Compare commits

..

322 Commits

Author SHA1 Message Date
Joost VandeVondele
e0bfc4b69b Stockfish 17
Official release version of Stockfish 17

Bench: 1484730

---

Stockfish 17

Today we have the pleasure to announce a new major release of Stockfish. As
always, you can freely download it at https://stockfishchess.org/download and
use it in the GUI of your choice.

Don’t forget to join our Discord server[1] to get in touch with the community
of developers and users of the project!

*Quality of chess play*

In tests against Stockfish 16, this release brings an Elo gain of up to 46
points[2] and wins up to 4.5 times more game pairs[3] than it loses. In
practice, high-quality moves are now found in less time, with a user upgrading
from Stockfish 14 being able to analyze games at least 6 times[4] faster with
Stockfish 17 while maintaining roughly the same quality.

During this development period, Stockfish won its 9th consecutive first place
in the main league of the Top Chess Engine Championship (TCEC)[5], and the 24th
consecutive first place in the main events (bullet, blitz, and rapid) of the
Computer Chess Championship (CCC)[6].

*Update highlights*

*Improved engine lines*

This release introduces principal variations (PVs) that are more informative
for mate and decisive table base (TB) scores. In both cases, the PV will
contain all moves up to checkmate. For mate scores, the PV shown is the best
variation known to the engine at that point, while for table base wins, it
follows, based on the TB, a sequence of moves that preserves the game outcome
to checkmate.

*NUMA performance optimization*

For high-end computers with multiple CPUs (typically a dual-socket architecture
with 100+ cores), this release automatically improves performance with a
`NumaPolicy` setting that optimizes non-uniform memory access (NUMA).  Although
typical consumer hardware will not benefit, speedups of up to 2.8x[7] have been
measured.

*Shoutouts*

*ChessDB*

During the past 1.5 years, hundreds of cores have been continuously running
Stockfish to grow a database of analyzed positions. This chess cloud
database[8] now contains well over 45 billion positions, providing excellent
coverage of all openings and commonly played lines. This database is already
integrated into GUIs such as En Croissant[9] and Nibbler[10], which access it
through the public API.

*Leela Chess Zero*

Generally considered to be the strongest GPU engine, it continues to provide
open data which is essential for training our NNUE networks. They released
version 0.31.1[11] of their engine a few weeks ago, check it out!

*Website redesign*

Our website has undergone a redesign in recent months, most notably in our home
page[12], now featuring a darker color scheme and a more modern aesthetic,
while still maintaining its core identity. We hope you'll like it as much as we
do!

*Thank you*

The Stockfish project builds on a thriving community of enthusiasts (thanks
everybody!) who contribute their expertise, time, and resources to build a free
and open-source chess engine that is robust, widely available, and very strong.

We would like to express our gratitude for the 11k stars[13] that light up our
GitHub project! Thank you for your support and encouragement – your recognition
means a lot to us.

We invite our chess fans to join the Fishtest testing framework[14] to
contribute compute resources needed for development. Programmers can contribute
to the project either directly to Stockfish[15] (C++), to Fishtest[16] (HTML,
CSS, JavaScript, and Python), to our trainer nnue-pytorch[17] (C++ and Python),
or to our website[18] (HTML, CSS/SCSS, and JavaScript).

The Stockfish team

[1] https://discord.gg/GWDRS3kU6R
[2] https://tests.stockfishchess.org/tests/view/66d738ba9de3e7f9b33d159a
[3] https://tests.stockfishchess.org/tests/view/66d738f39de3e7f9b33d15a0
[4] https://github.com/official-stockfish/Stockfish/wiki/Useful-data#equivalent-time-odds-and-normalized-game-pair-elo
[5] https://en.wikipedia.org/wiki/Stockfish_(chess)#Top_Chess_Engine_Championship
[6] https://en.wikipedia.org/wiki/Stockfish_(chess)#Chess.com_Computer_Chess_Championship
[7] https://github.com/official-stockfish/Stockfish/pull/5285
[8] https://chessdb.cn/queryc_en/
[9] https://encroissant.org/
[10] https://github.com/rooklift/nibbler
[11] https://github.com/LeelaChessZero/lc0/releases/tag/v0.31.1
[12] https://stockfishchess.org/
[13] https://github.com/official-stockfish/Stockfish/stargazers
[14] https://github.com/official-stockfish/fishtest/wiki/Running-the-worker
[15] https://github.com/official-stockfish/Stockfish
[16] https://github.com/official-stockfish/fishtest
[17] https://github.com/official-stockfish/nnue-pytorch
[18] https://github.com/official-stockfish/stockfish-web
2024-09-06 16:53:45 +02:00
Joost VandeVondele
38e0cc7b90 Update Top CPU Contributors
to the status as of Aug 31st 2024.

closes https://github.com/official-stockfish/Stockfish/pull/5561

No functional change
2024-09-03 17:53:23 +02:00
Robert Nurnberg @ elitebook
2054add23c Update the WDL model
updates the internal WDL model, using data from 2.6M games played by the revisions since 9fb5832.

https://github.com/official-stockfish/Stockfish/pull/5565

No functional change
2024-09-03 17:53:23 +02:00
Joost VandeVondele
ab00c24c7e Fix some of the tests
due to https://github.com/official-stockfish/Stockfish/issues/5185 some CI tests are skipped.
This patch fixes a few tests that need updating.

closes https://github.com/official-stockfish/Stockfish/pull/5560

No functional change
2024-09-03 17:48:58 +02:00
FauziAkram
451044202a Simpler formula for ss->cutoffCnt update
closes https://github.com/official-stockfish/Stockfish/pull/5548

No functional change
2024-08-28 09:35:21 +02:00
Taras Vuk
54def6f7eb rename !(PvNode || cutNode) to allNode
Passed STC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 108992 W: 28178 L: 28039 D: 52775
Ptnml(0-2): 356, 12428, 28762, 12621, 329
https://tests.stockfishchess.org/tests/view/66c73a51bf8c9d8780fda532

closes https://github.com/official-stockfish/Stockfish/pull/5549

No functional change
2024-08-28 09:34:09 +02:00
Tomasz Sobczyk
a0597b1281 Forcibly split NUMA nodes on Windows
split by processor groups due to Window's thread scheduler issues.

fixes #5551
closes https://github.com/official-stockfish/Stockfish/pull/5552

No functional change
2024-08-28 08:52:24 +02:00
Taras Vuk
9fb58328e3 Tweak late move extensions
Allow late move extensions only for PV and cut nodes.

Passed STC:
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 44512 W: 11688 L: 11355 D: 21469
Ptnml(0-2): 167, 5180, 11229, 5513, 167
https://tests.stockfishchess.org/tests/view/66c0509d4ff211be9d4ef10e

Passed LTC:
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 152970 W: 39026 L: 38466 D: 75478
Ptnml(0-2): 102, 16792, 42164, 17298, 129
https://tests.stockfishchess.org/tests/view/66c0994d21503a509c13b2b6

closes https://github.com/official-stockfish/Stockfish/pull/5541

bench: 1484730
2024-08-20 21:37:25 +02:00
Shawn Xu
d275bf9643 Introduce Fail Low History Bonus
When a node fails low, give TT move a small bonus 1/4 of normal value.

Passed STC:
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 92384 W: 24094 L: 23691 D: 44599
Ptnml(0-2): 323, 10852, 23465, 11203, 349
https://tests.stockfishchess.org/tests/view/66be80794ff211be9d4eed68

Passed LTC:
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 114660 W: 29260 L: 28778 D: 56622
Ptnml(0-2): 97, 12506, 31653, 12966, 108
https://tests.stockfishchess.org/tests/view/66bf63ee4ff211be9d4eeef0

closes https://github.com/official-stockfish/Stockfish/pull/5539

bench 1463003
2024-08-20 21:34:19 +02:00
Nonlinear2
6cf7f300ac Simplify stand pat adjustement
Remove && !PvNode condition for stand pat adjustement in quiescence search.

Passed non-regression STC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 108544 W: 28228 L: 28085 D: 52231
Ptnml(0-2): 389, 12902, 27554, 13031, 396
https://tests.stockfishchess.org/tests/view/66bb402e4ff211be9d4ee688

Passed non-regression LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 193014 W: 48796 L: 48751 D: 95467
Ptnml(0-2): 188, 21481, 53116, 21542, 180
https://tests.stockfishchess.org/tests/view/66bc78774ff211be9d4ee88f

closes https://github.com/official-stockfish/Stockfish/pull/5538

Bench 1787360
2024-08-20 21:31:33 +02:00
Shawn Xu
87814d2fb8 Simplify doShallowerSearch
Passed Non-regression STC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 242336 W: 62657 L: 62663 D: 117016
Ptnml(0-2): 941, 28949, 61418, 28895, 965
https://tests.stockfishchess.org/tests/view/66bc13c34ff211be9d4ee794

Passed Non-regression LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 128100 W: 32503 L: 32390 D: 63207
Ptnml(0-2): 106, 14319, 35113, 14380, 132
https://tests.stockfishchess.org/tests/view/66bdbb304ff211be9d4eec5d

closes https://github.com/official-stockfish/Stockfish/pull/5537

bench 1586246
2024-08-20 21:27:58 +02:00
Shawn Xu
175021721c Simplify bestMove promotion
Passed Non-regression STC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 216768 W: 56240 L: 56217 D: 104311
Ptnml(0-2): 794, 24900, 56956, 24957, 777
https://tests.stockfishchess.org/tests/view/66bc11324ff211be9d4ee78b

Passed Non-regression LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 44970 W: 11391 L: 11199 D: 22380
Ptnml(0-2): 44, 4596, 13002, 4810, 33
https://tests.stockfishchess.org/tests/view/66bdbb1b4ff211be9d4eec5a

closes https://github.com/official-stockfish/Stockfish/pull/5535

bench: 1613043
2024-08-20 21:24:04 +02:00
Linmiao Xu
5d81071953 Update default main net to nn-1111cefa1111.nnue
Created from 2 distinct spsa tunes of the latest main net (nn-31337bea577c.nnue)
and applying the params to the prior main net (nn-e8bac1c07a5a.nnue). This
effectively reverts the modifications to output weights and biases in
https://github.com/official-stockfish/Stockfish/pull/5509

SPSA:
A: 6000, alpha: 0.602, gamma: 0.101

1st - 437 feature transformer biases where values are < 25
54k / 120k games at 180+1.8
https://tests.stockfishchess.org/tests/view/66af98ac4ff211be9d4edad0
nn-808259761cca.nnue

2nd - 208 L2 weights where values are zero
112k / 120k games at 180+1.8
https://tests.stockfishchess.org/tests/view/66b0c3074ff211be9d4edbe5
nn-a56cb8c3d477.nnue

When creating the above 2 nets (nn-808259761cca.nnue, nn-a56cb8c3d477.nnue),
spsa params were unintentionally applied to nn-e8bac1c07a5a.nnue rather
than nn-31337bea577c.nnue due to an issue in a script that creates nets
by applying spsa results to base nets.

Since they both passed STC and were neutral or slightly positive at LTC,
they were combined to see if the elo from each set of params was additive.

The 2 nets can be merged on top of nn-e8bac1c07a5a.nnue with:
https://github.com/linrock/nnue-tools/blob/90942d3/spsa/combine_nnue.py
```
python3 combine_nnue.py \
  nn-e8bac1c07a5a.nnue \
  nn-808259761cca.nnue \
  nn-a56cb8c3d477.nnue
```

Merging yields nn-87caa003fc6a.nnue which was renamed to nn-1111cefa1111.nnue
with an updated nnue-namer around 10x faster than before by:
- using a prefix trie for efficient prefix matches
- modifying 4 non-functional bytes near the end of the file instead of 2
https://github.com/linrock/nnue-namer

Thanks to @MinetaS for pointing out in #nnue-dev what the non-functional bytes are:
  L3 is 32, 4 bytes for biases, 32 bytes for weights. (fc_2)
  So -38 and -37 are technically -2 and -1 of fc_1 (type AffineTransform<30, 32>)
  And since InputDimension is padded to 32 there are total 32 of 2 adjacent bytes padding.
  So yes, it's non-functional whatever values are there.
  It's possible to tweak bytes at -38 - 32 * N and -37 - 32 * N given N = 0 ... 31

The net renamed with the new method passed non-regression STC vs. the original net:
https://tests.stockfishchess.org/tests/view/66c0f0a821503a509c13b332

To print the spsa params with nnue-pytorch:
```
import features
from serialize import NNUEReader

feature_set = features.get_feature_set_from_name("HalfKAv2_hm")

with open("nn-31337bea577c.nnue", "rb") as f:
    model = NNUEReader(f, feature_set).model

c_end = 16
for i,ft_bias in enumerate(model.input.bias.data[:3072]):
    value = int(ft_bias * 254)
    if abs(value) < 25:
        print(f"ftB[{i}],{value},-1024,1024,{c_end},0.0020")

c_end = 6
for i in range(8):
    for j in range(32):
        for k in range(30):
            value = int(model.layer_stacks.l2.weight.data[32 * i + j, k] * 64)
            if value == 0:
                print(f"twoW[{i}][{j}][{k}],{value},-127,127,{c_end},0.0020")
```

New params found with the same method as:
https://github.com/official-stockfish/Stockfish/pull/5459

Passed STC:
https://tests.stockfishchess.org/tests/view/66b4d4464ff211be9d4edf6e
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 136416 W: 35753 L: 35283 D: 65380
Ptnml(0-2): 510, 16159, 34416, 16597, 526

Passed LTC:
https://tests.stockfishchess.org/tests/view/66b76e814ff211be9d4ee1cc
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 159336 W: 40753 L: 40178 D: 78405
Ptnml(0-2): 126, 17497, 43864, 18038, 143

closes https://github.com/official-stockfish/Stockfish/pull/5534

bench 1613043
2024-08-20 20:59:36 +02:00
FauziAkram
4995792a6c Simplify cutnode reduction formula
Passed STC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 137994 W: 34705 L: 34603 D: 68686
Ptnml(0-2): 124, 15371, 37903, 15477, 122
https://tests.stockfishchess.org/tests/view/66aeb74b4ff211be9d4eda10

Passed LTC:
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 131456 W: 34148 L: 34031 D: 63277
Ptnml(0-2): 506, 15571, 33465, 15672, 514
https://tests.stockfishchess.org/tests/view/66ae258b4ff211be9d4ed95d

closes https://github.com/official-stockfish/Stockfish/pull/5531

Bench: 1261995
2024-08-20 20:57:07 +02:00
Shawn Xu
a75717ede1 Simplify Post-LMR Continuation History Updates
Passed Non-regression STC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 55520 W: 14625 L: 14420 D: 26475
Ptnml(0-2): 247, 6522, 14007, 6747, 237
https://tests.stockfishchess.org/tests/view/66ad40874ff211be9d4ed8f7

Passed Non-regression LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 216168 W: 54561 L: 54540 D: 107067
Ptnml(0-2): 196, 24212, 59244, 24239, 193
https://tests.stockfishchess.org/tests/view/66aeac954ff211be9d4eda03

closes https://github.com/official-stockfish/Stockfish/pull/5530

bench 1418263
2024-08-20 20:51:39 +02:00
Shawn Xu
bc80ece6c7 Improve Comments for Pairwise Multiplication Optimization
closes https://github.com/official-stockfish/Stockfish/pull/5524

no functional change
2024-08-20 20:47:46 +02:00
Disservin
d626af5c3a Fix failing CI for MacOS 13 GCC 11
closes https://github.com/official-stockfish/Stockfish/pull/5540

No functional change
2024-08-20 20:44:55 +02:00
Shawn Xu
ae9e55cf53 Simplify Cutnode Reduction
Passed Non-regression STC:
LR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 143968 W: 37439 L: 37333 D: 69196
Ptnml(0-2): 521, 17228, 36456, 17182, 597
https://tests.stockfishchess.org/tests/view/66a73f9f4ff211be9d4ed27f

Passed Non-regression LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 198954 W: 50384 L: 50345 D: 98225
Ptnml(0-2): 201, 22360, 54347, 22337, 232
https://tests.stockfishchess.org/tests/view/66a906e94ff211be9d4ed423

closes https://github.com/official-stockfish/Stockfish/pull/5526

bench 1277466
2024-08-03 09:42:54 +02:00
MinetaS
b976f0a101 Move DotProd code into optimized affine layer
This patch moves the DotProd code into the propagation function which
has sequential access optimization. To prove the speedup, the comparison
is done without the sparse layer. With the sparse layer the effect is
marginal (GCC 0.3%, LLVM/Clang 0.1%).

For both tests, binary is compiled with GCC 14.1. Each test had 50 runs.

Sparse layer included:
```
speedup        = +0.0030
P(speedup > 0) =  1.0000
```

Sparse layer excluded:
```
speedup        = +0.0561
P(speedup > 0) =  1.0000
```

closes https://github.com/official-stockfish/Stockfish/pull/5520

No functional change
2024-08-03 09:42:03 +02:00
Tomasz Sobczyk
8e560c4fd3 Replicate network weights only to used NUMA nodes
On a system with multiple NUMA nodes, this patch avoids unneeded replicated
(e.g. 8x for a single threaded run), reducting memory use in that case.

Lazy initialization forced before search.

Passed STC:
https://tests.stockfishchess.org/tests/view/66a28c524ff211be9d4ecdd4
LLR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 691776 W: 179429 L: 179927 D: 332420
Ptnml(0-2): 2573, 79370, 182547, 78778, 2620

closes https://github.com/official-stockfish/Stockfish/pull/5515

No functional change
2024-08-03 09:41:37 +02:00
Shawn Xu
2343f71f3f Remove Killers
The removal of killers on line 1774 resulted in a substantial decrease
in pre-LMR history average, so a negative history fill is applied to
counter it.

