end(embeddedEnd),
size(embeddedSize) {}
const unsigned char* data;
const unsigned char* end;
const unsigned int size;
};
using namespace Stockfish::Eval::NNUE;
EmbeddedNNUE get_embedded(EmbeddedNNUEType type) {
if (type == EmbeddedNNUEType::BIG)
return EmbeddedNNUE(gEmbeddedNNUEBigData, gEmbeddedNNUEBigEnd, gEmbeddedNNUEBigSize);
else
return EmbeddedNNUE(gEmbeddedNNUESmallData, gEmbeddedNNUESmallEnd, gEmbeddedNNUESmallSize);
}
}
namespace Stockfish::Eval::NNUE {
namespace Detail {
// Read evaluation function parameters
template<typename T>
bool read_parameters(std::istream& stream, T& reference) {
std::uint32_t header;
header = read_little_endian<std::uint32_t>(stream);
if (!stream || header != T::get_hash_value())
return false;
return reference.read_parameters(stream);
}
// Write evaluation function parameters
template<typename T>
bool write_parameters(std::ostream& stream, T& reference) {
write_little_endian<std::uint32_t>(stream, T::get_hash_value());
return reference.write_parameters(stream);
}
} // namespace Detail
template<typename Arch, typename Transformer>
Network<Arch, Transformer>::Network(const Network<Arch, Transformer>& other) :
evalFile(other.evalFile),
embeddedType(other.embeddedType) {
if (other.featureTransformer)
featureTransformer = make_unique_large_page<Transformer>(*other.featureTransformer);
network = make_unique_aligned<Arch[]>(LayerStacks);
if (!other.network)
return;
for (std::size_t i = 0; i < LayerStacks; ++i)
network[i] = other.network[i];
}
template<typename Arch, typename Transformer>
Network<Arch, Transformer>&
Network<Arch, Transformer>::operator=(const Network<Arch, Transformer>& other) {
evalFile = other.evalFile;
embeddedType = other.embeddedType;
if (other.featureTransformer)
featureTransformer = make_unique_large_page<Transformer>(*other.featureTransformer);
network = make_unique_aligned<Arch[]>(LayerStacks);
if (!other.network)
return *this;
for (std::size_t i = 0; i < LayerStacks; ++i)
network[i] = other.network[i];
return *this;
}
template<typename Arch, typename Transformer>
void Network<Arch, Transformer>::load(const std::string& rootDirectory, std::string evalfilePath) {
#if defined(DEFAULT_NNUE_DIRECTORY)
std::vector<std::string> dirs = {"<internal>", "", rootDirectory,
stringify(DEFAULT_NNUE_DIRECTORY)};
#else
std::vector<std::string> dirs = {"<internal>", "", rootDirectory};
#endif
if (evalfilePath.empty())
evalfilePath = evalFile.defaultName;
for (const auto& directory : dirs)
{
if (evalFile.current != evalfilePath)
{
if (directory != "<internal>")
{
load_user_net(directory, evalfilePath);
}
if (directory == "<internal>" && evalfilePath == evalFile.defaultName)
{
load_internal();
}
}
}
}
template<typename Arch, typename Transformer>
bool Network<Arch, Transformer>::save(const std::optional<std::string>& filename) const {
std::string actualFilename;
std::string msg;
if (filename.has_value())
actualFilename = filename.value();
else
{
if (evalFile.current != evalFile.defaultName)
{
msg = "Failed to export a net. "
"A non-embedded net can only be saved if the filename is specified";
sync_cout << msg << sync_endl;
return false;
}
actualFilename = evalFile.defaultName;
}
std::ofstream stream(actualFilename, std::ios_base::binary);
bool saved = save(stream, evalFile.current, evalFile.netDescription);
msg = saved ? "Network saved successfully to " + actualFilename : "Failed to export a net";
sync_cout << msg << sync_endl;
return saved;
}
template<typename Arch, typename Transformer>
NetworkOutput
Network<Arch, Transformer>::evaluate(const Position& pos,
AccumulatorStack& accumulatorStack,
AccumulatorCaches::Cache<FTDimensions>* cache) const {
constexpr uint64_t alignment = CacheLineSize;
alignas(alignment)
TransformedFeatureType transformedFeatures[FeatureTransformer<FTDimensions>::BufferSize];
ASSERT_ALIGNED(transformedFeatures, alignment);
const int bucket = (pos.count<ALL_PIECES>() - 1) / 4;
const auto psqt =
featureTransformer->transform(pos, accumulatorStack, cache, transformedFeatures, bucket);
const auto positional = network[bucket].propagate(transformedFeatures);
return {static_cast<Value>(psqt / OutputScale), static_cast<Value>(positional / OutputScale)};
}
template<typename Arch, typename Transformer>
void Network<Arch, Transformer>::verify(std::string evalfilePath,
const std::function<void(std::string_view)>& f) const {
if (evalfilePath.empty())
evalfilePath = evalFile.defaultName;
if (evalFile.current != evalfilePath)
{
if (f)
{
std::string msg1 =
"Network evaluation parameters compatible with the engine must be available.";
std::string msg2 = "The network file " + evalfilePath + " was not loaded successfully.";
std::string msg3 = "The UCI option EvalFile might need to specify the full path, "
"including the directory name, to the network file.";
std::string msg4 = "The default net can be downloaded from: "
"https://tests.stockfishchess.org/api/nn/"
+ evalFile.defaultName;
std::string msg5 = "The engine will be terminated now.";
std::string msg = "ERROR: " + msg1 + '\n' + "ERROR: " + msg2 + '\n' + "ERROR: " + msg3
+ '\n' + "ERROR: " + msg4 + '\n' + "ERROR: " + msg5 + '\n';
f(msg);
}
exit(EXIT_FAILURE);
}
if (f)
{
size_t size = sizeof(*featureTransformer) + sizeof(Arch) * LayerStacks;
f("NNUE evaluation using " + evalfilePath + " (" + std::to_string(size / (1024 * 1024))
+ "MiB, (" + std::to_string(featureTransformer->InputDimensions) + ", "
+ std::to_string(network[0].TransformedFeatureDimensions) + ", "
+ std::to_string(network[0].FC_0_OUTPUTS) + ", " + std::to_string(network[0].FC_1_OUTPUTS)
+ ", 1))");
}
}
template<typename Arch, typename Transformer>
NnueEvalTrace
Network<Arch, Transformer>::trace_evaluate(const Position& pos,
AccumulatorStack& accumulatorStack,
AccumulatorCaches::Cache<FTDimensions>* cache) const {
constexpr uint64_t alignment = CacheLineSize;
alignas(alignment)
TransformedFeatureType transformedFeatures[FeatureTransformer<FTDimensions>::BufferSize];
ASSERT_ALIGNED(transformedFeatures, alignment);
NnueEvalTrace t{};
t.correctBucket = (pos.count<ALL_PIECES>() - 1) / 4;
for (IndexType bucket = 0; bucket < LayerStacks; ++bucket)
{
const auto materialist =
featureTransformer->transform(pos, accumulatorStack, cache, transformedFeatures, bucket);
const auto positional = network[bucket].propagate(transformedFeatures);
t.psqt[bucket] = static_cast<Value>(materialist / OutputScale);
t.positional[bucket] = static_cast<Value>(positional / OutputScale);
}
return t;
}
template<typename Arch, typename Transformer>
void Network<Arch, Transformer>::load_user_net(const std::string& dir,
const std::string& evalfilePath) {
std::ifstream stream(dir + evalfilePath, std::ios::binary);
auto description = load(stream);
if (description.has_value())
{
evalFile.current = evalfilePath;
evalFile.netDescription = description.value();
}
}
template<typename Arch, typename Transformer>
void Network<Arch, Transformer>::load_internal() {
// C++ way to prepare a buffer for a memory stream
class MemoryBuffer: public std::basic_streambuf<char> {
public:
MemoryBuffer(char* p, size_t n) {
setg(p, p, p + n);
setp(p, p + n);
}
};
const auto embedded = get_embedded(embeddedType);
MemoryBuffer buffer(const_cast<char*>(reinterpret_cast<const char*>(embedded.data)),
size_t(embedded.size));
std::istream stream(&buffer);
auto description = load(stream);
if (description.has_value())
{
evalFile.current = evalFile.defaultName;
evalFile.netDescription = description.value();
}
}
template<typename Arch, typename Transformer>
void Network<Arch, Transformer>::initialize() {
featureTransformer = make_unique_large_page<Transformer>();
network = make_unique_aligned<Arch[]>(LayerStacks);
}
template<typename Arch, typename Transformer>
bool Network<Arch, Transformer>::save(std::ostream& stream,
const std::string& name,
const std::string& netDescription) const {
if (name.empty() || name == "None")
return false;
return write_parameters(stream, netDescription);
}
template<typename Arch, typename Transformer>
std::optional<std::string> Network<Arch, Transformer>::load(std::istream& stream) {
initialize();
std::string description;
return read_parameters(stream, description) ? std::make_optional(description) : std::nullopt;
}
// Read network header
template<typename Arch, typename Transformer>
bool Network<Arch, Transformer>::read_header(std::istream& stream,
std::uint32_t* hashValue,
std::string* desc) const {
std::uint32_t version, size;
version = read_little_endian<std::uint32_t>(stream);
*hashValue = read_little_endian<std::uint32_t>(stream);
size = read_little_endian<std::uint32_t>(stream);
if (!stream || version != Version)
return false;
desc->resize(size);
stream.read(&(*desc)[0], size);
return !stream.fail();
}
// Write network header
template<typename Arch, typename Transformer>
bool Network<Arch, Transformer>::write_header(std::ostream& stream,
std::uint32_t hashValue,
const std::string& desc) const {
write_little_endian<std::uint32_t>(stream, Version);
write_little_endian<std::uint32_t>(stream, hashValue);
write_little_endian<std::uint32_t>(stream, std::uint32_t(desc.size()));
stream.write(&desc[0], desc.size());
return !stream.fail();
}
template<typename Arch, typename Transformer>
bool Network<Arch, Transformer>::read_parameters(std::istream& stream,
std::string& netDescription) const {
std::uint32_t hashValue;
if (!read_header(stream, &hashValue, &netDescription))
return false;
if (hashValue != Network::hash)
return false;
if (!Detail::read_parameters(stream, *featureTransformer))
return false;
for (std::size_t i = 0; i < LayerStacks; ++i)
{
if (!Detail::read_parameters(stream, network[i]))
return false;
}
return stream && stream.peek() == std::ios::traits_type::eof();
}
template<typename Arch, typename Transformer>
bool Network<Arch, Transformer>::write_parameters(std::ostream& stream,
const std::string& netDescription) const {
if (!write_header(stream, Network::hash, netDescription))
return false;
if (!Detail::write_parameters(stream, *featureTransformer))
return false;
for (std::size_t i = 0; i < LayerStacks; ++i)
{
if (!Detail::write_parameters(stream, network[i]))
return false;
}
return bool(stream);
}
// Explicit template instantiations
template class Network<NetworkArchitecture<TransformedFeatureDimensionsBig, L2Big, L3Big>,
FeatureTransformer<TransformedFeatureDimensionsBig>>;
template class Network<NetworkArchitecture<TransformedFeatureDimensionsSmall, L2Small, L3Small>,
FeatureTransformer<TransformedFeatureDimensionsSmall>>;
} // namespace Stockfish::Eval::NNUE

View File

@@ -1,137 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef NETWORK_H_INCLUDED
#define NETWORK_H_INCLUDED
#include <cstdint>
#include <functional>
#include <iostream>
#include <optional>
#include <string>
#include <string_view>
#include <tuple>
#include <utility>
#include "../memory.h"
#include "../types.h"
#include "nnue_accumulator.h"
#include "nnue_architecture.h"
#include "nnue_common.h"
#include "nnue_feature_transformer.h"
#include "nnue_misc.h"
namespace Stockfish {
class Position;
}
namespace Stockfish::Eval::NNUE {
enum class EmbeddedNNUEType {
BIG,
SMALL,
};
using NetworkOutput = std::tuple<Value, Value>;
template<typename Arch, typename Transformer>
class Network {
static constexpr IndexType FTDimensions = Arch::TransformedFeatureDimensions;
public:
Network(EvalFile file, EmbeddedNNUEType type) :
evalFile(file),
embeddedType(type) {}
Network(const Network& other);
Network(Network&& other) = default;
Network& operator=(const Network& other);
Network& operator=(Network&& other) = default;
void load(const std::string& rootDirectory, std::string evalfilePath);
bool save(const std::optional<std::string>& filename) const;
NetworkOutput evaluate(const Position& pos,
AccumulatorStack& accumulatorStack,
AccumulatorCaches::Cache<FTDimensions>* cache) const;
void verify(std::string evalfilePath, const std::function<void(std::string_view)>&) const;
NnueEvalTrace trace_evaluate(const Position& pos,
AccumulatorStack& accumulatorStack,
AccumulatorCaches::Cache<FTDimensions>* cache) const;
private:
void load_user_net(const std::string&, const std::string&);
void load_internal();
void initialize();
bool save(std::ostream&, const std::string&, const std::string&) const;
std::optional<std::string> load(std::istream&);
bool read_header(std::istream&, std::uint32_t*, std::string*) const;
bool write_header(std::ostream&, std::uint32_t, const std::string&) const;
bool read_parameters(std::istream&, std::string&) const;
bool write_parameters(std::ostream&, const std::string&) const;
// Input feature converter
LargePagePtr<Transformer> featureTransformer;
// Evaluation function
AlignedPtr<Arch[]> network;
EvalFile evalFile;
EmbeddedNNUEType embeddedType;
// Hash value of evaluation function structure
static constexpr std::uint32_t hash = Transformer::get_hash_value() ^ Arch::get_hash_value();
template<IndexType Size>
friend struct AccumulatorCaches::Cache;
friend class AccumulatorStack;
};
// Definitions of the network types
using SmallFeatureTransformer = FeatureTransformer<TransformedFeatureDimensionsSmall>;
using SmallNetworkArchitecture =
NetworkArchitecture<TransformedFeatureDimensionsSmall, L2Small, L3Small>;
using BigFeatureTransformer = FeatureTransformer<TransformedFeatureDimensionsBig>;
using BigNetworkArchitecture = NetworkArchitecture<TransformedFeatureDimensionsBig, L2Big, L3Big>;
using NetworkBig = Network<BigNetworkArchitecture, BigFeatureTransformer>;
using NetworkSmall = Network<SmallNetworkArchitecture, SmallFeatureTransformer>;
struct Networks {
Networks(NetworkBig&& nB, NetworkSmall&& nS) :
big(std::move(nB)),
small(std::move(nS)) {}
NetworkBig big;
NetworkSmall small;
};
} // namespace Stockfish
#endif

View File

@@ -1,531 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include "nnue_accumulator.h"
#include <cassert>
#include <cstdint>
#include <initializer_list>
#include <type_traits>
#include "../bitboard.h"
#include "../misc.h"
#include "../position.h"
#include "../types.h"
#include "nnue_architecture.h"
#include "nnue_feature_transformer.h" // IWYU pragma: keep
#include "simd.h"
namespace Stockfish::Eval::NNUE {
using namespace SIMD;
namespace {
template<Color Perspective, IndexType TransformedFeatureDimensions>
void double_inc_update(const FeatureTransformer<TransformedFeatureDimensions>& featureTransformer,
const Square ksq,
AccumulatorState& middle_state,
AccumulatorState& target_state,
const AccumulatorState& computed);
template<Color Perspective, bool Forward, IndexType TransformedFeatureDimensions>
void update_accumulator_incremental(
const FeatureTransformer<TransformedFeatureDimensions>& featureTransformer,
const Square ksq,
AccumulatorState& target_state,
const AccumulatorState& computed);
template<Color Perspective, IndexType Dimensions>
void update_accumulator_refresh_cache(const FeatureTransformer<Dimensions>& featureTransformer,
const Position& pos,
AccumulatorState& accumulatorState,
AccumulatorCaches::Cache<Dimensions>& cache);
}
void AccumulatorState::reset(const DirtyPiece& dp) noexcept {
dirtyPiece = dp;
accumulatorBig.computed.fill(false);
accumulatorSmall.computed.fill(false);
}
const AccumulatorState& AccumulatorStack::latest() const noexcept { return accumulators[size - 1]; }
AccumulatorState& AccumulatorStack::mut_latest() noexcept { return accumulators[size - 1]; }
void AccumulatorStack::reset() noexcept {
accumulators[0].reset({});
size = 1;
}
void AccumulatorStack::push(const DirtyPiece& dirtyPiece) noexcept {
assert(size + 1 < accumulators.size());
accumulators[size].reset(dirtyPiece);
size++;
}
void AccumulatorStack::pop() noexcept {
assert(size > 1);
size--;
}
template<IndexType Dimensions>
void AccumulatorStack::evaluate(const Position& pos,
const FeatureTransformer<Dimensions>& featureTransformer,
AccumulatorCaches::Cache<Dimensions>& cache) noexcept {
evaluate_side<WHITE>(pos, featureTransformer, cache);
evaluate_side<BLACK>(pos, featureTransformer, cache);
}
template<Color Perspective, IndexType Dimensions>
void AccumulatorStack::evaluate_side(const Position& pos,
const FeatureTransformer<Dimensions>& featureTransformer,
AccumulatorCaches::Cache<Dimensions>& cache) noexcept {
const auto last_usable_accum = find_last_usable_accumulator<Perspective, Dimensions>();
if ((accumulators[last_usable_accum].template acc<Dimensions>()).computed[Perspective])
forward_update_incremental<Perspective>(pos, featureTransformer, last_usable_accum);
else
{
update_accumulator_refresh_cache<Perspective>(featureTransformer, pos, mut_latest(), cache);
backward_update_incremental<Perspective>(pos, featureTransformer, last_usable_accum);
}
}
// Find the earliest usable accumulator, this can either be a computed accumulator or the accumulator
// state just before a change that requires full refresh.
template<Color Perspective, IndexType Dimensions>
std::size_t AccumulatorStack::find_last_usable_accumulator() const noexcept {
for (std::size_t curr_idx = size - 1; curr_idx > 0; curr_idx--)
{
if ((accumulators[curr_idx].template acc<Dimensions>()).computed[Perspective])
return curr_idx;
if (FeatureSet::requires_refresh(accumulators[curr_idx].dirtyPiece, Perspective))
return curr_idx;
}
return 0;
}
template<Color Perspective, IndexType Dimensions>
void AccumulatorStack::forward_update_incremental(
const Position& pos,
const FeatureTransformer<Dimensions>& featureTransformer,
const std::size_t begin) noexcept {
assert(begin < accumulators.size());
assert((accumulators[begin].acc<Dimensions>()).computed[Perspective]);
const Square ksq = pos.square<KING>(Perspective);
for (std::size_t next = begin + 1; next < size; next++)
{
if (next + 1 < size)
{
DirtyPiece& dp1 = accumulators[next].dirtyPiece;
DirtyPiece& dp2 = accumulators[next + 1].dirtyPiece;
if (dp1.to != SQ_NONE && dp1.to == dp2.remove_sq)
{
const Square captureSq = dp1.to;
dp1.to = dp2.remove_sq = SQ_NONE;
double_inc_update<Perspective>(featureTransformer, ksq, accumulators[next],
accumulators[next + 1], accumulators[next - 1]);
dp1.to = dp2.remove_sq = captureSq;
next++;
continue;
}
}
update_accumulator_incremental<Perspective, true>(
featureTransformer, ksq, accumulators[next], accumulators[next - 1]);
}
assert((latest().acc<Dimensions>()).computed[Perspective]);
}
template<Color Perspective, IndexType Dimensions>
void AccumulatorStack::backward_update_incremental(
const Position& pos,
const FeatureTransformer<Dimensions>& featureTransformer,
const std::size_t end) noexcept {
assert(end < accumulators.size());
assert(end < size);
assert((latest().acc<Dimensions>()).computed[Perspective]);
const Square ksq = pos.square<KING>(Perspective);
for (std::int64_t next = std::int64_t(size) - 2; next >= std::int64_t(end); next--)
update_accumulator_incremental<Perspective, false>(
featureTransformer, ksq, accumulators[next], accumulators[next + 1]);
assert((accumulators[end].acc<Dimensions>()).computed[Perspective]);
}
// Explicit template instantiations
template void AccumulatorStack::evaluate<TransformedFeatureDimensionsBig>(
const Position& pos,
const FeatureTransformer<TransformedFeatureDimensionsBig>& featureTransformer,
AccumulatorCaches::Cache<TransformedFeatureDimensionsBig>& cache) noexcept;
template void AccumulatorStack::evaluate<TransformedFeatureDimensionsSmall>(
const Position& pos,
const FeatureTransformer<TransformedFeatureDimensionsSmall>& featureTransformer,
AccumulatorCaches::Cache<TransformedFeatureDimensionsSmall>& cache) noexcept;
namespace {
template<typename VectorWrapper,
IndexType Width,
UpdateOperation... ops,
typename ElementType,
typename... Ts,
std::enable_if_t<is_all_same_v<ElementType, Ts...>, bool> = true>
void fused_row_reduce(const ElementType* in, ElementType* out, const Ts* const... rows) {
constexpr IndexType size = Width * sizeof(ElementType) / sizeof(typename VectorWrapper::type);
auto* vecIn = reinterpret_cast<const typename VectorWrapper::type*>(in);
auto* vecOut = reinterpret_cast<typename VectorWrapper::type*>(out);
for (IndexType i = 0; i < size; ++i)
vecOut[i] = fused<VectorWrapper, ops...>(
vecIn[i], reinterpret_cast<const typename VectorWrapper::type*>(rows)[i]...);
}
template<Color Perspective, IndexType Dimensions>
struct AccumulatorUpdateContext {
const FeatureTransformer<Dimensions>& featureTransformer;
const AccumulatorState& from;
AccumulatorState& to;
AccumulatorUpdateContext(const FeatureTransformer<Dimensions>& ft,
const AccumulatorState& accF,
AccumulatorState& accT) noexcept :
featureTransformer{ft},
from{accF},
to{accT} {}
template<UpdateOperation... ops,
typename... Ts,
std::enable_if_t<is_all_same_v<IndexType, Ts...>, bool> = true>
void apply(const Ts... indices) {
auto to_weight_vector = [&](const IndexType index) {
return &featureTransformer.weights[index * Dimensions];
};
auto to_psqt_weight_vector = [&](const IndexType index) {
return &featureTransformer.psqtWeights[index * PSQTBuckets];
};
fused_row_reduce<Vec16Wrapper, Dimensions, ops...>(
(from.acc<Dimensions>()).accumulation[Perspective],
(to.acc<Dimensions>()).accumulation[Perspective], to_weight_vector(indices)...);
fused_row_reduce<Vec32Wrapper, PSQTBuckets, ops...>(
(from.acc<Dimensions>()).psqtAccumulation[Perspective],
(to.acc<Dimensions>()).psqtAccumulation[Perspective], to_psqt_weight_vector(indices)...);
}
};
template<Color Perspective, IndexType Dimensions>
auto make_accumulator_update_context(const FeatureTransformer<Dimensions>& featureTransformer,
const AccumulatorState& accumulatorFrom,
AccumulatorState& accumulatorTo) noexcept {
return AccumulatorUpdateContext<Perspective, Dimensions>{featureTransformer, accumulatorFrom,
accumulatorTo};
}
template<Color Perspective, IndexType TransformedFeatureDimensions>
void double_inc_update(const FeatureTransformer<TransformedFeatureDimensions>& featureTransformer,
const Square ksq,
AccumulatorState& middle_state,
AccumulatorState& target_state,
const AccumulatorState& computed) {
assert(computed.acc<TransformedFeatureDimensions>().computed[Perspective]);
assert(!middle_state.acc<TransformedFeatureDimensions>().computed[Perspective]);
assert(!target_state.acc<TransformedFeatureDimensions>().computed[Perspective]);
FeatureSet::IndexList removed, added;
FeatureSet::append_changed_indices<Perspective>(ksq, middle_state.dirtyPiece, removed, added);
// you can't capture a piece that was just involved in castling since the rook ends up
// in a square that the king passed
assert(added.size() < 2);
FeatureSet::append_changed_indices<Perspective>(ksq, target_state.dirtyPiece, removed, added);
assert(added.size() == 1);
assert(removed.size() == 2 || removed.size() == 3);
// Workaround compiler warning for uninitialized variables, replicated on
// profile builds on windows with gcc 14.2.0.
// TODO remove once unneeded
sf_assume(added.size() == 1);
sf_assume(removed.size() == 2 || removed.size() == 3);
auto updateContext =
make_accumulator_update_context<Perspective>(featureTransformer, computed, target_state);
if (removed.size() == 2)
{
updateContext.template apply<Add, Sub, Sub>(added[0], removed[0], removed[1]);
}
else
{
updateContext.template apply<Add, Sub, Sub, Sub>(added[0], removed[0], removed[1],
removed[2]);
}
target_state.acc<TransformedFeatureDimensions>().computed[Perspective] = true;
}
template<Color Perspective, bool Forward, IndexType TransformedFeatureDimensions>
void update_accumulator_incremental(
const FeatureTransformer<TransformedFeatureDimensions>& featureTransformer,
const Square ksq,
AccumulatorState& target_state,
const AccumulatorState& computed) {
assert((computed.acc<TransformedFeatureDimensions>()).computed[Perspective]);
assert(!(target_state.acc<TransformedFeatureDimensions>()).computed[Perspective]);
// The size must be enough to contain the largest possible update.
// That might depend on the feature set and generally relies on the
// feature set's update cost calculation to be correct and never allow
// updates with more added/removed features than MaxActiveDimensions.
// In this case, the maximum size of both feature addition and removal
// is 2, since we are incrementally updating one move at a time.
FeatureSet::IndexList removed, added;
if constexpr (Forward)
FeatureSet::append_changed_indices<Perspective>(ksq, target_state.dirtyPiece, removed,
added);
else
FeatureSet::append_changed_indices<Perspective>(ksq, computed.dirtyPiece, added, removed);
assert(added.size() == 1 || added.size() == 2);
assert(removed.size() == 1 || removed.size() == 2);
assert((Forward && added.size() <= removed.size())
|| (!Forward && added.size() >= removed.size()));
// Workaround compiler warning for uninitialized variables, replicated on
// profile builds on windows with gcc 14.2.0.
// TODO remove once unneeded
sf_assume(added.size() == 1 || added.size() == 2);
sf_assume(removed.size() == 1 || removed.size() == 2);
auto updateContext =
make_accumulator_update_context<Perspective>(featureTransformer, computed, target_state);
if ((Forward && removed.size() == 1) || (!Forward && added.size() == 1))
{
assert(added.size() == 1 && removed.size() == 1);
updateContext.template apply<Add, Sub>(added[0], removed[0]);
}
else if (Forward && added.size() == 1)
{
assert(removed.size() == 2);
updateContext.template apply<Add, Sub, Sub>(added[0], removed[0], removed[1]);
}
else if (!Forward && removed.size() == 1)
{
assert(added.size() == 2);
updateContext.template apply<Add, Add, Sub>(added[0], added[1], removed[0]);
}
else
{
assert(added.size() == 2 && removed.size() == 2);
updateContext.template apply<Add, Add, Sub, Sub>(added[0], added[1], removed[0],
removed[1]);
}
(target_state.acc<TransformedFeatureDimensions>()).computed[Perspective] = true;
}
template<Color Perspective, IndexType Dimensions>
void update_accumulator_refresh_cache(const FeatureTransformer<Dimensions>& featureTransformer,
const Position& pos,
AccumulatorState& accumulatorState,
AccumulatorCaches::Cache<Dimensions>& cache) {
using Tiling [[maybe_unused]] = SIMDTiling<Dimensions, Dimensions, PSQTBuckets>;
const Square ksq = pos.square<KING>(Perspective);
auto& entry = cache[ksq][Perspective];
FeatureSet::IndexList removed, added;
for (Color c : {WHITE, BLACK})
{
for (PieceType pt = PAWN; pt <= KING; ++pt)
{
const Piece piece = make_piece(c, pt);
const Bitboard oldBB = entry.byColorBB[c] & entry.byTypeBB[pt];
const Bitboard newBB = pos.pieces(c, pt);
Bitboard toRemove = oldBB & ~newBB;
Bitboard toAdd = newBB & ~oldBB;
while (toRemove)
{
Square sq = pop_lsb(toRemove);
removed.push_back(FeatureSet::make_index<Perspective>(sq, piece, ksq));
}
while (toAdd)
{
Square sq = pop_lsb(toAdd);
added.push_back(FeatureSet::make_index<Perspective>(sq, piece, ksq));
}
}
}
auto& accumulator = accumulatorState.acc<Dimensions>();
accumulator.computed[Perspective] = true;
#ifdef VECTOR
vec_t acc[Tiling::NumRegs];
psqt_vec_t psqt[Tiling::NumPsqtRegs];
for (IndexType j = 0; j < Dimensions / Tiling::TileHeight; ++j)
{
auto* accTile =
reinterpret_cast<vec_t*>(&accumulator.accumulation[Perspective][j * Tiling::TileHeight]);
auto* entryTile = reinterpret_cast<vec_t*>(&entry.accumulation[j * Tiling::TileHeight]);
for (IndexType k = 0; k < Tiling::NumRegs; ++k)
acc[k] = entryTile[k];
IndexType i = 0;
for (; i < std::min(removed.size(), added.size()); ++i)
{
IndexType indexR = removed[i];
const IndexType offsetR = Dimensions * indexR + j * Tiling::TileHeight;
auto* columnR = reinterpret_cast<const vec_t*>(&featureTransformer.weights[offsetR]);
IndexType indexA = added[i];
const IndexType offsetA = Dimensions * indexA + j * Tiling::TileHeight;
auto* columnA = reinterpret_cast<const vec_t*>(&featureTransformer.weights[offsetA]);
for (IndexType k = 0; k < Tiling::NumRegs; ++k)
acc[k] = fused<Vec16Wrapper, Add, Sub>(acc[k], columnA[k], columnR[k]);
}
for (; i < removed.size(); ++i)
{
IndexType index = removed[i];
const IndexType offset = Dimensions * index + j * Tiling::TileHeight;
auto* column = reinterpret_cast<const vec_t*>(&featureTransformer.weights[offset]);
for (IndexType k = 0; k < Tiling::NumRegs; ++k)
acc[k] = vec_sub_16(acc[k], column[k]);
}
for (; i < added.size(); ++i)
{
IndexType index = added[i];
const IndexType offset = Dimensions * index + j * Tiling::TileHeight;
auto* column = reinterpret_cast<const vec_t*>(&featureTransformer.weights[offset]);
for (IndexType k = 0; k < Tiling::NumRegs; ++k)
acc[k] = vec_add_16(acc[k], column[k]);
}
for (IndexType k = 0; k < Tiling::NumRegs; k++)
vec_store(&entryTile[k], acc[k]);
for (IndexType k = 0; k < Tiling::NumRegs; k++)
vec_store(&accTile[k], acc[k]);
}
for (IndexType j = 0; j < PSQTBuckets / Tiling::PsqtTileHeight; ++j)
{
auto* accTilePsqt = reinterpret_cast<psqt_vec_t*>(
&accumulator.psqtAccumulation[Perspective][j * Tiling::PsqtTileHeight]);
auto* entryTilePsqt =
reinterpret_cast<psqt_vec_t*>(&entry.psqtAccumulation[j * Tiling::PsqtTileHeight]);
for (IndexType k = 0; k < Tiling::NumPsqtRegs; ++k)
psqt[k] = entryTilePsqt[k];
for (IndexType i = 0; i < removed.size(); ++i)
{
IndexType index = removed[i];
const IndexType offset = PSQTBuckets * index + j * Tiling::PsqtTileHeight;
auto* columnPsqt =
reinterpret_cast<const psqt_vec_t*>(&featureTransformer.psqtWeights[offset]);
for (std::size_t k = 0; k < Tiling::NumPsqtRegs; ++k)
psqt[k] = vec_sub_psqt_32(psqt[k], columnPsqt[k]);
}
for (IndexType i = 0; i < added.size(); ++i)
{
IndexType index = added[i];
const IndexType offset = PSQTBuckets * index + j * Tiling::PsqtTileHeight;
auto* columnPsqt =
reinterpret_cast<const psqt_vec_t*>(&featureTransformer.psqtWeights[offset]);
for (std::size_t k = 0; k < Tiling::NumPsqtRegs; ++k)
psqt[k] = vec_add_psqt_32(psqt[k], columnPsqt[k]);
}
for (IndexType k = 0; k < Tiling::NumPsqtRegs; ++k)
vec_store_psqt(&entryTilePsqt[k], psqt[k]);
for (IndexType k = 0; k < Tiling::NumPsqtRegs; ++k)
vec_store_psqt(&accTilePsqt[k], psqt[k]);
}
#else
for (const auto index : removed)
{
const IndexType offset = Dimensions * index;
for (IndexType j = 0; j < Dimensions; ++j)
entry.accumulation[j] -= featureTransformer.weights[offset + j];
for (std::size_t k = 0; k < PSQTBuckets; ++k)
entry.psqtAccumulation[k] -= featureTransformer.psqtWeights[index * PSQTBuckets + k];
}
for (const auto index : added)
{
const IndexType offset = Dimensions * index;
for (IndexType j = 0; j < Dimensions; ++j)
entry.accumulation[j] += featureTransformer.weights[offset + j];
for (std::size_t k = 0; k < PSQTBuckets; ++k)
entry.psqtAccumulation[k] += featureTransformer.psqtWeights[index * PSQTBuckets + k];
}
// The accumulator of the refresh entry has been updated.
// Now copy its content to the actual accumulator we were refreshing.
std::memcpy(accumulator.accumulation[Perspective], entry.accumulation,
sizeof(BiasType) * Dimensions);
std::memcpy(accumulator.psqtAccumulation[Perspective], entry.psqtAccumulation,
sizeof(int32_t) * PSQTBuckets);
#endif
for (Color c : {WHITE, BLACK})
entry.byColorBB[c] = pos.pieces(c);
for (PieceType pt = PAWN; pt <= KING; ++pt)
entry.byTypeBB[pt] = pos.pieces(pt);
}
}
}