Passed Non-regression STC (vs #5513):
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 21984 W: 5886 L: 5645 D: 10453
Ptnml(0-2): 80, 2492, 5628, 2691, 101
https://tests.stockfishchess.org/tests/view/66a095894ff211be9d4ecb9d

Passed Non-regression LTC (vs #5513):
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 95430 W: 24141 L: 23995 D: 47294
Ptnml(0-2): 97, 10537, 26298, 10689, 94
https://tests.stockfishchess.org/tests/view/66a11c8d4ff211be9d4ecbf8

closes https://github.com/official-stockfish/Stockfish/pull/5517

Bench: 1660869
2024-07-28 22:22:50 +02:00
Stéphane Nicolet
af802da65b Clean up comments for movepicker
Remove references to checks in MovePicker comments. Follow-up for
https://github.com/official-stockfish/Stockfish/pull/5498

closes https://github.com/official-stockfish/Stockfish/pull/5516

No functional change
2024-07-28 22:21:03 +02:00
Michael Chaly
607c3e404f Remove unneeded depth tracking in qsearch
Since simplification of quiet checks in qsearch this depth isn't used by
any function at all apart movepicker, which also doesn't use passed
qsearch depth in any way, so can be removed. No functional change.

closes https://github.com/official-stockfish/Stockfish/pull/5514

No functional change
2024-07-28 22:18:33 +02:00
Shawn Xu
85893ac1cd Simplify Away Killer Condition in Cutnode LMR
Passed Non-regression STC:
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 42944 W: 11240 L: 11024 D: 20680
Ptnml(0-2): 159, 5056, 10825, 5274, 158
https://tests.stockfishchess.org/tests/view/669c13384ff211be9d4ec69f

Passed Non-regression LTC:
LLR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 163548 W: 41366 L: 41289 D: 80893
Ptnml(0-2): 109, 18246, 45007, 18283, 129
https://tests.stockfishchess.org/tests/view/669cb1254ff211be9d4ec73a

closes https://github.com/official-stockfish/Stockfish/pull/5513

Bench: 1178570
2024-07-28 22:13:47 +02:00
Linmiao Xu
b55217fd02 Update default main net to nn-31337bea577c.nnue
Created by updating output weights (256) and biases (8)
of the previous main net with values found with spsa around
101k / 120k games at 140+1.4.

264 spsa params: output weights and biases in nn-e8bac1c07a5a.nnue
A: 6000, alpha: 0.602, gamma: 0.101
weights: [-127, 127], c_end = 6
biases: [-8192, 8192], c_end = 64

Among the 264 params, 189 weights and all 8 biases were changed.

Changes in the weights:
- mean: -0.111 +/- 3.57
- range: [-8, 8]

Found with the same method as:
https://github.com/official-stockfish/Stockfish/pull/5459

Due to the original name (nn-ea8c9128c325.nnue) being too similar
to the previous main net (nn-e8bac1c07a5a.nnue) and creating confusion,
it was renamed by making non-functional changes to the .nnue file
the same way as past nets with:
https://github.com/linrock/nnue-namer

To verify that bench is the same and view the modified non-functional bytes:
```
echo -e "setoption name EvalFile value nn-ea8c9128c325.nnue\nbench" | ./stockfish
echo -e "setoption name EvalFile value nn-31337bea577c.nnue\nbench" | ./stockfish

cmp -l nn-ea8c9128c325.nnue nn-31337bea577c.nnue

diff <(xxd nn-ea8c9128c325.nnue) <(xxd nn-31337bea577c.nnue)
```

Passed STC:
https://tests.stockfishchess.org/tests/view/669564154ff211be9d4ec080
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 57280 W: 15139 L: 14789 D: 27352
Ptnml(0-2): 209, 6685, 14522, 6995, 229

Passed LTC:
https://tests.stockfishchess.org/tests/view/669694204ff211be9d4ec1b4
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 63030 W: 16093 L: 15720 D: 31217
Ptnml(0-2): 47, 6766, 17516, 7139, 47

closes https://github.com/official-stockfish/Stockfish/pull/5509

bench 1371485
2024-07-23 19:34:27 +02:00
Michael Chaly
836154acb5 Introduce pre-qsearch ttmove extensions at pv nodes
The idea is that we are about to dive into qsearch (next search depth is <= 0)
but since we have the move in transposition table we should extend that move
and evaluate it with more precise search - because branch seems important.

Passed STC:
https://tests.stockfishchess.org/tests/view/6699d2564ff211be9d4ec488
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 83104 W: 21789 L: 21401 D: 39914
Ptnml(0-2): 293, 9748, 21128, 10044, 339

Passed LTC:
https://tests.stockfishchess.org/tests/view/669b3f1a4ff211be9d4ec602
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 136098 W: 34636 L: 34111 D: 67351
Ptnml(0-2): 105, 14882, 37550, 15407, 105

closes https://github.com/official-stockfish/Stockfish/pull/5512

bench 1526129
2024-07-23 19:24:00 +02:00
Shawn Xu
985b9fd7b0 Remove Killer Heuristic In Move Ordering
Passed Non-regression STC:
LLR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 80480 W: 20979 L: 20802 D: 38699
Ptnml(0-2): 279, 9610, 20337, 9683, 331
https://tests.stockfishchess.org/tests/view/669c12c14ff211be9d4ec69b

Passed Non-regression LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 77988 W: 19788 L: 19624 D: 38576
Ptnml(0-2): 66, 8605, 21481, 8783, 59
https://tests.stockfishchess.org/tests/view/669d628a4ff211be9d4ec7a8

closes https://github.com/official-stockfish/Stockfish/pull/5511

bench 1367740
2024-07-23 19:24:00 +02:00
Linmiao Xu
1e2f051103 Replace simple eval with psqt in re-eval condition
As a result, re-eval depends only on smallnet outputs
so an extra call to simple eval can be removed.

Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/669743054ff211be9d4ec232
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 214912 W: 55801 L: 55777 D: 103334
Ptnml(0-2): 746, 24597, 56760, 24593, 760

https://github.com/official-stockfish/Stockfish/pull/5501

Bench: 1440277
2024-07-23 19:24:00 +02:00
Shahin M. Shahin
bb4b01e306 Fix TB guard
even if beta is below TB range, once we return probcutBeta with beta + 390 we
can return wrong TB value, and guard against ttData.value being `VALUE_NONE`

closes https://github.com/official-stockfish/Stockfish/pull/5499

bench: 1440277
2024-07-23 19:24:00 +02:00
FauziAkram
986173264f Adding LowestElo and HighestElo constants
These values represent the lowest Elo rating in the skill level calculation,
and the highest one, but it's not clear from the code where these values come
from other than the comment.  This should improve code readability and
maintainability. It makes the purpose of the values clear and allows for easy
modification if the Elo range for skill level calculation changes in the
future.  Moved the Skill struct definition from search.cpp to search.h header
file to define the Search::Skill struct, making it accessible from other files.

closes https://github.com/official-stockfish/Stockfish/pull/5508

No functional change
2024-07-23 19:23:57 +02:00
FauziAkram
a2ba3e3362 Bonus Simplification
This tune removes completely a recently added term.

Passed STC:
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 61376 W: 16046 L: 15693 D: 29637
Ptnml(0-2): 207, 7132, 15665, 7469, 215
https://tests.stockfishchess.org/tests/view/669512b94ff211be9d4ebffb

Passed LTC:
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 100662 W: 25474 L: 25020 D: 50168
Ptnml(0-2): 64, 11092, 27581, 11514, 80
https://tests.stockfishchess.org/tests/view/66955f194ff211be9d4ec06a

Passed LTC#2:
LLR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 28056 W: 7128 L: 6909 D: 14019
Ptnml(0-2): 18, 3084, 7620, 3273, 33
https://tests.stockfishchess.org/tests/view/669a541a4ff211be9d4ec52b

closes https://github.com/official-stockfish/Stockfish/pull/5502

bench: 1619438
2024-07-23 18:01:14 +02:00
Dubslow
703f17975b Remove QS_CHECKS movepick stage
Passed STC: https://tests.stockfishchess.org/tests/view/669597cf4ff211be9d4ec147
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 199072 W: 52100 L: 52058 D: 94914
Ptnml(0-2): 829, 23679, 50406, 23865, 757

Passed LTC: https://tests.stockfishchess.org/tests/view/66988f5f4ff211be9d4ec33e
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 119778 W: 30420 L: 30299 D: 59059
Ptnml(0-2): 106, 13293, 32957, 13440, 93

closes https://github.com/official-stockfish/Stockfish/pull/5498

Bench 1499842
2024-07-23 17:56:52 +02:00
Joost VandeVondele
e57fba7fc9 Fix TB PV extension and MultiPV
in the case of MultiPV, the first move of the Nth multiPV could actually turn a
winning position in a losing one, so don't attempt to correct it. Instead,
always perform the first move without correction.

Fixes #5505

Closes https://github.com/official-stockfish/Stockfish/pull/5506

No functional change
2024-07-23 17:51:30 +02:00
Joost VandeVondele
1fb4dc2e0f Enable syzygy in the matetrack action
now checks correctness of PV lines with TB score.

uses 3-4-5 man table bases, downloaded from lichess,
which are cached with the appropriate action.

closes https://github.com/official-stockfish/Stockfish/pull/5500

No functional change
2024-07-23 17:49:07 +02:00
Michael Chaly
a8401e803d Adjust bonus to move that caused a fail low
This is an elo gainer and simultaneously a minor logical fix to bonuses that caused a fail low.
It increases maximum of statscore based subtraction - but disallows negative bonuses.

Passed STC:
https://tests.stockfishchess.org/tests/view/66955e6f4ff211be9d4ec063
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 44640 W: 11805 L: 11472 D: 21363
Ptnml(0-2): 166, 5178, 11335, 5439, 202

Passed LTC:
https://tests.stockfishchess.org/tests/view/66963fde4ff211be9d4ec190
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 72288 W: 18478 L: 18082 D: 35728
Ptnml(0-2): 50, 7919, 19825, 8285, 65

closes https://github.com/official-stockfish/Stockfish/pull/5494

Bench: 1477054
2024-07-19 08:41:38 +02:00
Linmiao Xu
c2837769e0 Avoid calculating nnue complexity twice
Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/6697459d4ff211be9d4ec236
LLR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 146848 W: 38289 L: 38189 D: 70370
Ptnml(0-2): 503, 16665, 39046, 16649, 561

closes https://github.com/official-stockfish/Stockfish/pull/5493

No functional change
2024-07-19 08:40:23 +02:00
Shahin M. Shahin
c8d8e362fc Try nullmoves only on cutnodes
since master only tries nullmoves on cutNodes already with 99.0224% of the
cases running bench, We can try null moves at 100% of cutNodes and achieve such
simplification, by making passing false already equivalent to passing !cutNode

This is a more correct form of PR #5482

Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/66941c044ff211be9d4ebf5f
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 153216 W: 39856 L: 39764 D: 73596
Ptnml(0-2): 590, 18174, 38979, 18284, 581

Passed non-regression LTC:
https://tests.stockfishchess.org/tests/view/6694e5cd4ff211be9d4ebfdf
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 67842 W: 17178 L: 17004 D: 33660
Ptnml(0-2): 52, 7437, 18759, 7631, 42

closes https://github.com/official-stockfish/Stockfish/pull/5490

bench: 1345400

Co-Authored-By: FauziAkram <11150271+fauziakram@users.noreply.github.com>
2024-07-19 08:38:13 +02:00
Dubslow
27042fe949 Linearize corrHist
Passed STC: https://tests.stockfishchess.org/tests/view/66919cdec6827afcdcee146f
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 130656 W: 33579 L: 33461 D: 63616
Ptnml(0-2): 394, 15548, 33318, 15682, 386

Passed VVLTC: https://tests.stockfishchess.org/tests/view/6691acb2c6827afcdcee1645
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 160314 W: 40925 L: 40854 D: 78535
Ptnml(0-2): 12, 14754, 50551, 14831, 9

closes https://github.com/official-stockfish/Stockfish/pull/5489

bench 1380295
2024-07-19 08:36:25 +02:00
yl25946
7bb45d05fa Replace ternary with std::min
equivalent and more readable.

closes https://github.com/official-stockfish/Stockfish/pull/5488

No functional change
2024-07-19 08:34:02 +02:00
Guenther Demetz
c755bc1a73 Simplify improving condition
if we were in check at our previous move we look back until we weren't
in check and take the staticEval of that position as reference.

Passed STC:
https://tests.stockfishchess.org/tests/view/668ba7b65034141ae5996665
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 74784 W: 19454 L: 19274 D: 36056
Ptnml(0-2): 260, 8874, 18952, 9038, 268

Passted LTC:
https://tests.stockfishchess.org/tests/view/668cb2db5034141ae599678b
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 241488 W: 61166 L: 61171 D: 119151
Ptnml(0-2): 190, 27154, 66062, 27147, 191

closes https://github.com/official-stockfish/Stockfish/pull/5492

bench: 1368313
2024-07-19 08:32:16 +02:00
Linmiao Xu
e443b2459e Separate eval params for smallnet and main net
Values found with spsa around 80% of 120k games at 60+0.6:
https://tests.stockfishchess.org/tests/view/669205dac6827afcdcee3ea4

Passed STC:
https://tests.stockfishchess.org/tests/view/6692928b4ff211be9d4e98a9
LLR: 2.96 (-2.94,2.94) <0.00,2.00>
Total: 313696 W: 81107 L: 80382 D: 152207
Ptnml(0-2): 934, 36942, 80363, 37683, 926

Passed LTC:
https://tests.stockfishchess.org/tests/view/6692aab54ff211be9d4e9915
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 228420 W: 57903 L: 57190 D: 113327
Ptnml(0-2): 131, 25003, 63243, 25688, 145

closes https://github.com/official-stockfish/Stockfish/pull/5486

bench 1319322
2024-07-15 13:38:14 +02:00
Michael Chaly
de2bf1a186 Remove quiet history pruning depth limit
This patch removes lmrDepth limit for quiet moves history based pruning.

Previously removal of this type of depth limits was considered bad because it
was performing bad for matetrack - but with this pruning heuristic this
shouldn't be that bad because it's "naturally" depth limited by history
threshold and should be completely disabled at depth >= 15 or so.  Also this
heuristic in previous years was known to scale non-linearly - bigger lmrDepth
thresholds were better at longer time controls and removing it completely
probably should scale pretty well.

Passed STC:
https://tests.stockfishchess.org/tests/view/6692b89b4ff211be9d4eab21
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 114464 W: 29675 L: 29545 D: 55244
Ptnml(0-2): 372, 12516, 31329, 12640, 375

Passed LTC:
https://tests.stockfishchess.org/tests/view/6692c4554ff211be9d4eab3d
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 67746 W: 17182 L: 17014 D: 33550
Ptnml(0-2): 28, 6993, 19652, 7183, 17

closes https://github.com/official-stockfish/Stockfish/pull/5485

Bench: 1250388
2024-07-15 13:35:06 +02:00
MinetaS
2b37b151dd Use ValueList to represent searched moves array
This PR replaces a pair of array and size with existing ValueList class.
Removes two local variables in search and two parameters of
update_all_stats.

Passed non-regression STC:
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 227040 W: 58472 L: 58463 D: 110105
Ptnml(0-2): 495, 23572, 65427, 23481, 545
https://tests.stockfishchess.org/tests/view/669299204ff211be9d4e98dc

closes https://github.com/official-stockfish/Stockfish/pull/5484

No functional change
2024-07-15 13:30:47 +02:00
FauziAkram
7395d56832 bonus calculation for prior countermoves
Introduce a new term to the bonus calculation for prior countermoves

Passed STC:
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 140896 W: 36545 L: 36079 D: 68272
Ptnml(0-2): 383, 16505, 36217, 16949, 394
https://tests.stockfishchess.org/tests/view/6691c73cc6827afcdcee1816

Passed LTC:
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 126660 W: 32089 L: 31587 D: 62984
Ptnml(0-2): 63, 13774, 35154, 14276, 63
https://tests.stockfishchess.org/tests/view/6691cdc4c6827afcdcee1930

closes https://github.com/official-stockfish/Stockfish/pull/5483

bench: 1250388
2024-07-15 13:27:42 +02:00
Linmiao Xu
558abdbe8a Set best value to futility value after pruned quiet move
Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/6691592f5034141ae599c68d
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 278496 W: 71818 L: 71865 D: 134813
Ptnml(0-2): 865, 33311, 70978, 33194, 900

Passed non-regression LTC:
https://tests.stockfishchess.org/tests/view/66918fca5034141ae599e761
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 202986 W: 51048 L: 51013 D: 100925
Ptnml(0-2): 107, 22552, 56133, 22601, 100

closes https://github.com/official-stockfish/Stockfish/pull/5480

bench 1715206
2024-07-15 13:24:14 +02:00
Michael Chaly
930915de90 Decrease delta
Decrease delta in aspiration windows - both initial value and quadratic
function of previous best value.

Passed STC:
https://tests.stockfishchess.org/tests/view/6691a52ec6827afcdcee1569
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 55456 W: 14449 L: 14107 D: 26900
Ptnml(0-2): 174, 6416, 14193, 6784, 161

Passed LTC:
https://tests.stockfishchess.org/tests/view/6691aac1c6827afcdcee1625
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 107940 W: 27530 L: 27065 D: 53345
Ptnml(0-2): 52, 11787, 29840, 12226, 65

closes https://github.com/official-stockfish/Stockfish/pull/5479

bench 1547707
2024-07-15 13:22:31 +02:00
MinetaS
563d268519 Simplify futility_move_count
This patch reverts changes from #4032 which was introduced as a speedup.
Modern compilers no longer use DIV/IDIV instructions, potentially making
the explicit branch perform worse. Since evaluations spend significantly
more time now, the impact of the speedup in search diminishes with old
compilers as well.

GCC 14.1.0 profile-build, x86-64-vnni512
```
.text:000000014010FEA9                 mov     ecx, [rsp+3FB8h+var_3F5C]
...
.text:000000014010FEBD                 mov     r10d, ecx
.text:000000014010FEC0                 imul    r10d, ecx
.text:000000014010FEC4                 mov     ecx, dword ptr [rsp+3FB8h+var_3F44+4]
.text:000000014010FEC8                 add     r10d, 3
.text:000000014010FECC                 mov     r11d, r10d
.text:000000014010FECF                 sar     r11d, 1
.text:000000014010FED2                 cmp     [rsp+3FB8h+var_3EE7], 0
.text:000000014010FEDA                 cmovnz  r11d, r10d
```

LLVM 18.1.18 profile-build, x86-64-vnni512
```
.text:0000000140001EDC                 mov     [rsp+40h+arg_E0], r13
.text:0000000140001EE4                 movsxd  rcx, r13d
.text:0000000140001EE7                 mov     rax, rcx
.text:0000000140001EEA                 mov     [rsp+40h+arg_B8], rcx
.text:0000000140001EF2                 imul    eax, eax
.text:0000000140001EF5                 add     eax, 3
.text:0000000140001EF8                 mov     ecx, [rsp+40h+arg_8C]
.text:0000000140001EFF                 shrx    eax, eax, ecx
.text:0000000140001F04                 mov     [rsp+40h+arg_190], rax
```

Passed non-regression STC:
LLR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 109504 W: 28420 L: 28280 D: 52804
Ptnml(0-2): 355, 12326, 29273, 12420, 378
https://tests.stockfishchess.org/tests/view/6690dc095034141ae599c5fe

closes https://github.com/official-stockfish/Stockfish/pull/5478

No functional change
2024-07-15 13:19:46 +02:00
Shawn Xu
024eb6f453 Unify Movepick Initializer
Passed Non-regression STC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 168704 W: 43524 L: 43455 D: 81725
Ptnml(0-2): 414, 17173, 49076, 17308, 381
https://tests.stockfishchess.org/tests/view/66904b7b5034141ae599a197

Passed Non-regression LTC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 120294 W: 30473 L: 30364 D: 59457
Ptnml(0-2): 40, 10974, 38032, 11039, 62
https://tests.stockfishchess.org/tests/view/66905b235034141ae599a223

closes https://github.com/official-stockfish/Stockfish/pull/5477

bench 1459677
2024-07-15 13:18:37 +02:00
Shawn Xu
3df09c04d7 Simplify Away Refutation Stage
Simplify away killer stage to a constant bonus given to the killer move during
quiet move scoring.

Passed Non-regression STC (Against then-pending PR #5472):
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 106176 W: 27685 L: 27539 D: 50952
Ptnml(0-2): 410, 12765, 26637, 12821, 455
https://tests.stockfishchess.org/tests/view/668dd0835034141ae5999e8f

Passed Non-regression LTC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 92472 W: 23426 L: 23276 D: 45770
Ptnml(0-2): 55, 10376, 25215, 10544, 46
https://tests.stockfishchess.org/tests/view/669019e45034141ae5999fd2

closes https://github.com/official-stockfish/Stockfish/pull/5476

Bench 1459677
2024-07-15 13:15:35 +02:00
Andyson007
42aae5fe8b Fixed non UCI compliance
print `<empty>` and accept `<empty>` for UCI string options,
accepting empty strings as well. Internally use empty strings (`""`).

closes https://github.com/official-stockfish/Stockfish/pull/5474

No functional change
2024-07-15 13:14:57 +02:00
yl25946
8d1e41458e removed second killer move
STC with movepicker rewrite:

LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 46656 W: 12208 L: 11995 D: 22453
Ptnml(0-2): 203, 5461, 11777, 5694, 193
https://tests.stockfishchess.org/tests/view/668d98a15034141ae5999e68

Earlier version passed STC:
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 468896 W: 120999 L: 120054 D: 227843
Ptnml(0-2): 1207, 55209, 120639, 56218, 1175
https://tests.stockfishchess.org/tests/view/668b17d2cf91c430fca58630

Earlier version passed LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 550524 W: 139553 L: 139877 D: 271094
Ptnml(0-2): 333, 61646, 151616, 61346, 321
https://tests.stockfishchess.org/tests/view/668b2e04cf91c430fca586b1

closes https://github.com/official-stockfish/Stockfish/pull/5472

bench 1234309

Co-authored-by: rn5f107s2 <clemens.lerchl@gmail.com>
2024-07-11 07:29:49 +02:00
Joost VandeVondele
6135a0e2f8 Provide more info on found TB files
now uses the following format:

`info string Found 510 WDL and 510 DTZ tablebase files (up to 6-man).`

this clarifies exactly what has been found, as the difference matters,
e.g. for the PV extension of TB scores.

closes https://github.com/official-stockfish/Stockfish/pull/5471

No functional change
2024-07-11 07:29:44 +02:00
Stéphane Nicolet
7e72b37e4c Clean up comments in code
- Capitalize comments
- Reformat multi-lines comments to equalize the widths of the lines
- Try to keep the width of comments around 85 characters
- Remove periods at the end of single-line comments

closes https://github.com/official-stockfish/Stockfish/pull/5469

No functional change
2024-07-11 07:29:33 +02:00
Disservin
98a7bb4436 CI give correct permissions for the clang-format action
closes https://github.com/official-stockfish/Stockfish/pull/5470

No functional change
2024-07-11 07:21:04 +02:00
yl25946
362a77a345 Move Loop Consistency in Probcut
In probcut move loop, everything is enclosed within a large if statement. I've
changed it to guard clauses to stay consistent with other move loops.

closes https://github.com/official-stockfish/Stockfish/pull/5463

No functional change
2024-07-09 18:54:12 +02:00
Linmiao Xu
b209f14b1e Update default main net to nn-e8bac1c07a5a.nnue
Created by modifying L2 weights from the previous main net (nn-74f1d263ae9a.nnue)
with params found by spsa around 9k / 120k games at 120+1.2.

370 spsa params - L2 weights in nn-74f1d263ae9a.nnue where |val| >= 50
A: 6000, alpha: 0.602, gamma: 0.101
weights: [-127, 127], c_end = 6

To print the spsa params with nnue-pytorch:
```
import features
from serialize import NNUEReader

feature_set = features.get_feature_set_from_name("HalfKAv2_hm")
with open("nn-74f1d263ae9a.nnue", "rb") as f:
    model = NNUEReader(f, feature_set).model

c_end = 6
for i in range(8):
    for j in range(32):
        for k in range(30):
            value = int(model.layer_stacks.l2.weight[32 * i + j, k] * 64)
            if abs(value) >= 50:
                print(f"twoW[{i}][{j}][{k}],{value},-127,127,{c_end},0.0020")
```

Among the 370 params, 229 weights were changed.
  avg change: 0.0961 ± 1.67
  range: [-4, 3]

The number of weights changed, grouped by layer stack index,
shows more weights were modified in the lower piece count buckets:
[54, 52, 29, 23, 22, 18, 14, 17]

Found with the same method described in:
https://github.com/official-stockfish/Stockfish/pull/5459

Passed STC:
https://tests.stockfishchess.org/tests/view/668aec9a58083e5fd88239e7
LLR: 3.00 (-2.94,2.94) <0.00,2.00>
Total: 52384 W: 13569 L: 13226 D: 25589
Ptnml(0-2): 127, 6141, 13335, 6440, 149

Passed LTC:
https://tests.stockfishchess.org/tests/view/668af50658083e5fd8823a0b
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 46974 W: 12006 L: 11668 D: 23300
Ptnml(0-2): 25, 4992, 13121, 5318, 31

closes https://github.com/official-stockfish/Stockfish/pull/5466

bench 1300471
2024-07-09 18:49:28 +02:00
Shawn Xu
4880ed4ad1 Simplify Probcut Malus
Passed Non-regression STC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 74880 W: 19261 L: 19083 D: 36536
Ptnml(0-2): 202, 8861, 19120, 9071, 186
https://tests.stockfishchess.org/tests/view/668a0966eca84f4d25864cba

Passed Non-regression LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 263916 W: 66690 L: 66718 D: 130508
Ptnml(0-2): 125, 29348, 73040, 29320, 125
https://tests.stockfishchess.org/tests/view/668a17e3eca84f4d25864e91

closes https://github.com/official-stockfish/Stockfish/pull/5464

bench 1331408
2024-07-09 18:44:39 +02:00
Stéphane Nicolet
acd0a933ad Fix compilation on Apple
Always use the posix function posix_memalign() as aligned memory
allocator on Apple computers. This should allow to compile Stockfish
out of the box on all versions of Mac OS X.

Patch tested on the following systems (apart from the CI) :
  • Mac OS 10.9.6 (arch x86-64-sse41-popcnt) with gcc-10
  • Mac OS 10.13.6 (arch x86-64-bmi2) with gcc-10, gcc-14 and clang-11
  • Mac OS 14.1.1 (arch apple-silicon) with clang-15

closes https://github.com/official-stockfish/Stockfish/pull/5462

No functional change
2024-07-09 18:42:21 +02:00
Michael Chaly
eac2d080a3 Further simplify stat bonuses
Based on recent simplification by linrock Since it completely removed any
special bonuses based on values difference and made it flat stat_bonus(depth +
1) I got an idea that we might as well remove all (depth + 1) bonuses and make
them usual depth bonuses.  Also removes weird negative bonus for depth 1 as a
side effect.

Passed STC:
https://tests.stockfishchess.org/tests/view/6689d817eca84f4d25863746
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 18080 W: 4789 L: 4552 D: 8739
Ptnml(0-2): 46, 1987, 4727, 2244, 36

Passed LTC:
https://tests.stockfishchess.org/tests/view/6689daa4eca84f4d258639d7
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 109062 W: 27548 L: 27417 D: 54097
Ptnml(0-2): 58, 11983, 30293, 12164, 33

Passed direct LTC vs linrock patch:
https://tests.stockfishchess.org/tests/view/668a46f8eca84f4d25866fe9
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 100002 W: 25351 L: 25209 D: 49442
Ptnml(0-2): 54, 11119, 27529, 11229, 70

closes https://github.com/official-stockfish/Stockfish/pull/5461

Bench 1175744
2024-07-09 18:41:36 +02:00
Joost VandeVondele
5d3517c601 Fix output for GUI
Fritz 19 can hang with the current way to provide output,
i.e. too much output in a short time for a mate / depth 245 found quickly.

fallout from 25361e514b

closes https://github.com/official-stockfish/Stockfish/pull/5460

No functional change
2024-07-09 18:36:46 +02:00
Linmiao Xu
5752529cab Update default main net to nn-74f1d263ae9a.nnue
Created by setting output weights (256) and biases (8) of the previous main net
nn-ddcfb9224cdb.nnue to values found around 12k / 120k spsa games at 120+1.2

This used modified fishtest dev workers to construct .nnue files from
spsa params, then load them with EvalFile when running tests:
https://github.com/linrock/fishtest/tree/spsa-file-modified-nnue/worker

Inspired by researching loading spsa params from files:
https://github.com/official-stockfish/fishtest/pull/1926

Scripts for modifying nnue files and preparing params:
https://github.com/linrock/nnue-pytorch/tree/no-gpu-modify-nnue

spsa params:
  weights: [-127, 127], c_end = 6
  biases: [-8192, 8192], c_end = 64

Example of reading output weights and biases from the previous main net using
nnue-pytorch and printing spsa params in a format compatible with fishtest:

```
import features
from serialize import NNUEReader

feature_set = features.get_feature_set_from_name("HalfKAv2_hm")
with open("nn-ddcfb9224cdb.nnue", "rb") as f:
    model = NNUEReader(f, feature_set).model

c_end_weights = 6
c_end_biases = 64

for i in range(8):
    for j in range(32):
        value = round(int(model.layer_stacks.output.weight[i, j] * 600 * 16) / 127)
        print(f"oW[{i}][{j}],{value},-127,127,{c_end_weights},0.0020")

for i in range(8):
    value = int(model.layer_stacks.output.bias[i] * 600 * 16)
    print(f"oB[{i}],{value},-8192,8192,{c_end_biases},0.0020")
```

For more info on spsa tuning params in nets:
https://github.com/official-stockfish/Stockfish/pull/5149
https://github.com/official-stockfish/Stockfish/pull/5254

Passed STC:
https://tests.stockfishchess.org/tests/view/66894d64e59d990b103f8a37
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 32000 W: 8443 L: 8137 D: 15420
Ptnml(0-2): 80, 3627, 8309, 3875, 109

Passed LTC:
https://tests.stockfishchess.org/tests/view/6689668ce59d990b103f8b8b
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 172176 W: 43822 L: 43225 D: 85129
Ptnml(0-2): 97, 18821, 47633, 19462, 75

closes https://github.com/official-stockfish/Stockfish/pull/5459

bench 1120091
2024-07-09 18:35:23 +02:00
MinetaS
cdb0b96e07 Clean up refutations array in MovePicker
This is a follow-up cleanup to a45c2bc34a.

closes https://github.com/official-stockfish/Stockfish/pull/5458

No functional change
2024-07-09 18:34:00 +02:00
Linmiao Xu
4e9fded5a6 Larger bonus when updating quiet stats
Also removes unused arguments to update_all_stats to
fix compiler warnings about unused parameters.

Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/6689a79a0fdd852d63cf52e9
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 26496 W: 6901 L: 6669 D: 12926
Ptnml(0-2): 62, 3094, 6715, 3304, 73

Passed non-regression LTC:
https://tests.stockfishchess.org/tests/view/6689a9960fdd852d63cf532d
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 41214 W: 10373 L: 10173 D: 20668
Ptnml(0-2): 11, 4491, 11412, 4673, 20

closes https://github.com/official-stockfish/Stockfish/pull/5456

bench 1169958
2024-07-09 18:31:02 +02:00
Michael Chaly
75c8cb2c2f Adjust usage of previous statscore in bonus assignments
This patch adjusts usage of previous statscore for bonus assginments - allowing
it for any statscores and clamping it to wider range.

Passed STC:
https://tests.stockfishchess.org/tests/view/66892e76e59d990b103f6a91
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 431520 W: 111767 L: 110872 D: 208881
Ptnml(0-2): 1180, 51165, 110133, 52144, 1138

Passed LTC:
https://tests.stockfishchess.org/tests/view/66897176e59d990b103f9605
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 143184 W: 36463 L: 35929 D: 70792
Ptnml(0-2): 55, 15540, 39863, 16084, 50

closes https://github.com/official-stockfish/Stockfish/pull/5455

bench 1330556
2024-07-09 18:29:09 +02:00
Linmiao Xu
bb9b65408f Simplify improving deduction in futility margin
Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/668981d4df142e108ffc9bb4
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 312672 W: 80280 L: 80363 D: 152029
Ptnml(0-2): 729, 37198, 80529, 37187, 693

Passed non-regression LTC:
https://tests.stockfishchess.org/tests/view/668988c6df142e108ffca042
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 126042 W: 31971 L: 31857 D: 62214
Ptnml(0-2): 50, 13988, 34832, 14100, 51

closes https://github.com/official-stockfish/Stockfish/pull/5454

bench 1100483
2024-07-09 18:28:06 +02:00
Shawn Xu
2d3ef434b4 Tweak LMR at Root
Passed STC:
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 328192 W: 84751 L: 84014 D: 159427
Ptnml(0-2): 758, 38802, 84253, 39511, 772
https://tests.stockfishchess.org/tests/view/6689203959cb3228a4759a49

Passed LTC:
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 56748 W: 14494 L: 14136 D: 28118
Ptnml(0-2): 19, 6089, 15803, 6441, 22
https://tests.stockfishchess.org/tests/view/66892d76e59d990b103f6626

closes https://github.com/official-stockfish/Stockfish/pull/5452

Bench 1253593
2024-07-09 18:26:35 +02:00
Shawn Xu
b79ac764ff Simplify in-check condition for Probcut-in-check
dont let your memes be dreams !?

Passed Non-regression STC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 512000 W: 132193 L: 132497 D: 247310
Ptnml(0-2): 1600, 61170, 130704, 60986, 1540
https://tests.stockfishchess.org/tests/view/66838911c4f539faa03268a2

Passed Non-regression LTC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 380268 W: 95894 L: 96042 D: 188332
Ptnml(0-2): 193, 42861, 104180, 42701, 199
https://tests.stockfishchess.org/tests/view/6688d0550c9d7c1ab33ed5a8

closes https://github.com/official-stockfish/Stockfish/pull/5443

Bench: 1130282
2024-07-09 18:24:40 +02:00
Shawn Xu
b1f522930d Simplify Away Move Count Pruning Adjustment
Using Singular Search Result

Passed Non-regression STC:
LLR: 3.01 (-2.94,2.94) <-1.75,0.25>
Total: 62688 W: 16319 L: 16121 D: 30248
Ptnml(0-2): 196, 7317, 16104, 7547, 180
https://tests.stockfishchess.org/tests/view/66879bf51b527f04dd477ff9

Passed Non-regression LTC:
LLR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 116502 W: 29504 L: 29379 D: 57619
Ptnml(0-2): 66, 12881, 32226, 13018, 60
https://tests.stockfishchess.org/tests/view/6688629e0c9d7c1ab33ed030

closes https://github.com/official-stockfish/Stockfish/pull/5442

bench 1207930
2024-07-09 18:20:26 +02:00
Muzhen Gaming
4d6e1225bd Simplify ttPv reduction formula
This is a revert of 2046c92.
This patch is based on the fact that the ttPv reduction has proven non-linear scaling (as documented in the code, along with testing guidelines); however, the original patch had (erroneously) not been tested at VLTC or longer.

Simplification STC: https://tests.stockfishchess.org/tests/view/6689266e59cb3228a4759b28
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 100320 W: 25913 L: 25763 D: 48644
Ptnml(0-2): 270, 11842, 25750, 12064, 234

Simplification LTC: https://tests.stockfishchess.org/tests/view/66893103e59d990b103f6ab3
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 57078 W: 14466 L: 14282 D: 28330
Ptnml(0-2): 34, 6214, 15851, 6414, 26

closes https://github.com/official-stockfish/Stockfish/pull/5448

Bench: 1124658
2024-07-06 18:00:09 +02:00
Muzhen Gaming
55cb235d47 Simplify internal iterative reductions
This is a revert of cc992e5.
This patch is based on consistent observations that decreasing depth more in IIR generally has a bad scaling behaviour (good at STC, bad at longer time controls).