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -21,167 +21,19 @@
#ifndef NNUE_ACCUMULATOR_H_INCLUDED
#define NNUE_ACCUMULATOR_H_INCLUDED
#include <array>
#include <cstddef>
#include <cstdint>
#include <cstring>
#include <vector>
#include "../types.h"
#include "nnue_architecture.h"
#include "nnue_common.h"
namespace Stockfish {
class Position;
}
namespace Eval::NNUE {
namespace Stockfish::Eval::NNUE {
// Class that holds the result of affine transformation of input features
struct alignas(32) Accumulator {
std::int16_t
accumulation[2][kRefreshTriggers.size()][kTransformedFeatureDimensions];
Value score;
bool computed_accumulation;
bool computed_score;
};
template<IndexType Size>
struct alignas(CacheLineSize) Accumulator;
} // namespace Eval::NNUE
template<IndexType TransformedFeatureDimensions>
class FeatureTransformer;
// Class that holds the result of affine transformation of input features
template<IndexType Size>
struct alignas(CacheLineSize) Accumulator {
std::int16_t accumulation[COLOR_NB][Size];
std::int32_t psqtAccumulation[COLOR_NB][PSQTBuckets];
std::array<bool, COLOR_NB> computed;
};
// AccumulatorCaches struct provides per-thread accumulator caches, where each
// cache contains multiple entries for each of the possible king squares.
// When the accumulator needs to be refreshed, the cached entry is used to more
// efficiently update the accumulator, instead of rebuilding it from scratch.
// This idea, was first described by Luecx (author of Koivisto) and
// is commonly referred to as "Finny Tables".
struct AccumulatorCaches {
template<typename Networks>
AccumulatorCaches(const Networks& networks) {
clear(networks);
}
template<IndexType Size>
struct alignas(CacheLineSize) Cache {
struct alignas(CacheLineSize) Entry {
BiasType accumulation[Size];
PSQTWeightType psqtAccumulation[PSQTBuckets];
Bitboard byColorBB[COLOR_NB];
Bitboard byTypeBB[PIECE_TYPE_NB];
// To initialize a refresh entry, we set all its bitboards empty,
// so we put the biases in the accumulation, without any weights on top
void clear(const BiasType* biases) {
std::memcpy(accumulation, biases, sizeof(accumulation));
std::memset((uint8_t*) this + offsetof(Entry, psqtAccumulation), 0,
sizeof(Entry) - offsetof(Entry, psqtAccumulation));
}
};
template<typename Network>
void clear(const Network& network) {
for (auto& entries1D : entries)
for (auto& entry : entries1D)
entry.clear(network.featureTransformer->biases);
}
std::array<Entry, COLOR_NB>& operator[](Square sq) { return entries[sq]; }
std::array<std::array<Entry, COLOR_NB>, SQUARE_NB> entries;
};
template<typename Networks>
void clear(const Networks& networks) {
big.clear(networks.big);
small.clear(networks.small);
}
Cache<TransformedFeatureDimensionsBig> big;
Cache<TransformedFeatureDimensionsSmall> small;
};
struct AccumulatorState {
Accumulator<TransformedFeatureDimensionsBig> accumulatorBig;
Accumulator<TransformedFeatureDimensionsSmall> accumulatorSmall;
DirtyPiece dirtyPiece;
template<IndexType Size>
auto& acc() noexcept {
static_assert(Size == TransformedFeatureDimensionsBig
|| Size == TransformedFeatureDimensionsSmall,
"Invalid size for accumulator");
if constexpr (Size == TransformedFeatureDimensionsBig)
return accumulatorBig;
else if constexpr (Size == TransformedFeatureDimensionsSmall)
return accumulatorSmall;
}
template<IndexType Size>
const auto& acc() const noexcept {
static_assert(Size == TransformedFeatureDimensionsBig
|| Size == TransformedFeatureDimensionsSmall,
"Invalid size for accumulator");
if constexpr (Size == TransformedFeatureDimensionsBig)
return accumulatorBig;
else if constexpr (Size == TransformedFeatureDimensionsSmall)
return accumulatorSmall;
}
void reset(const DirtyPiece& dp) noexcept;
};
class AccumulatorStack {
public:
AccumulatorStack() :
accumulators(MAX_PLY + 1),
size{1} {}
[[nodiscard]] const AccumulatorState& latest() const noexcept;
void reset() noexcept;
void push(const DirtyPiece& dirtyPiece) noexcept;
void pop() noexcept;
template<IndexType Dimensions>
void evaluate(const Position& pos,
const FeatureTransformer<Dimensions>& featureTransformer,
AccumulatorCaches::Cache<Dimensions>& cache) noexcept;
private:
[[nodiscard]] AccumulatorState& mut_latest() noexcept;
template<Color Perspective, IndexType Dimensions>
void evaluate_side(const Position& pos,
const FeatureTransformer<Dimensions>& featureTransformer,
AccumulatorCaches::Cache<Dimensions>& cache) noexcept;
template<Color Perspective, IndexType Dimensions>
[[nodiscard]] std::size_t find_last_usable_accumulator() const noexcept;
template<Color Perspective, IndexType Dimensions>
void forward_update_incremental(const Position& pos,
const FeatureTransformer<Dimensions>& featureTransformer,
const std::size_t begin) noexcept;
template<Color Perspective, IndexType Dimensions>
void backward_update_incremental(const Position& pos,
const FeatureTransformer<Dimensions>& featureTransformer,
const std::size_t end) noexcept;
std::vector<AccumulatorState> accumulators;
std::size_t size;
};
} // namespace Stockfish::Eval::NNUE
#endif // NNUE_ACCUMULATOR_H_INCLUDED
#endif // NNUE_ACCUMULATOR_H_INCLUDED

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -21,123 +21,18 @@
#ifndef NNUE_ARCHITECTURE_H_INCLUDED
#define NNUE_ARCHITECTURE_H_INCLUDED
#include <cstdint>
#include <cstring>
#include <iosfwd>
// Defines the network structure
#include "architectures/halfkp_256x2-32-32.h"
#include "features/half_ka_v2_hm.h"
#include "layers/affine_transform.h"
#include "layers/affine_transform_sparse_input.h"
#include "layers/clipped_relu.h"
#include "layers/sqr_clipped_relu.h"
#include "nnue_common.h"
namespace Eval::NNUE {
namespace Stockfish::Eval::NNUE {
static_assert(kTransformedFeatureDimensions % kMaxSimdWidth == 0, "");
static_assert(Network::kOutputDimensions == 1, "");
static_assert(std::is_same<Network::OutputType, std::int32_t>::value, "");
// Input features used in evaluation function
using FeatureSet = Features::HalfKAv2_hm;
// Trigger for full calculation instead of difference calculation
constexpr auto kRefreshTriggers = RawFeatures::kRefreshTriggers;
// Number of input feature dimensions after conversion
constexpr IndexType TransformedFeatureDimensionsBig = 3072;
constexpr int L2Big = 15;
constexpr int L3Big = 32;
} // namespace Eval::NNUE
constexpr IndexType TransformedFeatureDimensionsSmall = 128;
constexpr int L2Small = 15;
constexpr int L3Small = 32;
constexpr IndexType PSQTBuckets = 8;
constexpr IndexType LayerStacks = 8;
// If vector instructions are enabled, we update and refresh the
// accumulator tile by tile such that each tile fits in the CPU's
// vector registers.
static_assert(PSQTBuckets % 8 == 0,
"Per feature PSQT values cannot be processed at granularity lower than 8 at a time.");
template<IndexType L1, int L2, int L3>
struct NetworkArchitecture {
static constexpr IndexType TransformedFeatureDimensions = L1;
static constexpr int FC_0_OUTPUTS = L2;
static constexpr int FC_1_OUTPUTS = L3;
Layers::AffineTransformSparseInput<TransformedFeatureDimensions, FC_0_OUTPUTS + 1> fc_0;
Layers::SqrClippedReLU<FC_0_OUTPUTS + 1> ac_sqr_0;
Layers::ClippedReLU<FC_0_OUTPUTS + 1> ac_0;
Layers::AffineTransform<FC_0_OUTPUTS * 2, FC_1_OUTPUTS> fc_1;
Layers::ClippedReLU<FC_1_OUTPUTS> ac_1;
Layers::AffineTransform<FC_1_OUTPUTS, 1> fc_2;
// Hash value embedded in the evaluation file
static constexpr std::uint32_t get_hash_value() {
// input slice hash
std::uint32_t hashValue = 0xEC42E90Du;
hashValue ^= TransformedFeatureDimensions * 2;
hashValue = decltype(fc_0)::get_hash_value(hashValue);
hashValue = decltype(ac_0)::get_hash_value(hashValue);
hashValue = decltype(fc_1)::get_hash_value(hashValue);
hashValue = decltype(ac_1)::get_hash_value(hashValue);
hashValue = decltype(fc_2)::get_hash_value(hashValue);
return hashValue;
}
// Read network parameters
bool read_parameters(std::istream& stream) {
return fc_0.read_parameters(stream) && ac_0.read_parameters(stream)
&& fc_1.read_parameters(stream) && ac_1.read_parameters(stream)
&& fc_2.read_parameters(stream);
}
// Write network parameters
bool write_parameters(std::ostream& stream) const {
return fc_0.write_parameters(stream) && ac_0.write_parameters(stream)
&& fc_1.write_parameters(stream) && ac_1.write_parameters(stream)
&& fc_2.write_parameters(stream);
}
std::int32_t propagate(const TransformedFeatureType* transformedFeatures) {
struct alignas(CacheLineSize) Buffer {
alignas(CacheLineSize) typename decltype(fc_0)::OutputBuffer fc_0_out;
alignas(CacheLineSize) typename decltype(ac_sqr_0)::OutputType
ac_sqr_0_out[ceil_to_multiple<IndexType>(FC_0_OUTPUTS * 2, 32)];
alignas(CacheLineSize) typename decltype(ac_0)::OutputBuffer ac_0_out;
alignas(CacheLineSize) typename decltype(fc_1)::OutputBuffer fc_1_out;
alignas(CacheLineSize) typename decltype(ac_1)::OutputBuffer ac_1_out;
alignas(CacheLineSize) typename decltype(fc_2)::OutputBuffer fc_2_out;
Buffer() { std::memset(this, 0, sizeof(*this)); }
};
#if defined(__clang__) && (__APPLE__)
// workaround for a bug reported with xcode 12
static thread_local auto tlsBuffer = std::make_unique<Buffer>();
// Access TLS only once, cache result.
Buffer& buffer = *tlsBuffer;
#else
alignas(CacheLineSize) static thread_local Buffer buffer;
#endif
fc_0.propagate(transformedFeatures, buffer.fc_0_out);
ac_sqr_0.propagate(buffer.fc_0_out, buffer.ac_sqr_0_out);
ac_0.propagate(buffer.fc_0_out, buffer.ac_0_out);
std::memcpy(buffer.ac_sqr_0_out + FC_0_OUTPUTS, buffer.ac_0_out,
FC_0_OUTPUTS * sizeof(typename decltype(ac_0)::OutputType));
fc_1.propagate(buffer.ac_sqr_0_out, buffer.fc_1_out);
ac_1.propagate(buffer.fc_1_out, buffer.ac_1_out);
fc_2.propagate(buffer.ac_1_out, buffer.fc_2_out);
// buffer.fc_0_out[FC_0_OUTPUTS] is such that 1.0 is equal to 127*(1<<WeightScaleBits) in
// quantized form, but we want 1.0 to be equal to 600*OutputScale
std::int32_t fwdOut =
(buffer.fc_0_out[FC_0_OUTPUTS]) * (600 * OutputScale) / (127 * (1 << WeightScaleBits));
std::int32_t outputValue = buffer.fc_2_out[0] + fwdOut;
return outputValue;
}
};
} // namespace Stockfish::Eval::NNUE
#endif // #ifndef NNUE_ARCHITECTURE_H_INCLUDED
#endif // #ifndef NNUE_ARCHITECTURE_H_INCLUDED

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -21,268 +21,57 @@
#ifndef NNUE_COMMON_H_INCLUDED
#define NNUE_COMMON_H_INCLUDED
#include <algorithm>
#include <cassert>
#include <cstdint>
#include <cstring>
#include <iostream>
#include <type_traits>
#include "../misc.h"
#if defined(USE_AVX2)
#include <immintrin.h>
#include <immintrin.h>
#elif defined(USE_SSE41)
#include <smmintrin.h>
#include <smmintrin.h>
#elif defined(USE_SSSE3)
#include <tmmintrin.h>
#include <tmmintrin.h>
#elif defined(USE_SSE2)
#include <emmintrin.h>
#include <emmintrin.h>
#elif defined(USE_NEON)
#include <arm_neon.h>
#include <arm_neon.h>
#endif
namespace Stockfish::Eval::NNUE {
namespace Eval::NNUE {
using BiasType = std::int16_t;
using WeightType = std::int16_t;
using PSQTWeightType = std::int32_t;
using IndexType = std::uint32_t;
// Version of the evaluation file
constexpr std::uint32_t kVersion = 0x7AF32F16u;
// Version of the evaluation file
constexpr std::uint32_t Version = 0x7AF32F20u;
// Constant used in evaluation value calculation
constexpr int FV_SCALE = 16;
constexpr int kWeightScaleBits = 6;
// Constant used in evaluation value calculation
constexpr int OutputScale = 16;
constexpr int WeightScaleBits = 6;
// Size of cache line (in bytes)
constexpr std::size_t kCacheLineSize = 64;
// Size of cache line (in bytes)
constexpr std::size_t CacheLineSize = 64;
// SIMD width (in bytes)
#if defined(USE_AVX2)
constexpr std::size_t kSimdWidth = 32;
constexpr const char Leb128MagicString[] = "COMPRESSED_LEB128";
constexpr const std::size_t Leb128MagicStringSize = sizeof(Leb128MagicString) - 1;
#elif defined(USE_SSE2)
constexpr std::size_t kSimdWidth = 16;
// SIMD width (in bytes)
#if defined(USE_AVX2)
constexpr std::size_t SimdWidth = 32;
#elif defined(USE_NEON)
constexpr std::size_t kSimdWidth = 16;
#endif
#elif defined(USE_SSE2)
constexpr std::size_t SimdWidth = 16;
constexpr std::size_t kMaxSimdWidth = 32;
#elif defined(USE_NEON)
constexpr std::size_t SimdWidth = 16;
#endif
// Type of input feature after conversion
using TransformedFeatureType = std::uint8_t;
using IndexType = std::uint32_t;
constexpr std::size_t MaxSimdWidth = 32;
// Type of input feature after conversion
using TransformedFeatureType = std::uint8_t;
// Round n up to be a multiple of base
template<typename IntType>
constexpr IntType ceil_to_multiple(IntType n, IntType base) {
// Round n up to be a multiple of base
template <typename IntType>
constexpr IntType CeilToMultiple(IntType n, IntType base) {
return (n + base - 1) / base * base;
}
}
} // namespace Eval::NNUE
// Utility to read an integer (signed or unsigned, any size)
// from a stream in little-endian order. We swap the byte order after the read if
// necessary to return a result with the byte ordering of the compiling machine.
template<typename IntType>
inline IntType read_little_endian(std::istream& stream) {
IntType result;
if (IsLittleEndian)
stream.read(reinterpret_cast<char*>(&result), sizeof(IntType));
else
{
std::uint8_t u[sizeof(IntType)];
std::make_unsigned_t<IntType> v = 0;
stream.read(reinterpret_cast<char*>(u), sizeof(IntType));
for (std::size_t i = 0; i < sizeof(IntType); ++i)
v = (v << 8) | u[sizeof(IntType) - i - 1];
std::memcpy(&result, &v, sizeof(IntType));
}
return result;
}
// Utility to write an integer (signed or unsigned, any size)
// to a stream in little-endian order. We swap the byte order before the write if
// necessary to always write in little-endian order, independently of the byte
// ordering of the compiling machine.
template<typename IntType>
inline void write_little_endian(std::ostream& stream, IntType value) {
if (IsLittleEndian)
stream.write(reinterpret_cast<const char*>(&value), sizeof(IntType));
else
{
std::uint8_t u[sizeof(IntType)];
std::make_unsigned_t<IntType> v = value;
std::size_t i = 0;
// if constexpr to silence the warning about shift by 8
if constexpr (sizeof(IntType) > 1)
{
for (; i + 1 < sizeof(IntType); ++i)
{
u[i] = std::uint8_t(v);
v >>= 8;
}
}
u[i] = std::uint8_t(v);
stream.write(reinterpret_cast<char*>(u), sizeof(IntType));
}
}
// Read integers in bulk from a little-endian stream.
// This reads N integers from stream s and puts them in array out.
template<typename IntType>
inline void read_little_endian(std::istream& stream, IntType* out, std::size_t count) {
if (IsLittleEndian)
stream.read(reinterpret_cast<char*>(out), sizeof(IntType) * count);
else
for (std::size_t i = 0; i < count; ++i)
out[i] = read_little_endian<IntType>(stream);
}
// Write integers in bulk to a little-endian stream.
// This takes N integers from array values and writes them on stream s.
template<typename IntType>
inline void write_little_endian(std::ostream& stream, const IntType* values, std::size_t count) {
if (IsLittleEndian)
stream.write(reinterpret_cast<const char*>(values), sizeof(IntType) * count);
else
for (std::size_t i = 0; i < count; ++i)
write_little_endian<IntType>(stream, values[i]);
}
// Read N signed integers from the stream s, putting them in the array out.
// The stream is assumed to be compressed using the signed LEB128 format.
// See https://en.wikipedia.org/wiki/LEB128 for a description of the compression scheme.
template<typename IntType>
inline void read_leb_128(std::istream& stream, IntType* out, std::size_t count) {
// Check the presence of our LEB128 magic string
char leb128MagicString[Leb128MagicStringSize];
stream.read(leb128MagicString, Leb128MagicStringSize);
assert(strncmp(Leb128MagicString, leb128MagicString, Leb128MagicStringSize) == 0);
static_assert(std::is_signed_v<IntType>, "Not implemented for unsigned types");
const std::uint32_t BUF_SIZE = 4096;
std::uint8_t buf[BUF_SIZE];
auto bytes_left = read_little_endian<std::uint32_t>(stream);
std::uint32_t buf_pos = BUF_SIZE;
for (std::size_t i = 0; i < count; ++i)
{
IntType result = 0;
size_t shift = 0;
do
{
if (buf_pos == BUF_SIZE)
{
stream.read(reinterpret_cast<char*>(buf), std::min(bytes_left, BUF_SIZE));
buf_pos = 0;
}
std::uint8_t byte = buf[buf_pos++];
--bytes_left;
result |= (byte & 0x7f) << shift;
shift += 7;
if ((byte & 0x80) == 0)
{
out[i] = (sizeof(IntType) * 8 <= shift || (byte & 0x40) == 0)
? result
: result | ~((1 << shift) - 1);
break;
}
} while (shift < sizeof(IntType) * 8);
}
assert(bytes_left == 0);
}
// Write signed integers to a stream with LEB128 compression.
// This takes N integers from array values, compresses them with
// the LEB128 algorithm and writes the result on the stream s.
// See https://en.wikipedia.org/wiki/LEB128 for a description of the compression scheme.
template<typename IntType>
inline void write_leb_128(std::ostream& stream, const IntType* values, std::size_t count) {
// Write our LEB128 magic string
stream.write(Leb128MagicString, Leb128MagicStringSize);
static_assert(std::is_signed_v<IntType>, "Not implemented for unsigned types");
std::uint32_t byte_count = 0;
for (std::size_t i = 0; i < count; ++i)
{
IntType value = values[i];
std::uint8_t byte;
do
{
byte = value & 0x7f;
value >>= 7;
++byte_count;
} while ((byte & 0x40) == 0 ? value != 0 : value != -1);
}
write_little_endian(stream, byte_count);
const std::uint32_t BUF_SIZE = 4096;
std::uint8_t buf[BUF_SIZE];
std::uint32_t buf_pos = 0;
auto flush = [&]() {
if (buf_pos > 0)
{
stream.write(reinterpret_cast<char*>(buf), buf_pos);
buf_pos = 0;
}
};
auto write = [&](std::uint8_t byte) {
buf[buf_pos++] = byte;
if (buf_pos == BUF_SIZE)
flush();
};
for (std::size_t i = 0; i < count; ++i)
{
IntType value = values[i];
while (true)
{
std::uint8_t byte = value & 0x7f;
value >>= 7;
if ((byte & 0x40) == 0 ? value == 0 : value == -1)
{
write(byte);
break;
}
write(byte | 0x80);
}
}
flush();
}
} // namespace Stockfish::Eval::NNUE
#endif // #ifndef NNUE_COMMON_H_INCLUDED
#endif // #ifndef NNUE_COMMON_H_INCLUDED

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -21,292 +21,335 @@
#ifndef NNUE_FEATURE_TRANSFORMER_H_INCLUDED
#define NNUE_FEATURE_TRANSFORMER_H_INCLUDED
#include <algorithm>
#include <cstdint>
#include <cstring>
#include <iosfwd>
#include "../position.h"
#include "../types.h"
#include "nnue_accumulator.h"
#include "nnue_architecture.h"
#include "nnue_common.h"
#include "simd.h"
#include "nnue_architecture.h"
#include "features/index_list.h"
namespace Stockfish::Eval::NNUE {
#include <cstring> // std::memset()
// Returns the inverse of a permutation
template<std::size_t Len>
constexpr std::array<std::size_t, Len>
invert_permutation(const std::array<std::size_t, Len>& order) {
std::array<std::size_t, Len> inverse{};
for (std::size_t i = 0; i < order.size(); i++)
inverse[order[i]] = i;
return inverse;
}
namespace Eval::NNUE {
// Divide a byte region of size TotalSize to chunks of size
// BlockSize, and permute the blocks by a given order
template<std::size_t BlockSize, typename T, std::size_t N, std::size_t OrderSize>
void permute(T (&data)[N], const std::array<std::size_t, OrderSize>& order) {
constexpr std::size_t TotalSize = N * sizeof(T);
static_assert(TotalSize % (BlockSize * OrderSize) == 0,
"ChunkSize * OrderSize must perfectly divide TotalSize");
constexpr std::size_t ProcessChunkSize = BlockSize * OrderSize;
std::array<std::byte, ProcessChunkSize> buffer{};
std::byte* const bytes = reinterpret_cast<std::byte*>(data);
for (std::size_t i = 0; i < TotalSize; i += ProcessChunkSize)
{
std::byte* const values = &bytes[i];
for (std::size_t j = 0; j < OrderSize; j++)
{
auto* const buffer_chunk = &buffer[j * BlockSize];
auto* const value_chunk = &values[order[j] * BlockSize];
std::copy(value_chunk, value_chunk + BlockSize, buffer_chunk);
}
std::copy(std::begin(buffer), std::end(buffer), values);
}
}
// Input feature converter
template<IndexType TransformedFeatureDimensions>
class FeatureTransformer {
// Input feature converter
class FeatureTransformer {
private:
// Number of output dimensions for one side
static constexpr IndexType HalfDimensions = TransformedFeatureDimensions;
static constexpr IndexType kHalfDimensions = kTransformedFeatureDimensions;
public:
// Output type
using OutputType = TransformedFeatureType;
// Number of input/output dimensions
static constexpr IndexType InputDimensions = FeatureSet::Dimensions;
static constexpr IndexType OutputDimensions = HalfDimensions;
static constexpr IndexType kInputDimensions = RawFeatures::kDimensions;
static constexpr IndexType kOutputDimensions = kHalfDimensions * 2;
// Size of forward propagation buffer
static constexpr std::size_t BufferSize = OutputDimensions * sizeof(OutputType);
// Store the order by which 128-bit blocks of a 1024-bit data must
// be permuted so that calling packus on adjacent vectors of 16-bit
// integers loaded from the data results in the pre-permutation order
static constexpr auto PackusEpi16Order = []() -> std::array<std::size_t, 8> {
#if defined(USE_AVX512)
// _mm512_packus_epi16 after permutation:
// | 0 | 2 | 4 | 6 | // Vector 0
// | 1 | 3 | 5 | 7 | // Vector 1
// | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | // Packed Result
return {0, 2, 4, 6, 1, 3, 5, 7};
#elif defined(USE_AVX2)
// _mm256_packus_epi16 after permutation:
// | 0 | 2 | | 4 | 6 | // Vector 0, 2
// | 1 | 3 | | 5 | 7 | // Vector 1, 3
// | 0 | 1 | 2 | 3 | | 4 | 5 | 6 | 7 | // Packed Result
return {0, 2, 1, 3, 4, 6, 5, 7};
#else
return {0, 1, 2, 3, 4, 5, 6, 7};
#endif
}();
static constexpr auto InversePackusEpi16Order = invert_permutation(PackusEpi16Order);
static constexpr std::size_t kBufferSize =
kOutputDimensions * sizeof(OutputType);
// Hash value embedded in the evaluation file
static constexpr std::uint32_t get_hash_value() {
return FeatureSet::HashValue ^ (OutputDimensions * 2);
}
void permute_weights() {
permute<16>(biases, PackusEpi16Order);
permute<16>(weights, PackusEpi16Order);
}
void unpermute_weights() {
permute<16>(biases, InversePackusEpi16Order);
permute<16>(weights, InversePackusEpi16Order);
}
inline void scale_weights(bool read) {
for (IndexType j = 0; j < InputDimensions; ++j)
{
WeightType* w = &weights[j * HalfDimensions];
for (IndexType i = 0; i < HalfDimensions; ++i)
w[i] = read ? w[i] * 2 : w[i] / 2;
}
for (IndexType i = 0; i < HalfDimensions; ++i)
biases[i] = read ? biases[i] * 2 : biases[i] / 2;
static constexpr std::uint32_t GetHashValue() {
return RawFeatures::kHashValue ^ kOutputDimensions;
}
// Read network parameters
bool read_parameters(std::istream& stream) {
read_leb_128<BiasType>(stream, biases, HalfDimensions);
read_leb_128<WeightType>(stream, weights, HalfDimensions * InputDimensions);
read_leb_128<PSQTWeightType>(stream, psqtWeights, PSQTBuckets * InputDimensions);
permute_weights();
scale_weights(true);
return !stream.fail();
bool ReadParameters(std::istream& stream) {
stream.read(reinterpret_cast<char*>(biases_),
kHalfDimensions * sizeof(BiasType));
stream.read(reinterpret_cast<char*>(weights_),
kHalfDimensions * kInputDimensions * sizeof(WeightType));
return !stream.fail();
}
// Write network parameters
bool write_parameters(std::ostream& stream) {
unpermute_weights();
scale_weights(false);
write_leb_128<BiasType>(stream, biases, HalfDimensions);
write_leb_128<WeightType>(stream, weights, HalfDimensions * InputDimensions);
write_leb_128<PSQTWeightType>(stream, psqtWeights, PSQTBuckets * InputDimensions);
permute_weights();
scale_weights(true);
return !stream.fail();
// Proceed with the difference calculation if possible
bool UpdateAccumulatorIfPossible(const Position& pos) const {
const auto now = pos.state();
if (now->accumulator.computed_accumulation) {
return true;
}
const auto prev = now->previous;
if (prev && prev->accumulator.computed_accumulation) {
UpdateAccumulator(pos);
return true;
}
return false;
}
// Convert input features
std::int32_t transform(const Position& pos,
AccumulatorStack& accumulatorStack,
AccumulatorCaches::Cache<HalfDimensions>* cache,
OutputType* output,
int bucket) const {
void Transform(const Position& pos, OutputType* output, bool refresh) const {
if (refresh || !UpdateAccumulatorIfPossible(pos)) {
RefreshAccumulator(pos);
}
const auto& accumulation = pos.state()->accumulator.accumulation;
using namespace SIMD;
#if defined(USE_AVX2)
constexpr IndexType kNumChunks = kHalfDimensions / kSimdWidth;
constexpr int kControl = 0b11011000;
const __m256i kZero = _mm256_setzero_si256();
accumulatorStack.evaluate(pos, *this, *cache);
const auto& accumulatorState = accumulatorStack.latest();
#elif defined(USE_SSSE3)
constexpr IndexType kNumChunks = kHalfDimensions / kSimdWidth;
const Color perspectives[2] = {pos.side_to_move(), ~pos.side_to_move()};
const auto& psqtAccumulation = (accumulatorState.acc<HalfDimensions>()).psqtAccumulation;
const auto psqt =
(psqtAccumulation[perspectives[0]][bucket] - psqtAccumulation[perspectives[1]][bucket])
/ 2;
#ifdef USE_SSE41
const __m128i kZero = _mm_setzero_si128();
#else
const __m128i k0x80s = _mm_set1_epi8(-128);
#endif
const auto& accumulation = (accumulatorState.acc<HalfDimensions>()).accumulation;
#elif defined(USE_NEON)
constexpr IndexType kNumChunks = kHalfDimensions / (kSimdWidth / 2);
const int8x8_t kZero = {0};
#endif
for (IndexType p = 0; p < 2; ++p)
{
const IndexType offset = (HalfDimensions / 2) * p;
const Color perspectives[2] = {pos.side_to_move(), ~pos.side_to_move()};
for (IndexType p = 0; p < 2; ++p) {
const IndexType offset = kHalfDimensions * p;
#if defined(VECTOR)
#if defined(USE_AVX2)
auto out = reinterpret_cast<__m256i*>(&output[offset]);
for (IndexType j = 0; j < kNumChunks; ++j) {
__m256i sum0 =
constexpr IndexType OutputChunkSize = MaxChunkSize;
static_assert((HalfDimensions / 2) % OutputChunkSize == 0);
constexpr IndexType NumOutputChunks = HalfDimensions / 2 / OutputChunkSize;
#if defined(__MINGW32__) || defined(__MINGW64__)
// HACK: Use _mm256_loadu_si256() instead of _mm256_load_si256. Because the binary
// compiled with g++ in MSYS2 crashes here because the output memory is not aligned
// even though alignas is specified.
_mm256_loadu_si256
#else
_mm256_load_si256
#endif
const vec_t Zero = vec_zero();
const vec_t One = vec_set_16(127 * 2);
(&reinterpret_cast<const __m256i*>(
accumulation[perspectives[p]][0])[j * 2 + 0]);
__m256i sum1 =
const vec_t* in0 = reinterpret_cast<const vec_t*>(&(accumulation[perspectives[p]][0]));
const vec_t* in1 =
reinterpret_cast<const vec_t*>(&(accumulation[perspectives[p]][HalfDimensions / 2]));
vec_t* out = reinterpret_cast<vec_t*>(output + offset);
#if defined(__MINGW32__) || defined(__MINGW64__)
_mm256_loadu_si256
#else
_mm256_load_si256
#endif
// Per the NNUE architecture, here we want to multiply pairs of
// clipped elements and divide the product by 128. To do this,
// we can naively perform min/max operation to clip each of the
// four int16 vectors, mullo pairs together, then pack them into
// one int8 vector. However, there exists a faster way.
(&reinterpret_cast<const __m256i*>(
accumulation[perspectives[p]][0])[j * 2 + 1]);
// The idea here is to use the implicit clipping from packus to
// save us two vec_max_16 instructions. This clipping works due
// to the fact that any int16 integer below zero will be zeroed
// on packus.
#if defined(__MINGW32__) || defined(__MINGW64__)
_mm256_storeu_si256
#else
_mm256_store_si256
#endif
// Consider the case where the second element is negative.
// If we do standard clipping, that element will be zero, which
// means our pairwise product is zero. If we perform packus and
// remove the lower-side clip for the second element, then our
// product before packus will be negative, and is zeroed on pack.
// The two operation produce equivalent results, but the second
// one (using packus) saves one max operation per pair.
// But here we run into a problem: mullo does not preserve the
// sign of the multiplication. We can get around this by doing
// mulhi, which keeps the sign. But that requires an additional
// tweak.
// mulhi cuts off the last 16 bits of the resulting product,
// which is the same as performing a rightward shift of 16 bits.
// We can use this to our advantage. Recall that we want to
// divide the final product by 128, which is equivalent to a
// 7-bit right shift. Intuitively, if we shift the clipped
// value left by 9, and perform mulhi, which shifts the product
// right by 16 bits, then we will net a right shift of 7 bits.
// However, this won't work as intended. Since we clip the
// values to have a maximum value of 127, shifting it by 9 bits
// might occupy the signed bit, resulting in some positive
// values being interpreted as negative after the shift.
// There is a way, however, to get around this limitation. When
// loading the network, scale accumulator weights and biases by
// 2. To get the same pairwise multiplication result as before,
// we need to divide the product by 128 * 2 * 2 = 512, which
// amounts to a right shift of 9 bits. So now we only have to
// shift left by 7 bits, perform mulhi (shifts right by 16 bits)
// and net a 9 bit right shift. Since we scaled everything by
// two, the values are clipped at 127 * 2 = 254, which occupies
// 8 bits. Shifting it by 7 bits left will no longer occupy the
// signed bit, so we are safe.
// Note that on NEON processors, we shift left by 6 instead
// because the instruction "vqdmulhq_s16" also doubles the
// return value after the multiplication, adding an extra shift
// to the left by 1, so we compensate by shifting less before
// the multiplication.
constexpr int shift =
#if defined(USE_SSE2)
7;
#else
6;
#endif
for (IndexType j = 0; j < NumOutputChunks; ++j)
{
const vec_t sum0a =
vec_slli_16(vec_max_16(vec_min_16(in0[j * 2 + 0], One), Zero), shift);
const vec_t sum0b =
vec_slli_16(vec_max_16(vec_min_16(in0[j * 2 + 1], One), Zero), shift);
const vec_t sum1a = vec_min_16(in1[j * 2 + 0], One);
const vec_t sum1b = vec_min_16(in1[j * 2 + 1], One);
const vec_t pa = vec_mulhi_16(sum0a, sum1a);
const vec_t pb = vec_mulhi_16(sum0b, sum1b);
out[j] = vec_packus_16(pa, pb);
}
#else
for (IndexType j = 0; j < HalfDimensions / 2; ++j)
{
BiasType sum0 = accumulation[static_cast<int>(perspectives[p])][j + 0];
BiasType sum1 =
accumulation[static_cast<int>(perspectives[p])][j + HalfDimensions / 2];
sum0 = std::clamp<BiasType>(sum0, 0, 127 * 2);
sum1 = std::clamp<BiasType>(sum1, 0, 127 * 2);
output[offset + j] = static_cast<OutputType>(unsigned(sum0 * sum1) / 512);
}
#endif
(&out[j], _mm256_permute4x64_epi64(_mm256_max_epi8(
_mm256_packs_epi16(sum0, sum1), kZero), kControl));
}
return psqt;
} // end of function transform()
#elif defined(USE_SSSE3)
auto out = reinterpret_cast<__m128i*>(&output[offset]);
for (IndexType j = 0; j < kNumChunks; ++j) {
__m128i sum0 = _mm_load_si128(&reinterpret_cast<const __m128i*>(
accumulation[perspectives[p]][0])[j * 2 + 0]);
__m128i sum1 = _mm_load_si128(&reinterpret_cast<const __m128i*>(
accumulation[perspectives[p]][0])[j * 2 + 1]);
const __m128i packedbytes = _mm_packs_epi16(sum0, sum1);
alignas(CacheLineSize) BiasType biases[HalfDimensions];
alignas(CacheLineSize) WeightType weights[HalfDimensions * InputDimensions];
alignas(CacheLineSize) PSQTWeightType psqtWeights[InputDimensions * PSQTBuckets];
};
_mm_store_si128(&out[j],
} // namespace Stockfish::Eval::NNUE
#ifdef USE_SSE41
_mm_max_epi8(packedbytes, kZero)
#else
_mm_subs_epi8(_mm_adds_epi8(packedbytes, k0x80s), k0x80s)
#endif
#endif // #ifndef NNUE_FEATURE_TRANSFORMER_H_INCLUDED
);
}
#elif defined(USE_NEON)
const auto out = reinterpret_cast<int8x8_t*>(&output[offset]);
for (IndexType j = 0; j < kNumChunks; ++j) {
int16x8_t sum = reinterpret_cast<const int16x8_t*>(
accumulation[perspectives[p]][0])[j];
out[j] = vmax_s8(vqmovn_s16(sum), kZero);
}
#else
for (IndexType j = 0; j < kHalfDimensions; ++j) {
BiasType sum = accumulation[static_cast<int>(perspectives[p])][0][j];
output[offset + j] = static_cast<OutputType>(
std::max<int>(0, std::min<int>(127, sum)));
}
#endif
}
}
private:
// Calculate cumulative value without using difference calculation
void RefreshAccumulator(const Position& pos) const {
auto& accumulator = pos.state()->accumulator;
IndexType i = 0;
Features::IndexList active_indices[2];
RawFeatures::AppendActiveIndices(pos, kRefreshTriggers[i],
active_indices);
for (Color perspective : { WHITE, BLACK }) {
std::memcpy(accumulator.accumulation[perspective][i], biases_,
kHalfDimensions * sizeof(BiasType));
for (const auto index : active_indices[perspective]) {
const IndexType offset = kHalfDimensions * index;
#if defined(USE_AVX2)
auto accumulation = reinterpret_cast<__m256i*>(
&accumulator.accumulation[perspective][i][0]);
auto column = reinterpret_cast<const __m256i*>(&weights_[offset]);
constexpr IndexType kNumChunks = kHalfDimensions / (kSimdWidth / 2);
for (IndexType j = 0; j < kNumChunks; ++j) {
#if defined(__MINGW32__) || defined(__MINGW64__)
_mm256_storeu_si256(&accumulation[j], _mm256_add_epi16(_mm256_loadu_si256(&accumulation[j]), column[j]));
#else
accumulation[j] = _mm256_add_epi16(accumulation[j], column[j]);
#endif
}
#elif defined(USE_SSE2)
auto accumulation = reinterpret_cast<__m128i*>(
&accumulator.accumulation[perspective][i][0]);
auto column = reinterpret_cast<const __m128i*>(&weights_[offset]);
constexpr IndexType kNumChunks = kHalfDimensions / (kSimdWidth / 2);
for (IndexType j = 0; j < kNumChunks; ++j) {
accumulation[j] = _mm_add_epi16(accumulation[j], column[j]);
}
#elif defined(USE_NEON)
auto accumulation = reinterpret_cast<int16x8_t*>(
&accumulator.accumulation[perspective][i][0]);
auto column = reinterpret_cast<const int16x8_t*>(&weights_[offset]);
constexpr IndexType kNumChunks = kHalfDimensions / (kSimdWidth / 2);
for (IndexType j = 0; j < kNumChunks; ++j) {
accumulation[j] = vaddq_s16(accumulation[j], column[j]);
}
#else
for (IndexType j = 0; j < kHalfDimensions; ++j) {
accumulator.accumulation[perspective][i][j] += weights_[offset + j];
}
#endif
}
}
accumulator.computed_accumulation = true;
accumulator.computed_score = false;
}
// Calculate cumulative value using difference calculation
void UpdateAccumulator(const Position& pos) const {
const auto prev_accumulator = pos.state()->previous->accumulator;
auto& accumulator = pos.state()->accumulator;
IndexType i = 0;
Features::IndexList removed_indices[2], added_indices[2];
bool reset[2];
RawFeatures::AppendChangedIndices(pos, kRefreshTriggers[i],
removed_indices, added_indices, reset);
for (Color perspective : { WHITE, BLACK }) {
#if defined(USE_AVX2)
constexpr IndexType kNumChunks = kHalfDimensions / (kSimdWidth / 2);
auto accumulation = reinterpret_cast<__m256i*>(
&accumulator.accumulation[perspective][i][0]);
#elif defined(USE_SSE2)
constexpr IndexType kNumChunks = kHalfDimensions / (kSimdWidth / 2);
auto accumulation = reinterpret_cast<__m128i*>(
&accumulator.accumulation[perspective][i][0]);
#elif defined(USE_NEON)
constexpr IndexType kNumChunks = kHalfDimensions / (kSimdWidth / 2);
auto accumulation = reinterpret_cast<int16x8_t*>(
&accumulator.accumulation[perspective][i][0]);
#endif
if (reset[perspective]) {
std::memcpy(accumulator.accumulation[perspective][i], biases_,
kHalfDimensions * sizeof(BiasType));
} else {
std::memcpy(accumulator.accumulation[perspective][i],
prev_accumulator.accumulation[perspective][i],
kHalfDimensions * sizeof(BiasType));
// Difference calculation for the deactivated features
for (const auto index : removed_indices[perspective]) {
const IndexType offset = kHalfDimensions * index;
#if defined(USE_AVX2)
auto column = reinterpret_cast<const __m256i*>(&weights_[offset]);
for (IndexType j = 0; j < kNumChunks; ++j) {
accumulation[j] = _mm256_sub_epi16(accumulation[j], column[j]);
}
#elif defined(USE_SSE2)
auto column = reinterpret_cast<const __m128i*>(&weights_[offset]);
for (IndexType j = 0; j < kNumChunks; ++j) {
accumulation[j] = _mm_sub_epi16(accumulation[j], column[j]);
}
#elif defined(USE_NEON)
auto column = reinterpret_cast<const int16x8_t*>(&weights_[offset]);
for (IndexType j = 0; j < kNumChunks; ++j) {
accumulation[j] = vsubq_s16(accumulation[j], column[j]);
}
#else
for (IndexType j = 0; j < kHalfDimensions; ++j) {
accumulator.accumulation[perspective][i][j] -=
weights_[offset + j];
}
#endif
}
}
{ // Difference calculation for the activated features
for (const auto index : added_indices[perspective]) {
const IndexType offset = kHalfDimensions * index;
#if defined(USE_AVX2)
auto column = reinterpret_cast<const __m256i*>(&weights_[offset]);
for (IndexType j = 0; j < kNumChunks; ++j) {
accumulation[j] = _mm256_add_epi16(accumulation[j], column[j]);
}
#elif defined(USE_SSE2)
auto column = reinterpret_cast<const __m128i*>(&weights_[offset]);
for (IndexType j = 0; j < kNumChunks; ++j) {
accumulation[j] = _mm_add_epi16(accumulation[j], column[j]);
}
#elif defined(USE_NEON)
auto column = reinterpret_cast<const int16x8_t*>(&weights_[offset]);
for (IndexType j = 0; j < kNumChunks; ++j) {
accumulation[j] = vaddq_s16(accumulation[j], column[j]);
}
#else
for (IndexType j = 0; j < kHalfDimensions; ++j) {
accumulator.accumulation[perspective][i][j] +=
weights_[offset + j];
}
#endif
}
}
}
accumulator.computed_accumulation = true;
accumulator.computed_score = false;
}
using BiasType = std::int16_t;
using WeightType = std::int16_t;
alignas(kCacheLineSize) BiasType biases_[kHalfDimensions];
alignas(kCacheLineSize)
WeightType weights_[kHalfDimensions * kInputDimensions];
};
} // namespace Eval::NNUE
#endif // #ifndef NNUE_FEATURE_TRANSFORMER_H_INCLUDED