Simplification STC: https://tests.stockfishchess.org/tests/view/6689266659cb3228a4759b26
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 96992 W: 24977 L: 24824 D: 47191
Ptnml(0-2): 251, 11497, 24851, 11642, 255

Simplification LTC: https://tests.stockfishchess.org/tests/view/668930ffe59d990b103f6ab1
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 35808 W: 9185 L: 8980 D: 17643
Ptnml(0-2): 25, 3776, 10101, 3973, 29

closes https://github.com/official-stockfish/Stockfish/pull/5447

Bench: 1097766
2024-07-06 17:58:23 +02:00
Shawn Xu
24ab46c511 Non-functional Fixes & Updates
Fixes a missing default slot for dbg_extremes of, removes a extra newline, and
updates SE elo estimate from
https://tests.stockfishchess.org/tests/view/664ebd1e928b1fb18de4e4b7 while we
are at it.

closes https://github.com/official-stockfish/Stockfish/pull/5446

No functional change
2024-07-06 17:56:31 +02:00
FauziAkram
ec8288fe0d Simplify away eval in TM
Passed STC:
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 40160 W: 10523 L: 10309 D: 19328
Ptnml(0-2): 129, 4543, 10524, 4753, 131
https://tests.stockfishchess.org/tests/view/6685ab8b99271ae49479dbe9

Passed LTC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 195672 W: 49681 L: 49639 D: 96352
Ptnml(0-2): 112, 20976, 55597, 21060, 91
https://tests.stockfishchess.org/tests/view/6686f27a7092ade1206f7889

closes https://github.com/official-stockfish/Stockfish/pull/5445

No functional change
2024-07-06 17:54:22 +02:00
Shawn Xu
a45c2bc34a Simplify Away Countermove Heuristic
Passed Non-regression STC:
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 977824 W: 252072 L: 252888 D: 472864
Ptnml(0-2): 2518, 117120, 250560, 116088, 2626
https://tests.stockfishchess.org/tests/view/6683452d95b0d1e881e81541

Passed Non-regression LTC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 81048 W: 20630 L: 20470 D: 39948
Ptnml(0-2): 36, 8915, 22464, 9071, 38
https://tests.stockfishchess.org/tests/view/66886b7b0c9d7c1ab33ed281

closes https://github.com/official-stockfish/Stockfish/pull/5441

bench 1276784
2024-07-06 17:48:11 +02:00
Muzhen Gaming
daa9e217ab VVLTC search tune
Passed VVLTC 1st sprt: https://tests.stockfishchess.org/tests/view/6688af640c9d7c1ab33ed327
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 16050 W: 4200 L: 3959 D: 7891
Ptnml(0-2): 0, 1383, 5018, 1624, 0

Passed VVLTC 2nd sprt: https://tests.stockfishchess.org/tests/view/6688e8900c9d7c1ab33efd60
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 44044 W: 11303 L: 10999 D: 21742
Ptnml(0-2): 1, 3973, 13772, 4273, 3

closes https://github.com/official-stockfish/Stockfish/pull/5444

Bench: 992058
2024-07-06 17:45:58 +02:00
Stéphane Nicolet
d212e663bb Introduction evaluation grain of 16 (and randomize)
This patch uses an evaluation grain of 16 in order to get more cutoffs in
the alpha-beta algorithm. For a discussion of the efficiency of alpha-beta
related to changes in the number of discrete values of terminal nodes, see
for instance section 9.1.2 of Judea Pearl's classical book "Heuristics" :

https://mat.uab.cat/~alseda/MasterOpt/Judea_Pearl-Heuristics_Intelligent_Search_Strategies_for_Computer_Problem_Solving.pdf

Moreover, we add a small (-1, +1) random component after the quantification
to help the search exploration a little bit. This is similar in spirit to
the (-1, +1) random component already present in the function draw_value()
to make Stockfish more robust in draw evaluations.

passed STC:
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 220960 W: 57249 L: 56668 D: 107043
Ptnml(0-2): 499, 26017, 56882, 26568, 514
https://tests.stockfishchess.org/tests/view/668907fb7edfb6f233f999f8

passed LTC :
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 48966 W: 12574 L: 12233 D: 24159
Ptnml(0-2): 14, 5233, 13654, 5562, 20
https://tests.stockfishchess.org/tests/view/6689105659cb3228a47598bf

closes https://github.com/official-stockfish/Stockfish/pull/5449

bench: 1336007
2024-07-06 17:43:39 +02:00
Joost VandeVondele
c40dd26cbc CI give creditials for the clang-format action
following up from earlier changes

closes https://github.com/official-stockfish/Stockfish/pull/5450

No functional change
2024-07-06 17:42:23 +02:00
Joost VandeVondele
2cbc20e846 Correct and extend PV lines with decisive TB score
Currently (after #5407), SF has the property that any PV line with a decisive
TB score contains the corresponding TB position, with a score that correctly
identifies the depth at which TB are entered. The PV line that follows might
not preserve the game outcome, but can easily be verified and extended based on
TB information. This patch provides this functionality, simply extending the PV
lines on output, this doesn't affect search.

Indeed, if DTZ tables are available, search based PV lines that correspond to
decisive TB scores are verified to preserve game outcome, truncating the line
as needed. Subsequently, such PV lines are extended with a game outcome
preserving line until mate, as a possible continuation.  These lines are not
optimal mating lines, but are similar to what a user could produce on a website
like https://syzygy-tables.info/ clicking always the top ranked move, i.e.
minimizing or maximizing DTZ (with a simple tie-breaker for moves that have
identical DTZ), and are thus an just an illustration of how to game can be won.

A similar approach is already in established in
https://github.com/joergoster/Stockfish/tree/matefish2

This also contributes to addressing #5175 where SF can give an incorrect TB
win/loss for positions in TB with a movecounter that doesn't reflect optimal
play. While the full solution requires either TB generated differently, or a
search when ranking rootmoves, current SF will eventually find a draw in these
cases, in practice quite quickly, e.g.
`1kq5/q2r4/5K2/8/8/8/8/7Q w - - 96 1`
`8/8/6k1/3B4/3K4/4N3/8/8 w - - 54 106`

Gives the same results as master on an extended set of test positions from
9173d29c41
with the exception of the above mentioned fen where this commit improves.

With https://github.com/vondele/matetrack using 6men TB, all generated PVs verify:
```
Using ../Stockfish/src/stockfish.syzygyExtend on matetrack.epd with --nodes 1000000 --syzygyPath /chess/syzygy/3-4-5-6/WDL:/chess/syzygy/3-4-5-6/DTZ
Engine ID:     Stockfish dev-20240704-ff227954
Total FENs:    6555
Found mates:   3299
Best mates:    2582
Found TB wins: 568
```

As repeated DTZ probing could be slow a procedure (100ms+ on HDD, a few ms on
SSD), the extension is only done as long as the time taken is less than half
the `Move Overhead` parameter. For tournaments where these lines might be of
interest to the user, a suitable `Move Overhead` might be needed (e.g. TCEC has
1000ms already).

closes https://github.com/official-stockfish/Stockfish/pull/5414

No functional change
2024-07-05 15:43:49 +02:00
Linmiao Xu
3c379e55d9 Update 7 stat bonus/malus params
Values found around 119k / 120k spsa games at 60+0.6:
https://tests.stockfishchess.org/tests/view/6683112a192114e61f92f87a

Passed STC:
https://tests.stockfishchess.org/tests/view/66838148c4f539faa0326897
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 40928 W: 10835 L: 10508 D: 19585
Ptnml(0-2): 139, 4802, 10254, 5131, 138

Passed LTC:
https://tests.stockfishchess.org/tests/view/668448a87a1863935cee42c6
LLR: 2.96 (-2.94,2.94) <0.50,2.50>
Total: 29208 W: 7559 L: 7253 D: 14396
Ptnml(0-2): 17, 3118, 8019, 3442, 8

closes https://github.com/official-stockfish/Stockfish/pull/5439

bench 1138753
2024-07-05 15:43:49 +02:00
Joost VandeVondele
25361e514b Output from a fix depth onward, instead of 3s.
To avoid output that depends on timing, output currmove and similar only from depth > 30
onward.  Current choice of 3s makes the output of the same search depending on
the system load, and doesn't always start at move 1. Depth 30 is nowadays
reached in a few seconds on most systems.

closes https://github.com/official-stockfish/Stockfish/pull/5436

No functional change
2024-07-05 15:43:42 +02:00
Disservin
74a8fc0604 Use explicit action permissions in CI
Necessary modifications according to changes in the GitHub Action settings.

closes https://github.com/official-stockfish/Stockfish/pull/5437

Follow up from the report by Yaron Avital (yaronav) earlier.

No functional change
2024-07-05 15:35:13 +02:00
Joost VandeVondele
ee6fc7e38b CI: limit artifact uploads
do not upload some unneeded intermediate directories,
disable running authenticated git commands with the checkout action.

Thanks to Yaron A for the report.

closes https://github.com/official-stockfish/Stockfish/pull/5435

No functional change
2024-07-03 13:45:14 +02:00
Shawn Xu
b9ff5bb93b Implement dbg_extremes_of
An alternative to #5431, implements one function `dbg_extremes_of` to keep track
of min and max.

closes https://github.com/official-stockfish/Stockfish/pull/5434

No functional change
2024-07-03 13:44:01 +02:00
Joost VandeVondele
ad0f1fecda Move info strings once more
Follow up from #5404 ... current location leads to troubles with Aquarium GUI

Fixes #5430

Now prints the information on threads and available processors at the beginning
of search, where info about the networks is already printed (and is known to
work)

closes https://github.com/official-stockfish/Stockfish/pull/5433

No functional change.
2024-07-03 13:39:31 +02:00
Shahin M. Shahin
6b7822119f Limit has_game_cycle() to only upcoming repetition
use the original algorithm according to the paper
http://web.archive.org/web/20201107002606/https://marcelk.net/2013-04-06/paper/upcoming-rep-v2.pdf,
which detects accurately if a position has an upcoming repetition. The 'no
progress' part of has_game_cycle has been removed, the function has been
renamed to upcoming_repetition to reflect this.

As a result of this fix, to the best of our knowledge, all PVs for completed
iterations that yield a mate or decisive table base score now end in mate or
contain a TB position, respectively.

passed non-regression STC:
https://tests.stockfishchess.org/tests/view/6679fa1d0c2db3fa2dcecbf2
LLR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 63584 W: 16666 L: 16472 D: 30446
Ptnml(0-2): 186, 7552, 16146, 7698, 210

Passed non-regression LTC:
https://tests.stockfishchess.org/tests/view/667ac965e439ed1c7a9ca042
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 464574 W: 117493 L: 117729 D: 229352
Ptnml(0-2): 311, 52468, 126974, 52214, 320

closes https://github.com/official-stockfish/Stockfish/pull/5432

bench: 1209805
2024-07-03 13:35:49 +02:00
Shawn Xu
69ad4667fb Do Capture History Updates In Probcut
This patch introduces history updates to probcut. Standard depth - 3 bonus and
maluses are given to the capture that caused fail high and previously searched
captures, respectively. Similar to #5243, a negative history fill is applied to
compensate for an increase in capture history average, thus improving the
scaling of this patch.

Passed STC:
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 84832 W: 21941 L: 21556 D: 41335
Ptnml(0-2): 226, 9927, 21688, 10386, 189
https://tests.stockfishchess.org/tests/view/6682fab9389b9ee542b1d029

Passed LTC:
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 104298 W: 26469 L: 26011 D: 51818
Ptnml(0-2): 43, 11458, 28677, 11940, 31
https://tests.stockfishchess.org/tests/view/6682ff06389b9ee542b1d0a0

closes https://github.com/official-stockfish/Stockfish/pull/5428

bench 1281351
2024-07-03 13:18:00 +02:00
Dubslow
6138a0fd0e Probcut in check no matter if pv or capture
Passed STC: https://tests.stockfishchess.org/tests/view/6681e9c8c1657e386d294cef
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 217824 W: 56149 L: 56129 D: 105546
Ptnml(0-2): 587, 25926, 55848, 25982, 569

Passed LTC: https://tests.stockfishchess.org/tests/view/6681fcb8c1657e386d294db1
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 357552 W: 90546 L: 90671 D: 176335
Ptnml(0-2): 207, 40064, 98362, 39933, 210

Each half of this also passed STC+LTC separately

closes https://github.com/official-stockfish/Stockfish/pull/5427

bench 1227870
2024-07-01 20:07:03 +02:00
Linmiao Xu
843b6f7c98 Update some params for pruning at shallow depth
Values found around 82k / 120k spsa games at 60+0.6:
https://tests.stockfishchess.org/tests/view/6681aca4481148df247298bd

Passed STC:
https://tests.stockfishchess.org/tests/view/6681c795c1657e386d2948fa
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 145216 W: 37595 L: 37122 D: 70499
Ptnml(0-2): 375, 17122, 37185, 17507, 419

Passed LTC:
https://tests.stockfishchess.org/tests/view/6681d4eec1657e386d2949e0
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 154062 W: 39117 L: 38557 D: 76388
Ptnml(0-2): 67, 16874, 42608, 17396, 86

closes https://github.com/official-stockfish/Stockfish/pull/5425

bench 996419
2024-07-01 20:04:13 +02:00
Linmiao Xu
f6842a145c Simplify worsening deduction in futility margin
Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/66817d46442423e547141226
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 345408 W: 89146 L: 89266 D: 166996
Ptnml(0-2): 954, 41317, 88286, 41189, 958

Passed non-regression LTC:
https://tests.stockfishchess.org/tests/view/66818dbe1e90a146232d1f62
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 173214 W: 43821 L: 43755 D: 85638
Ptnml(0-2): 108, 19407, 47492, 19511, 89

closes https://github.com/official-stockfish/Stockfish/pull/5424

bench 981017
2024-07-01 20:02:38 +02:00
FauziAkram
5deb262393 Simplify rm.averageScore calculation
Passed STC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 485056 W: 125222 L: 125497 D: 234337
Ptnml(0-2): 1384, 58197, 123614, 57976, 1357
https://tests.stockfishchess.org/tests/view/6681816d442423e54714133f

Passed LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 56622 W: 14301 L: 14115 D: 28206
Ptnml(0-2): 31, 6259, 15538, 6459, 24
https://tests.stockfishchess.org/tests/view/6681a9a5596d543edc677490

closes https://github.com/official-stockfish/Stockfish/pull/5423

bench: 1171203
2024-07-01 20:01:05 +02:00
Shahin M. Shahin
38c5fc33e4 Increase reduction based on correct expectation
If the current node is not a cutNode then it means that the child is one in LMR
and the cutoff count is expected, so more reduction when the cutoffs are
expected

Passed STC:
https://tests.stockfishchess.org/tests/view/66815e791c5b344a34ca7090
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 64416 W: 16876 L: 16519 D: 31021
Ptnml(0-2): 150, 7670, 16264, 7921, 203

Passed LTC:
https://tests.stockfishchess.org/tests/view/668162f61c5b344a34ca725c
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 78186 W: 19905 L: 19499 D: 38782
Ptnml(0-2): 55, 8561, 21437, 9003, 37

closes https://github.com/official-stockfish/Stockfish/pull/5422

bench: 1161531
2024-07-01 19:58:13 +02:00
Michael Chaly
7b49f9dd70 Tweak multicut
This patch is an original patch by author of Altair
(https://github.com/Alex2262/AltairChessEngine) chess engine.

It allows to produce more aggressive multicut compared to master by changing
condition it needs to fulfil and also returns bigger value.  Also has applied
matetrack fix on top.

Passed STC:
https://tests.stockfishchess.org/tests/view/667223ab602682471b0650e2
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 50048 W: 13200 L: 12860 D: 23988
Ptnml(0-2): 181, 5822, 12679, 6160, 182

Passed LTC:
https://tests.stockfishchess.org/tests/view/6672f777602682471b06515d
LLR: 2.97 (-2.94,2.94) <0.50,2.50>
Total: 706380 W: 179707 L: 177981 D: 348692
Ptnml(0-2): 656, 79250, 191665, 80950, 669

closes https://github.com/official-stockfish/Stockfish/pull/5421

bench 1148966
2024-07-01 19:56:38 +02:00
Daniel Monroe
91ec31dac4 Grade countermove bonus for low statscores
Passed STC:
LLR: 2.96 (-2.94,2.94) <0.00,2.00>
Total: 338592 W: 88396 L: 87627 D: 162569
Ptnml(0-2): 1161, 40201, 85788, 41000, 1146
https://tests.stockfishchess.org/tests/view/6679d40c0c2db3fa2dcecbcc

Passed LTC:
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 83526 W: 21429 L: 21010 D: 41087
Ptnml(0-2): 54, 9173, 22913, 9546, 77
https://tests.stockfishchess.org/tests/view/667c5f2980450dba965911fc

closes https://github.com/official-stockfish/Stockfish/pull/5418

bench: 1489815
2024-07-01 19:53:45 +02:00
mstembera
90eca83e7f Simplify away a useless TTEntry::read()
Not needed when we don hit an entry.

closes https://github.com/official-stockfish/Stockfish/pull/5416

No functional change
2024-07-01 19:50:32 +02:00
Taras Vuk
22a502ac74 Skip futility pruning if beta is below TB loss value
Passed STC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 77024 W: 20122 L: 19946 D: 36956
Ptnml(0-2): 278, 8754, 20277, 8920, 283
https://tests.stockfishchess.org/tests/view/66752d59602682471b0652f3

Passed LTC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 93114 W: 23623 L: 23477 D: 46014
Ptnml(0-2): 77, 9839, 26566, 10011, 64
https://tests.stockfishchess.org/tests/view/6676b3e1602682471b065395

closes https://github.com/official-stockfish/Stockfish/pull/5413

bench: 1003441
2024-07-01 19:48:06 +02:00
Joost VandeVondele
66e6274d32 Fix typos in comments
closes https://github.com/official-stockfish/Stockfish/pull/5409

No functional change
2024-07-01 19:44:17 +02:00
FauziAkram
b2a12917e2 Remove redundant inline
constexpr implies inline anyway

closes https://github.com/official-stockfish/Stockfish/pull/5406

No functional change
2024-07-01 19:40:04 +02:00
Joost VandeVondele
5fbfd06171 Move info output afer uciok
fixes #5393 : an incompatibility with an older GUI (Chesspartner)
fixes #5396 : an incompatibility with an older GUI (Fritz9)

closes https://github.com/official-stockfish/Stockfish/pull/5404

No functional change
2024-07-01 19:37:25 +02:00
FauziAkram
cc992e5e4a Internal iterative reductions: decrease depth more
For PV nodes without a ttMove, we decrease depth.
But in this patch, additionally, if the current position is found in the TT, and the stored depth in the TT is greater than or equal to
the current search depth, we decrease the search depth even further.

Passed STC:
LLR: 2.96 (-2.94,2.94) <0.00,2.00>
Total: 84384 W: 22154 L: 21761 D: 40469
Ptnml(0-2): 292, 9972, 21315, 10277, 336
https://tests.stockfishchess.org/tests/view/666b0a4d602682471b064db6

Passed LTC:
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 92106 W: 23471 L: 23032 D: 45603
Ptnml(0-2): 79, 10155, 25154, 10578, 87
https://tests.stockfishchess.org/tests/view/666c423d602682471b064e56

closes https://github.com/official-stockfish/Stockfish/pull/5397

bench: 1038234
2024-06-23 11:46:41 +02:00
Shawn Xu
d5c130569b Simplify Bonus Formula In History Adjustment
Inspired by a discord message [1] from Vizvezdenec, this patch simplifies the
bonus adjustment bonus = bonus > 0 ? 2 * bonus : bonus / 2 to a constant
addition, maintaining bonus average at around 0 in regular bench. As cj5716
pointed in discord [2], the constant bonus can also be considered as factoring
tempo when calculating bonus, yielding a better value of the move.