View File

@@ -1,193 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
// Code for calculating NNUE evaluation function
#include "nnue_misc.h"
#include <cmath>
#include <cstdlib>
#include <cstring>
#include <iomanip>
#include <iosfwd>
#include <iostream>
#include <sstream>
#include <string_view>
#include <tuple>
#include "../position.h"
#include "../types.h"
#include "../uci.h"
#include "network.h"
#include "nnue_accumulator.h"
namespace Stockfish::Eval::NNUE {
constexpr std::string_view PieceToChar(" PNBRQK pnbrqk");
namespace {
// Converts a Value into (centi)pawns and writes it in a buffer.
// The buffer must have capacity for at least 5 chars.
void format_cp_compact(Value v, char* buffer, const Position& pos) {
buffer[0] = (v < 0 ? '-' : v > 0 ? '+' : ' ');
int cp = std::abs(UCIEngine::to_cp(v, pos));
if (cp >= 10000)
{
buffer[1] = '0' + cp / 10000;
cp %= 10000;
buffer[2] = '0' + cp / 1000;
cp %= 1000;
buffer[3] = '0' + cp / 100;
buffer[4] = ' ';
}
else if (cp >= 1000)
{
buffer[1] = '0' + cp / 1000;
cp %= 1000;
buffer[2] = '0' + cp / 100;
cp %= 100;
buffer[3] = '.';
buffer[4] = '0' + cp / 10;
}
else
{
buffer[1] = '0' + cp / 100;
cp %= 100;
buffer[2] = '.';
buffer[3] = '0' + cp / 10;
cp %= 10;
buffer[4] = '0' + cp / 1;
}
}
// Converts a Value into pawns, always keeping two decimals
void format_cp_aligned_dot(Value v, std::stringstream& stream, const Position& pos) {
const double pawns = std::abs(0.01 * UCIEngine::to_cp(v, pos));
stream << (v < 0 ? '-'
: v > 0 ? '+'
: ' ')
<< std::setiosflags(std::ios::fixed) << std::setw(6) << std::setprecision(2) << pawns;
}
}
// Returns a string with the value of each piece on a board,
// and a table for (PSQT, Layers) values bucket by bucket.
std::string
trace(Position& pos, const Eval::NNUE::Networks& networks, Eval::NNUE::AccumulatorCaches& caches) {
std::stringstream ss;
char board[3 * 8 + 1][8 * 8 + 2];
std::memset(board, ' ', sizeof(board));
for (int row = 0; row < 3 * 8 + 1; ++row)
board[row][8 * 8 + 1] = '\0';
// A lambda to output one box of the board
auto writeSquare = [&board, &pos](File file, Rank rank, Piece pc, Value value) {
const int x = int(file) * 8;
const int y = (7 - int(rank)) * 3;
for (int i = 1; i < 8; ++i)
board[y][x + i] = board[y + 3][x + i] = '-';
for (int i = 1; i < 3; ++i)
board[y + i][x] = board[y + i][x + 8] = '|';
board[y][x] = board[y][x + 8] = board[y + 3][x + 8] = board[y + 3][x] = '+';
if (pc != NO_PIECE)
board[y + 1][x + 4] = PieceToChar[pc];
if (is_valid(value))
format_cp_compact(value, &board[y + 2][x + 2], pos);
};
AccumulatorStack accumulators;
// We estimate the value of each piece by doing a differential evaluation from
// the current base eval, simulating the removal of the piece from its square.
auto [psqt, positional] = networks.big.evaluate(pos, accumulators, &caches.big);
Value base = psqt + positional;
base = pos.side_to_move() == WHITE ? base : -base;
for (File f = FILE_A; f <= FILE_H; ++f)
for (Rank r = RANK_1; r <= RANK_8; ++r)
{
Square sq = make_square(f, r);
Piece pc = pos.piece_on(sq);
Value v = VALUE_NONE;
if (pc != NO_PIECE && type_of(pc) != KING)
{
pos.remove_piece(sq);
accumulators.reset();
std::tie(psqt, positional) = networks.big.evaluate(pos, accumulators, &caches.big);
Value eval = psqt + positional;
eval = pos.side_to_move() == WHITE ? eval : -eval;
v = base - eval;
pos.put_piece(pc, sq);
}
writeSquare(f, r, pc, v);
}
ss << " NNUE derived piece values:\n";
for (int row = 0; row < 3 * 8 + 1; ++row)
ss << board[row] << '\n';
ss << '\n';
accumulators.reset();
auto t = networks.big.trace_evaluate(pos, accumulators, &caches.big);
ss << " NNUE network contributions "
<< (pos.side_to_move() == WHITE ? "(White to move)" : "(Black to move)") << std::endl
<< "+------------+------------+------------+------------+\n"
<< "| Bucket | Material | Positional | Total |\n"
<< "| | (PSQT) | (Layers) | |\n"
<< "+------------+------------+------------+------------+\n";
for (std::size_t bucket = 0; bucket < LayerStacks; ++bucket)
{
ss << "| " << bucket << " " //
<< " | ";
format_cp_aligned_dot(t.psqt[bucket], ss, pos);
ss << " " //
<< " | ";
format_cp_aligned_dot(t.positional[bucket], ss, pos);
ss << " " //
<< " | ";
format_cp_aligned_dot(t.psqt[bucket] + t.positional[bucket], ss, pos);
ss << " " //
<< " |";
if (bucket == t.correctBucket)
ss << " <-- this bucket is used";
ss << '\n';
}
ss << "+------------+------------+------------+------------+\n";
return ss.str();
}
} // namespace Stockfish::Eval::NNUE

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@@ -1,61 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef NNUE_MISC_H_INCLUDED
#define NNUE_MISC_H_INCLUDED
#include <cstddef>
#include <string>
#include "../types.h"
#include "nnue_architecture.h"
namespace Stockfish {
class Position;
namespace Eval::NNUE {
struct EvalFile {
// Default net name, will use one of the EvalFileDefaultName* macros defined
// in evaluate.h
std::string defaultName;
// Selected net name, either via uci option or default
std::string current;
// Net description extracted from the net file
std::string netDescription;
};
struct NnueEvalTrace {
static_assert(LayerStacks == PSQTBuckets);
Value psqt[LayerStacks];
Value positional[LayerStacks];
std::size_t correctBucket;
};
struct Networks;
struct AccumulatorCaches;
std::string trace(Position& pos, const Networks& networks, AccumulatorCaches& caches);
} // namespace Stockfish::Eval::NNUE
} // namespace Stockfish
#endif // #ifndef NNUE_MISC_H_INCLUDED

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@@ -1,406 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef NNUE_SIMD_H_INCLUDED
#define NNUE_SIMD_H_INCLUDED
#if defined(USE_AVX2)
#include <immintrin.h>
#elif defined(USE_SSE41)
#include <smmintrin.h>
#elif defined(USE_SSSE3)
#include <tmmintrin.h>
#elif defined(USE_SSE2)
#include <emmintrin.h>
#elif defined(USE_NEON)
#include <arm_neon.h>
#endif
#include "../types.h"
#include "nnue_common.h"
namespace Stockfish::Eval::NNUE::SIMD {
// If vector instructions are enabled, we update and refresh the
// accumulator tile by tile such that each tile fits in the CPU's
// vector registers.
#define VECTOR
#ifdef USE_AVX512
using vec_t = __m512i;
using vec128_t = __m128i;
using psqt_vec_t = __m256i;
using vec_uint_t = __m512i;
#define vec_load(a) _mm512_load_si512(a)
#define vec_store(a, b) _mm512_store_si512(a, b)
#define vec_add_16(a, b) _mm512_add_epi16(a, b)
#define vec_sub_16(a, b) _mm512_sub_epi16(a, b)
#define vec_mulhi_16(a, b) _mm512_mulhi_epi16(a, b)
#define vec_zero() _mm512_setzero_epi32()
#define vec_set_16(a) _mm512_set1_epi16(a)
#define vec_max_16(a, b) _mm512_max_epi16(a, b)
#define vec_min_16(a, b) _mm512_min_epi16(a, b)
#define vec_slli_16(a, b) _mm512_slli_epi16(a, b)
// Inverse permuted at load time
#define vec_packus_16(a, b) _mm512_packus_epi16(a, b)
#define vec_load_psqt(a) _mm256_load_si256(a)
#define vec_store_psqt(a, b) _mm256_store_si256(a, b)
#define vec_add_psqt_32(a, b) _mm256_add_epi32(a, b)
#define vec_sub_psqt_32(a, b) _mm256_sub_epi32(a, b)
#define vec_zero_psqt() _mm256_setzero_si256()
#ifdef USE_SSSE3
#define vec_nnz(a) _mm512_cmpgt_epi32_mask(a, _mm512_setzero_si512())
#endif
#define vec128_zero _mm_setzero_si128()
#define vec128_set_16(a) _mm_set1_epi16(a)
#define vec128_load(a) _mm_load_si128(a)
#define vec128_storeu(a, b) _mm_storeu_si128(a, b)
#define vec128_add(a, b) _mm_add_epi16(a, b)
#define NumRegistersSIMD 16
#define MaxChunkSize 64
#elif USE_AVX2
using vec_t = __m256i;
using vec128_t = __m128i;
using psqt_vec_t = __m256i;
using vec_uint_t = __m256i;
#define vec_load(a) _mm256_load_si256(a)
#define vec_store(a, b) _mm256_store_si256(a, b)
#define vec_add_16(a, b) _mm256_add_epi16(a, b)
#define vec_sub_16(a, b) _mm256_sub_epi16(a, b)
#define vec_mulhi_16(a, b) _mm256_mulhi_epi16(a, b)
#define vec_zero() _mm256_setzero_si256()
#define vec_set_16(a) _mm256_set1_epi16(a)
#define vec_max_16(a, b) _mm256_max_epi16(a, b)
#define vec_min_16(a, b) _mm256_min_epi16(a, b)
#define vec_slli_16(a, b) _mm256_slli_epi16(a, b)
// Inverse permuted at load time
#define vec_packus_16(a, b) _mm256_packus_epi16(a, b)
#define vec_load_psqt(a) _mm256_load_si256(a)
#define vec_store_psqt(a, b) _mm256_store_si256(a, b)
#define vec_add_psqt_32(a, b) _mm256_add_epi32(a, b)
#define vec_sub_psqt_32(a, b) _mm256_sub_epi32(a, b)
#define vec_zero_psqt() _mm256_setzero_si256()
#ifdef USE_SSSE3
#if defined(USE_VNNI) && !defined(USE_AVXVNNI)
#define vec_nnz(a) _mm256_cmpgt_epi32_mask(a, _mm256_setzero_si256())
#else
#define vec_nnz(a) \
_mm256_movemask_ps( \
_mm256_castsi256_ps(_mm256_cmpgt_epi32(a, _mm256_setzero_si256())))
#endif
#endif
#define vec128_zero _mm_setzero_si128()
#define vec128_set_16(a) _mm_set1_epi16(a)
#define vec128_load(a) _mm_load_si128(a)
#define vec128_storeu(a, b) _mm_storeu_si128(a, b)
#define vec128_add(a, b) _mm_add_epi16(a, b)
#define NumRegistersSIMD 16
#define MaxChunkSize 32
#elif USE_SSE2
using vec_t = __m128i;
using vec128_t = __m128i;
using psqt_vec_t = __m128i;
using vec_uint_t = __m128i;
#define vec_load(a) (*(a))
#define vec_store(a, b) *(a) = (b)
#define vec_add_16(a, b) _mm_add_epi16(a, b)
#define vec_sub_16(a, b) _mm_sub_epi16(a, b)
#define vec_mulhi_16(a, b) _mm_mulhi_epi16(a, b)
#define vec_zero() _mm_setzero_si128()
#define vec_set_16(a) _mm_set1_epi16(a)
#define vec_max_16(a, b) _mm_max_epi16(a, b)
#define vec_min_16(a, b) _mm_min_epi16(a, b)
#define vec_slli_16(a, b) _mm_slli_epi16(a, b)
#define vec_packus_16(a, b) _mm_packus_epi16(a, b)
#define vec_load_psqt(a) (*(a))
#define vec_store_psqt(a, b) *(a) = (b)
#define vec_add_psqt_32(a, b) _mm_add_epi32(a, b)
#define vec_sub_psqt_32(a, b) _mm_sub_epi32(a, b)
#define vec_zero_psqt() _mm_setzero_si128()
#ifdef USE_SSSE3
#define vec_nnz(a) \
_mm_movemask_ps(_mm_castsi128_ps(_mm_cmpgt_epi32(a, _mm_setzero_si128())))
#endif
#define vec128_zero _mm_setzero_si128()
#define vec128_set_16(a) _mm_set1_epi16(a)
#define vec128_load(a) _mm_load_si128(a)
#define vec128_storeu(a, b) _mm_storeu_si128(a, b)
#define vec128_add(a, b) _mm_add_epi16(a, b)
#define NumRegistersSIMD (Is64Bit ? 16 : 8)
#define MaxChunkSize 16
#elif USE_NEON
using vec_t = int16x8_t;
using psqt_vec_t = int32x4_t;
using vec128_t = uint16x8_t;
using vec_uint_t = uint32x4_t;
#define vec_load(a) (*(a))
#define vec_store(a, b) *(a) = (b)
#define vec_add_16(a, b) vaddq_s16(a, b)
#define vec_sub_16(a, b) vsubq_s16(a, b)
#define vec_mulhi_16(a, b) vqdmulhq_s16(a, b)
#define vec_zero() vec_t{0}
#define vec_set_16(a) vdupq_n_s16(a)
#define vec_max_16(a, b) vmaxq_s16(a, b)
#define vec_min_16(a, b) vminq_s16(a, b)
#define vec_slli_16(a, b) vshlq_s16(a, vec_set_16(b))
#define vec_packus_16(a, b) reinterpret_cast<vec_t>(vcombine_u8(vqmovun_s16(a), vqmovun_s16(b)))
#define vec_load_psqt(a) (*(a))
#define vec_store_psqt(a, b) *(a) = (b)
#define vec_add_psqt_32(a, b) vaddq_s32(a, b)
#define vec_sub_psqt_32(a, b) vsubq_s32(a, b)
#define vec_zero_psqt() psqt_vec_t{0}
static constexpr std::uint32_t Mask[4] = {1, 2, 4, 8};
#define vec_nnz(a) vaddvq_u32(vandq_u32(vtstq_u32(a, a), vld1q_u32(Mask)))
#define vec128_zero vdupq_n_u16(0)
#define vec128_set_16(a) vdupq_n_u16(a)
#define vec128_load(a) vld1q_u16(reinterpret_cast<const std::uint16_t*>(a))
#define vec128_storeu(a, b) vst1q_u16(reinterpret_cast<std::uint16_t*>(a), b)
#define vec128_add(a, b) vaddq_u16(a, b)
#define NumRegistersSIMD 16
#define MaxChunkSize 16
#else
#undef VECTOR
#endif
struct Vec16Wrapper {
#ifdef VECTOR
using type = vec_t;
static type add(const type& lhs, const type& rhs) { return vec_add_16(lhs, rhs); }
static type sub(const type& lhs, const type& rhs) { return vec_sub_16(lhs, rhs); }
#else
using type = BiasType;
static type add(const type& lhs, const type& rhs) { return lhs + rhs; }
static type sub(const type& lhs, const type& rhs) { return lhs - rhs; }
#endif
};
struct Vec32Wrapper {
#ifdef VECTOR
using type = psqt_vec_t;
static type add(const type& lhs, const type& rhs) { return vec_add_psqt_32(lhs, rhs); }
static type sub(const type& lhs, const type& rhs) { return vec_sub_psqt_32(lhs, rhs); }
#else
using type = PSQTWeightType;
static type add(const type& lhs, const type& rhs) { return lhs + rhs; }
static type sub(const type& lhs, const type& rhs) { return lhs - rhs; }
#endif
};
enum UpdateOperation {
Add,
Sub
};
template<typename VecWrapper,
UpdateOperation... ops,
std::enable_if_t<sizeof...(ops) == 0, bool> = true>
typename VecWrapper::type fused(const typename VecWrapper::type& in) {
return in;
}
template<typename VecWrapper,
UpdateOperation update_op,
UpdateOperation... ops,
typename T,
typename... Ts,
std::enable_if_t<is_all_same_v<typename VecWrapper::type, T, Ts...>, bool> = true,
std::enable_if_t<sizeof...(ops) == sizeof...(Ts), bool> = true>
typename VecWrapper::type
fused(const typename VecWrapper::type& in, const T& operand, const Ts&... operands) {
switch (update_op)
{
case Add :
return fused<VecWrapper, ops...>(VecWrapper::add(in, operand), operands...);
case Sub :
return fused<VecWrapper, ops...>(VecWrapper::sub(in, operand), operands...);
default :
static_assert(update_op == Add || update_op == Sub,
"Only Add and Sub are currently supported.");
return typename VecWrapper::type();
}
}
#if defined(USE_AVX512)
[[maybe_unused]] static int m512_hadd(__m512i sum, int bias) {
return _mm512_reduce_add_epi32(sum) + bias;
}
[[maybe_unused]] static void m512_add_dpbusd_epi32(__m512i& acc, __m512i a, __m512i b) {
#if defined(USE_VNNI)
acc = _mm512_dpbusd_epi32(acc, a, b);
#else
__m512i product0 = _mm512_maddubs_epi16(a, b);
product0 = _mm512_madd_epi16(product0, _mm512_set1_epi16(1));
acc = _mm512_add_epi32(acc, product0);
#endif
}
#endif
#if defined(USE_AVX2)
[[maybe_unused]] static int m256_hadd(__m256i sum, int bias) {
__m128i sum128 = _mm_add_epi32(_mm256_castsi256_si128(sum), _mm256_extracti128_si256(sum, 1));
sum128 = _mm_add_epi32(sum128, _mm_shuffle_epi32(sum128, _MM_PERM_BADC));
sum128 = _mm_add_epi32(sum128, _mm_shuffle_epi32(sum128, _MM_PERM_CDAB));
return _mm_cvtsi128_si32(sum128) + bias;
}
[[maybe_unused]] static void m256_add_dpbusd_epi32(__m256i& acc, __m256i a, __m256i b) {
#if defined(USE_VNNI)
acc = _mm256_dpbusd_epi32(acc, a, b);
#else
__m256i product0 = _mm256_maddubs_epi16(a, b);
product0 = _mm256_madd_epi16(product0, _mm256_set1_epi16(1));
acc = _mm256_add_epi32(acc, product0);
#endif
}
#endif
#if defined(USE_SSSE3)
[[maybe_unused]] static int m128_hadd(__m128i sum, int bias) {
sum = _mm_add_epi32(sum, _mm_shuffle_epi32(sum, 0x4E)); //_MM_PERM_BADC
sum = _mm_add_epi32(sum, _mm_shuffle_epi32(sum, 0xB1)); //_MM_PERM_CDAB
return _mm_cvtsi128_si32(sum) + bias;
}
[[maybe_unused]] static void m128_add_dpbusd_epi32(__m128i& acc, __m128i a, __m128i b) {
__m128i product0 = _mm_maddubs_epi16(a, b);
product0 = _mm_madd_epi16(product0, _mm_set1_epi16(1));
acc = _mm_add_epi32(acc, product0);
}
#endif
#if defined(USE_NEON_DOTPROD)
[[maybe_unused]] static void
dotprod_m128_add_dpbusd_epi32(int32x4_t& acc, int8x16_t a, int8x16_t b) {
acc = vdotq_s32(acc, a, b);
}
#endif
#if defined(USE_NEON)
[[maybe_unused]] static int neon_m128_reduce_add_epi32(int32x4_t s) {
#if USE_NEON >= 8
return vaddvq_s32(s);
#else
return s[0] + s[1] + s[2] + s[3];
#endif
}
[[maybe_unused]] static int neon_m128_hadd(int32x4_t sum, int bias) {
return neon_m128_reduce_add_epi32(sum) + bias;
}
#endif
#if USE_NEON >= 8
[[maybe_unused]] static void neon_m128_add_dpbusd_epi32(int32x4_t& acc, int8x16_t a, int8x16_t b) {
int16x8_t product0 = vmull_s8(vget_low_s8(a), vget_low_s8(b));
int16x8_t product1 = vmull_high_s8(a, b);
int16x8_t sum = vpaddq_s16(product0, product1);
acc = vpadalq_s16(acc, sum);
}
#endif
// Compute optimal SIMD register count for feature transformer accumulation.
template<IndexType TransformedFeatureWidth, IndexType HalfDimensions, IndexType PSQTBuckets>
class SIMDTiling {
#ifdef VECTOR
// We use __m* types as template arguments, which causes GCC to emit warnings
// about losing some attribute information. This is irrelevant to us as we
// only take their size, so the following pragma are harmless.
#if defined(__GNUC__)
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wignored-attributes"
#endif
template<typename SIMDRegisterType, typename LaneType, int NumLanes, int MaxRegisters>
static constexpr int BestRegisterCount() {
constexpr std::size_t RegisterSize = sizeof(SIMDRegisterType);
constexpr std::size_t LaneSize = sizeof(LaneType);
static_assert(RegisterSize >= LaneSize);
static_assert(MaxRegisters <= NumRegistersSIMD);
static_assert(MaxRegisters > 0);
static_assert(NumRegistersSIMD > 0);
static_assert(RegisterSize % LaneSize == 0);
static_assert((NumLanes * LaneSize) % RegisterSize == 0);
const int ideal = (NumLanes * LaneSize) / RegisterSize;
if (ideal <= MaxRegisters)
return ideal;
// Look for the largest divisor of the ideal register count that is smaller than MaxRegisters
for (int divisor = MaxRegisters; divisor > 1; --divisor)
if (ideal % divisor == 0)
return divisor;
return 1;
}
#if defined(__GNUC__)
#pragma GCC diagnostic pop
#endif
public:
static constexpr int NumRegs =
BestRegisterCount<vec_t, WeightType, TransformedFeatureWidth, NumRegistersSIMD>();
static constexpr int NumPsqtRegs =
BestRegisterCount<psqt_vec_t, PSQTWeightType, PSQTBuckets, NumRegistersSIMD>();
static constexpr IndexType TileHeight = NumRegs * sizeof(vec_t) / 2;
static constexpr IndexType PsqtTileHeight = NumPsqtRegs * sizeof(psqt_vec_t) / 4;
static_assert(HalfDimensions % TileHeight == 0, "TileHeight must divide HalfDimensions");
static_assert(PSQTBuckets % PsqtTileHeight == 0, "PsqtTileHeight must divide PSQTBuckets");
#endif
};
}
#endif

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/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include <algorithm>
#include <cassert>
#include "bitboard.h"
#include "pawns.h"
#include "position.h"
#include "thread.h"
namespace {
#define V Value
#define S(mg, eg) make_score(mg, eg)
// Pawn penalties
constexpr Score Backward = S( 9, 24);
constexpr Score Doubled = S(11, 56);
constexpr Score Isolated = S( 5, 15);
constexpr Score WeakLever = S( 0, 56);
constexpr Score WeakUnopposed = S(13, 27);
// Bonus for blocked pawns at 5th or 6th rank
constexpr Score BlockedPawn[2] = { S(-11, -4), S(-3, 4) };
constexpr Score BlockedStorm[RANK_NB] = {
S(0, 0), S(0, 0), S(76, 78), S(-10, 15), S(-7, 10), S(-4, 6), S(-1, 2)
};
// Connected pawn bonus
constexpr int Connected[RANK_NB] = { 0, 7, 8, 12, 29, 48, 86 };
// Strength of pawn shelter for our king by [distance from edge][rank].
// RANK_1 = 0 is used for files where we have no pawn, or pawn is behind our king.
constexpr Value ShelterStrength[int(FILE_NB) / 2][RANK_NB] = {
{ V( -6), V( 81), V( 93), V( 58), V( 39), V( 18), V( 25) },
{ V(-43), V( 61), V( 35), V(-49), V(-29), V(-11), V( -63) },
{ V(-10), V( 75), V( 23), V( -2), V( 32), V( 3), V( -45) },
{ V(-39), V(-13), V(-29), V(-52), V(-48), V(-67), V(-166) }
};
// Danger of enemy pawns moving toward our king by [distance from edge][rank].
// RANK_1 = 0 is used for files where the enemy has no pawn, or their pawn
// is behind our king. Note that UnblockedStorm[0][1-2] accommodate opponent pawn
// on edge, likely blocked by our king.
constexpr Value UnblockedStorm[int(FILE_NB) / 2][RANK_NB] = {
{ V( 85), V(-289), V(-166), V(97), V(50), V( 45), V( 50) },
{ V( 46), V( -25), V( 122), V(45), V(37), V(-10), V( 20) },
{ V( -6), V( 51), V( 168), V(34), V(-2), V(-22), V(-14) },
{ V(-15), V( -11), V( 101), V( 4), V(11), V(-15), V(-29) }
};
#undef S
#undef V
/// evaluate() calculates a score for the static pawn structure of the given position.
/// We cannot use the location of pieces or king in this function, as the evaluation
/// of the pawn structure will be stored in a small cache for speed reasons, and will
/// be re-used even when the pieces have moved.
template<Color Us>
Score evaluate(const Position& pos, Pawns::Entry* e) {
constexpr Color Them = ~Us;
constexpr Direction Up = pawn_push(Us);
Bitboard neighbours, stoppers, support, phalanx, opposed;
Bitboard lever, leverPush, blocked;
Square s;
bool backward, passed, doubled;
Score score = SCORE_ZERO;
const Square* pl = pos.squares<PAWN>(Us);
Bitboard ourPawns = pos.pieces( Us, PAWN);
Bitboard theirPawns = pos.pieces(Them, PAWN);
Bitboard doubleAttackThem = pawn_double_attacks_bb<Them>(theirPawns);
e->passedPawns[Us] = 0;
e->kingSquares[Us] = SQ_NONE;
e->pawnAttacks[Us] = e->pawnAttacksSpan[Us] = pawn_attacks_bb<Us>(ourPawns);
e->blockedCount += popcount(shift<Up>(ourPawns) & (theirPawns | doubleAttackThem));
// Loop through all pawns of the current color and score each pawn
while ((s = *pl++) != SQ_NONE)
{
assert(pos.piece_on(s) == make_piece(Us, PAWN));
Rank r = relative_rank(Us, s);
// Flag the pawn
opposed = theirPawns & forward_file_bb(Us, s);
blocked = theirPawns & (s + Up);
stoppers = theirPawns & passed_pawn_span(Us, s);
lever = theirPawns & pawn_attacks_bb(Us, s);
leverPush = theirPawns & pawn_attacks_bb(Us, s + Up);
doubled = ourPawns & (s - Up);
neighbours = ourPawns & adjacent_files_bb(s);
phalanx = neighbours & rank_bb(s);
support = neighbours & rank_bb(s - Up);
// A pawn is backward when it is behind all pawns of the same color on
// the adjacent files and cannot safely advance.
backward = !(neighbours & forward_ranks_bb(Them, s + Up))
&& (leverPush | blocked);
// Compute additional span if pawn is not backward nor blocked
if (!backward && !blocked)
e->pawnAttacksSpan[Us] |= pawn_attack_span(Us, s);
// A pawn is passed if one of the three following conditions is true:
// (a) there is no stoppers except some levers
// (b) the only stoppers are the leverPush, but we outnumber them
// (c) there is only one front stopper which can be levered.
// (Refined in Evaluation::passed)
passed = !(stoppers ^ lever)
|| ( !(stoppers ^ leverPush)
&& popcount(phalanx) >= popcount(leverPush))
|| ( stoppers == blocked && r >= RANK_5
&& (shift<Up>(support) & ~(theirPawns | doubleAttackThem)));
passed &= !(forward_file_bb(Us, s) & ourPawns);
// Passed pawns will be properly scored later in evaluation when we have
// full attack info.
if (passed)
e->passedPawns[Us] |= s;
// Score this pawn
if (support | phalanx)
{
int v = Connected[r] * (2 + bool(phalanx) - bool(opposed))
+ 21 * popcount(support);
score += make_score(v, v * (r - 2) / 4);
}
else if (!neighbours)
{
if ( opposed
&& (ourPawns & forward_file_bb(Them, s))
&& !(theirPawns & adjacent_files_bb(s)))
score -= Doubled;
else
score -= Isolated
+ WeakUnopposed * !opposed;
}
else if (backward)
score -= Backward
+ WeakUnopposed * !opposed;
if (!support)
score -= Doubled * doubled
+ WeakLever * more_than_one(lever);
if (blocked && r > RANK_4)
score += BlockedPawn[r-4];
}
return score;
}
} // namespace
namespace Pawns {
/// Pawns::probe() looks up the current position's pawns configuration in
/// the pawns hash table. It returns a pointer to the Entry if the position
/// is found. Otherwise a new Entry is computed and stored there, so we don't
/// have to recompute all when the same pawns configuration occurs again.
Entry* probe(const Position& pos) {
Key key = pos.pawn_key();
Entry* e = pos.this_thread()->pawnsTable[key];
if (e->key == key)
return e;
e->key = key;
e->blockedCount = 0;
e->scores[WHITE] = evaluate<WHITE>(pos, e);
e->scores[BLACK] = evaluate<BLACK>(pos, e);
return e;
}
/// Entry::evaluate_shelter() calculates the shelter bonus and the storm
/// penalty for a king, looking at the king file and the two closest files.
template<Color Us>
Score Entry::evaluate_shelter(const Position& pos, Square ksq) const {
constexpr Color Them = ~Us;
Bitboard b = pos.pieces(PAWN) & ~forward_ranks_bb(Them, ksq);
Bitboard ourPawns = b & pos.pieces(Us) & ~pawnAttacks[Them];
Bitboard theirPawns = b & pos.pieces(Them);
Score bonus = make_score(5, 5);
File center = Utility::clamp(file_of(ksq), FILE_B, FILE_G);
for (File f = File(center - 1); f <= File(center + 1); ++f)
{
b = ourPawns & file_bb(f);
int ourRank = b ? relative_rank(Us, frontmost_sq(Them, b)) : 0;
b = theirPawns & file_bb(f);
int theirRank = b ? relative_rank(Us, frontmost_sq(Them, b)) : 0;
int d = edge_distance(f);
bonus += make_score(ShelterStrength[d][ourRank], 0);
if (ourRank && (ourRank == theirRank - 1))
bonus -= BlockedStorm[theirRank];
else
bonus -= make_score(UnblockedStorm[d][theirRank], 0);
}
return bonus;
}
/// Entry::do_king_safety() calculates a bonus for king safety. It is called only
/// when king square changes, which is about 20% of total king_safety() calls.
template<Color Us>
Score Entry::do_king_safety(const Position& pos) {
Square ksq = pos.square<KING>(Us);
kingSquares[Us] = ksq;
castlingRights[Us] = pos.castling_rights(Us);
auto compare = [](Score a, Score b) { return mg_value(a) < mg_value(b); };
Score shelter = evaluate_shelter<Us>(pos, ksq);
// If we can castle use the bonus after castling if it is bigger
if (pos.can_castle(Us & KING_SIDE))
shelter = std::max(shelter, evaluate_shelter<Us>(pos, relative_square(Us, SQ_G1)), compare);
if (pos.can_castle(Us & QUEEN_SIDE))
shelter = std::max(shelter, evaluate_shelter<Us>(pos, relative_square(Us, SQ_C1)), compare);
// In endgame we like to bring our king near our closest pawn
Bitboard pawns = pos.pieces(Us, PAWN);
int minPawnDist = 6;
if (pawns & attacks_bb<KING>(ksq))
minPawnDist = 1;
else while (pawns)
minPawnDist = std::min(minPawnDist, distance(ksq, pop_lsb(&pawns)));
return shelter - make_score(0, 16 * minPawnDist);
}
// Explicit template instantiation
template Score Entry::do_king_safety<WHITE>(const Position& pos);
template Score Entry::do_king_safety<BLACK>(const Position& pos);
} // namespace Pawns

70
src/pawns.h Normal file
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@@ -0,0 +1,70 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef PAWNS_H_INCLUDED
#define PAWNS_H_INCLUDED
#include "misc.h"
#include "position.h"
#include "types.h"
namespace Pawns {
/// Pawns::Entry contains various information about a pawn structure. A lookup
/// to the pawn hash table (performed by calling the probe function) returns a
/// pointer to an Entry object.
struct Entry {
Score pawn_score(Color c) const { return scores[c]; }
Bitboard pawn_attacks(Color c) const { return pawnAttacks[c]; }
Bitboard passed_pawns(Color c) const { return passedPawns[c]; }
Bitboard pawn_attacks_span(Color c) const { return pawnAttacksSpan[c]; }
int passed_count() const { return popcount(passedPawns[WHITE] | passedPawns[BLACK]); }
int blocked_count() const { return blockedCount; }
template<Color Us>
Score king_safety(const Position& pos) {
return kingSquares[Us] == pos.square<KING>(Us) && castlingRights[Us] == pos.castling_rights(Us)
? kingSafety[Us] : (kingSafety[Us] = do_king_safety<Us>(pos));
}
template<Color Us>
Score do_king_safety(const Position& pos);
template<Color Us>
Score evaluate_shelter(const Position& pos, Square ksq) const;
Key key;
Score scores[COLOR_NB];
Bitboard passedPawns[COLOR_NB];
Bitboard pawnAttacks[COLOR_NB];
Bitboard pawnAttacksSpan[COLOR_NB];
Square kingSquares[COLOR_NB];
Score kingSafety[COLOR_NB];
int castlingRights[COLOR_NB];
int blockedCount;
};
typedef HashTable<Entry, 131072> Table;
Entry* probe(const Position& pos);
} // namespace Pawns
#endif // #ifndef PAWNS_H_INCLUDED

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@@ -1,67 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef PERFT_H_INCLUDED
#define PERFT_H_INCLUDED
#include <cstdint>
#include "movegen.h"
#include "position.h"
#include "types.h"
#include "uci.h"
namespace Stockfish::Benchmark {
// Utility to verify move generation. All the leaf nodes up
// to the given depth are generated and counted, and the sum is returned.
template<bool Root>
uint64_t perft(Position& pos, Depth depth) {
StateInfo st;
uint64_t cnt, nodes = 0;
const bool leaf = (depth == 2);
for (const auto& m : MoveList<LEGAL>(pos))
{
if (Root && depth <= 1)
cnt = 1, nodes++;
else
{
pos.do_move(m, st);
cnt = leaf ? MoveList<LEGAL>(pos).size() : perft<false>(pos, depth - 1);
nodes += cnt;
pos.undo_move(m);
}
if (Root)
sync_cout << UCIEngine::move(m, pos.is_chess960()) << ": " << cnt << sync_endl;
}
return nodes;
}
inline uint64_t perft(const std::string& fen, Depth depth, bool isChess960) {
StateListPtr states(new std::deque<StateInfo>(1));
Position p;
p.set(fen, isChess960, &states->back());
return perft<true>(p, depth);
}
}
#endif // PERFT_H_INCLUDED

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@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -21,352 +21,445 @@
#include <cassert>
#include <deque>
#include <iosfwd>
#include <memory>
#include <memory> // For std::unique_ptr
#include <string>
#include "bitboard.h"
#include "evaluate.h"
#include "types.h"
namespace Stockfish {
#include "nnue/nnue_accumulator.h"
class TranspositionTable;
// StateInfo struct stores information needed to restore a Position object to
// its previous state when we retract a move. Whenever a move is made on the
// board (by calling Position::do_move), a StateInfo object must be passed.
/// StateInfo struct stores information needed to restore a Position object to
/// its previous state when we retract a move. Whenever a move is made on the
/// board (by calling Position::do_move), a StateInfo object must be passed.
struct StateInfo {
// Copied when making a move
Key materialKey;
Key pawnKey;
Key minorPieceKey;
Key nonPawnKey[COLOR_NB];
Value nonPawnMaterial[COLOR_NB];
int castlingRights;
int rule50;
int pliesFromNull;
Square epSquare;
// Copied when making a move
Key pawnKey;
Key materialKey;
Value nonPawnMaterial[COLOR_NB];
int castlingRights;
int rule50;
int pliesFromNull;
Square epSquare;
// Not copied when making a move (will be recomputed anyhow)
Key key;
Bitboard checkersBB;
StateInfo* previous;
Bitboard blockersForKing[COLOR_NB];
Bitboard pinners[COLOR_NB];
Bitboard checkSquares[PIECE_TYPE_NB];
Piece capturedPiece;
int repetition;
// Not copied when making a move (will be recomputed anyhow)
Key key;
Bitboard checkersBB;
Piece capturedPiece;
StateInfo* previous;
Bitboard blockersForKing[COLOR_NB];
Bitboard pinners[COLOR_NB];
Bitboard checkSquares[PIECE_TYPE_NB];
int repetition;
// Used by NNUE
Eval::NNUE::Accumulator accumulator;
DirtyPiece dirtyPiece;
};
// A list to keep track of the position states along the setup moves (from the
// start position to the position just before the search starts). Needed by
// 'draw by repetition' detection. Use a std::deque because pointers to
// elements are not invalidated upon list resizing.
using StateListPtr = std::unique_ptr<std::deque<StateInfo>>;
/// A list to keep track of the position states along the setup moves (from the
/// start position to the position just before the search starts). Needed by
/// 'draw by repetition' detection. Use a std::deque because pointers to
/// elements are not invalidated upon list resizing.
typedef std::unique_ptr<std::deque<StateInfo>> StateListPtr;
// Position class stores information regarding the board representation as
// pieces, side to move, hash keys, castling info, etc. Important methods are
// do_move() and undo_move(), used by the search to update node info when
// traversing the search tree.
/// Position class stores information regarding the board representation as
/// pieces, side to move, hash keys, castling info, etc. Important methods are
/// do_move() and undo_move(), used by the search to update node info when
/// traversing the search tree.
class Thread;
class Position {
public:
static void init();
public:
static void init();
Position() = default;
Position(const Position&) = delete;
Position& operator=(const Position&) = delete;
Position() = default;
Position(const Position&) = delete;
Position& operator=(const Position&) = delete;
// FEN string input/output
Position& set(const std::string& fenStr, bool isChess960, StateInfo* si);
Position& set(const std::string& code, Color c, StateInfo* si);
std::string fen() const;
// FEN string input/output
Position& set(const std::string& fenStr, bool isChess960, StateInfo* si, Thread* th);
Position& set(const std::string& code, Color c, StateInfo* si);
const std::string fen() const;
// Position representation
Bitboard pieces() const; // All pieces
template<typename... PieceTypes>
Bitboard pieces(PieceTypes... pts) const;
Bitboard pieces(Color c) const;
template<typename... PieceTypes>
Bitboard pieces(Color c, PieceTypes... pts) const;
Piece piece_on(Square s) const;
Square ep_square() const;
bool empty(Square s) const;
template<PieceType Pt>
int count(Color c) const;
template<PieceType Pt>
int count() const;
template<PieceType Pt>
Square square(Color c) const;
// Position representation
Bitboard pieces(PieceType pt) const;
Bitboard pieces(PieceType pt1, PieceType pt2) const;
Bitboard pieces(Color c) const;
Bitboard pieces(Color c, PieceType pt) const;
Bitboard pieces(Color c, PieceType pt1, PieceType pt2) const;
Piece piece_on(Square s) const;
Square ep_square() const;
bool empty(Square s) const;
template<PieceType Pt> int count(Color c) const;
template<PieceType Pt> int count() const;
template<PieceType Pt> const Square* squares(Color c) const;
template<PieceType Pt> Square square(Color c) const;
bool is_on_semiopen_file(Color c, Square s) const;
// Castling
CastlingRights castling_rights(Color c) const;
bool can_castle(CastlingRights cr) const;
bool castling_impeded(CastlingRights cr) const;
Square castling_rook_square(CastlingRights cr) const;
// Castling
CastlingRights castling_rights(Color c) const;
bool can_castle(CastlingRights cr) const;
bool castling_impeded(CastlingRights cr) const;
Square castling_rook_square(CastlingRights cr) const;
// Checking
Bitboard checkers() const;
Bitboard blockers_for_king(Color c) const;
Bitboard check_squares(PieceType pt) const;
Bitboard pinners(Color c) const;
// Checking
Bitboard checkers() const;
Bitboard blockers_for_king(Color c) const;
Bitboard check_squares(PieceType pt) const;
bool is_discovery_check_on_king(Color c, Move m) const;
// Attacks to/from a given square
Bitboard attackers_to(Square s) const;
Bitboard attackers_to(Square s, Bitboard occupied) const;
bool attackers_to_exist(Square s, Bitboard occupied, Color c) const;
void update_slider_blockers(Color c) const;
template<PieceType Pt>
Bitboard attacks_by(Color c) const;
// Attacks to/from a given square
Bitboard attackers_to(Square s) const;
Bitboard attackers_to(Square s, Bitboard occupied) const;
Bitboard slider_blockers(Bitboard sliders, Square s, Bitboard& pinners) const;
// Properties of moves
bool legal(Move m) const;
bool pseudo_legal(const Move m) const;
bool capture(Move m) const;
bool capture_stage(Move m) const;
bool gives_check(Move m) const;
Piece moved_piece(Move m) const;
Piece captured_piece() const;
// Properties of moves
bool legal(Move m) const;
bool pseudo_legal(const Move m) const;
bool capture(Move m) const;
bool capture_or_promotion(Move m) const;
bool gives_check(Move m) const;
bool advanced_pawn_push(Move m) const;
Piece moved_piece(Move m) const;
Piece captured_piece() const;
// Doing and undoing moves
void do_move(Move m, StateInfo& newSt, const TranspositionTable* tt);
DirtyPiece do_move(Move m, StateInfo& newSt, bool givesCheck, const TranspositionTable* tt);
void undo_move(Move m);
void do_null_move(StateInfo& newSt, const TranspositionTable& tt);
void undo_null_move();
// Piece specific
bool pawn_passed(Color c, Square s) const;
bool opposite_bishops() const;
int pawns_on_same_color_squares(Color c, Square s) const;
// Static Exchange Evaluation
bool see_ge(Move m, int threshold = 0) const;
// Doing and undoing moves
void do_move(Move m, StateInfo& newSt);
void do_move(Move m, StateInfo& newSt, bool givesCheck);
void undo_move(Move m);
void do_null_move(StateInfo& newSt);
void undo_null_move();
// Accessing hash keys
Key key() const;
Key material_key() const;
Key pawn_key() const;
Key minor_piece_key() const;
Key non_pawn_key(Color c) const;
// Static Exchange Evaluation
bool see_ge(Move m, Value threshold = VALUE_ZERO) const;
// Other properties of the position
Color side_to_move() const;
int game_ply() const;
bool is_chess960() const;
bool is_draw(int ply) const;
bool is_repetition(int ply) const;
bool upcoming_repetition(int ply) const;
bool has_repeated() const;
int rule50_count() const;
Value non_pawn_material(Color c) const;
Value non_pawn_material() const;
// Accessing hash keys
Key key() const;
Key key_after(Move m) const;
Key material_key() const;
Key pawn_key() const;
// Position consistency check, for debugging
bool pos_is_ok() const;
void flip();
// Other properties of the position
Color side_to_move() const;
int game_ply() const;
bool is_chess960() const;
Thread* this_thread() const;
bool is_draw(int ply) const;
bool has_game_cycle(int ply) const;
bool has_repeated() const;
int rule50_count() const;
Score psq_score() const;
Value non_pawn_material(Color c) const;
Value non_pawn_material() const;
StateInfo* state() const;
// Position consistency check, for debugging
bool pos_is_ok() const;
void flip();
void put_piece(Piece pc, Square s);
void remove_piece(Square s);
// Used by NNUE
StateInfo* state() const;
const EvalList* eval_list() const;
private:
// Initialization helpers (used while setting up a position)
void set_castling_right(Color c, Square rfrom);
void set_state() const;
void set_check_info() const;
private:
// Initialization helpers (used while setting up a position)
void set_castling_right(Color c, Square rfrom);
void set_state(StateInfo* si) const;
void set_check_info(StateInfo* si) const;
// Other helpers
void move_piece(Square from, Square to);
template<bool Do>
void do_castling(Color us,
Square from,
Square& to,
Square& rfrom,
Square& rto,
DirtyPiece* const dp = nullptr);
template<bool AfterMove>
Key adjust_key50(Key k) const;
// Other helpers
void put_piece(Piece pc, Square s);
void remove_piece(Square s);
void move_piece(Square from, Square to);
template<bool Do>
void do_castling(Color us, Square from, Square& to, Square& rfrom, Square& rto);
// Data members
Piece board[SQUARE_NB];
Bitboard byTypeBB[PIECE_TYPE_NB];
Bitboard byColorBB[COLOR_NB];
int pieceCount[PIECE_NB];
int castlingRightsMask[SQUARE_NB];
Square castlingRookSquare[CASTLING_RIGHT_NB];
Bitboard castlingPath[CASTLING_RIGHT_NB];
StateInfo* st;
int gamePly;
Color sideToMove;
bool chess960;
// ID of a piece on a given square
PieceId piece_id_on(Square sq) const;
// Data members
Piece board[SQUARE_NB];
Bitboard byTypeBB[PIECE_TYPE_NB];
Bitboard byColorBB[COLOR_NB];
int pieceCount[PIECE_NB];
Square pieceList[PIECE_NB][16];
int index[SQUARE_NB];
int castlingRightsMask[SQUARE_NB];
Square castlingRookSquare[CASTLING_RIGHT_NB];
Bitboard castlingPath[CASTLING_RIGHT_NB];
int gamePly;
Color sideToMove;
Score psq;
Thread* thisThread;
StateInfo* st;
bool chess960;
// List of pieces used in NNUE evaluation function
EvalList evalList;
};
std::ostream& operator<<(std::ostream& os, const Position& pos);
namespace PSQT {
extern Score psq[PIECE_NB][SQUARE_NB];
}
inline Color Position::side_to_move() const { return sideToMove; }
extern std::ostream& operator<<(std::ostream& os, const Position& pos);
inline Color Position::side_to_move() const {
return sideToMove;
}
inline Piece Position::piece_on(Square s) const {
assert(is_ok(s));
return board[s];
assert(is_ok(s));
return board[s];
}
inline bool Position::empty(Square s) const { return piece_on(s) == NO_PIECE; }
inline Piece Position::moved_piece(Move m) const { return piece_on(m.from_sq()); }
inline Bitboard Position::pieces() const { return byTypeBB[ALL_PIECES]; }
template<typename... PieceTypes>
inline Bitboard Position::pieces(PieceTypes... pts) const {
return (byTypeBB[pts] | ...);
inline bool Position::empty(Square s) const {
return piece_on(s) == NO_PIECE;
}
inline Bitboard Position::pieces(Color c) const { return byColorBB[c]; }
template<typename... PieceTypes>
inline Bitboard Position::pieces(Color c, PieceTypes... pts) const {
return pieces(c) & pieces(pts...);
inline Piece Position::moved_piece(Move m) const {
return piece_on(from_sq(m));
}
template<PieceType Pt>
inline int Position::count(Color c) const {
return pieceCount[make_piece(c, Pt)];
inline Bitboard Position::pieces(PieceType pt = ALL_PIECES) const {
return byTypeBB[pt];
}
template<PieceType Pt>
inline int Position::count() const {
return count<Pt>(WHITE) + count<Pt>(BLACK);
inline Bitboard Position::pieces(PieceType pt1, PieceType pt2) const {
return pieces(pt1) | pieces(pt2);
}
template<PieceType Pt>
inline Square Position::square(Color c) const {
assert(count<Pt>(c) == 1);
return lsb(pieces(c, Pt));
inline Bitboard Position::pieces(Color c) const {
return byColorBB[c];
}
inline Square Position::ep_square() const { return st->epSquare; }
inline Bitboard Position::pieces(Color c, PieceType pt) const {
return pieces(c) & pieces(pt);
}
inline bool Position::can_castle(CastlingRights cr) const { return st->castlingRights & cr; }
inline Bitboard Position::pieces(Color c, PieceType pt1, PieceType pt2) const {
return pieces(c) & (pieces(pt1) | pieces(pt2));
}
template<PieceType Pt> inline int Position::count(Color c) const {
return pieceCount[make_piece(c, Pt)];
}
template<PieceType Pt> inline int Position::count() const {
return count<Pt>(WHITE) + count<Pt>(BLACK);
}
template<PieceType Pt> inline const Square* Position::squares(Color c) const {
return pieceList[make_piece(c, Pt)];
}
template<PieceType Pt> inline Square Position::square(Color c) const {
assert(pieceCount[make_piece(c, Pt)] == 1);
return squares<Pt>(c)[0];
}
inline Square Position::ep_square() const {
return st->epSquare;
}
inline bool Position::is_on_semiopen_file(Color c, Square s) const {
return !(pieces(c, PAWN) & file_bb(s));
}
inline bool Position::can_castle(CastlingRights cr) const {
return st->castlingRights & cr;
}
inline CastlingRights Position::castling_rights(Color c) const {
return c & CastlingRights(st->castlingRights);
return c & CastlingRights(st->castlingRights);
}
inline bool Position::castling_impeded(CastlingRights cr) const {
assert(cr == WHITE_OO || cr == WHITE_OOO || cr == BLACK_OO || cr == BLACK_OOO);
return pieces() & castlingPath[cr];
assert(cr == WHITE_OO || cr == WHITE_OOO || cr == BLACK_OO || cr == BLACK_OOO);
return pieces() & castlingPath[cr];
}
inline Square Position::castling_rook_square(CastlingRights cr) const {
assert(cr == WHITE_OO || cr == WHITE_OOO || cr == BLACK_OO || cr == BLACK_OOO);
return castlingRookSquare[cr];
assert(cr == WHITE_OO || cr == WHITE_OOO || cr == BLACK_OO || cr == BLACK_OOO);
return castlingRookSquare[cr];
}
inline Bitboard Position::attackers_to(Square s) const { return attackers_to(s, pieces()); }
template<PieceType Pt>
inline Bitboard Position::attacks_by(Color c) const {
if constexpr (Pt == PAWN)
return c == WHITE ? pawn_attacks_bb<WHITE>(pieces(WHITE, PAWN))
: pawn_attacks_bb<BLACK>(pieces(BLACK, PAWN));
else
{
Bitboard threats = 0;
Bitboard attackers = pieces(c, Pt);
while (attackers)
threats |= attacks_bb<Pt>(pop_lsb(attackers), pieces());
return threats;
}
inline Bitboard Position::attackers_to(Square s) const {
return attackers_to(s, pieces());
}
inline Bitboard Position::checkers() const { return st->checkersBB; }
inline Bitboard Position::blockers_for_king(Color c) const { return st->blockersForKing[c]; }
inline Bitboard Position::pinners(Color c) const { return st->pinners[c]; }
inline Bitboard Position::check_squares(PieceType pt) const { return st->checkSquares[pt]; }
inline Key Position::key() const { return adjust_key50<false>(st->key); }
template<bool AfterMove>
inline Key Position::adjust_key50(Key k) const {
return st->rule50 < 14 - AfterMove ? k : k ^ make_key((st->rule50 - (14 - AfterMove)) / 8);
inline Bitboard Position::checkers() const {
return st->checkersBB;
}
inline Key Position::pawn_key() const { return st->pawnKey; }
inline Bitboard Position::blockers_for_king(Color c) const {
return st->blockersForKing[c];
}
inline Key Position::material_key() const { return st->materialKey; }
inline Bitboard Position::check_squares(PieceType pt) const {
return st->checkSquares[pt];
}
inline Key Position::minor_piece_key() const { return st->minorPieceKey; }
inline bool Position::is_discovery_check_on_king(Color c, Move m) const {
return st->blockersForKing[c] & from_sq(m);
}
inline Key Position::non_pawn_key(Color c) const { return st->nonPawnKey[c]; }
inline bool Position::pawn_passed(Color c, Square s) const {
return !(pieces(~c, PAWN) & passed_pawn_span(c, s));
}
inline Value Position::non_pawn_material(Color c) const { return st->nonPawnMaterial[c]; }
inline bool Position::advanced_pawn_push(Move m) const {
return type_of(moved_piece(m)) == PAWN
&& relative_rank(sideToMove, to_sq(m)) > RANK_5;
}
inline int Position::pawns_on_same_color_squares(Color c, Square s) const {
return popcount(pieces(c, PAWN) & ((DarkSquares & s) ? DarkSquares : ~DarkSquares));
}
inline Key Position::key() const {
return st->key;
}
inline Key Position::pawn_key() const {
return st->pawnKey;
}
inline Key Position::material_key() const {
return st->materialKey;
}
inline Score Position::psq_score() const {
return psq;
}
inline Value Position::non_pawn_material(Color c) const {
return st->nonPawnMaterial[c];
}
inline Value Position::non_pawn_material() const {
return non_pawn_material(WHITE) + non_pawn_material(BLACK);
return non_pawn_material(WHITE) + non_pawn_material(BLACK);
}
inline int Position::game_ply() const { return gamePly; }
inline int Position::game_ply() const {
return gamePly;
}
inline int Position::rule50_count() const { return st->rule50; }
inline int Position::rule50_count() const {
return st->rule50;
}
inline bool Position::is_chess960() const { return chess960; }
inline bool Position::opposite_bishops() const {
return count<BISHOP>(WHITE) == 1
&& count<BISHOP>(BLACK) == 1
&& opposite_colors(square<BISHOP>(WHITE), square<BISHOP>(BLACK));
}
inline bool Position::is_chess960() const {
return chess960;
}
inline bool Position::capture_or_promotion(Move m) const {
assert(is_ok(m));
return type_of(m) != NORMAL ? type_of(m) != CASTLING : !empty(to_sq(m));
}
inline bool Position::capture(Move m) const {
assert(m.is_ok());
return (!empty(m.to_sq()) && m.type_of() != CASTLING) || m.type_of() == EN_PASSANT;
assert(is_ok(m));
// Castling is encoded as "king captures rook"
return (!empty(to_sq(m)) && type_of(m) != CASTLING) || type_of(m) == ENPASSANT;
}
// Returns true if a move is generated from the capture stage, having also
// queen promotions covered, i.e. consistency with the capture stage move
// generation is needed to avoid the generation of duplicate moves.
inline bool Position::capture_stage(Move m) const {
assert(m.is_ok());
return capture(m) || m.promotion_type() == QUEEN;
inline Piece Position::captured_piece() const {
return st->capturedPiece;
}
inline Piece Position::captured_piece() const { return st->capturedPiece; }
inline Thread* Position::this_thread() const {
return thisThread;
}
inline void Position::put_piece(Piece pc, Square s) {
board[s] = pc;
byTypeBB[ALL_PIECES] |= byTypeBB[type_of(pc)] |= s;
byColorBB[color_of(pc)] |= s;
pieceCount[pc]++;
pieceCount[make_piece(color_of(pc), ALL_PIECES)]++;
board[s] = pc;
byTypeBB[ALL_PIECES] |= byTypeBB[type_of(pc)] |= s;
byColorBB[color_of(pc)] |= s;
index[s] = pieceCount[pc]++;
pieceList[pc][index[s]] = s;
pieceCount[make_piece(color_of(pc), ALL_PIECES)]++;
psq += PSQT::psq[pc][s];
}
inline void Position::remove_piece(Square s) {
Piece pc = board[s];
byTypeBB[ALL_PIECES] ^= s;
byTypeBB[type_of(pc)] ^= s;
byColorBB[color_of(pc)] ^= s;
board[s] = NO_PIECE;
pieceCount[pc]--;
pieceCount[make_piece(color_of(pc), ALL_PIECES)]--;
// WARNING: This is not a reversible operation. If we remove a piece in
// do_move() and then replace it in undo_move() we will put it at the end of
// the list and not in its original place, it means index[] and pieceList[]
// are not invariant to a do_move() + undo_move() sequence.
Piece pc = board[s];
byTypeBB[ALL_PIECES] ^= s;
byTypeBB[type_of(pc)] ^= s;
byColorBB[color_of(pc)] ^= s;
/* board[s] = NO_PIECE; Not needed, overwritten by the capturing one */
Square lastSquare = pieceList[pc][--pieceCount[pc]];
index[lastSquare] = index[s];
pieceList[pc][index[lastSquare]] = lastSquare;
pieceList[pc][pieceCount[pc]] = SQ_NONE;
pieceCount[make_piece(color_of(pc), ALL_PIECES)]--;
psq -= PSQT::psq[pc][s];
}
inline void Position::move_piece(Square from, Square to) {
Piece pc = board[from];
Bitboard fromTo = from | to;
byTypeBB[ALL_PIECES] ^= fromTo;
byTypeBB[type_of(pc)] ^= fromTo;
byColorBB[color_of(pc)] ^= fromTo;
board[from] = NO_PIECE;
board[to] = pc;
// index[from] is not updated and becomes stale. This works as long as index[]
// is accessed just by known occupied squares.
Piece pc = board[from];
Bitboard fromTo = from | to;
byTypeBB[ALL_PIECES] ^= fromTo;
byTypeBB[type_of(pc)] ^= fromTo;
byColorBB[color_of(pc)] ^= fromTo;
board[from] = NO_PIECE;
board[to] = pc;
index[to] = index[from];
pieceList[pc][index[to]] = to;
psq += PSQT::psq[pc][to] - PSQT::psq[pc][from];
}
inline void Position::do_move(Move m, StateInfo& newSt, const TranspositionTable* tt = nullptr) {
do_move(m, newSt, gives_check(m), tt);
inline void Position::do_move(Move m, StateInfo& newSt) {
do_move(m, newSt, gives_check(m));
}
inline StateInfo* Position::state() const { return st; }
inline StateInfo* Position::state() const {
} // namespace Stockfish
return st;
}
#endif // #ifndef POSITION_H_INCLUDED
inline const EvalList* Position::eval_list() const {
return &evalList;
}
inline PieceId Position::piece_id_on(Square sq) const
{
assert(piece_on(sq) != NO_PIECE);
PieceId pid = evalList.piece_id_list[sq];
assert(is_ok(pid));
return pid;
}
#endif // #ifndef POSITION_H_INCLUDED