[1] https://discord.com/channels/435943710472011776/882956631514689597/1243877089443188776
[2] https://discord.com/channels/435943710472011776/813919248455827515/1252277437249622077

Passed Non-regression STC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 29984 W: 7908 L: 7677 D: 14399
Ptnml(0-2): 95, 3502, 7594, 3679, 122
https://tests.stockfishchess.org/tests/view/666f7210602682471b064fa2

Passed Non-regression LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 170136 W: 43214 L: 43145 D: 83777
Ptnml(0-2): 158, 19185, 46311, 19258, 156
https://tests.stockfishchess.org/tests/view/666fb32e602682471b064fb5

closes https://github.com/official-stockfish/Stockfish/pull/5401

bench 1438375
2024-06-23 11:41:48 +02:00
evqsx
8806a58ebf Simplify static exchange evaluation pruning formula
Passed STC: https://tests.stockfishchess.org/tests/view/666bda31602682471b064e1f
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 141696 W: 36932 L: 36826 D: 67938
Ptnml(0-2): 510, 16880, 35989, 16932, 537

Passed LTC: https://tests.stockfishchess.org/tests/view/666e6b67602682471b064f4b
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 159504 W: 40552 L: 40471 D: 78481
Ptnml(0-2): 130, 18160, 43103, 18217, 142

closes https://github.com/official-stockfish/Stockfish/pull/5400

bench: 1084115
2024-06-23 11:37:32 +02:00
Joost VandeVondele
5514690f8e CI/CD: play games
this action plays games under fast-chess with a `debug=yes` compiled binary.

It checks for triggered asserts in the code, or generally for engine disconnects.

closes https://github.com/official-stockfish/Stockfish/pull/5403

No functional change
2024-06-23 11:35:50 +02:00
xoto10
2678606e8d Consider wider range of moves near leaves.
try to avoid missing good moves for opponent or engine, by updating bestMove
also when value == bestValue (i.e. value == alpha) under certain conditions.
In particular require this is at higher depth in the tree, leaving the logic
near the root unchanged, and only apply randomly. Avoid doing this near mate
scores, leaving mate PVs intact.

Passed SMP STC 6+0.06 th7 :
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 42040 W: 10930 L: 10624 D: 20486
Ptnml(0-2): 28, 4682, 11289, 4998, 23
https://tests.stockfishchess.org/tests/view/66608b00c340c8eed7757d1d

Passed SMP LTC 24+0.24 th7 :
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 73692 W: 18978 L: 18600 D: 36114
Ptnml(0-2): 9, 7421, 21614, 7787, 15
https://tests.stockfishchess.org/tests/view/666095e8c340c8eed7757d49

closes https://github.com/official-stockfish/Stockfish/pull/5367

Bench 1205168
2024-06-23 11:29:02 +02:00
FauziAkram
2046c92ad4 Tweak the reduction formula
Tweak the reduction formula if position is or has been on the PV
Taking inspiration from an old Viren test.

Passed STC:
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 78528 W: 20607 L: 20225 D: 37696
Ptnml(0-2): 262, 9297, 19785, 9637, 283
https://tests.stockfishchess.org/tests/view/666339c70ff7cb4868d1fe24

Passed LTC:
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 138630 W: 35666 L: 35132 D: 67832
Ptnml(0-2): 118, 15345, 37835, 15919, 98
https://tests.stockfishchess.org/tests/view/66645dec0612cd151f9e77b0

closes https://github.com/official-stockfish/Stockfish/pull/5385

Bench: 1134281
2024-06-15 12:13:59 +02:00
Dubslow
ff10f4ac65 Fix readability of TTEntry occupancy check
Passed STC:
https://tests.stockfishchess.org/tests/view/66695b6a602682471b064cfc
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 107520 W: 28138 L: 27998 D: 51384
Ptnml(0-2): 373, 12257, 28358, 12401, 371

closes https://github.com/official-stockfish/Stockfish/pull/5394

No functional change
2024-06-15 12:10:49 +02:00
Joost VandeVondele
b01fdb596a Fix upperbound/lowerbound output in multithreaded case
In case a stop is received during multithreaded searches, the PV of the best
thread might be printed without the correct upperbound/lowerbound indicators.
This was due to the pvIdx variable being incremented after receiving the stop.

passed STC:
https://tests.stockfishchess.org/tests/view/666985da602682471b064d08
 LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 196576 W: 51039 L: 50996 D: 94541
Ptnml(0-2): 760, 22545, 51603, 22652, 728

closes https://github.com/official-stockfish/Stockfish/pull/5391

Bench: 1160467
2024-06-15 12:08:29 +02:00
Joost VandeVondele
44cddbd962 Add matetrack to CI
verifies that all mate PVs printed for finished iterations (i.e. no lower or upper bounds),
are complete, i.e. of the expected length and ending in mate, and do not contain drawing
or illegal moves.

based on a set of 2000 positions and the code in https://github.com/vondele/matetrack

closes https://github.com/official-stockfish/Stockfish/pull/5390

No functional change
2024-06-15 12:06:45 +02:00
Tomasz Sobczyk
7c0607d2d3 Fix printing of empty info strings.
Handle printing of `info string` in a single place.

Fixes #5386

closes https://github.com/official-stockfish/Stockfish/pull/5387

No functional change
2024-06-15 12:04:16 +02:00
Joost VandeVondele
3d92950859 Limit depth after extensions to avoid asserts.
currently extensions can cause depth to exceed MAX_PLY.

This triggers the assert near line 542 in search when running a binary compiled with `debug=yes` on a testcase like:
```
position fen 7K/P1p1p1p1/2P1P1Pk/6pP/3p2P1/1P6/3P4/8 w - - 0 1
go nodes 1000000
```

passed STC
https://tests.stockfishchess.org/tests/view/6668a56a602682471b064c8d
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 143936 W: 37338 L: 37238 D: 69360
Ptnml(0-2): 514, 16335, 38149, 16477, 493

closes https://github.com/official-stockfish/Stockfish/pull/5383

Bench: 1160467
2024-06-15 12:02:56 +02:00
Linmiao Xu
025da6a0d1 Give positional output more weight in nnue eval
This effectively reverts the removal of delta in:
https://github.com/official-stockfish/Stockfish/pull/5373

Passed STC:
https://tests.stockfishchess.org/tests/view/6664d41922234461cef58e6b
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 56448 W: 14849 L: 14500 D: 27099
Ptnml(0-2): 227, 6481, 14457, 6834, 225

Passed LTC:
https://tests.stockfishchess.org/tests/view/666587a1996b40829f4ee007
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 91686 W: 23402 L: 22963 D: 45321
Ptnml(0-2): 78, 10205, 24840, 10640, 80

closes https://github.com/official-stockfish/Stockfish/pull/5382

bench 1160467
2024-06-12 09:17:04 +02:00
Disservin
7013a22b74 Move options into the engine
Move the engine options into the engine class, also avoid duplicated
initializations after startup.  UCIEngine needs to register an add_listener to
listen to all option changes and print these.  Also avoid a double
initialization of the TT, which was the case with the old state.

closes https://github.com/official-stockfish/Stockfish/pull/5356

No functional change
2024-06-12 09:17:04 +02:00
Dubslow
c8213ba0d0 Simplify TT interface and avoid changing TT info
This commit builds on the work and ideas of #5345, #5348, and #5364.

Place as much as possible of the TT implementation in tt.cpp, rather than in the
header.  Some commentary is added to better document the public interface.

Fix the search read-TT races, or at least contain them to within TT methods only.

Passed SMP STC: https://tests.stockfishchess.org/tests/view/666134ab91e372763104b443
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 512552 W: 132387 L: 132676 D: 247489
Ptnml(0-2): 469, 58429, 138771, 58136, 471

The unmerged version has bench identical to the other PR (see also #5348) and
therefore those same-functionality tests:

SMP LTC: https://tests.stockfishchess.org/tests/view/665c7021fd45fb0f907c214a
SMP LTC: https://tests.stockfishchess.org/tests/view/665d28a7fd45fb0f907c5495

closes https://github.com/official-stockfish/Stockfish/pull/5369

bench 1205675
2024-06-12 09:17:04 +02:00
Joost VandeVondele
7e890fd048 Keep mate PVs intact.
do not return a cutoff value in razoring if that value is in the mate/tb range.

passed STC:
https://tests.stockfishchess.org/tests/view/666381880ff7cb4868d1fe58
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 130848 W: 34046 L: 33931 D: 62871
Ptnml(0-2): 429, 14968, 34524, 15065, 438

passed LTC:
https://tests.stockfishchess.org/tests/view/66643f120612cd151f9e7788
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 39702 W: 10157 L: 9959 D: 19586
Ptnml(0-2): 20, 4108, 11402, 4296, 25

closes https://github.com/official-stockfish/Stockfish/pull/5379

Bench: 1174094
2024-06-12 09:03:32 +02:00
cj5716
e271059e08 Make repeated bench runs identical
fixes https://github.com/official-stockfish/Stockfish/issues/5376
closes https://github.com/official-stockfish/Stockfish/pull/5377

No functional changes
2024-06-08 23:40:22 +02:00
evqsx
4151c06b74 Remove the correction history bonus in null move search
Passed STC:
https://tests.stockfishchess.org/tests/view/666168e191e372763104c664
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 94848 W: 24708 L: 24550 D: 45590
Ptnml(0-2): 289, 11355, 24033, 11403, 344

Passed LTC:
https://tests.stockfishchess.org/tests/view/6661e73591e372763104c751
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 70452 W: 17849 L: 17679 D: 34924
Ptnml(0-2): 27, 7707, 19596, 7861, 35

closes https://github.com/official-stockfish/Stockfish/pull/5375

Bench: 1174094
2024-06-08 23:39:46 +02:00
Dubslow
1c67b46caf Linearize corrHist
Passed STC: https://tests.stockfishchess.org/tests/view/6661fff88dd8f31ed3c5d819
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 17504 W: 4651 L: 4406 D: 8447
Ptnml(0-2): 71, 1975, 4384, 2282, 40

Passed LTC: https://tests.stockfishchess.org/tests/view/666205b48dd8f31ed3c61296
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 24522 W: 6313 L: 6094 D: 12115
Ptnml(0-2): 14, 2643, 6726, 2866, 12

closes https://github.com/official-stockfish/Stockfish/pull/5374

Bench: 1237729
2024-06-08 23:35:00 +02:00
Dubslow
7d4ffa175c Remove delta from evaluation
Passed STC: https://tests.stockfishchess.org/tests/view/6660e49c6489614cdad14e29
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 188768 W: 48907 L: 48854 D: 91007
Ptnml(0-2): 584, 22571, 48005, 22656, 568

Passed LTC: https://tests.stockfishchess.org/tests/view/6660ff9791e372763104b38c
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 310680 W: 78651 L: 78727 D: 153302
Ptnml(0-2): 180, 34818, 85433, 34716, 193

closes https://github.com/official-stockfish/Stockfish/pull/5373

Bench: 1214575
2024-06-08 23:34:03 +02:00
Tomasz Sobczyk
f55239b2f3 NumaPolicy fixes and robustness improvements
1. Fix GetProcessGroupAffinity still not getting properly aligned memory
   sometimes.
2. Fix a very theoretically possible heap corruption if
   GetActiveProcessorGroupCount changes between calls.
3. Fully determine affinity on Windows 11 and Windows Server 2022. It
   should only ever be indeterminate in case of an error.
4. Separate isDeterminate for old and new API, as they are &'d together
   we still can end up with a subset of processors even if one API is
   indeterminate.
5. likely_used_old_api() that is based on actual affinity that's been
   detected
6. IMPORTANT: Gather affinities at startup, so that we only later use
   the affinites set at startup. Not only does this prevent us from our
   own calls interfering with detection but it also means subsequent
   setoption NumaPolicy calls should behave as expected.
7. Fix ERROR_INSUFFICIENT_BUFFER from GetThreadSelectedCpuSetMasks being
   treated like an error.

Should resolve
02ff76630b (commitcomment-142790025)

closes https://github.com/official-stockfish/Stockfish/pull/5372

Bench: 1231853
2024-06-08 23:32:27 +02:00
FauziAkram
e2be0aaf67 Tweak pruning formula
Tweak pruning formula, including a constant. I started from an old
yellow patch, if I'm not mistaken by Viz (Unfortunately I lost the link)
where he tried something similar.
I worked on it, trying different variations, until I came up with a good
configuration to pass.

Passed STC:
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 213120 W: 55351 L: 54778 D: 102991
Ptnml(0-2): 572, 25209, 54437, 25758, 584
https://tests.stockfishchess.org/tests/view/6660c9a7c340c8eed7758195

Passed LTC:
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 315324 W: 80176 L: 79284 D: 155864
Ptnml(0-2): 155, 34711, 87030, 35619, 147
https://tests.stockfishchess.org/tests/view/6660d7bb6489614cdad13d66

closes https://github.com/official-stockfish/Stockfish/pull/5370

Bench: 1231853
2024-06-08 23:28:07 +02:00
rn5f107s2
5dda4037c7 Simplify razor changes
Remove razoring changes from
https://github.com/official-stockfish/Stockfish/pull/5360

The mentioned patch introduced the usage of futility_margin into
razoring alongside a tune to futility_margin. It seems the elo gained in
this patch comes from the tune of futility_margin and not the
introduction of futility_margin to razoring, so simplify it away here.

Passed Non-regression STC:
https://tests.stockfishchess.org/tests/view/66606581c340c8eed7757bc8
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 169056 W: 43922 L: 43848 D: 81286
Ptnml(0-2): 438, 20288, 43034, 20298, 470

Passed Non-regression LTC:
https://tests.stockfishchess.org/tests/view/66607764c340c8eed7757c58
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 157134 W: 39805 L: 39723 D: 77606
Ptnml(0-2): 74, 17444, 43461, 17502, 86

Passed rebased Non-regression LTC:
https://tests.stockfishchess.org/tests/view/6660c696c340c8eed77580c0
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 135984 W: 34427 L: 34324 D: 67233
Ptnml(0-2): 67, 15063, 37615, 15194, 53

closes https://github.com/official-stockfish/Stockfish/pull/5366

Bench: 1150518
2024-06-08 23:10:59 +02:00
Disservin
66ed4312f2 Workaround the clang-format inconsistencies
closes https://github.com/official-stockfish/Stockfish/pull/5378

No functional change
2024-06-08 23:09:02 +02:00
R-Goc
e6c83beed1 Change PGO type for clang
Change type of PGO in clang to IR which is recommended by LLVM/clang and
could result in a speedup.
https://github.com/llvm/llvm-project/issues/45668

closes https://github.com/official-stockfish/Stockfish/pull/5355

No functional change
2024-06-08 23:05:56 +02:00
cj5716
5688b188cc Simplify evaluation constants
Passed STC (<0, 2> by accident):
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 346016 W: 89529 L: 88756 D: 167731
Ptnml(0-2): 1012, 41074, 88027, 41919, 976
https://tests.stockfishchess.org/tests/view/6659d6ecf426908fcc6b6929

Passed LTC:
LLR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 89862 W: 22887 L: 22734 D: 44241
Ptnml(0-2): 45, 9999, 24694, 10144, 49
https://tests.stockfishchess.org/tests/view/665a6ebb062b2c3cf814fde8

Passed LTC (Rebased):
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 325500 W: 82734 L: 82826 D: 159940
Ptnml(0-2): 193, 36409, 89665, 36263, 220
https://tests.stockfishchess.org/tests/view/665bd39f44e8416a9cdc1909

closes https://github.com/official-stockfish/Stockfish/pull/5361

Bench 961982
2024-06-05 21:49:29 +02:00
Disservin
fb18caae7a Update clang-format to version 18
clang-format-18 is available in ubuntu noble(24.04), if you are on
a version lower than that you can use the update script from llvm.
https://apt.llvm.org/

Windows users should be able to download and use clang-format from
their release builds https://github.com/llvm/llvm-project/releases
or get the latest from msys2
https://packages.msys2.org/package/mingw-w64-x86_64-clang.

macOS users can resort to "brew install clang-format".

closes https://github.com/official-stockfish/Stockfish/pull/5365

No functional change
2024-06-05 21:41:43 +02:00
Viren6
36eb9bc783 Use futility margin in razoring margin
Uses futilityMargin * depth to set the razoring margin. This retains the
quadratic depth scaling to preserve mate finding capabilities. This patch is
nice because it increases the elo sensitivity of the futility margin
heuristics.

Passed STC:
https://tests.stockfishchess.org/tests/view/665f9892fd11ae7170b4849c
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 39392 W: 10348 L: 10030 D: 19014
Ptnml(0-2): 99, 4585, 10009, 4905, 98

Passed LTC:
https://tests.stockfishchess.org/tests/view/665f9d2dfd11ae7170b484a8
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 107910 W: 27521 L: 27053 D: 53336
Ptnml(0-2): 73, 11835, 29670, 12305, 72

closes https://github.com/official-stockfish/Stockfish/pull/5360

bench 1277173
2024-06-05 21:33:46 +02:00
Muzhen Gaming
a08fcacb28 VVLTC search tune
Parameters were tuned with 199k games of VVLTC: https://tests.stockfishchess.org/tests/view/665c67e73542f91ad1c54fe2

Passed VVLTC 1st sprt: https://tests.stockfishchess.org/tests/view/665e9c83fd45fb0f907c837c
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 83494 W: 21546 L: 21219 D: 40729
Ptnml(0-2): 6, 7707, 25993, 8036, 5

Passed VVLTC 2nd sprt: https://tests.stockfishchess.org/tests/view/665f650bfd45fb0f907cb360
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 151056 W: 38796 L: 38295 D: 73965
Ptnml(0-2): 5, 13742, 47536, 14237, 8

https://github.com/official-stockfish/Stockfish/pull/5359

Bench: 1154524
2024-06-05 21:10:55 +02:00
mstembera
21ba32af6d Remove m512_hadd128x16_interleave()
This functionality is no longer used anywhere.

closes https://github.com/official-stockfish/Stockfish/pull/5357

No functional change
2024-06-05 21:07:07 +02:00
Tomasz Sobczyk
02ff76630b Add NumaPolicy "hardware" option that bypasses current processor affinity.
Can be used in case a GUI (e.g. ChessBase 17 see #5307) sets affinity to a
single processor group, but the user would like to use the full capabilities of
the hardware.  Improves affinity handling on Windows in case of multiple
available APIs and existing affinities.

closes https://github.com/official-stockfish/Stockfish/pull/5353

No functional change
2024-06-05 21:01:45 +02:00
Gahtan Nahdi
daaccd9fc9 Simplify smallnet threshold
remove pawncount

Passed STC non-reg:
https://tests.stockfishchess.org/tests/view/665e4548fd45fb0f907c80d5
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 60896 W: 15710 L: 15518 D: 29668
Ptnml(0-2): 149, 7145, 15660, 7353, 141

Passed LTC non-reg:
https://tests.stockfishchess.org/tests/view/665e4c52fd45fb0f907c815f
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 58068 W: 14773 L: 14590 D: 28705
Ptnml(0-2): 16, 6368, 16090, 6537, 23

closes https://github.com/official-stockfish/Stockfish/pull/5349

Bench: 1343156
2024-06-05 20:59:56 +02:00
Disservin
4f53560d24 Accumulate nodes over all bench positions not just the last
closes https://github.com/official-stockfish/Stockfish/pull/5352

No functional change
2024-06-04 08:26:35 +02:00
Disservin
7f09d06b83 Properly initialize the TT in a multithreaded way again 2024-06-04 07:53:25 +02:00
Disservin
ba06671aa9 Normalize some variable names and reuse existing logic
closes https://github.com/official-stockfish/Stockfish/pull/5346

No functional change
2024-06-03 23:28:23 +02:00
Dubslow
86b564055d Remove delta, adjusted, complexity from nnue code
...rather they're the consumer's concern whether to tweak the result or not.