122
src/psqt.cpp Normal file
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@@ -0,0 +1,122 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include <algorithm>
#include "types.h"
#include "bitboard.h"
namespace PSQT {
#define S(mg, eg) make_score(mg, eg)
// Bonus[PieceType][Square / 2] contains Piece-Square scores. For each piece
// type on a given square a (middlegame, endgame) score pair is assigned. Table
// is defined for files A..D and white side: it is symmetric for black side and
// second half of the files.
constexpr Score Bonus[][RANK_NB][int(FILE_NB) / 2] = {
{ },
{ },
{ // Knight
{ S(-175, -96), S(-92,-65), S(-74,-49), S(-73,-21) },
{ S( -77, -67), S(-41,-54), S(-27,-18), S(-15, 8) },
{ S( -61, -40), S(-17,-27), S( 6, -8), S( 12, 29) },
{ S( -35, -35), S( 8, -2), S( 40, 13), S( 49, 28) },
{ S( -34, -45), S( 13,-16), S( 44, 9), S( 51, 39) },
{ S( -9, -51), S( 22,-44), S( 58,-16), S( 53, 17) },
{ S( -67, -69), S(-27,-50), S( 4,-51), S( 37, 12) },
{ S(-201,-100), S(-83,-88), S(-56,-56), S(-26,-17) }
},
{ // Bishop
{ S(-53,-57), S( -5,-30), S( -8,-37), S(-23,-12) },
{ S(-15,-37), S( 8,-13), S( 19,-17), S( 4, 1) },
{ S( -7,-16), S( 21, -1), S( -5, -2), S( 17, 10) },
{ S( -5,-20), S( 11, -6), S( 25, 0), S( 39, 17) },
{ S(-12,-17), S( 29, -1), S( 22,-14), S( 31, 15) },
{ S(-16,-30), S( 6, 6), S( 1, 4), S( 11, 6) },
{ S(-17,-31), S(-14,-20), S( 5, -1), S( 0, 1) },
{ S(-48,-46), S( 1,-42), S(-14,-37), S(-23,-24) }
},
{ // Rook
{ S(-31, -9), S(-20,-13), S(-14,-10), S(-5, -9) },
{ S(-21,-12), S(-13, -9), S( -8, -1), S( 6, -2) },
{ S(-25, 6), S(-11, -8), S( -1, -2), S( 3, -6) },
{ S(-13, -6), S( -5, 1), S( -4, -9), S(-6, 7) },
{ S(-27, -5), S(-15, 8), S( -4, 7), S( 3, -6) },
{ S(-22, 6), S( -2, 1), S( 6, -7), S(12, 10) },
{ S( -2, 4), S( 12, 5), S( 16, 20), S(18, -5) },
{ S(-17, 18), S(-19, 0), S( -1, 19), S( 9, 13) }
},
{ // Queen
{ S( 3,-69), S(-5,-57), S(-5,-47), S( 4,-26) },
{ S(-3,-55), S( 5,-31), S( 8,-22), S(12, -4) },
{ S(-3,-39), S( 6,-18), S(13, -9), S( 7, 3) },
{ S( 4,-23), S( 5, -3), S( 9, 13), S( 8, 24) },
{ S( 0,-29), S(14, -6), S(12, 9), S( 5, 21) },
{ S(-4,-38), S(10,-18), S( 6,-12), S( 8, 1) },
{ S(-5,-50), S( 6,-27), S(10,-24), S( 8, -8) },
{ S(-2,-75), S(-2,-52), S( 1,-43), S(-2,-36) }
},
{ // King
{ S(271, 1), S(327, 45), S(271, 85), S(198, 76) },
{ S(278, 53), S(303,100), S(234,133), S(179,135) },
{ S(195, 88), S(258,130), S(169,169), S(120,175) },
{ S(164,103), S(190,156), S(138,172), S( 98,172) },
{ S(154, 96), S(179,166), S(105,199), S( 70,199) },
{ S(123, 92), S(145,172), S( 81,184), S( 31,191) },
{ S( 88, 47), S(120,121), S( 65,116), S( 33,131) },
{ S( 59, 11), S( 89, 59), S( 45, 73), S( -1, 78) }
}
};
constexpr Score PBonus[RANK_NB][FILE_NB] =
{ // Pawn (asymmetric distribution)
{ },
{ S( 3,-10), S( 3, -6), S( 10, 10), S( 19, 0), S( 16, 14), S( 19, 7), S( 7, -5), S( -5,-19) },
{ S( -9,-10), S(-15,-10), S( 11,-10), S( 15, 4), S( 32, 4), S( 22, 3), S( 5, -6), S(-22, -4) },
{ S( -4, 6), S(-23, -2), S( 6, -8), S( 20, -4), S( 40,-13), S( 17,-12), S( 4,-10), S( -8, -9) },
{ S( 13, 10), S( 0, 5), S(-13, 4), S( 1, -5), S( 11, -5), S( -2, -5), S(-13, 14), S( 5, 9) },
{ S( 5, 28), S(-12, 20), S( -7, 21), S( 22, 28), S( -8, 30), S( -5, 7), S(-15, 6), S( -8, 13) },
{ S( -7, 0), S( 7,-11), S( -3, 12), S(-13, 21), S( 5, 25), S(-16, 19), S( 10, 4), S( -8, 7) }
};
#undef S
Score psq[PIECE_NB][SQUARE_NB];
// PSQT::init() initializes piece-square tables: the white halves of the tables are
// copied from Bonus[] and PBonus[], adding the piece value, then the black halves of
// the tables are initialized by flipping and changing the sign of the white scores.
void init() {
for (Piece pc : {W_PAWN, W_KNIGHT, W_BISHOP, W_ROOK, W_QUEEN, W_KING})
{
Score score = make_score(PieceValue[MG][pc], PieceValue[EG][pc]);
for (Square s = SQ_A1; s <= SQ_H8; ++s)
{
File f = File(edge_distance(file_of(s)));
psq[ pc][s] = score + (type_of(pc) == PAWN ? PBonus[rank_of(s)][file_of(s)]
: Bonus[pc][rank_of(s)][f]);
psq[~pc][flip_rank(s)] = -psq[pc][s];
}
}
}
} // namespace PSQT

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@@ -1,48 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include "score.h"
#include <cassert>
#include <cmath>
#include <cstdlib>
#include "uci.h"
namespace Stockfish {
Score::Score(Value v, const Position& pos) {
assert(-VALUE_INFINITE < v && v < VALUE_INFINITE);
if (!is_decisive(v))
{
score = InternalUnits{UCIEngine::to_cp(v, pos)};
}
else if (std::abs(v) <= VALUE_TB)
{
auto distance = VALUE_TB - std::abs(v);
score = (v > 0) ? Tablebase{distance, true} : Tablebase{-distance, false};
}
else
{
auto distance = VALUE_MATE - std::abs(v);
score = (v > 0) ? Mate{distance} : Mate{-distance};
}
}
}

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@@ -1,70 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef SCORE_H_INCLUDED
#define SCORE_H_INCLUDED
#include <variant>
#include <utility>
#include "types.h"
namespace Stockfish {
class Position;
class Score {
public:
struct Mate {
int plies;
};
struct Tablebase {
int plies;
bool win;
};
struct InternalUnits {
int value;
};
Score() = default;
Score(Value v, const Position& pos);
template<typename T>
bool is() const {
return std::holds_alternative<T>(score);
}
template<typename T>
T get() const {
return std::get<T>(score);
}
template<typename F>
decltype(auto) visit(F&& f) const {
return std::visit(std::forward<F>(f), score);
}
private:
std::variant<Mate, Tablebase, InternalUnits> score;
};
}
#endif // #ifndef SCORE_H_INCLUDED

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@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -19,358 +19,90 @@
#ifndef SEARCH_H_INCLUDED
#define SEARCH_H_INCLUDED
#include <algorithm>
#include <array>
#include <atomic>
#include <cassert>
#include <cstddef>
#include <cstdint>
#include <functional>
#include <memory>
#include <string>
#include <string_view>
#include <vector>
#include "history.h"
#include "misc.h"
#include "nnue/network.h"
#include "nnue/nnue_accumulator.h"
#include "numa.h"
#include "position.h"
#include "score.h"
#include "syzygy/tbprobe.h"
#include "timeman.h"
#include "movepick.h"
#include "types.h"
namespace Stockfish {
// Different node types, used as a template parameter
enum NodeType {
NonPV,
PV,
Root
};
class TranspositionTable;
class ThreadPool;
class OptionsMap;
class Position;
namespace Search {
// Stack struct keeps track of the information we need to remember from nodes
// shallower and deeper in the tree during the search. Each search thread has
// its own array of Stack objects, indexed by the current ply.
/// Threshold used for countermoves based pruning
constexpr int CounterMovePruneThreshold = 0;
/// Stack struct keeps track of the information we need to remember from nodes
/// shallower and deeper in the tree during the search. Each search thread has
/// its own array of Stack objects, indexed by the current ply.
struct Stack {
Move* pv;
PieceToHistory* continuationHistory;
CorrectionHistory<PieceTo>* continuationCorrectionHistory;
int ply;
Move currentMove;
Move excludedMove;
Value staticEval;
int statScore;
int moveCount;
bool inCheck;
bool ttPv;
bool ttHit;
int cutoffCnt;
int reduction;
bool isPvNode;
int quietMoveStreak;
Move* pv;
PieceToHistory* continuationHistory;
int ply;
Move currentMove;
Move excludedMove;
Move killers[2];
Value staticEval;
int statScore;
int moveCount;
bool inCheck;
};
// RootMove struct is used for moves at the root of the tree. For each root move
// we store a score and a PV (really a refutation in the case of moves which
// fail low). Score is normally set at -VALUE_INFINITE for all non-pv moves.
/// RootMove struct is used for moves at the root of the tree. For each root move
/// we store a score and a PV (really a refutation in the case of moves which
/// fail low). Score is normally set at -VALUE_INFINITE for all non-pv moves.
struct RootMove {
explicit RootMove(Move m) :
pv(1, m) {}
bool extract_ponder_from_tt(const TranspositionTable& tt, Position& pos);
bool operator==(const Move& m) const { return pv[0] == m; }
// Sort in descending order
bool operator<(const RootMove& m) const {
return m.score != score ? m.score < score : m.previousScore < previousScore;
}
explicit RootMove(Move m) : pv(1, m) {}
bool extract_ponder_from_tt(Position& pos);
bool operator==(const Move& m) const { return pv[0] == m; }
bool operator<(const RootMove& m) const { // Sort in descending order
return m.score != score ? m.score < score
: m.previousScore < previousScore;
}
uint64_t effort = 0;
Value score = -VALUE_INFINITE;
Value previousScore = -VALUE_INFINITE;
Value averageScore = -VALUE_INFINITE;
Value meanSquaredScore = -VALUE_INFINITE * VALUE_INFINITE;
Value uciScore = -VALUE_INFINITE;
bool scoreLowerbound = false;
bool scoreUpperbound = false;
int selDepth = 0;
int tbRank = 0;
Value tbScore;
std::vector<Move> pv;
Value score = -VALUE_INFINITE;
Value previousScore = -VALUE_INFINITE;
int selDepth = 0;
int tbRank = 0;
int bestMoveCount = 0;
Value tbScore;
std::vector<Move> pv;
};
using RootMoves = std::vector<RootMove>;
typedef std::vector<RootMove> RootMoves;
// LimitsType struct stores information sent by the caller about the analysis required.
/// LimitsType struct stores information sent by GUI about available time to
/// search the current move, maximum depth/time, or if we are in analysis mode.
struct LimitsType {
// Init explicitly due to broken value-initialization of non POD in MSVC
LimitsType() {
time[WHITE] = time[BLACK] = inc[WHITE] = inc[BLACK] = npmsec = movetime = TimePoint(0);
movestogo = depth = mate = perft = infinite = 0;
nodes = 0;
ponderMode = false;
}
LimitsType() { // Init explicitly due to broken value-initialization of non POD in MSVC
time[WHITE] = time[BLACK] = inc[WHITE] = inc[BLACK] = npmsec = movetime = TimePoint(0);
movestogo = depth = mate = perft = infinite = 0;
nodes = 0;
}
bool use_time_management() const { return time[WHITE] || time[BLACK]; }
bool use_time_management() const {
return time[WHITE] || time[BLACK];
}
std::vector<std::string> searchmoves;
TimePoint time[COLOR_NB], inc[COLOR_NB], npmsec, movetime, startTime;
int movestogo, depth, mate, perft, infinite;
uint64_t nodes;
bool ponderMode;
std::vector<Move> searchmoves;
TimePoint time[COLOR_NB], inc[COLOR_NB], npmsec, movetime, startTime;
int movestogo, depth, mate, perft, infinite;
int64_t nodes;
};
extern LimitsType Limits;
// The UCI stores the uci options, thread pool, and transposition table.
// This struct is used to easily forward data to the Search::Worker class.
struct SharedState {
SharedState(const OptionsMap& optionsMap,
ThreadPool& threadPool,
TranspositionTable& transpositionTable,
const LazyNumaReplicated<Eval::NNUE::Networks>& nets) :
options(optionsMap),
threads(threadPool),
tt(transpositionTable),
networks(nets) {}
void init();
void clear();
const OptionsMap& options;
ThreadPool& threads;
TranspositionTable& tt;
const LazyNumaReplicated<Eval::NNUE::Networks>& networks;
};
} // namespace Search
class Worker;
// Null Object Pattern, implement a common interface for the SearchManagers.
// A Null Object will be given to non-mainthread workers.
class ISearchManager {
public:
virtual ~ISearchManager() {}
virtual void check_time(Search::Worker&) = 0;
};
struct InfoShort {
int depth;
Score score;
};
struct InfoFull: InfoShort {
int selDepth;
size_t multiPV;
std::string_view wdl;
std::string_view bound;
size_t timeMs;
size_t nodes;
size_t nps;
size_t tbHits;
std::string_view pv;
int hashfull;
};
struct InfoIteration {
int depth;
std::string_view currmove;
size_t currmovenumber;
};
// Skill structure is used to implement strength limit. If we have a UCI_Elo,
// we convert it to an appropriate skill level, anchored to the Stash engine.
// This method is based on a fit of the Elo results for games played between
// Stockfish at various skill levels and various versions of the Stash engine.
// Skill 0 .. 19 now covers CCRL Blitz Elo from 1320 to 3190, approximately
// Reference: https://github.com/vondele/Stockfish/commit/a08b8d4e9711c2
struct Skill {
// Lowest and highest Elo ratings used in the skill level calculation
constexpr static int LowestElo = 1320;
constexpr static int HighestElo = 3190;
Skill(int skill_level, int uci_elo) {
if (uci_elo)
{
double e = double(uci_elo - LowestElo) / (HighestElo - LowestElo);
level = std::clamp((((37.2473 * e - 40.8525) * e + 22.2943) * e - 0.311438), 0.0, 19.0);
}
else
level = double(skill_level);
}
bool enabled() const { return level < 20.0; }
bool time_to_pick(Depth depth) const { return depth == 1 + int(level); }
Move pick_best(const RootMoves&, size_t multiPV);
double level;
Move best = Move::none();
};
// SearchManager manages the search from the main thread. It is responsible for
// keeping track of the time, and storing data strictly related to the main thread.
class SearchManager: public ISearchManager {
public:
using UpdateShort = std::function<void(const InfoShort&)>;
using UpdateFull = std::function<void(const InfoFull&)>;
using UpdateIter = std::function<void(const InfoIteration&)>;
using UpdateBestmove = std::function<void(std::string_view, std::string_view)>;
struct UpdateContext {
UpdateShort onUpdateNoMoves;
UpdateFull onUpdateFull;
UpdateIter onIter;
UpdateBestmove onBestmove;
};
SearchManager(const UpdateContext& updateContext) :
updates(updateContext) {}
void check_time(Search::Worker& worker) override;
void pv(Search::Worker& worker,
const ThreadPool& threads,
const TranspositionTable& tt,
Depth depth);
Stockfish::TimeManagement tm;
double originalTimeAdjust;
int callsCnt;
std::atomic_bool ponder;
std::array<Value, 4> iterValue;
double previousTimeReduction;
Value bestPreviousScore;
Value bestPreviousAverageScore;
bool stopOnPonderhit;
size_t id;
const UpdateContext& updates;
};
class NullSearchManager: public ISearchManager {
public:
void check_time(Search::Worker&) override {}
};
// Search::Worker is the class that does the actual search.
// It is instantiated once per thread, and it is responsible for keeping track
// of the search history, and storing data required for the search.
class Worker {
public:
Worker(SharedState&, std::unique_ptr<ISearchManager>, size_t, NumaReplicatedAccessToken);
// Called at instantiation to initialize reductions tables.
// Reset histories, usually before a new game.
void clear();
// Called when the program receives the UCI 'go' command.
// It searches from the root position and outputs the "bestmove".
void start_searching();
bool is_mainthread() const { return threadIdx == 0; }
void ensure_network_replicated();
// Public because they need to be updatable by the stats
ButterflyHistory mainHistory;
LowPlyHistory lowPlyHistory;
CapturePieceToHistory captureHistory;
ContinuationHistory continuationHistory[2][2];
PawnHistory pawnHistory;
CorrectionHistory<Pawn> pawnCorrectionHistory;
CorrectionHistory<Minor> minorPieceCorrectionHistory;
CorrectionHistory<NonPawn> nonPawnCorrectionHistory;
CorrectionHistory<Continuation> continuationCorrectionHistory;
TTMoveHistory ttMoveHistory;
private:
void iterative_deepening();
void do_move(Position& pos, const Move move, StateInfo& st);
void do_move(Position& pos, const Move move, StateInfo& st, const bool givesCheck);
void do_null_move(Position& pos, StateInfo& st);
void undo_move(Position& pos, const Move move);
void undo_null_move(Position& pos);
// This is the main search function, for both PV and non-PV nodes
template<NodeType nodeType>
Value search(Position& pos, Stack* ss, Value alpha, Value beta, Depth depth, bool cutNode);
// Quiescence search function, which is called by the main search
template<NodeType nodeType>
Value qsearch(Position& pos, Stack* ss, Value alpha, Value beta);
Depth reduction(bool i, Depth d, int mn, int delta) const;
// Pointer to the search manager, only allowed to be called by the main thread
SearchManager* main_manager() const {
assert(threadIdx == 0);
return static_cast<SearchManager*>(manager.get());
}
TimePoint elapsed() const;
TimePoint elapsed_time() const;
Value evaluate(const Position&);
LimitsType limits;
size_t pvIdx, pvLast;
std::atomic<uint64_t> nodes, tbHits, bestMoveChanges;
int selDepth, nmpMinPly;
Value optimism[COLOR_NB];
Position rootPos;
StateInfo rootState;
RootMoves rootMoves;
Depth rootDepth, completedDepth;
Value rootDelta;
size_t threadIdx;
NumaReplicatedAccessToken numaAccessToken;
// Reductions lookup table initialized at startup
std::array<int, MAX_MOVES> reductions; // [depth or moveNumber]
// The main thread has a SearchManager, the others have a NullSearchManager
std::unique_ptr<ISearchManager> manager;
Tablebases::Config tbConfig;
const OptionsMap& options;
ThreadPool& threads;
TranspositionTable& tt;
const LazyNumaReplicated<Eval::NNUE::Networks>& networks;
// Used by NNUE
Eval::NNUE::AccumulatorStack accumulatorStack;
Eval::NNUE::AccumulatorCaches refreshTable;
friend class Stockfish::ThreadPool;
friend class SearchManager;
};
struct ConthistBonus {
int index;
int weight;
};
} // namespace Search
} // namespace Stockfish
#endif // #ifndef SEARCH_H_INCLUDED
#endif // #ifndef SEARCH_H_INCLUDED

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@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -19,60 +19,60 @@
#ifndef TBPROBE_H
#define TBPROBE_H
#include <string>
#include <vector>
#include <ostream>
#include "../search.h"
namespace Stockfish {
class Position;
class OptionsMap;
using Depth = int;
namespace Search {
struct RootMove;
using RootMoves = std::vector<RootMove>;
}
}
namespace Stockfish::Tablebases {
struct Config {
int cardinality = 0;
bool rootInTB = false;
bool useRule50 = false;
Depth probeDepth = 0;
};
namespace Tablebases {
enum WDLScore {
WDLLoss = -2, // Loss
WDLBlessedLoss = -1, // Loss, but draw under 50-move rule
WDLDraw = 0, // Draw
WDLCursedWin = 1, // Win, but draw under 50-move rule
WDLWin = 2, // Win
WDLLoss = -2, // Loss
WDLBlessedLoss = -1, // Loss, but draw under 50-move rule
WDLDraw = 0, // Draw
WDLCursedWin = 1, // Win, but draw under 50-move rule
WDLWin = 2, // Win
WDLScoreNone = -1000
};
// Possible states after a probing operation
enum ProbeState {
FAIL = 0, // Probe failed (missing file table)
OK = 1, // Probe successful
CHANGE_STM = -1, // DTZ should check the other side
ZEROING_BEST_MOVE = 2 // Best move zeroes DTZ (capture or pawn move)
FAIL = 0, // Probe failed (missing file table)
OK = 1, // Probe succesful
CHANGE_STM = -1, // DTZ should check the other side
ZEROING_BEST_MOVE = 2 // Best move zeroes DTZ (capture or pawn move)
};
extern int MaxCardinality;
void init(const std::string& paths);
void init(const std::string& paths);
WDLScore probe_wdl(Position& pos, ProbeState* result);
int probe_dtz(Position& pos, ProbeState* result);
bool root_probe(Position& pos, Search::RootMoves& rootMoves, bool rule50, bool rankDTZ);
bool root_probe_wdl(Position& pos, Search::RootMoves& rootMoves, bool rule50);
Config rank_root_moves(const OptionsMap& options,
Position& pos,
Search::RootMoves& rootMoves,
bool rankDTZ = false);
int probe_dtz(Position& pos, ProbeState* result);
bool root_probe(Position& pos, Search::RootMoves& rootMoves);
bool root_probe_wdl(Position& pos, Search::RootMoves& rootMoves);
void rank_root_moves(Position& pos, Search::RootMoves& rootMoves);
} // namespace Stockfish::Tablebases
inline std::ostream& operator<<(std::ostream& os, const WDLScore v) {
os << (v == WDLLoss ? "Loss" :
v == WDLBlessedLoss ? "Blessed loss" :
v == WDLDraw ? "Draw" :
v == WDLCursedWin ? "Cursed win" :
v == WDLWin ? "Win" : "None");
return os;
}
inline std::ostream& operator<<(std::ostream& os, const ProbeState v) {
os << (v == FAIL ? "Failed" :
v == OK ? "Success" :
v == CHANGE_STM ? "Probed opponent side" :
v == ZEROING_BEST_MOVE ? "Best move zeroes DTZ" : "None");
return os;
}
}
#endif