Passed STC:
https://tests.stockfishchess.org/tests/view/665cea9ffd45fb0f907c53bd
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 69696 W: 18101 L: 17918 D: 33677
Ptnml(0-2): 195, 8171, 17929, 8362, 191

Passed LTC:
https://tests.stockfishchess.org/tests/view/665cf761fd45fb0f907c5406
LLR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 63720 W: 16344 L: 16165 D: 31211
Ptnml(0-2): 32, 6990, 17625, 7193, 20

Non functional except for rounding issues of OutputScale changing bench.

closes https://github.com/official-stockfish/Stockfish/pull/5344

Bench: 1378596
2024-06-03 23:27:58 +02:00
Dubslow
397f47a7a1 Adjust lowest depth constants to the natural place
Passed STC:
https://tests.stockfishchess.org/tests/view/665ce3f8fd45fb0f907c537f
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 282784 W: 73032 L: 73082 D: 136670
Ptnml(0-2): 680, 31845, 76364, 31851, 652

Recently when I overhauled these comments, Disservin asked why these
were so much lower: they're a relic from when we had a third QS stage at
-5. Now we don't, so fix these to the obvious place.

I was fairly sure it was nonfunctional but ran the nonreg to be double
sure.

closes https://github.com/official-stockfish/Stockfish/pull/5343

Bench: 1057383
2024-06-03 23:20:02 +02:00
Gahtan Nahdi
fe298953f8 Simplify smallnet threshold
Turns the quadratic threshold to a linear one

STC non-reg:
https://tests.stockfishchess.org/tests/view/665ba0b744e8416a9cdc188d
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 330432 W: 85351 L: 85454 D: 159627
Ptnml(0-2): 888, 39643, 84283, 39488, 914

LTC non-reg:
https://tests.stockfishchess.org/tests/view/665cd60ffd45fb0f907c4306
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 139146 W: 35194 L: 35093 D: 68859
Ptnml(0-2): 58, 15523, 38313, 15618, 61

closes https://github.com/official-stockfish/Stockfish/pull/5342

Bench: 1057383
2024-06-03 23:18:36 +02:00
FauziAkram
924a843594 Simplify recapture extension
Simplifying the extension formula by removing the move == ttMove
condition.

Passed STC:
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 47328 W: 12324 L: 12117 D: 22887
Ptnml(0-2): 134, 5532, 12097, 5795, 106
https://tests.stockfishchess.org/tests/view/665ca5e6fd45fb0f907c41be

Passed LTC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 72126 W: 18378 L: 18209 D: 35539
Ptnml(0-2): 36, 7841, 20130, 8030, 26
https://tests.stockfishchess.org/tests/view/665cb276fd45fb0f907c41f9

closes https://github.com/official-stockfish/Stockfish/pull/5341

Bench: 1399468
2024-06-03 23:17:09 +02:00
FauziAkram
3d6756769c Simplify continuation histories
Functional simplification.

Simplify continuation histories, therefore increasing the effect of
stats updates and movepicker bonuses for continuation history 3 plies
deep.

Passed STC:
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 229184 W: 59087 L: 59080 D: 111017
Ptnml(0-2): 554, 27248, 59002, 27213, 575
https://tests.stockfishchess.org/tests/view/665c7a09fd45fb0f907c223b

Passed LTC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 44532 W: 11419 L: 11223 D: 21890
Ptnml(0-2): 18, 4787, 12457, 4989, 15
https://tests.stockfishchess.org/tests/view/665c8842fd45fb0f907c23ec

closes https://github.com/official-stockfish/Stockfish/pull/5339

Bench: 1326444
2024-06-03 23:12:13 +02:00
Disservin
00a28ae325 Add helpers for managing aligned memory
Previously, we had two type aliases, LargePagePtr and AlignedPtr, which
required manually initializing the aligned memory for the pointer.

The new helpers:

- make_unique_aligned
- make_unique_large_page

are now available for allocating aligned memory (with large pages). They
behave similarly to std::make_unique, ensuring objects allocated with
these functions follow RAII.

The old approach had issues with initializing non-trivial types or
arrays of objects. The evaluation function of the network is now a
unique pointer to an array instead of an array of unique pointers.

Memory related functions have been moved into memory.h

Passed High Hash Pressure Test Non-Regression STC:
https://tests.stockfishchess.org/tests/view/665b2b36586058766677cfd2
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 476992 W: 122426 L: 122677 D: 231889
Ptnml(0-2): 1145, 51027, 134419, 50744, 1161

Failed Normal Non-Regression STC:
https://tests.stockfishchess.org/tests/view/665b2997586058766677cfc8
LLR: -2.94 (-2.94,2.94) <-1.75,0.25>
Total: 877312 W: 225233 L: 226395 D: 425684
Ptnml(0-2): 2110, 94642, 246239, 93630, 2035

Probably a fluke since there shouldn't be a real slowndown and it has also
passed the high hash pressure test.

closes https://github.com/official-stockfish/Stockfish/pull/5332

No functional change
2024-06-03 23:11:59 +02:00
Tomasz Sobczyk
a2a7edf4c8 Fix GetProcessGroupAffinity call
`GetProcessGroupAffinity` appears to require 4 byte alignment for `GroupArray` memory.

See https://stackoverflow.com/q/78567676 for further information

closes https://github.com/official-stockfish/Stockfish/pull/5340

No functional change
2024-06-03 08:54:24 +02:00
Joost VandeVondele
8aaae0367c Revert "Adjust return bonus from tt cutoffs at fail highs"
This reverts commit 783dfc2eb2.

could lead to a division by zero for:

ttValue = (ttValue * tte->depth() + beta) / (tte->depth() + 1)

as other threads can overwrite the tte with a QS depth of -1.

closes https://github.com/official-stockfish/Stockfish/pull/5338

Bench: 1280020
2024-06-02 09:23:28 +02:00
Linmiao Xu
c17d73c554 Simplify statScore divisor into a constant
Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/665b392ff4a1fd0c208ea864
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 114752 W: 29628 L: 29495 D: 55629
Ptnml(0-2): 293, 13694, 29269, 13827, 293

Passed non-regression LTC:
https://tests.stockfishchess.org/tests/view/665b588c11645bd3d3fac467
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 65322 W: 16549 L: 16373 D: 32400
Ptnml(0-2): 30, 7146, 18133, 7322, 30

closes https://github.com/official-stockfish/Stockfish/pull/5337

bench 1241443
2024-06-01 20:17:38 +02:00
xoto10
b009c43254 Simplify tm, removing faster 1st move and 1.13 extraTime.
Passed STC 10+0.1 :
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 349760 W: 90112 L: 90231 D: 169417
Ptnml(0-2): 784, 37970, 97496, 37841, 789
https://tests.stockfishchess.org/tests/view/665aeee00223e235f05b7d21

Passed LTC 60+0.6 :
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 140082 W: 35463 L: 35370 D: 69249
Ptnml(0-2): 59, 13492, 42851, 13575, 64
https://tests.stockfishchess.org/tests/view/665b15e78da109e362924e5a

closes https://github.com/official-stockfish/Stockfish/pull/5334

No functional change
2024-06-01 20:12:36 +02:00
MinetaS
180cab4438 Simplify 50 move rule dampening
Refactor the logic of 50 move rule dampening by removing a constant.

Passed non-regression STC:
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 35232 W: 9214 L: 8992 D: 17026
Ptnml(0-2): 114, 4081, 8999, 4313, 109
https://tests.stockfishchess.org/tests/view/665a329013d08af3c1725610

Passed non-regression LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 38406 W: 9732 L: 9530 D: 19144
Ptnml(0-2): 14, 4132, 10708, 4336, 13
https://tests.stockfishchess.org/tests/view/665a370913d08af3c1725651

https://github.com/official-stockfish/Stockfish/pull/5327

Bench: 1059739
2024-06-01 20:09:47 +02:00
FauziAkram
ec1cda1d81 Simplify histories movepick formula
Passed STC:
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 81440 W: 21100 L: 20929 D: 39411
Ptnml(0-2): 248, 9659, 20718, 9864, 231
https://tests.stockfishchess.org/tests/view/6659a8b7ea624d64ea5f3208

Passed LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 85758 W: 21763 L: 21607 D: 42388
Ptnml(0-2): 34, 9606, 23463, 9722, 54
https://tests.stockfishchess.org/tests/view/6659d7bff426908fcc6b692c

closes https://github.com/official-stockfish/Stockfish/pull/5326

bench: 1280472
2024-06-01 20:08:08 +02:00
Joost VandeVondele
b0870cf528 Avoid changing bestvalue
in the case the ttValue contains mate scores, do not return them as bestValue, since they are not proven.

passed STC
https://tests.stockfishchess.org/tests/view/665b1ea5586058766677cfa3
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 58912 W: 15319 L: 15130 D: 28463
Ptnml(0-2): 141, 6562, 15854, 6765, 134

passed LTC:
https://tests.stockfishchess.org/tests/view/665b2712586058766677cfc4
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 141666 W: 35976 L: 35879 D: 69811
Ptnml(0-2): 61, 15513, 39584, 15618, 57

closes https://github.com/official-stockfish/Stockfish/pull/5335

Bench: 1336115
2024-06-01 20:04:30 +02:00
Michael Chaly
783dfc2eb2 Adjust return bonus from tt cutoffs at fail highs
This is reintroduction of the recently simplified logic - if positive tt cutoff
occurs return not a tt value but smth between it and beta.  Difference is that
instead of static linear combination there we use basically the same formula as
we do in the main search - with the only difference being using tt depth
instead of depth, which makes a lot of sense.

Passed STC:
https://tests.stockfishchess.org/tests/view/665b3a34f4a1fd0c208ea870
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 54944 W: 14239 L: 13896 D: 26809
Ptnml(0-2): 151, 6407, 14008, 6760, 146

Passed LTC:
https://tests.stockfishchess.org/tests/view/665b520011645bd3d3fac341
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 90540 W: 23070 L: 22640 D: 44830
Ptnml(0-2): 39, 9903, 24965, 10315, 48

closes https://github.com/official-stockfish/Stockfish/pull/5336

bench 1381237
2024-06-01 20:02:09 +02:00
Linmiao Xu
cb4a623119 Update default smallnet to nn-37f18f62d772.nnue
Created by training L1-128 from scratch with:
- skipping based on simple eval in the trainer, for compatibility with
  regular binpacks without requiring pre-filtering all binpacks
- minimum simple eval of 950, lower than 1000 previously
- usage of some hse-v1 binpacks with minimum simple eval 1000
- addition of hse-v6 binpacks with minimum simple eval 500
- permuting the FT with 10k positions from fishpack32.binpack
- torch.compile to speed up smallnet training

Training is significantly slower when using non-pre-filtered binpacks due to
the increased skipping required.

This net was reached at epoch 339.

```
experiment-name: 128--S1-hse-1k-T80-v6-unfilt-less-sf--se-gt950-no-wld-skip

training-dataset:
  /data/:
    - dfrc99-16tb7p.v2.min.binpack

  /data/hse-v1/:
    - leela96-filt-v2.min.high-simple-eval-1k.min-v2.binpack

    - test60-novdec2021-12tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-1k.min-v2.binpack

    - test77-nov2021-2tb7p.no-db.min.high-simple-eval-1k.min-v2.binpack
    - test77-dec2021-16tb7p.no-db.min.high-simple-eval-1k.min-v2.binpack
    - test77-jan2022-2tb7p.high-simple-eval-1k.min-v2.binpack

    - test78-jantomay2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-1k.min-v2.binpack
    - test78-juntosep2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-1k.min-v2.binpack

    - test79-apr2022-16tb7p.min.high-simple-eval-1k.min-v2.binpack
    - test79-may2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-1k.min-v2.binpack

    - test80-apr2022-16tb7p.min.high-simple-eval-1k.min-v2.binpack
    - test80-may2022-16tb7p.high-simple-eval-1k.min-v2.binpack
    - test80-jun2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-1k.min-v2.binpack
    - test80-jul2022-16tb7p.v6-dd.min.high-simple-eval-1k.min-v2.binpack
    - test80-sep2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-1k.min-v2.binpack
    - test80-nov2022-16tb7p-v6-dd.min.high-simple-eval-1k.min-v2.binpack

  /data/S11-mar2024/:
    - test80-2022-08-aug-16tb7p.v6-dd.min.binpack
    - test80-2022-10-oct-16tb7p.v6-dd.binpack
    - test80-2022-12-dec-16tb7p.min.binpack

    - test80-2023-01-jan-16tb7p.v6-sk20.min.binpack
    - test80-2023-02-feb-16tb7p.v6-sk20.min.binpack
    - test80-2023-03-mar-2tb7p.v6-sk16.min.binpack
    - test80-2023-04-apr-2tb7p.v6-sk16.min.binpack
    - test80-2023-05-may-2tb7p.v6.min.binpack
    - test80-2023-06-jun-2tb7p.binpack.min-v2.binpack
    - test80-2023-07-jul-2tb7p.binpack.min-v2.binpack
    - test80-2023-08-aug-2tb7p.v6.min.binpack
    - test80-2023-09-sep-2tb7p.binpack.hse-v6.binpack
    - test80-2023-10-oct-2tb7p.binpack.hse-v6.binpack
    - test80-2023-11-nov-2tb7p.binpack.hse-v6.binpack
    - test80-2023-12-dec-2tb7p.binpack.hse-v6.binpack

    - test80-2024-01-jan-2tb7p.binpack.hse-v6.binpack
    - test80-2024-02-feb-2tb7p.binpack.hse-v6.binpack
    - test80-2024-03-mar-2tb7p.binpack

wld-fen-skipping: False

nnue-pytorch-branch: linrock/nnue-pytorch/128-skipSimpleEval-lt950-torch-compile
engine-test-branch: linrock/Stockfish/L1-128-nolazy
engine-base-branch: linrock/Stockfish/L1-128
start-from-engine-test-net: False

num-epochs: 500
start-lambda: 1.0
end-lambda: 1.0
```

Training data can be found at:
https://robotmoon.com/nnue-training-data/

Passed STC:
https://tests.stockfishchess.org/tests/view/66549c16a86388d5e27daff5
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 196608 W: 51254 L: 50697 D: 94657
Ptnml(0-2): 722, 23244, 49796, 23839, 703

Passed LTC:
https://tests.stockfishchess.org/tests/view/6658d1aa6b0e318cefa90122
LLR: 2.96 (-2.94,2.94) <0.50,2.50>
Total: 122538 W: 31332 L: 30835 D: 60371
Ptnml(0-2): 69, 13407, 33811, 13922, 60

closes https://github.com/official-stockfish/Stockfish/pull/5333

bench
2024-06-01 19:59:07 +02:00
rn5f107s2
b34a690cd4 MCP more after a bad singular search
The idea is, that if we have the information that the singular search failed low and therefore produced an upperbound score, we can use the score from singularsearch as approximate upperbound as to what bestValue our non ttMoves will produce. If this value is well below alpha, we assume that all non-ttMoves will score below alpha and therfore can skip more moves.
This patch also sets up variables for future patches wanting to use teh singular search result outside of singular extensions, in singularBound and singularValue, meaning further patches using this search result to affect various pruning techniques can be tried.

Passed STC:
https://tests.stockfishchess.org/tests/view/6658d13e6b0e318cefa90120
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 85632 W: 22112 L: 21725 D: 41795
Ptnml(0-2): 243, 10010, 21947, 10349, 267

Passed LTC:
https://tests.stockfishchess.org/tests/view/6658dd356b0e318cefa9016a
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 243978 W: 62014 L: 61272 D: 120692
Ptnml(0-2): 128, 26598, 67791, 27348, 124

closes https://github.com/official-stockfish/Stockfish/pull/5325

bench 1397172
2024-06-01 19:58:20 +02:00
Linmiao Xu
0ef809ac71 Quadratic smallnet threshold with re-evaluation
The threshold now decreases more quickly as pawn count decreases,
using the smallnet more compared to before.

Combo of two eval patches:
https://tests.stockfishchess.org/tests/view/66576c5f6b0e318cefa8d26e
https://tests.stockfishchess.org/tests/view/664ced40830eb9f886616a77

Passed STC:
https://tests.stockfishchess.org/tests/view/66588c136b0e318cefa8ff21
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 112608 W: 29336 L: 28908 D: 54364
Ptnml(0-2): 344, 13223, 28718, 13699, 320

Passed LTC:
https://tests.stockfishchess.org/tests/view/6658c8786b0e318cefa900f5
LLR: 2.96 (-2.94,2.94) <0.50,2.50>
Total: 108288 W: 27493 L: 27026 D: 53769
Ptnml(0-2): 54, 11821, 29930, 12282, 57

closes https://github.com/official-stockfish/Stockfish/pull/5323

bench 1728074
2024-06-01 19:56:05 +02:00
FauziAkram
de1ae4949d Tweak first picked move (ttMove) reduction rule
Tweak first picked move (ttMove) reduction rule:

Instead of always resetting the reduction to 0, we now only do so if the current reduction is less than 2.
If the current reduction is 2 or more, we decrease it by 2 instead.

Passed STC:
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 109504 W: 28340 L: 27919 D: 53245
Ptnml(0-2): 305, 12848, 28028, 13263, 308
https://tests.stockfishchess.org/tests/view/6658c2fa6b0e318cefa900c2

Passed LTC:
LLR: 2.96 (-2.94,2.94) <0.50,2.50>
Total: 130410 W: 33248 L: 32738 D: 64424
Ptnml(0-2): 53, 14139, 36328, 14615, 70
https://tests.stockfishchess.org/tests/view/6658dd8a6b0e318cefa90173

closes https://github.com/official-stockfish/Stockfish/pull/5321

bench: 1224588
2024-06-01 19:53:13 +02:00
Joost VandeVondele
54e74919d4 Fix cross from Linux to Windows
specifies Windows 7 required

https://learn.microsoft.com/en-us/cpp/porting/modifying-winver-and-win32-winnt?view=msvc-170

closes https://github.com/official-stockfish/Stockfish/pull/5319

No functional change
2024-05-30 23:07:25 +02:00
Tomasz Sobczyk
c8375c2fbd On linux use sysfs instead of lscpu
Use sysfs (https://www.kernel.org/doc/Documentation/ABI/stable/sysfs-devices-node)
to determine processor to NUMA node mapping.

Avoids problems on some machines with high core count where lscpu was showing high cpu utilization.

closes https://github.com/official-stockfish/Stockfish/pull/5315

No functional change
2024-05-30 23:05:25 +02:00
Tomasz Sobczyk
86694b5914 Replace std::from_chars with std::stoull
the former was not widely supported, requiring newer compiler versions.

closes https://github.com/official-stockfish/Stockfish/pull/5313

No functional change
2024-05-30 23:05:21 +02:00
Tomasz Sobczyk
f1bb4164bf Fix process' processor affinity determination on Windows.
Specialize and privatize NumaConfig::get_process_affinity.
Only enable NUMA capability for 64-bit Windows.

Following #5307 and some more testing it was determined that the way affinity
was being determined on Windows was incorrect, based on incorrect assumptions
about GetNumaProcessorNodeEx.

This patch fixes the issue by attempting to retrieve the actual process'
processor affinity using Windows API. However one issue persists that is not
addressable due to limitations of Windows, and will have to be considered a
limitation. If affinities were set using SetThreadAffinityMask instead of
SetThreadSelectedCpuSetMasks and GetProcessGroupAffinity returns more than 1
group it is NOT POSSIBLE to determine the affinity programmatically on Windows.
In such case the implementation assumes no affinites are set and will consider
all processors available for execution.

closes https://github.com/official-stockfish/Stockfish/pull/5312

No functional change
2024-05-30 23:05:16 +02:00
Disservin
596fb4842b NUMA: Fix concurrency counting for windows systems
If there is more than 1 processor group, std:🧵:hardware_concurrency should not be used.

fixes #5307

closes https://github.com/official-stockfish/Stockfish/pull/5311

No functional change
2024-05-30 23:05:01 +02:00
FauziAkram
02eae52833 Simplifying the malus for putting piece en prise formula
Simplifying the malus for putting piece en prise
formula by merging the minor pieces and pawns
(removing the pawn exclusion from the formula).

Passed STC:
https://tests.stockfishchess.org/tests/view/66578d9c6b0e318cefa8d441
LLR: 2.99 (-2.94,2.94) <-1.75,0.25>
Total: 314272 W: 80705 L: 80786 D: 152781
Ptnml(0-2): 873, 37577, 80366, 37398, 922

Passed LTC (before rebasing):
https://tests.stockfishchess.org/tests/view/6657b5ee6b0e318cefa8d6ab
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 117000 W: 29447 L: 29324 D: 58229
Ptnml(0-2): 47, 12877, 32535, 12988, 53

Passed LTC (also after rebasing):
https://tests.stockfishchess.org/tests/view/6658803d6b0e318cefa8fd99
LLR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 244992 W: 61807 L: 61814 D: 121371
Ptnml(0-2): 125, 27420, 67414, 27411, 126

closes https://github.com/official-stockfish/Stockfish/pull/5316

Bench: 1484840
2024-05-30 23:00:22 +02:00
Michael Chaly
b280d2f065 Allow tt cutoffs for shallower depths in certain conditions
Current master allows tt cutoffs only when depth
from tt is strictly greater than current node
depth. This patch also allows them when it's equal
and if tt value is lower or equal to beta.

Passed STC:
https://tests.stockfishchess.org/tests/view/66578e2e6b0e318cefa8d447
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 26592 W: 6944 L: 6645 D: 13003
Ptnml(0-2): 67, 3039, 6795, 3318, 77

Passed LTC:
https://tests.stockfishchess.org/tests/view/6657f46b6b0e318cefa8d7e9
LLR: 2.96 (-2.94,2.94) <0.50,2.50>
Total: 142572 W: 36315 L: 35776 D: 70481
Ptnml(0-2): 70, 15666, 39288, 16179, 83

closes https://github.com/official-stockfish/Stockfish/pull/5314

Bench: 1368486
2024-05-30 22:54:23 +02:00
FauziAkram
d1a71fdaa7 Functional simplification in the transposition table
Passed STC:
LLR: 2.98 (-2.94,2.94) <-1.75,0.25>
Total: 154848 W: 39838 L: 39750 D: 75260
Ptnml(0-2): 404, 16214, 44087, 16328, 391
https://tests.stockfishchess.org/tests/view/664892b088b8c6a2bbe430fc

Passed LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 68172 W: 17296 L: 17137 D: 33739
Ptnml(0-2): 23, 6349, 21185, 6504, 25
https://tests.stockfishchess.org/tests/view/6648aabfa0781149e383e526

closes https://github.com/official-stockfish/Stockfish/pull/5263

Bench: 1623228
2024-05-30 22:53:20 +02:00
Viren6
a77a895c3b Add extension condition to cutoffCnt
Decrease cutoffCnt increment by 1 if extension is 2 or greater.

Passed STC:
https://tests.stockfishchess.org/tests/view/66577a696b0e318cefa8d34d
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 99200 W: 25703 L: 25297 D: 48200
Ptnml(0-2): 253, 11660, 25390, 12022, 275

Passed LTC:
https://tests.stockfishchess.org/tests/view/665787ab6b0e318cefa8d411
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 124530 W: 31659 L: 31161 D: 61710
Ptnml(0-2): 58, 13578, 34489, 14088, 52

closes https://github.com/official-stockfish/Stockfish/pull/5310

bench 1623228
2024-05-30 14:34:24 +02:00
Robert Nurnberg @ elitebook
a4ea183e78 Tweak and update the WDL model
This PR updates the internal WDL model, using data from 2.5M games played by SF-dev (3c62ad7).
Note that the normalizing constant has increased from 329 to 368.

Changes to the fitting procedure:

* the value for --materialMin was increased from 10 to 17: including data with less material leads to less accuracy for larger material count values
* the data was filtered to only include single thread LTC games at 60+0.6
* the data was filtered to only include games from master against patches that are (approximatively) within 5 nElo of master

For more information and plots of the model see PR#5309

closes https://github.com/official-stockfish/Stockfish/pull/5309

No functional change
2024-05-30 14:29:31 +02:00
Linmiao Xu
35aff79843 Update default main net to nn-ddcfb9224cdb.nnue
Created by further tuning the spsa-tuned main net `nn-c721dfca8cd3.nnue`
with the same methods described in https://github.com/official-stockfish/Stockfish/pull/5254

This net was reached at 61k / 120k spsa games at 70+0.7 th 7:
https://tests.stockfishchess.org/tests/view/665639d0a86388d5e27dd259

Passed STC:
https://tests.stockfishchess.org/tests/view/6657d44e6b0e318cefa8d771
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 114688 W: 29775 L: 29344 D: 55569
Ptnml(0-2): 274, 13633, 29149, 13964, 324

Passed LTC:
https://tests.stockfishchess.org/tests/view/6657e1e46b0e318cefa8d7a6
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 88152 W: 22412 L: 21988 D: 43752
Ptnml(0-2): 56, 9560, 24409, 10006, 45

closes https://github.com/official-stockfish/Stockfish/pull/5308

Bench: 1434678
2024-05-30 14:28:07 +02:00
FauziAkram
0ea6337ccf Remove Queen threatenedByMinor
Remove Queen threatenedByMinor from movepick

Passed STC:
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 54432 W: 14053 L: 13855 D: 26524
Ptnml(0-2): 124, 6347, 14090, 6517, 138
https://tests.stockfishchess.org/tests/view/66578d036b0e318cefa8d43d

Passed LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 198168 W: 49979 L: 49940 D: 98249
Ptnml(0-2): 84, 21824, 55236, 21849, 91
https://tests.stockfishchess.org/tests/view/66579cf86b0e318cefa8d5b1

closes https://github.com/official-stockfish/Stockfish/pull/5306

bench: 1342438
2024-05-30 14:21:28 +02:00
Linmiao Xu
5ab3fe6db8 Simplify blending eval with nnue complexity
Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/66567377a86388d5e27dd89c
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 144000 W: 37443 L: 37338 D: 69219
Ptnml(0-2): 587, 17260, 36208, 17351, 594

Passed non-regression LTC:
https://tests.stockfishchess.org/tests/view/66567f29a86388d5e27dd924
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 112326 W: 28550 L: 28421 D: 55355
Ptnml(0-2): 66, 12732, 30434, 12869, 62

closes https://github.com/official-stockfish/Stockfish/pull/5305

bench 1554486
2024-05-30 14:18:39 +02:00
Shawn Xu
4a2291ed33 Simplify Away Quadruple Extension
Passed non-regression VVLTC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 90792 W: 23155 L: 23018 D: 44619
Ptnml(0-2): 6, 8406, 28432, 8549, 3
https://tests.stockfishchess.org/tests/view/664ffa4ca86388d5e27d8e7a

Passed non-regression VLTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 288136 W: 72608 L: 72659 D: 142869
Ptnml(0-2): 38, 30258, 83525, 30211, 36
https://tests.stockfishchess.org/tests/view/66551609a86388d5e27db9ae

closes https://github.com/official-stockfish/Stockfish/pull/5293

bench 1501735
2024-05-30 14:16:17 +02:00
xoto10
3c62ad7e07 Add compensation factor to adjust extra time according to time control
As stockfish nets and search evolve, the existing time control appears
to give too little time at STC, roughly correct at LTC, and too little
at VLTC+.

This change adds an adjustment to the optExtra calculation. This
adjustment is easy to retune and refine, so it should be easier to keep
up-to-date than the more complex calculations used for optConstant and
optScale.

Passed STC 10+0.1:
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 169568 W: 43803 L: 43295 D: 82470
Ptnml(0-2): 485, 19679, 44055, 19973, 592
https://tests.stockfishchess.org/tests/view/66531865a86388d5e27da9fa

Yellow LTC 60+0.6:
LLR: -2.94 (-2.94,2.94) <0.50,2.50>
Total: 209970 W: 53087 L: 52914 D: 103969
Ptnml(0-2): 91, 19652, 65314, 19849, 79
https://tests.stockfishchess.org/tests/view/6653e38ba86388d5e27daaa0

Passed VLTC 180+1.8 :
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 85618 W: 21735 L: 21342 D: 42541
Ptnml(0-2): 15, 8267, 25848, 8668, 11
https://tests.stockfishchess.org/tests/view/6655131da86388d5e27db95f

closes https://github.com/official-stockfish/Stockfish/pull/5297

Bench: 1212167
2024-05-29 19:04:57 +02:00
Shawn Xu
ae7eef51fd Simplify Fail Low Bonus Formula
Tested against PR #5299

Passed Non-regression STC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 76352 W: 19797 L: 19619 D: 36936
Ptnml(0-2): 236, 9017, 19509, 9161, 253
https://tests.stockfishchess.org/tests/view/66564f60a86388d5e27dd307

Passed Non-regression LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 114624 W: 28946 L: 28821 D: 56857
Ptnml(0-2): 59, 12675, 31714, 12810, 54
https://tests.stockfishchess.org/tests/view/6656543da86388d5e27dd329

closes https://github.com/official-stockfish/Stockfish/pull/5301

Bench: 1212167
2024-05-29 19:01:50 +02:00
mstembera
a2f4e988aa Fix MSVC NUMA compile issues
closes https://github.com/official-stockfish/Stockfish/pull/5298

No functional change
2024-05-29 19:00:37 +02:00
Shawn Xu
c14297a483 Tune Fail Low Bonus
Fractional bonus idea is from @Ergodice on
[discord](https://discord.com/channels/435943710472011776/735707599353151579/1244039134499180614).
Values are tuned for 149k games at LTC.

SPSA tune:
https://tests.stockfishchess.org/tests/view/6652d5d5a86388d5e27da9d6

Failed STC:
LLR: -2.95 (-2.94,2.94) <0.00,2.00>
Total: 67424 W: 17364 L: 17528 D: 32532
Ptnml(0-2): 238, 8043, 17299, 7909, 223
https://tests.stockfishchess.org/tests/view/66551e1ba86388d5e27db9f9

Passed LTC:
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 146910 W: 37141 L: 36695 D: 73074
Ptnml(0-2): 84, 16201, 40441, 16643, 86
https://tests.stockfishchess.org/tests/view/66559949a86388d5e27dcc5d

Passed VLTC:
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 27248 W: 6924 L: 6633 D: 13691
Ptnml(0-2): 5, 2744, 7835, 3035, 5
https://tests.stockfishchess.org/tests/view/66563f4da86388d5e27dd27a

closes https://github.com/official-stockfish/Stockfish/pull/5299

Bench: 1390709
2024-05-29 18:58:38 +02:00
Stéphane Nicolet
c7b80f6c8a Merge pawn count terms using their average
This simplification patch merges the pawn count terms in the eval
formula with the material term, updating the offset constant for
the nnue part of the formula from 34000 to 34300 because the average
pawn count in middlegame positions evaluated during search is around 8.

STC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 138240 W: 35834 L: 35723 D: 66683
Ptnml(0-2): 527, 16587, 34817, 16626, 563
https://tests.stockfishchess.org/tests/view/6653f474a86388d5e27daaac

LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 454272 W: 114787 L: 115012 D: 224473
Ptnml(0-2): 246, 51168, 124553, 50903, 266
https://tests.stockfishchess.org/tests/view/6654f256a86388d5e27db131

closes https://github.com/official-stockfish/Stockfish/pull/5303

Bench: 1279635
2024-05-29 18:57:32 +02:00
FauziAkram
41acbcae1a Simplifying malus for putting piece en prise formula
Patch author: @ehsanrashid

Passed STC:
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 116192 W: 30229 L: 30094 D: 55869
Ptnml(0-2): 451, 13880, 29351, 13911, 503
https://tests.stockfishchess.org/tests/view/66510a40a86388d5e27da936

Passed LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 441312 W: 111009 L: 111220 D: 219083
Ptnml(0-2): 217, 49390, 121659, 49167, 223
https://tests.stockfishchess.org/tests/view/66530696a86388d5e27da9e3

closes https://github.com/official-stockfish/Stockfish/pull/5304

Bench: 1987574
2024-05-29 18:55:30 +02:00
Tomasz Sobczyk
a169c78b6d Improve performance on NUMA systems
Allow for NUMA memory replication for NNUE weights.  Bind threads to ensure execution on a specific NUMA node.

This patch introduces NUMA memory replication, currently only utilized for the NNUE weights. Along with it comes all machinery required to identify NUMA nodes and bind threads to specific processors/nodes. It also comes with small changes to Thread and ThreadPool to allow easier execution of custom functions on the designated thread. Old thread binding (WinProcGroup) machinery is removed because it's incompatible with this patch. Small changes to unrelated parts of the code were made to ensure correctness, like some classes being made unmovable, raw pointers replaced with unique_ptr. etc.

Windows 7 and Windows 10 is partially supported. Windows 11 is fully supported. Linux is fully supported, with explicit exclusion of Android. No additional dependencies.

-----------------

A new UCI option `NumaPolicy` is introduced. It can take the following values:
```
system - gathers NUMA node information from the system (lscpu or windows api), for each threads binds it to a single NUMA node
none - assumes there is 1 NUMA node, never binds threads
auto - this is the default value, depends on the number of set threads and NUMA nodes, will only enable binding on multinode systems and when the number of threads reaches a threshold (dependent on node size and count)
[[custom]] -
  // ':'-separated numa nodes
  // ','-separated cpu indices
  // supports "first-last" range syntax for cpu indices,
  for example '0-15,32-47:16-31,48-63'
```

Setting `NumaPolicy` forces recreation of the threads in the ThreadPool, which in turn forces the recreation of the TT.

The threads are distributed among NUMA nodes in a round-robin fashion based on fill percentage (i.e. it will strive to fill all NUMA nodes evenly). Threads are bound to NUMA nodes, not specific processors, because that's our only requirement and the OS can schedule them better.

Special care is made that maximum memory usage on systems that do not require memory replication stays as previously, that is, unnecessary copies are avoided.

On linux the process' processor affinity is respected. This means that if you for example use taskset to restrict Stockfish to a single NUMA node then the `system` and `auto` settings will only see a single NUMA node (more precisely, the processors included in the current affinity mask) and act accordingly.

-----------------

We can't ensure that a memory allocation takes place on a given NUMA node without using libnuma on linux, or using appropriate custom allocators on windows (https://learn.microsoft.com/en-us/windows/win32/memory/allocating-memory-from-a-numa-node), so to avoid complications the current implementation relies on first-touch policy. Due to this we also rely on the memory allocator to give us a new chunk of untouched memory from the system. This appears to work reliably on linux, but results may vary.

MacOS is not supported, because AFAIK it's not affected, and implementation would be problematic anyway.

Windows is supported since Windows 7 (https://learn.microsoft.com/en-us/windows/win32/api/processtopologyapi/nf-processtopologyapi-setthreadgroupaffinity). Until Windows 11/Server 2022 NUMA nodes are split such that they cannot span processor groups. This is because before Windows 11/Server 2022 it's not possible to set thread affinity spanning processor groups. The splitting is done manually in some cases (required after Windows 10 Build 20348). Since Windows 11/Server 2022 we can set affinites spanning processor group so this splitting is not done, so the behaviour is pretty much like on linux.

Linux is supported, **without** libnuma requirement. `lscpu` is expected.

-----------------

Passed 60+1 @ 256t 16000MB hash: https://tests.stockfishchess.org/tests/view/6654e443a86388d5e27db0d8
```
LLR: 2.95 (-2.94,2.94) <0.00,10.00>
Total: 278 W: 110 L: 29 D: 139
Ptnml(0-2): 0, 1, 56, 82, 0
```

Passed SMP STC: https://tests.stockfishchess.org/tests/view/6654fc74a86388d5e27db1cd
```
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 67152 W: 17354 L: 17177 D: 32621
Ptnml(0-2): 64, 7428, 18408, 7619, 57
```

Passed STC: https://tests.stockfishchess.org/tests/view/6654fb27a86388d5e27db15c
```
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 131648 W: 34155 L: 34045 D: 63448
Ptnml(0-2): 426, 13878, 37096, 14008, 416
```

fixes #5253
closes https://github.com/official-stockfish/Stockfish/pull/5285

No functional change
2024-05-28 18:34:15 +02:00
Disservin
b0287dcb1c apply const to prefetch parameter
closes https://github.com/official-stockfish/Stockfish/pull/5296

No functional change
2024-05-28 18:31:06 +02:00
FauziAkram
d0b9411b82 Tweak return value in futility pruning
Tweak the return value formula in futility pruning.