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@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -16,395 +16,259 @@
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include "thread.h"
#include <algorithm>
#include <cassert>
#include <deque>
#include <memory>
#include <string>
#include <unordered_map>
#include <utility>
#include <algorithm> // For std::count
#include "movegen.h"
#include "search.h"
#include "syzygy/tbprobe.h"
#include "timeman.h"
#include "types.h"
#include "thread.h"
#include "uci.h"
#include "ucioption.h"
#include "syzygy/tbprobe.h"
#include "tt.h"
namespace Stockfish {
ThreadPool Threads; // Global object
// Constructor launches the thread and waits until it goes to sleep
// in idle_loop(). Note that 'searching' and 'exit' should be already set.
Thread::Thread(Search::SharedState& sharedState,
std::unique_ptr<Search::ISearchManager> sm,
size_t n,
OptionalThreadToNumaNodeBinder binder) :
idx(n),
nthreads(sharedState.options["Threads"]),
stdThread(&Thread::idle_loop, this) {
wait_for_search_finished();
/// Thread constructor launches the thread and waits until it goes to sleep
/// in idle_loop(). Note that 'searching' and 'exit' should be already set.
run_custom_job([this, &binder, &sharedState, &sm, n]() {
// Use the binder to [maybe] bind the threads to a NUMA node before doing
// the Worker allocation. Ideally we would also allocate the SearchManager
// here, but that's minor.
this->numaAccessToken = binder();
this->worker =
std::make_unique<Search::Worker>(sharedState, std::move(sm), n, this->numaAccessToken);
});
Thread::Thread(size_t n) : idx(n), stdThread(&Thread::idle_loop, this) {
wait_for_search_finished();
wait_for_search_finished();
}
// Destructor wakes up the thread in idle_loop() and waits
// for its termination. Thread should be already waiting.
/// Thread destructor wakes up the thread in idle_loop() and waits
/// for its termination. Thread should be already waiting.
Thread::~Thread() {
assert(!searching);
assert(!searching);
exit = true;
start_searching();
stdThread.join();
exit = true;
start_searching();
stdThread.join();
}
// Wakes up the thread that will start the search
/// Thread::bestMoveCount(Move move) return best move counter for the given root move
int Thread::best_move_count(Move move) const {
auto rm = std::find(rootMoves.begin() + pvIdx,
rootMoves.begin() + pvLast, move);
return rm != rootMoves.begin() + pvLast ? rm->bestMoveCount : 0;
}
/// Thread::clear() reset histories, usually before a new game
void Thread::clear() {
counterMoves.fill(MOVE_NONE);
mainHistory.fill(0);
lowPlyHistory.fill(0);
captureHistory.fill(0);
for (bool inCheck : { false, true })
for (StatsType c : { NoCaptures, Captures })
{
for (auto& to : continuationHistory[inCheck][c])
for (auto& h : to)
h->fill(0);
continuationHistory[inCheck][c][NO_PIECE][0]->fill(Search::CounterMovePruneThreshold - 1);
}
}
/// Thread::start_searching() wakes up the thread that will start the search
void Thread::start_searching() {
assert(worker != nullptr);
run_custom_job([this]() { worker->start_searching(); });
std::lock_guard<std::mutex> lk(mutex);
searching = true;
cv.notify_one(); // Wake up the thread in idle_loop()
}
// Clears the histories for the thread worker (usually before a new game)
void Thread::clear_worker() {
assert(worker != nullptr);
run_custom_job([this]() { worker->clear(); });
}
// Blocks on the condition variable until the thread has finished searching
/// Thread::wait_for_search_finished() blocks on the condition variable
/// until the thread has finished searching.
void Thread::wait_for_search_finished() {
std::unique_lock<std::mutex> lk(mutex);
cv.wait(lk, [&] { return !searching; });
std::unique_lock<std::mutex> lk(mutex);
cv.wait(lk, [&]{ return !searching; });
}
// Launching a function in the thread
void Thread::run_custom_job(std::function<void()> f) {
{
std::unique_lock<std::mutex> lk(mutex);
cv.wait(lk, [&] { return !searching; });
jobFunc = std::move(f);
searching = true;
}
cv.notify_one();
}
void Thread::ensure_network_replicated() { worker->ensure_network_replicated(); }
// Thread gets parked here, blocked on the condition variable
// when the thread has no work to do.
/// Thread::idle_loop() is where the thread is parked, blocked on the
/// condition variable, when it has no work to do.
void Thread::idle_loop() {
while (true)
{
std::unique_lock<std::mutex> lk(mutex);
searching = false;
cv.notify_one(); // Wake up anyone waiting for search finished
cv.wait(lk, [&] { return searching; });
if (exit)
return;
// If OS already scheduled us on a different group than 0 then don't overwrite
// the choice, eventually we are one of many one-threaded processes running on
// some Windows NUMA hardware, for instance in fishtest. To make it simple,
// just check if running threads are below a threshold, in this case all this
// NUMA machinery is not needed.
if (Options["Threads"] > 8)
WinProcGroup::bindThisThread(idx);
std::function<void()> job = std::move(jobFunc);
jobFunc = nullptr;
while (true)
{
std::unique_lock<std::mutex> lk(mutex);
searching = false;
cv.notify_one(); // Wake up anyone waiting for search finished
cv.wait(lk, [&]{ return searching; });
lk.unlock();
if (exit)
return;
if (job)
job();
}
lk.unlock();
search();
}
}
Search::SearchManager* ThreadPool::main_manager() { return main_thread()->worker->main_manager(); }
/// ThreadPool::set() creates/destroys threads to match the requested number.
/// Created and launched threads will immediately go to sleep in idle_loop.
/// Upon resizing, threads are recreated to allow for binding if necessary.
uint64_t ThreadPool::nodes_searched() const { return accumulate(&Search::Worker::nodes); }
uint64_t ThreadPool::tb_hits() const { return accumulate(&Search::Worker::tbHits); }
void ThreadPool::set(size_t requested) {
// Creates/destroys threads to match the requested number.
// Created and launched threads will immediately go to sleep in idle_loop.
// Upon resizing, threads are recreated to allow for binding if necessary.
void ThreadPool::set(const NumaConfig& numaConfig,
Search::SharedState sharedState,
const Search::SearchManager::UpdateContext& updateContext) {
if (size() > 0) { // destroy any existing thread(s)
main()->wait_for_search_finished();
if (threads.size() > 0) // destroy any existing thread(s)
{
main_thread()->wait_for_search_finished();
while (size() > 0)
delete back(), pop_back();
}
threads.clear();
if (requested > 0) { // create new thread(s)
push_back(new MainThread(0));
boundThreadToNumaNode.clear();
}
while (size() < requested)
push_back(new Thread(size()));
clear();
const size_t requested = sharedState.options["Threads"];
// Reallocate the hash with the new threadpool size
TT.resize(size_t(Options["Hash"]));
if (requested > 0) // create new thread(s)
{
// Binding threads may be problematic when there's multiple NUMA nodes and
// multiple Stockfish instances running. In particular, if each instance
// runs a single thread then they would all be mapped to the first NUMA node.
// This is undesirable, and so the default behaviour (i.e. when the user does not
// change the NumaConfig UCI setting) is to not bind the threads to processors
// unless we know for sure that we span NUMA nodes and replication is required.
const std::string numaPolicy(sharedState.options["NumaPolicy"]);
const bool doBindThreads = [&]() {
if (numaPolicy == "none")
return false;
if (numaPolicy == "auto")
return numaConfig.suggests_binding_threads(requested);
// numaPolicy == "system", or explicitly set by the user
return true;
}();
boundThreadToNumaNode = doBindThreads
? numaConfig.distribute_threads_among_numa_nodes(requested)
: std::vector<NumaIndex>{};
while (threads.size() < requested)
{
const size_t threadId = threads.size();
const NumaIndex numaId = doBindThreads ? boundThreadToNumaNode[threadId] : 0;
auto manager = threadId == 0 ? std::unique_ptr<Search::ISearchManager>(
std::make_unique<Search::SearchManager>(updateContext))
: std::make_unique<Search::NullSearchManager>();
// When not binding threads we want to force all access to happen
// from the same NUMA node, because in case of NUMA replicated memory
// accesses we don't want to trash cache in case the threads get scheduled
// on the same NUMA node.
auto binder = doBindThreads ? OptionalThreadToNumaNodeBinder(numaConfig, numaId)
: OptionalThreadToNumaNodeBinder(numaId);
threads.emplace_back(
std::make_unique<Thread>(sharedState, std::move(manager), threadId, binder));
}
clear();
main_thread()->wait_for_search_finished();
}
// Init thread number dependent search params.
Search::init();
}
}
// Sets threadPool data to initial values
/// ThreadPool::clear() sets threadPool data to initial values
void ThreadPool::clear() {
if (threads.size() == 0)
return;
for (auto&& th : threads)
th->clear_worker();
for (Thread* th : *this)
th->clear();
for (auto&& th : threads)
th->wait_for_search_finished();
// These two affect the time taken on the first move of a game:
main_manager()->bestPreviousAverageScore = VALUE_INFINITE;
main_manager()->previousTimeReduction = 0.85;
main_manager()->callsCnt = 0;
main_manager()->bestPreviousScore = VALUE_INFINITE;
main_manager()->originalTimeAdjust = -1;
main_manager()->tm.clear();
main()->callsCnt = 0;
main()->bestPreviousScore = VALUE_INFINITE;
main()->previousTimeReduction = 1.0;
}
void ThreadPool::run_on_thread(size_t threadId, std::function<void()> f) {
assert(threads.size() > threadId);
threads[threadId]->run_custom_job(std::move(f));
}
void ThreadPool::wait_on_thread(size_t threadId) {
assert(threads.size() > threadId);
threads[threadId]->wait_for_search_finished();
}
/// ThreadPool::start_thinking() wakes up main thread waiting in idle_loop() and
/// returns immediately. Main thread will wake up other threads and start the search.
size_t ThreadPool::num_threads() const { return threads.size(); }
void ThreadPool::start_thinking(Position& pos, StateListPtr& states,
const Search::LimitsType& limits, bool ponderMode) {
main()->wait_for_search_finished();
// Wakes up main thread waiting in idle_loop() and returns immediately.
// Main thread will wake up other threads and start the search.
void ThreadPool::start_thinking(const OptionsMap& options,
Position& pos,
StateListPtr& states,
Search::LimitsType limits) {
main()->stopOnPonderhit = stop = false;
increaseDepth = true;
main()->ponder = ponderMode;
Search::Limits = limits;
Search::RootMoves rootMoves;
main_thread()->wait_for_search_finished();
for (const auto& m : MoveList<LEGAL>(pos))
if ( limits.searchmoves.empty()
|| std::count(limits.searchmoves.begin(), limits.searchmoves.end(), m))
rootMoves.emplace_back(m);
main_manager()->stopOnPonderhit = stop = abortedSearch = false;
main_manager()->ponder = limits.ponderMode;
if (!rootMoves.empty())
Tablebases::rank_root_moves(pos, rootMoves);
increaseDepth = true;
// After ownership transfer 'states' becomes empty, so if we stop the search
// and call 'go' again without setting a new position states.get() == NULL.
assert(states.get() || setupStates.get());
Search::RootMoves rootMoves;
const auto legalmoves = MoveList<LEGAL>(pos);
if (states.get())
setupStates = std::move(states); // Ownership transfer, states is now empty
for (const auto& uciMove : limits.searchmoves)
{
auto move = UCIEngine::to_move(pos, uciMove);
// We use Position::set() to set root position across threads. But there are
// some StateInfo fields (previous, pliesFromNull, capturedPiece) that cannot
// be deduced from a fen string, so set() clears them and to not lose the info
// we need to backup and later restore setupStates->back(). Note that setupStates
// is shared by threads but is accessed in read-only mode.
StateInfo tmp = setupStates->back();
if (std::find(legalmoves.begin(), legalmoves.end(), move) != legalmoves.end())
rootMoves.emplace_back(move);
}
for (Thread* th : *this)
{
th->nodes = th->tbHits = th->nmpMinPly = th->bestMoveChanges = 0;
th->rootDepth = th->completedDepth = 0;
th->rootMoves = rootMoves;
th->rootPos.set(pos.fen(), pos.is_chess960(), &setupStates->back(), th);
}
if (rootMoves.empty())
for (const auto& m : legalmoves)
rootMoves.emplace_back(m);
setupStates->back() = tmp;
Tablebases::Config tbConfig = Tablebases::rank_root_moves(options, pos, rootMoves);
// After ownership transfer 'states' becomes empty, so if we stop the search
// and call 'go' again without setting a new position states.get() == nullptr.
assert(states.get() || setupStates.get());
if (states.get())
setupStates = std::move(states); // Ownership transfer, states is now empty
// We use Position::set() to set root position across threads. But there are
// some StateInfo fields (previous, pliesFromNull, capturedPiece) that cannot
// be deduced from a fen string, so set() clears them and they are set from
// setupStates->back() later. The rootState is per thread, earlier states are
// shared since they are read-only.
for (auto&& th : threads)
{
th->run_custom_job([&]() {
th->worker->limits = limits;
th->worker->nodes = th->worker->tbHits = th->worker->nmpMinPly =
th->worker->bestMoveChanges = 0;
th->worker->rootDepth = th->worker->completedDepth = 0;
th->worker->rootMoves = rootMoves;
th->worker->rootPos.set(pos.fen(), pos.is_chess960(), &th->worker->rootState);
th->worker->rootState = setupStates->back();
th->worker->tbConfig = tbConfig;
});
}
for (auto&& th : threads)
th->wait_for_search_finished();
main_thread()->start_searching();
main()->start_searching();
}
Thread* ThreadPool::get_best_thread() const {
Thread* bestThread = threads.front().get();
Value minScore = VALUE_NONE;
Thread* bestThread = front();
std::map<Move, int64_t> votes;
Value minScore = VALUE_NONE;
std::unordered_map<Move, int64_t, Move::MoveHash> votes(
2 * std::min(size(), bestThread->worker->rootMoves.size()));
// Find the minimum score of all threads
for (auto&& th : threads)
minScore = std::min(minScore, th->worker->rootMoves[0].score);
// Find minimum score of all threads
for (Thread* th: *this)
minScore = std::min(minScore, th->rootMoves[0].score);
// Vote according to score and depth, and select the best thread
auto thread_voting_value = [minScore](Thread* th) {
return (th->worker->rootMoves[0].score - minScore + 14) * int(th->worker->completedDepth);
};
for (auto&& th : threads)
votes[th->worker->rootMoves[0].pv[0]] += thread_voting_value(th.get());
for (auto&& th : threads)
for (Thread* th : *this)
{
const auto bestThreadScore = bestThread->worker->rootMoves[0].score;
const auto newThreadScore = th->worker->rootMoves[0].score;
votes[th->rootMoves[0].pv[0]] +=
(th->rootMoves[0].score - minScore + 14) * int(th->completedDepth);
const auto& bestThreadPV = bestThread->worker->rootMoves[0].pv;
const auto& newThreadPV = th->worker->rootMoves[0].pv;
const auto bestThreadMoveVote = votes[bestThreadPV[0]];
const auto newThreadMoveVote = votes[newThreadPV[0]];
const bool bestThreadInProvenWin = is_win(bestThreadScore);
const bool newThreadInProvenWin = is_win(newThreadScore);
const bool bestThreadInProvenLoss =
bestThreadScore != -VALUE_INFINITE && is_loss(bestThreadScore);
const bool newThreadInProvenLoss =
newThreadScore != -VALUE_INFINITE && is_loss(newThreadScore);
// We make sure not to pick a thread with truncated principal variation
const bool betterVotingValue =
thread_voting_value(th.get()) * int(newThreadPV.size() > 2)
> thread_voting_value(bestThread) * int(bestThreadPV.size() > 2);
if (bestThreadInProvenWin)
{
// Make sure we pick the shortest mate / TB conversion
if (newThreadScore > bestThreadScore)
bestThread = th.get();
}
else if (bestThreadInProvenLoss)
{
// Make sure we pick the shortest mated / TB conversion
if (newThreadInProvenLoss && newThreadScore < bestThreadScore)
bestThread = th.get();
}
else if (newThreadInProvenWin || newThreadInProvenLoss
|| (!is_loss(newThreadScore)
&& (newThreadMoveVote > bestThreadMoveVote
|| (newThreadMoveVote == bestThreadMoveVote && betterVotingValue))))
bestThread = th.get();
if (abs(bestThread->rootMoves[0].score) >= VALUE_TB_WIN_IN_MAX_PLY)
{
// Make sure we pick the shortest mate / TB conversion or stave off mate the longest
if (th->rootMoves[0].score > bestThread->rootMoves[0].score)
bestThread = th;
}
else if ( th->rootMoves[0].score >= VALUE_TB_WIN_IN_MAX_PLY
|| ( th->rootMoves[0].score > VALUE_TB_LOSS_IN_MAX_PLY
&& votes[th->rootMoves[0].pv[0]] > votes[bestThread->rootMoves[0].pv[0]]))
bestThread = th;
}
return bestThread;
}
// Start non-main threads.
// Will be invoked by main thread after it has started searching.
/// Start non-main threads
void ThreadPool::start_searching() {
for (auto&& th : threads)
if (th != threads.front())
for (Thread* th : *this)
if (th != front())
th->start_searching();
}
// Wait for non-main threads
/// Wait for non-main threads
void ThreadPool::wait_for_search_finished() const {
for (auto&& th : threads)
if (th != threads.front())
for (Thread* th : *this)
if (th != front())
th->wait_for_search_finished();
}
std::vector<size_t> ThreadPool::get_bound_thread_count_by_numa_node() const {
std::vector<size_t> counts;
if (!boundThreadToNumaNode.empty())
{
NumaIndex highestNumaNode = 0;
for (NumaIndex n : boundThreadToNumaNode)
if (n > highestNumaNode)
highestNumaNode = n;
counts.resize(highestNumaNode + 1, 0);
for (NumaIndex n : boundThreadToNumaNode)
counts[n] += 1;
}
return counts;
}
void ThreadPool::ensure_network_replicated() {
for (auto&& th : threads)
th->ensure_network_replicated();
}
} // namespace Stockfish

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -21,158 +21,110 @@
#include <atomic>
#include <condition_variable>
#include <cstddef>
#include <cstdint>
#include <functional>
#include <memory>
#include <mutex>
#include <thread>
#include <vector>
#include "numa.h"
#include "material.h"
#include "movepick.h"
#include "pawns.h"
#include "position.h"
#include "search.h"
#include "thread_win32_osx.h"
namespace Stockfish {
/// Thread class keeps together all the thread-related stuff. We use
/// per-thread pawn and material hash tables so that once we get a
/// pointer to an entry its life time is unlimited and we don't have
/// to care about someone changing the entry under our feet.
class OptionsMap;
using Value = int;
// Sometimes we don't want to actually bind the threads, but the recipient still
// needs to think it runs on *some* NUMA node, such that it can access structures
// that rely on NUMA node knowledge. This class encapsulates this optional process
// such that the recipient does not need to know whether the binding happened or not.
class OptionalThreadToNumaNodeBinder {
public:
OptionalThreadToNumaNodeBinder(NumaIndex n) :
numaConfig(nullptr),
numaId(n) {}
OptionalThreadToNumaNodeBinder(const NumaConfig& cfg, NumaIndex n) :
numaConfig(&cfg),
numaId(n) {}
NumaReplicatedAccessToken operator()() const {
if (numaConfig != nullptr)
return numaConfig->bind_current_thread_to_numa_node(numaId);
else
return NumaReplicatedAccessToken(numaId);
}
private:
const NumaConfig* numaConfig;
NumaIndex numaId;
};
// Abstraction of a thread. It contains a pointer to the worker and a native thread.
// After construction, the native thread is started with idle_loop()
// waiting for a signal to start searching.
// When the signal is received, the thread starts searching and when
// the search is finished, it goes back to idle_loop() waiting for a new signal.
class Thread {
public:
Thread(Search::SharedState&,
std::unique_ptr<Search::ISearchManager>,
size_t,
OptionalThreadToNumaNodeBinder);
virtual ~Thread();
void idle_loop();
void start_searching();
void clear_worker();
void run_custom_job(std::function<void()> f);
std::mutex mutex;
std::condition_variable cv;
size_t idx;
bool exit = false, searching = true; // Set before starting std::thread
NativeThread stdThread;
void ensure_network_replicated();
public:
explicit Thread(size_t);
virtual ~Thread();
virtual void search();
void clear();
void idle_loop();
void start_searching();
void wait_for_search_finished();
int best_move_count(Move move) const;
// Thread has been slightly altered to allow running custom jobs, so
// this name is no longer correct. However, this class (and ThreadPool)
// require further work to make them properly generic while maintaining
// appropriate specificity regarding search, from the point of view of an
// outside user, so renaming of this function is left for whenever that happens.
void wait_for_search_finished();
size_t id() const { return idx; }
Pawns::Table pawnsTable;
Material::Table materialTable;
size_t pvIdx, pvLast;
uint64_t ttHitAverage;
int selDepth, nmpMinPly;
Color nmpColor;
std::atomic<uint64_t> nodes, tbHits, bestMoveChanges;
std::unique_ptr<Search::Worker> worker;
std::function<void()> jobFunc;
private:
std::mutex mutex;
std::condition_variable cv;
size_t idx, nthreads;
bool exit = false, searching = true; // Set before starting std::thread
NativeThread stdThread;
NumaReplicatedAccessToken numaAccessToken;
Position rootPos;
Search::RootMoves rootMoves;
Depth rootDepth, completedDepth;
CounterMoveHistory counterMoves;
ButterflyHistory mainHistory;
LowPlyHistory lowPlyHistory;
CapturePieceToHistory captureHistory;
ContinuationHistory continuationHistory[2][2];
Score contempt;
};
// ThreadPool struct handles all the threads-related stuff like init, starting,
// parking and, most importantly, launching a thread. All the access to threads
// is done through this class.
class ThreadPool {
public:
ThreadPool() {}
/// MainThread is a derived class specific for main thread
~ThreadPool() {
// destroy any existing thread(s)
if (threads.size() > 0)
{
main_thread()->wait_for_search_finished();
struct MainThread : public Thread {
threads.clear();
}
}
using Thread::Thread;
ThreadPool(const ThreadPool&) = delete;
ThreadPool(ThreadPool&&) = delete;
void search() override;
void check_time();
ThreadPool& operator=(const ThreadPool&) = delete;
ThreadPool& operator=(ThreadPool&&) = delete;
void start_thinking(const OptionsMap&, Position&, StateListPtr&, Search::LimitsType);
void run_on_thread(size_t threadId, std::function<void()> f);
void wait_on_thread(size_t threadId);
size_t num_threads() const;
void clear();
void set(const NumaConfig& numaConfig,
Search::SharedState,
const Search::SearchManager::UpdateContext&);
Search::SearchManager* main_manager();
Thread* main_thread() const { return threads.front().get(); }
uint64_t nodes_searched() const;
uint64_t tb_hits() const;
Thread* get_best_thread() const;
void start_searching();
void wait_for_search_finished() const;
std::vector<size_t> get_bound_thread_count_by_numa_node() const;
void ensure_network_replicated();
std::atomic_bool stop, abortedSearch, increaseDepth;
auto cbegin() const noexcept { return threads.cbegin(); }
auto begin() noexcept { return threads.begin(); }
auto end() noexcept { return threads.end(); }
auto cend() const noexcept { return threads.cend(); }
auto size() const noexcept { return threads.size(); }
auto empty() const noexcept { return threads.empty(); }
private:
StateListPtr setupStates;
std::vector<std::unique_ptr<Thread>> threads;
std::vector<NumaIndex> boundThreadToNumaNode;
uint64_t accumulate(std::atomic<uint64_t> Search::Worker::* member) const {
uint64_t sum = 0;
for (auto&& th : threads)
sum += (th->worker.get()->*member).load(std::memory_order_relaxed);
return sum;
}
double previousTimeReduction;
Value bestPreviousScore;
Value iterValue[4];
int callsCnt;
bool stopOnPonderhit;
std::atomic_bool ponder;
};
} // namespace Stockfish
#endif // #ifndef THREAD_H_INCLUDED
/// ThreadPool struct handles all the threads-related stuff like init, starting,
/// parking and, most importantly, launching a thread. All the access to threads
/// is done through this class.
struct ThreadPool : public std::vector<Thread*> {
void start_thinking(Position&, StateListPtr&, const Search::LimitsType&, bool = false);
void clear();
void set(size_t);
MainThread* main() const { return static_cast<MainThread*>(front()); }
uint64_t nodes_searched() const { return accumulate(&Thread::nodes); }
uint64_t tb_hits() const { return accumulate(&Thread::tbHits); }
Thread* get_best_thread() const;
void start_searching();
void wait_for_search_finished() const;
std::atomic_bool stop, increaseDepth;
private:
StateListPtr setupStates;
uint64_t accumulate(std::atomic<uint64_t> Thread::* member) const {
uint64_t sum = 0;
for (Thread* th : *this)
sum += (th->*member).load(std::memory_order_relaxed);
return sum;
}
};
extern ThreadPool Threads;
#endif // #ifndef THREAD_H_INCLUDED

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -21,58 +21,46 @@
#include <thread>
// On OSX threads other than the main thread are created with a reduced stack
// size of 512KB by default, this is too low for deep searches, which require
// somewhat more than 1MB stack, so adjust it to TH_STACK_SIZE.
// The implementation calls pthread_create() with the stack size parameter
// equal to the Linux 8MB default, on platforms that support it.
/// On OSX threads other than the main thread are created with a reduced stack
/// size of 512KB by default, this is too low for deep searches, which require
/// somewhat more than 1MB stack, so adjust it to TH_STACK_SIZE.
/// The implementation calls pthread_create() with the stack size parameter
/// equal to the linux 8MB default, on platforms that support it.
#if defined(__APPLE__) || defined(__MINGW32__) || defined(__MINGW64__) || defined(USE_PTHREADS)
#if defined(__APPLE__) || defined(__MINGW32__) || defined(__MINGW64__)
#include <pthread.h>
#include <functional>
#include <pthread.h>
namespace Stockfish {
static const size_t TH_STACK_SIZE = 8 * 1024 * 1024;
template <class T, class P = std::pair<T*, void(T::*)()>>
void* start_routine(void* ptr)
{
P* p = reinterpret_cast<P*>(ptr);
(p->first->*(p->second))(); // Call member function pointer
delete p;
return NULL;
}
class NativeThread {
pthread_t thread;
static constexpr size_t TH_STACK_SIZE = 8 * 1024 * 1024;
pthread_t thread;
public:
template<class Function, class... Args>
explicit NativeThread(Function&& fun, Args&&... args) {
auto func = new std::function<void()>(
std::bind(std::forward<Function>(fun), std::forward<Args>(args)...));
pthread_attr_t attr_storage, *attr = &attr_storage;
pthread_attr_init(attr);
pthread_attr_setstacksize(attr, TH_STACK_SIZE);
auto start_routine = [](void* ptr) -> void* {
auto f = reinterpret_cast<std::function<void()>*>(ptr);
// Call the function
(*f)();
delete f;
return nullptr;
};
pthread_create(&thread, attr, start_routine, func);
}
void join() { pthread_join(thread, nullptr); }
public:
template<class T, class P = std::pair<T*, void(T::*)()>>
explicit NativeThread(void(T::*fun)(), T* obj) {
pthread_attr_t attr_storage, *attr = &attr_storage;
pthread_attr_init(attr);
pthread_attr_setstacksize(attr, TH_STACK_SIZE);
pthread_create(&thread, attr, start_routine<T>, new P(obj, fun));
}
void join() { pthread_join(thread, NULL); }
};
} // namespace Stockfish
#else // Default case: use STL classes
#else // Default case: use STL classes
namespace Stockfish {
using NativeThread = std::thread;
} // namespace Stockfish
typedef std::thread NativeThread;
#endif
#endif // #ifndef THREAD_WIN32_OSX_H_INCLUDED
#endif // #ifndef THREAD_WIN32_OSX_H_INCLUDED

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -16,125 +16,82 @@
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include "timeman.h"
#include <algorithm>
#include <cassert>
#include <cfloat>
#include <cmath>
#include <cstdint>
#include "search.h"
#include "ucioption.h"
#include "timeman.h"
#include "uci.h"
namespace Stockfish {
TimeManagement Time; // Our global time management object
TimePoint TimeManagement::optimum() const { return optimumTime; }
TimePoint TimeManagement::maximum() const { return maximumTime; }
void TimeManagement::clear() {
availableNodes = -1; // When in 'nodes as time' mode
}
void TimeManagement::advance_nodes_time(std::int64_t nodes) {
assert(useNodesTime);
availableNodes = std::max(int64_t(0), availableNodes - nodes);
}
// Called at the beginning of the search and calculates
// the bounds of time allowed for the current game ply. We currently support:
/// TimeManagement::init() is called at the beginning of the search and calculates
/// the bounds of time allowed for the current game ply. We currently support:
// 1) x basetime (+ z increment)
// 2) x moves in y seconds (+ z increment)
void TimeManagement::init(Search::LimitsType& limits,
Color us,
int ply,
const OptionsMap& options,
double& originalTimeAdjust) {
TimePoint npmsec = TimePoint(options["nodestime"]);
// If we have no time, we don't need to fully initialize TM.
// startTime is used by movetime and useNodesTime is used in elapsed calls.
startTime = limits.startTime;
useNodesTime = npmsec != 0;
void TimeManagement::init(Search::LimitsType& limits, Color us, int ply) {
if (limits.time[us] == 0)
return;
TimePoint moveOverhead = TimePoint(Options["Move Overhead"]);
TimePoint slowMover = TimePoint(Options["Slow Mover"]);
TimePoint npmsec = TimePoint(Options["nodestime"]);
TimePoint moveOverhead = TimePoint(options["Move Overhead"]);
// opt_scale is a percentage of available time to use for the current move.
// max_scale is a multiplier applied to optimumTime.
double opt_scale, max_scale;
// optScale is a percentage of available time to use for the current move.
// maxScale is a multiplier applied to optimumTime.
double optScale, maxScale;
// If we have to play in 'nodes as time' mode, then convert from time
// to nodes, and use resulting values in time management formulas.
// WARNING: to avoid time losses, the given npmsec (nodes per millisecond)
// must be much lower than the real engine speed.
if (npmsec)
{
if (!availableNodes) // Only once at game start
availableNodes = npmsec * limits.time[us]; // Time is in msec
// If we have to play in 'nodes as time' mode, then convert from time
// to nodes, and use resulting values in time management formulas.
// WARNING: to avoid time losses, the given npmsec (nodes per millisecond)
// must be much lower than the real engine speed.
if (useNodesTime)
{
if (availableNodes == -1) // Only once at game start
availableNodes = npmsec * limits.time[us]; // Time is in msec
// Convert from milliseconds to nodes
limits.time[us] = TimePoint(availableNodes);
limits.inc[us] *= npmsec;
limits.npmsec = npmsec;
}
// Convert from milliseconds to nodes
limits.time[us] = TimePoint(availableNodes);
limits.inc[us] *= npmsec;
limits.npmsec = npmsec;
moveOverhead *= npmsec;
}
startTime = limits.startTime;
// These numbers are used where multiplications, divisions or comparisons
// with constants are involved.
const int64_t scaleFactor = useNodesTime ? npmsec : 1;
const TimePoint scaledTime = limits.time[us] / scaleFactor;
// Maximum move horizon of 50 moves
int mtg = limits.movestogo ? std::min(limits.movestogo, 50) : 50;
// Maximum move horizon
int centiMTG = limits.movestogo ? std::min(limits.movestogo * 100, 5000) : 5051;
// Make sure timeLeft is > 0 since we may use it as a divisor
TimePoint timeLeft = std::max(TimePoint(1),
limits.time[us] + limits.inc[us] * (mtg - 1) - moveOverhead * (2 + mtg));
// If less than one second, gradually reduce mtg
if (scaledTime < 1000)
centiMTG = scaledTime * 5.051;
// A user may scale time usage by setting UCI option "Slow Mover"
// Default is 100 and changing this value will probably lose elo.
timeLeft = slowMover * timeLeft / 100;
// Make sure timeLeft is > 0 since we may use it as a divisor
TimePoint timeLeft =
std::max(TimePoint(1),
limits.time[us]
+ (limits.inc[us] * (centiMTG - 100) - moveOverhead * (200 + centiMTG)) / 100);
// x basetime (+ z increment)
// If there is a healthy increment, timeLeft can exceed actual available
// game time for the current move, so also cap to 20% of available game time.
if (limits.movestogo == 0)
{
opt_scale = std::min(0.008 + std::pow(ply + 3.0, 0.5) / 250.0,
0.2 * limits.time[us] / double(timeLeft));
max_scale = std::min(7.0, 4.0 + ply / 12.0);
}
// x basetime (+ z increment)
// If there is a healthy increment, timeLeft can exceed the actual available
// game time for the current move, so also cap to a percentage of available game time.
if (limits.movestogo == 0)
{
// Extra time according to timeLeft
if (originalTimeAdjust < 0)
originalTimeAdjust = 0.3128 * std::log10(timeLeft) - 0.4354;
// x moves in y seconds (+ z increment)
else
{
opt_scale = std::min((0.8 + ply / 128.0) / mtg,
0.8 * limits.time[us] / double(timeLeft));
max_scale = std::min(6.3, 1.5 + 0.11 * mtg);
}
// Calculate time constants based on current time left.
double logTimeInSec = std::log10(scaledTime / 1000.0);
double optConstant = std::min(0.0032116 + 0.000321123 * logTimeInSec, 0.00508017);
double maxConstant = std::max(3.3977 + 3.03950 * logTimeInSec, 2.94761);
// Never use more than 80% of the available time for this move
optimumTime = TimePoint(opt_scale * timeLeft);
maximumTime = TimePoint(std::min(0.8 * limits.time[us] - moveOverhead, max_scale * optimumTime));
optScale = std::min(0.0121431 + std::pow(ply + 2.94693, 0.461073) * optConstant,
0.213035 * limits.time[us] / timeLeft)
* originalTimeAdjust;
maxScale = std::min(6.67704, maxConstant + ply / 11.9847);
}
// x moves in y seconds (+ z increment)
else
{
optScale =
std::min((0.88 + ply / 116.4) / (centiMTG / 100.0), 0.88 * limits.time[us] / timeLeft);
maxScale = 1.3 + 0.11 * (centiMTG / 100.0);
}
// Limit the maximum possible time for this move
optimumTime = TimePoint(optScale * timeLeft);
maximumTime =
TimePoint(std::min(0.825179 * limits.time[us] - moveOverhead, maxScale * optimumTime)) - 10;
if (options["Ponder"])
optimumTime += optimumTime / 4;
if (Options["Ponder"])
optimumTime += optimumTime / 4;
}
} // namespace Stockfish

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -19,49 +19,29 @@
#ifndef TIMEMAN_H_INCLUDED
#define TIMEMAN_H_INCLUDED
#include <cstdint>
#include "misc.h"
#include "search.h"
#include "thread.h"
namespace Stockfish {
/// The TimeManagement class computes the optimal time to think depending on
/// the maximum available time, the game move number and other parameters.
class OptionsMap;
enum Color : int8_t;
namespace Search {
struct LimitsType;
}
// The TimeManagement class computes the optimal time to think depending on
// the maximum available time, the game move number, and other parameters.
class TimeManagement {
public:
void init(Search::LimitsType& limits,
Color us,
int ply,
const OptionsMap& options,
double& originalTimeAdjust);
public:
void init(Search::LimitsType& limits, Color us, int ply);
TimePoint optimum() const { return optimumTime; }
TimePoint maximum() const { return maximumTime; }
TimePoint elapsed() const { return Search::Limits.npmsec ?
TimePoint(Threads.nodes_searched()) : now() - startTime; }
TimePoint optimum() const;
TimePoint maximum() const;
template<typename FUNC>
TimePoint elapsed(FUNC nodes) const {
return useNodesTime ? TimePoint(nodes()) : elapsed_time();
}
TimePoint elapsed_time() const { return now() - startTime; };
int64_t availableNodes; // When in 'nodes as time' mode
void clear();
void advance_nodes_time(std::int64_t nodes);
private:
TimePoint startTime;
TimePoint optimumTime;
TimePoint maximumTime;
std::int64_t availableNodes = -1; // When in 'nodes as time' mode
bool useNodesTime = false; // True if we are in 'nodes as time' mode
private:
TimePoint startTime;
TimePoint optimumTime;
TimePoint maximumTime;
};
} // namespace Stockfish
extern TimeManagement Time;
#endif // #ifndef TIMEMAN_H_INCLUDED
#endif // #ifndef TIMEMAN_H_INCLUDED

View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -16,238 +16,140 @@
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include "tt.h"
#include <cassert>
#include <cstdint>
#include <cstdlib>
#include <cstring>
#include <cstring> // For std::memset
#include <iostream>
#include <thread>
#include "memory.h"
#include "bitboard.h"
#include "misc.h"
#include "syzygy/tbprobe.h"
#include "thread.h"
#include "tt.h"
#include "uci.h"
namespace Stockfish {
TranspositionTable TT; // Our global transposition table
/// TTEntry::save() populates the TTEntry with a new node's data, possibly
/// overwriting an old position. Update is not atomic and can be racy.
// TTEntry struct is the 10 bytes transposition table entry, defined as below:
//
// key 16 bit
// depth 8 bit
// generation 5 bit
// pv node 1 bit
// bound type 2 bit
// move 16 bit
// value 16 bit
// evaluation 16 bit
//
// These fields are in the same order as accessed by TT::probe(), since memory is fastest sequentially.
// Equally, the store order in save() matches this order.
void TTEntry::save(Key k, Value v, bool pv, Bound b, Depth d, Move m, Value ev) {
struct TTEntry {
// Preserve any existing move for the same position
if (m || (uint16_t)k != key16)
move16 = (uint16_t)m;
// Convert internal bitfields to external types
TTData read() const {
return TTData{Move(move16), Value(value16),
Value(eval16), Depth(depth8 + DEPTH_ENTRY_OFFSET),
Bound(genBound8 & 0x3), bool(genBound8 & 0x4)};
}
// Overwrite less valuable entries
if ((uint16_t)k != key16
|| d - DEPTH_OFFSET > depth8 - 4
|| b == BOUND_EXACT)
{
assert(d >= DEPTH_OFFSET);
bool is_occupied() const;
void save(Key k, Value v, bool pv, Bound b, Depth d, Move m, Value ev, uint8_t generation8);
// The returned age is a multiple of TranspositionTable::GENERATION_DELTA
uint8_t relative_age(const uint8_t generation8) const;
private:
friend class TranspositionTable;
uint16_t key16;
uint8_t depth8;
uint8_t genBound8;
Move move16;
int16_t value16;
int16_t eval16;
};
// `genBound8` is where most of the details are. We use the following constants to manipulate 5 leading generation bits
// and 3 trailing miscellaneous bits.
// These bits are reserved for other things.
static constexpr unsigned GENERATION_BITS = 3;
// increment for generation field
static constexpr int GENERATION_DELTA = (1 << GENERATION_BITS);
// cycle length
static constexpr int GENERATION_CYCLE = 255 + GENERATION_DELTA;
// mask to pull out generation number
static constexpr int GENERATION_MASK = (0xFF << GENERATION_BITS) & 0xFF;
// DEPTH_ENTRY_OFFSET exists because 1) we use `bool(depth8)` as the occupancy check, but
// 2) we need to store negative depths for QS. (`depth8` is the only field with "spare bits":
// we sacrifice the ability to store depths greater than 1<<8 less the offset, as asserted in `save`.)
bool TTEntry::is_occupied() const { return bool(depth8); }
// Populates the TTEntry with a new node's data, possibly
// overwriting an old position. The update is not atomic and can be racy.
void TTEntry::save(
Key k, Value v, bool pv, Bound b, Depth d, Move m, Value ev, uint8_t generation8) {
// Preserve the old ttmove if we don't have a new one
if (m || uint16_t(k) != key16)
move16 = m;
// Overwrite less valuable entries (cheapest checks first)
if (b == BOUND_EXACT || uint16_t(k) != key16 || d - DEPTH_ENTRY_OFFSET + 2 * pv > depth8 - 4
|| relative_age(generation8))
{
assert(d > DEPTH_ENTRY_OFFSET);
assert(d < 256 + DEPTH_ENTRY_OFFSET);
key16 = uint16_t(k);
depth8 = uint8_t(d - DEPTH_ENTRY_OFFSET);
genBound8 = uint8_t(generation8 | uint8_t(pv) << 2 | b);
value16 = int16_t(v);
eval16 = int16_t(ev);
}
else if (depth8 + DEPTH_ENTRY_OFFSET >= 5 && Bound(genBound8 & 0x3) != BOUND_EXACT)
depth8--;
key16 = (uint16_t)k;
value16 = (int16_t)v;
eval16 = (int16_t)ev;
genBound8 = (uint8_t)(TT.generation8 | uint8_t(pv) << 2 | b);
depth8 = (uint8_t)(d - DEPTH_OFFSET);
}
}
uint8_t TTEntry::relative_age(const uint8_t generation8) const {
// Due to our packed storage format for generation and its cyclic
// nature we add GENERATION_CYCLE (256 is the modulus, plus what
// is needed to keep the unrelated lowest n bits from affecting
// the result) to calculate the entry age correctly even after
// generation8 overflows into the next cycle.
return (GENERATION_CYCLE + generation8 - genBound8) & GENERATION_MASK;
/// TranspositionTable::resize() sets the size of the transposition table,
/// measured in megabytes. Transposition table consists of a power of 2 number
/// of clusters and each cluster consists of ClusterSize number of TTEntry.
void TranspositionTable::resize(size_t mbSize) {
Threads.main()->wait_for_search_finished();
aligned_ttmem_free(mem);
clusterCount = mbSize * 1024 * 1024 / sizeof(Cluster);
table = static_cast<Cluster*>(aligned_ttmem_alloc(clusterCount * sizeof(Cluster), mem));
if (!mem)
{
std::cerr << "Failed to allocate " << mbSize
<< "MB for transposition table." << std::endl;
exit(EXIT_FAILURE);
}
clear();
}
// TTWriter is but a very thin wrapper around the pointer
TTWriter::TTWriter(TTEntry* tte) :
entry(tte) {}
/// TranspositionTable::clear() initializes the entire transposition table to zero,
// in a multi-threaded way.
void TTWriter::write(
Key k, Value v, bool pv, Bound b, Depth d, Move m, Value ev, uint8_t generation8) {
entry->save(k, v, pv, b, d, m, ev, generation8);
void TranspositionTable::clear() {
std::vector<std::thread> threads;
for (size_t idx = 0; idx < Options["Threads"]; ++idx)
{
threads.emplace_back([this, idx]() {
// Thread binding gives faster search on systems with a first-touch policy
if (Options["Threads"] > 8)
WinProcGroup::bindThisThread(idx);
// Each thread will zero its part of the hash table
const size_t stride = size_t(clusterCount / Options["Threads"]),
start = size_t(stride * idx),
len = idx != Options["Threads"] - 1 ?
stride : clusterCount - start;
std::memset(&table[start], 0, len * sizeof(Cluster));
});
}
for (std::thread& th : threads)
th.join();
}
// A TranspositionTable is an array of Cluster, of size clusterCount. Each cluster consists of ClusterSize number
// of TTEntry. Each non-empty TTEntry contains information on exactly one position. The size of a Cluster should
// divide the size of a cache line for best performance, as the cacheline is prefetched when possible.
/// TranspositionTable::probe() looks up the current position in the transposition
/// table. It returns true and a pointer to the TTEntry if the position is found.
/// Otherwise, it returns false and a pointer to an empty or least valuable TTEntry
/// to be replaced later. The replace value of an entry is calculated as its depth
/// minus 8 times its relative age. TTEntry t1 is considered more valuable than
/// TTEntry t2 if its replace value is greater than that of t2.
static constexpr int ClusterSize = 3;
TTEntry* TranspositionTable::probe(const Key key, bool& found) const {
struct Cluster {
TTEntry entry[ClusterSize];
char padding[2]; // Pad to 32 bytes
};
TTEntry* const tte = first_entry(key);
const uint16_t key16 = (uint16_t)key; // Use the low 16 bits as key inside the cluster
static_assert(sizeof(Cluster) == 32, "Suboptimal Cluster size");
for (int i = 0; i < ClusterSize; ++i)
if (!tte[i].key16 || tte[i].key16 == key16)
{
tte[i].genBound8 = uint8_t(generation8 | (tte[i].genBound8 & 0x7)); // Refresh
return found = (bool)tte[i].key16, &tte[i];
}
// Sets the size of the transposition table,
// measured in megabytes. Transposition table consists
// of clusters and each cluster consists of ClusterSize number of TTEntry.
void TranspositionTable::resize(size_t mbSize, ThreadPool& threads) {
aligned_large_pages_free(table);
// Find an entry to be replaced according to the replacement strategy
TTEntry* replace = tte;
for (int i = 1; i < ClusterSize; ++i)
// Due to our packed storage format for generation and its cyclic
// nature we add 263 (256 is the modulus plus 7 to keep the unrelated
// lowest three bits from affecting the result) to calculate the entry
// age correctly even after generation8 overflows into the next cycle.
if ( replace->depth8 - ((263 + generation8 - replace->genBound8) & 0xF8)
> tte[i].depth8 - ((263 + generation8 - tte[i].genBound8) & 0xF8))
replace = &tte[i];
clusterCount = mbSize * 1024 * 1024 / sizeof(Cluster);
table = static_cast<Cluster*>(aligned_large_pages_alloc(clusterCount * sizeof(Cluster)));
if (!table)
{
std::cerr << "Failed to allocate " << mbSize << "MB for transposition table." << std::endl;
exit(EXIT_FAILURE);
}
clear(threads);
return found = false, replace;
}
// Initializes the entire transposition table to zero,
// in a multi-threaded way.
void TranspositionTable::clear(ThreadPool& threads) {
generation8 = 0;
const size_t threadCount = threads.num_threads();
/// TranspositionTable::hashfull() returns an approximation of the hashtable
/// occupation during a search. The hash is x permill full, as per UCI protocol.
for (size_t i = 0; i < threadCount; ++i)
{
threads.run_on_thread(i, [this, i, threadCount]() {
// Each thread will zero its part of the hash table
const size_t stride = clusterCount / threadCount;
const size_t start = stride * i;
const size_t len = i + 1 != threadCount ? stride : clusterCount - start;
int TranspositionTable::hashfull() const {
std::memset(&table[start], 0, len * sizeof(Cluster));
});
}
int cnt = 0;
for (int i = 0; i < 1000; ++i)
for (int j = 0; j < ClusterSize; ++j)
cnt += (table[i].entry[j].genBound8 & 0xF8) == generation8;
for (size_t i = 0; i < threadCount; ++i)
threads.wait_on_thread(i);
return cnt / ClusterSize;
}
// Returns an approximation of the hashtable
// occupation during a search. The hash is x permill full, as per UCI protocol.
// Only counts entries which match the current generation.
int TranspositionTable::hashfull(int maxAge) const {
int maxAgeInternal = maxAge << GENERATION_BITS;
int cnt = 0;
for (int i = 0; i < 1000; ++i)
for (int j = 0; j < ClusterSize; ++j)
cnt += table[i].entry[j].is_occupied()
&& table[i].entry[j].relative_age(generation8) <= maxAgeInternal;
return cnt / ClusterSize;
}
void TranspositionTable::new_search() {
// increment by delta to keep lower bits as is
generation8 += GENERATION_DELTA;
}
uint8_t TranspositionTable::generation() const { return generation8; }
// Looks up the current position in the transposition
// table. It returns true if the position is found.
// Otherwise, it returns false and a pointer to an empty or least valuable TTEntry
// to be replaced later. The replace value of an entry is calculated as its depth
// minus 8 times its relative age. TTEntry t1 is considered more valuable than
// TTEntry t2 if its replace value is greater than that of t2.
std::tuple<bool, TTData, TTWriter> TranspositionTable::probe(const Key key) const {
TTEntry* const tte = first_entry(key);
const uint16_t key16 = uint16_t(key); // Use the low 16 bits as key inside the cluster
for (int i = 0; i < ClusterSize; ++i)
if (tte[i].key16 == key16)
// This gap is the main place for read races.
// After `read()` completes that copy is final, but may be self-inconsistent.
return {tte[i].is_occupied(), tte[i].read(), TTWriter(&tte[i])};
// Find an entry to be replaced according to the replacement strategy
TTEntry* replace = tte;
for (int i = 1; i < ClusterSize; ++i)
if (replace->depth8 - replace->relative_age(generation8)
> tte[i].depth8 - tte[i].relative_age(generation8))
replace = &tte[i];
return {false,
TTData{Move::none(), VALUE_NONE, VALUE_NONE, DEPTH_ENTRY_OFFSET, BOUND_NONE, false},
TTWriter(replace)};
}
TTEntry* TranspositionTable::first_entry(const Key key) const {
return &table[mul_hi64(key, clusterCount)].entry[0];
}
} // namespace Stockfish

128
src/tt.h
View File

@@ -1,6 +1,6 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2025 The Stockfish developers (see AUTHORS file)
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@@ -19,92 +19,80 @@
#ifndef TT_H_INCLUDED
#define TT_H_INCLUDED
#include <cstddef>
#include <cstdint>
#include <tuple>
#include "memory.h"
#include "misc.h"
#include "types.h"
namespace Stockfish {
/// TTEntry struct is the 10 bytes transposition table entry, defined as below:
///
/// key 16 bit
/// move 16 bit
/// value 16 bit
/// eval value 16 bit
/// generation 5 bit
/// pv node 1 bit
/// bound type 2 bit
/// depth 8 bit
class ThreadPool;
struct TTEntry;
struct Cluster;
struct TTEntry {
// There is only one global hash table for the engine and all its threads. For chess in particular, we even allow racy
// updates between threads to and from the TT, as taking the time to synchronize access would cost thinking time and
// thus elo. As a hash table, collisions are possible and may cause chess playing issues (bizarre blunders, faulty mate
// reports, etc). Fixing these also loses elo; however such risk decreases quickly with larger TT size.
//
// `probe` is the primary method: given a board position, we lookup its entry in the table, and return a tuple of:
// 1) whether the entry already has this position
// 2) a copy of the prior data (if any) (may be inconsistent due to read races)
// 3) a writer object to this entry
// The copied data and the writer are separated to maintain clear boundaries between local vs global objects.
Move move() const { return (Move )move16; }
Value value() const { return (Value)value16; }
Value eval() const { return (Value)eval16; }
Depth depth() const { return (Depth)depth8 + DEPTH_OFFSET; }
bool is_pv() const { return (bool)(genBound8 & 0x4); }
Bound bound() const { return (Bound)(genBound8 & 0x3); }
void save(Key k, Value v, bool pv, Bound b, Depth d, Move m, Value ev);
private:
friend class TranspositionTable;
// A copy of the data already in the entry (possibly collided). `probe` may be racy, resulting in inconsistent data.
struct TTData {
Move move;
Value value, eval;
Depth depth;
Bound bound;
bool is_pv;
TTData() = delete;
// clang-format off
TTData(Move m, Value v, Value ev, Depth d, Bound b, bool pv) :
move(m),
value(v),
eval(ev),
depth(d),
bound(b),
is_pv(pv) {};
// clang-format on
uint16_t key16;
uint16_t move16;
int16_t value16;
int16_t eval16;
uint8_t genBound8;
uint8_t depth8;
};
// This is used to make racy writes to the global TT.
struct TTWriter {
public:
void write(Key k, Value v, bool pv, Bound b, Depth d, Move m, Value ev, uint8_t generation8);
private:
friend class TranspositionTable;
TTEntry* entry;
TTWriter(TTEntry* tte);
};
/// A TranspositionTable is an array of Cluster, of size clusterCount. Each
/// cluster consists of ClusterSize number of TTEntry. Each non-empty TTEntry
/// contains information on exactly one position. The size of a Cluster should
/// divide the size of a cache line for best performance, as the cacheline is
/// prefetched when possible.
class TranspositionTable {
public:
~TranspositionTable() { aligned_large_pages_free(table); }
static constexpr int ClusterSize = 3;
void resize(size_t mbSize, ThreadPool& threads); // Set TT size
void clear(ThreadPool& threads); // Re-initialize memory, multithreaded
int hashfull(int maxAge = 0)
const; // Approximate what fraction of entries (permille) have been written to during this root search
struct Cluster {
TTEntry entry[ClusterSize];
char padding[2]; // Pad to 32 bytes
};
void
new_search(); // This must be called at the beginning of each root search to track entry aging
uint8_t generation() const; // The current age, used when writing new data to the TT
std::tuple<bool, TTData, TTWriter>
probe(const Key key) const; // The main method, whose retvals separate local vs global objects
TTEntry* first_entry(const Key key)
const; // This is the hash function; its only external use is memory prefetching.
static_assert(sizeof(Cluster) == 32, "Unexpected Cluster size");
private:
friend struct TTEntry;
public:
~TranspositionTable() { aligned_ttmem_free(mem); }
void new_search() { generation8 += 8; } // Lower 3 bits are used by PV flag and Bound
TTEntry* probe(const Key key, bool& found) const;
int hashfull() const;
void resize(size_t mbSize);
void clear();
size_t clusterCount;
Cluster* table = nullptr;
TTEntry* first_entry(const Key key) const {
return &table[mul_hi64(key, clusterCount)].entry[0];
}
uint8_t generation8 = 0; // Size must be not bigger than TTEntry::genBound8
private:
friend struct TTEntry;
size_t clusterCount;
Cluster* table;
void* mem;
uint8_t generation8; // Size must be not bigger than TTEntry::genBound8
};
} // namespace Stockfish
extern TranspositionTable TT;
#endif // #ifndef TT_H_INCLUDED
#endif // #ifndef TT_H_INCLUDED

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