Passed STC:
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 60544 W: 15791 L: 15440 D: 29313
Ptnml(0-2): 193, 7024, 15520, 7309, 226
https://tests.stockfishchess.org/tests/view/6654ef22a86388d5e27db122

Passed LTC:
LLR: 2.96 (-2.94,2.94) <0.50,2.50>
Total: 126426 W: 32317 L: 31812 D: 62297
Ptnml(0-2): 55, 13871, 34869, 14350, 68
https://tests.stockfishchess.org/tests/view/66550644a86388d5e27db649

closes https://github.com/official-stockfish/Stockfish/pull/5295

bench: 1856147
2024-05-28 18:30:24 +02:00
Shawn Xu
5e98a4e43d Simplify Away TT Cutoff Return Value Adjustments
Passed Non-regression STC:
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 198432 W: 51161 L: 51119 D: 96152
Ptnml(0-2): 772, 23670, 50273, 23746, 755
https://tests.stockfishchess.org/tests/view/66517b9ea86388d5e27da966

Passed Non-regression LTC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 234150 W: 59200 L: 59197 D: 115753
Ptnml(0-2): 126, 26200, 64404, 26235, 110
https://tests.stockfishchess.org/tests/view/6653a84da86388d5e27daa63

closes https://github.com/official-stockfish/Stockfish/pull/5292

bench 1555200
2024-05-28 18:26:42 +02:00
Shahin M. Shahin
8e1f273c7d Remove rootDelta branch
This makes rootDelta logic easier to understand, recalculating the value
where it belongs so removes an unnecessary branch.

Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/664fc147a86388d5e27d8d8e
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 206016 W: 53120 L: 53089 D: 99807
Ptnml(0-2): 591, 20928, 59888, 21061, 540

closes https://github.com/official-stockfish/Stockfish/pull/5289

No functional change
2024-05-26 20:32:41 +02:00
Linmiao Xu
8bc3fd3871 Lower smallnet threshold with tuned eval params
The smallnet threshold is now below the training data range
of the current smallnet (simple eval diff > 1k, nn-baff1edelf90.nnue)
when no pawns are on the board.

Params found with spsa at 93k / 120k games at 60+06:
https://tests.stockfishchess.org/tests/view/664fa166a86388d5e27d7d6b

Tuned on top of: https://github.com/official-stockfish/Stockfish/pull/5287

Passed STC:
https://tests.stockfishchess.org/tests/view/664fc8b7a86388d5e27d8dac
LLR: 2.96 (-2.94,2.94) <0.00,2.00>
Total: 64672 W: 16731 L: 16371 D: 31570
Ptnml(0-2): 239, 7463, 16517, 7933, 184

Passed LTC:
https://tests.stockfishchess.org/tests/view/664fd5f9a86388d5e27d8dfe
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 210648 W: 53489 L: 52813 D: 104346
Ptnml(0-2): 102, 23129, 58164, 23849, 80

closes https://github.com/official-stockfish/Stockfish/pull/5288

Bench: 1717838
2024-05-26 20:32:30 +02:00
Stéphane Nicolet
4d876275cf Simplify material weights in evaluation
This patch uses the same material weights for the nnue
amplification term and the optimism term in evaluate().

STC:
LLR: 2.99 (-2.94,2.94) <-1.75,0.25>
Total: 83360 W: 21489 L: 21313 D: 40558
Ptnml(0-2): 303, 9934, 21056, 10058, 329
https://tests.stockfishchess.org/tests/view/664eee69928b1fb18de500d9

LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 192648 W: 48675 L: 48630 D: 95343
Ptnml(0-2): 82, 21484, 53161, 21501, 96
https://tests.stockfishchess.org/tests/view/664fa17aa86388d5e27d7d6e

closes https://github.com/official-stockfish/Stockfish/pull/5287

Bench: 1495602
2024-05-26 20:24:05 +02:00
Muzhen Gaming
61acbfc7d3 VVLTC search tune
Parameters were tuned in 2 stages:
1. 127k games at VVLTC:
   https://tests.stockfishchess.org/tests/view/6649f8dfb8fa20e74c39f52a.
2. 106k games at VVLTC:
   https://tests.stockfishchess.org/tests/view/664bfb77830eb9f886615a9d.

Passed VVLTC 1st sprt:
https://tests.stockfishchess.org/tests/view/664e8dd9928b1fb18de4e410
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 20466 W: 5340 L: 5093 D: 10033
Ptnml(0-2): 0, 1796, 6397, 2037, 3

Passed VVLTC 2nd sprt:
https://tests.stockfishchess.org/tests/view/664eb4aa928b1fb18de4e47d
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 15854 W: 4186 L: 3934 D: 7734
Ptnml(0-2): 1, 1367, 4938, 1621, 0

closes https://github.com/official-stockfish/Stockfish/pull/5286

Bench: 1558110
2024-05-23 21:37:46 +02:00
Linmiao Xu
365aa85dce Remove material imbalance param when adjusting optimism
Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/664d033d830eb9f886616aff
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 102144 W: 26283 L: 26135 D: 49726
Ptnml(0-2): 292, 12201, 25991, 12243, 345

Passed non-regression LTC:
https://tests.stockfishchess.org/tests/view/664d5c00830eb9f886616cb3
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 250032 W: 63022 L: 63036 D: 123974
Ptnml(0-2): 103, 27941, 68970, 27871, 131

closes https://github.com/official-stockfish/Stockfish/pull/5284

Bench: 1330940
2024-05-23 21:37:46 +02:00
Muzhen Gaming
72a345873d Revert "Reduce When TTValue is Above Alpha"
The patch regressed significantly at longer time controls. In
particular, the `depth--` behavior was predicted to scale badly based on
data from other variations of the patch.

Passed VVLTC 1st sprt:
https://tests.stockfishchess.org/tests/view/664d45cf830eb9f886616c7d
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 51292 W: 13242 L: 12954 D: 25096
Ptnml(0-2): 5, 4724, 15896, 5020, 1

Passed VVLTC 2nd sprt:
https://tests.stockfishchess.org/tests/view/664e641a928b1fb18de4e385
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 41884 W: 10933 L: 10634 D: 20317
Ptnml(0-2): 1, 3759, 13125, 4054, 3

closes https://github.com/official-stockfish/Stockfish/pull/5283

Bench: 1503815
2024-05-23 21:37:46 +02:00
cj5716
c6a1e7fd42 Optimise pairwise multiplication
This speedup was first inspired by a comment by @AndyGrant on my recent
PR "If mullo_epi16 would preserve the signedness, then this could be
used to remove 50% of the max operations during the halfkp-pairwise
mat-mul relu deal."

That got me thinking, because although mullo_epi16 did not preserve the
signedness, mulhi_epi16 did, and so we could shift left and then use
mulhi_epi16, instead of shifting right after the mullo.

However, due to some issues with shifting into the sign bit, the FT
weights and biases had to be multiplied by 2 for the optimisation to
work.

Speedup on "Arch=x86-64-bmi2 COMP=clang", courtesy of @Torom
Result of 50 runs
base (...es/stockfish) =     962946  +/- 1202
test (...ise-max-less) =     979696  +/- 1084
diff                   =     +16750  +/- 1794

speedup        = +0.0174
P(speedup > 0) =  1.0000

CPU: 4 x Intel(R) Core(TM) i7-6700K CPU @ 4.00GHz
Hyperthreading: on

Also a speedup on "COMP=gcc", courtesy of Torom once again
Result of 50 runs
base (...tockfish_gcc) =     966033  +/- 1574
test (...max-less_gcc) =     983319  +/- 1513
diff                   =     +17286  +/- 2515

speedup        = +0.0179
P(speedup > 0) =  1.0000

CPU: 4 x Intel(R) Core(TM) i7-6700K CPU @ 4.00GHz
Hyperthreading: on

Passed STC:
LLR: 2.96 (-2.94,2.94) <0.00,2.00>
Total: 67712 W: 17715 L: 17358 D: 32639
Ptnml(0-2): 225, 7472, 18140, 7759, 260
https://tests.stockfishchess.org/tests/view/664c1d75830eb9f886616906

closes https://github.com/official-stockfish/Stockfish/pull/5282

No functional change
2024-05-23 21:37:46 +02:00
Shawn Xu
c39b98b9e3 Simplify Away History Updates in Multicut
Passed Non-regression STC:
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 44896 W: 11600 L: 11388 D: 21908
Ptnml(0-2): 140, 5230, 11532, 5370, 176
https://tests.stockfishchess.org/tests/view/664cee31830eb9f886616a80

Passed Non-regression LTC:
LLR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 56832 W: 14421 L: 14234 D: 28177
Ptnml(0-2): 37, 6251, 15643, 6458, 27
https://tests.stockfishchess.org/tests/view/664cfd4e830eb9f886616aa6

closes https://github.com/official-stockfish/Stockfish/pull/5281

Bench: 1119412
2024-05-23 21:30:33 +02:00
Linmiao Xu
1dcffa6210 Comment about re-evaluating positions
While the smallNet bool is no longer used as of now,
setting it to false upon re-evaluation represents the
correct eval state.

closes https://github.com/official-stockfish/Stockfish/pull/5279

No functional change
2024-05-23 21:30:24 +02:00
Viren6
6db47ed71a Addition of new scaling comments
This patch is intended to prevent patches like 9b90cd8 and the
subsequent reversion e3c9ed7 from happening again. Scaling behaviour of
the reduction adjustments in the non-linear scaling
section have been proven to >8 sigma:

STC: https://tests.stockfishchess.org/tests/view/6647b19f6dcff0d1d6b05d52
Elo: 4.28 ± 0.8 (95%) LOS: 100.0%
Total: 200000 W: 52555 L: 50094 D: 97351
Ptnml(0-2): 573, 22628, 51248, 24867, 684
nElo: 8.35 ± 1.5 (95%) PairsRatio: 1.10

VLTC: https://tests.stockfishchess.org/tests/view/6647b1b06dcff0d1d6b05d54
Elo: -1.48 ± 1.0 (95%) LOS: 0.2%
Total: 100000 W: 25009 L: 25436 D: 49555
Ptnml(0-2): 11, 10716, 28971, 10293, 9
nElo: -3.23 ± 2.2 (95%) PairsRatio: 0.96

The else if condition is moved to the non scaling section based on:
https://tests.stockfishchess.org/tests/view/664567a193ce6da3e93b3232 (It
has no proven scaling)

General comment improvements and removal of a redundant margin condition
have also been included.

closes https://github.com/official-stockfish/Stockfish/pull/5266

No functional change
2024-05-23 21:29:36 +02:00
Dubslow
ed79745bb9 Improve comments about DEPTH constants
Also "fix" movepicker to allow depths between CHECKS and NO_CHECKS,
which makes them easier to tweak (not that they get tweaked hardly ever)
(This was more beneficial when there was a third stage to DEPTH_QS, but
it's still an improvement now)

closes https://github.com/official-stockfish/Stockfish/pull/5205

No functional change
2024-05-23 21:29:11 +02:00
Linmiao Xu
c14b69790a Lower smallnet threshold with updated eval divisors
Params found after 30k spsa games at 60+0.6, with initial
values from 64k spsa games at 45+0.45

First spsa with 64k / 120k games at 45+0.45:
https://tests.stockfishchess.org/tests/view/664a561b5fc7b70b8817c663
https://tests.stockfishchess.org/tests/view/664ae88e830eb9f8866146f9

Second spsa with 30k / 120k games at 60+0.6:
https://tests.stockfishchess.org/tests/view/664be227830eb9f886615a36

Values found at 10k games at 60+0.6 also passed STC and LTC:
https://tests.stockfishchess.org/tests/view/664bf4bd830eb9f886615a72
https://tests.stockfishchess.org/tests/view/664c0905830eb9f886615abf

Passed STC:
https://tests.stockfishchess.org/tests/view/664c139e830eb9f886615af2
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 69408 W: 18216 L: 17842 D: 33350
Ptnml(0-2): 257, 8275, 17401, 8379, 392

Passed LTC:
https://tests.stockfishchess.org/tests/view/664cdaf7830eb9f886616a24
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 35466 W: 9075 L: 8758 D: 17633
Ptnml(0-2): 27, 3783, 9794, 4104, 25

closes https://github.com/official-stockfish/Stockfish/pull/5280

bench 1301287
2024-05-21 22:06:17 +02:00
MinetaS
c86ec8ec29 Remove cutoffCnt margin adjustment in razoring
Passed non-regression STC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 65344 W: 16767 L: 16578 D: 31999
Ptnml(0-2): 198, 7557, 16987, 7718, 212
https://tests.stockfishchess.org/tests/view/664bd895830eb9f886615a26

Passed non-regression LTC:
LLR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 35214 W: 8999 L: 8791 D: 17424
Ptnml(0-2): 16, 3804, 9760, 4010, 17
https://tests.stockfishchess.org/tests/view/664bead5830eb9f886615a52

closes https://github.com/official-stockfish/Stockfish/pull/5278

Bench: 1296223
2024-05-21 08:46:12 +02:00
FauziAkram
87bad0c38a Refine Evaluation Scaling with Piece-Specific Weights
Refine Evaluation Scaling with Piece-Specific Weights, instead of the simplified npm method.
I took the initial idea from Viren6 , as he worked on it in September of last year.
I worked on it, and tuned it, and now it passed both tests.

Passed STC:
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 95712 W: 24731 L: 24325 D: 46656
Ptnml(0-2): 363, 11152, 24357, 11684, 300
https://tests.stockfishchess.org/tests/view/664b5493830eb9f886614af3

Passed LTC:
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 204480 W: 52167 L: 51501 D: 100812
Ptnml(0-2): 114, 22579, 56166, 23289, 92
https://tests.stockfishchess.org/tests/view/664b75dd830eb9f886614b44

closes https://github.com/official-stockfish/Stockfish/pull/5277

Bench: 1384337
2024-05-21 08:44:59 +02:00
Shawn Xu
f27a9be29c Reduce When TTValue is Above Alpha
Passed STC:
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 53376 W: 13818 L: 13476 D: 26082
Ptnml(0-2): 156, 6212, 13626, 6522, 172
https://tests.stockfishchess.org/tests/view/664aa261830eb9f8866145e5

Passed LTC:
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 393444 W: 100096 L: 99042 D: 194306
Ptnml(0-2): 191, 43516, 108248, 44582, 185
https://tests.stockfishchess.org/tests/view/664ab54f830eb9f88661463c

closes https://github.com/official-stockfish/Stockfish/pull/5276

Bench: 1024562
2024-05-21 08:40:37 +02:00
Michael Chaly
daf9787de1 Rescale pawn history updates
This patch is somewhat of a continuation of recent pawn history gainers.
It makes pawn history updates after search twice smaller. Since on average they make pawn history more negative offset is changed to lower value to remain average value approximately the same.

https://tests.stockfishchess.org/tests/view/664b3af9830eb9f886614aab
Passed STC:
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 170464 W: 44239 L: 43724 D: 82501
Ptnml(0-2): 523, 20278, 43128, 20767, 536

Passed LTC against pending PR :
https://tests.stockfishchess.org/tests/view/664b8c58830eb9f886614b64
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 98178 W: 25015 L: 24569 D: 48594
Ptnml(0-2): 48, 10769, 27005, 11223, 44

closes https://github.com/official-stockfish/Stockfish/pull/5275

Bench: 1343175
2024-05-21 08:36:32 +02:00
FauziAkram
b8ccaf038a Use same shuffling Constant for both nets
Passed STC:
https://tests.stockfishchess.org/tests/view/664a42b15fc7b70b8817aeef
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 87840 W: 22759 L: 22594 D: 42487
Ptnml(0-2): 335, 10351, 22324, 10634, 276

Passed LTC:
https://tests.stockfishchess.org/tests/view/664a46995fc7b70b8817af02
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 163122 W: 41443 L: 41367 D: 80312
Ptnml(0-2): 105, 18154, 44927, 18310, 65

closes https://github.com/official-stockfish/Stockfish/pull/5273

bench: 1190174
2024-05-21 08:27:16 +02:00
Michael Chaly
0c797367a3 Update correction history in case of successful null move pruning
Since null move pruning uses the same position it makes some sense to try to update correction history there in case of fail high.
Update value is 4 times less than normal update.

Passed STC:
https://tests.stockfishchess.org/tests/view/664a011cae57c1758ac5b4dd
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 419360 W: 108390 L: 107505 D: 203465
Ptnml(0-2): 1416, 49603, 106724, 50554, 1383

Passed LTC:
https://tests.stockfishchess.org/tests/view/664a53d95fc7b70b8817c65b
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 193518 W: 49076 L: 48434 D: 96008
Ptnml(0-2): 89, 21335, 53263, 21989, 83

closes https://github.com/official-stockfish/Stockfish/pull/5272

bench 1301487
2024-05-21 08:17:20 +02:00
Linmiao Xu
4d88a63e60 Re-eval only if smallnet output flips from simple eval
Recent attempts to change the smallnet nnue re-eval
threshold did not show much elo difference:
https://tests.stockfishchess.org/tests/view/664a29bb25a9058c4d21d53c
https://tests.stockfishchess.org/tests/view/664a299925a9058c4d21d53a

Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/664a3ea95fc7b70b8817aee2
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 22304 W: 5905 L: 5664 D: 10735
Ptnml(0-2): 67, 2602, 5603, 2783, 97

Passed non-regression LTC:
https://tests.stockfishchess.org/tests/view/664a43d35fc7b70b8817aef4
LLR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 37536 W: 9667 L: 9460 D: 18409
Ptnml(0-2): 25, 4090, 10321, 4317, 15

closes https://github.com/official-stockfish/Stockfish/pull/5271

bench 1287409
2024-05-21 08:13:25 +02:00
Stefan Geschwentner
81e21a69f0 Simplify the recently introduced ply-based cmh bonus factor.
Replace it with a constant which is an approximation of the limit of the factor.

STC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 120064 W: 30967 L: 30836 D: 58261
Ptnml(0-2): 421, 14238, 30608, 14319, 446
https://tests.stockfishchess.org/tests/view/6649d146b8fa20e74c39f4ad

LTC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 53856 W: 13719 L: 13530 D: 26607
Ptnml(0-2): 31, 5879, 14922, 6062, 34
https://tests.stockfishchess.org/tests/view/664a027fae57c1758ac5b4ee

closes https://github.com/official-stockfish/Stockfish/pull/5270

Bench: 1355618
2024-05-21 08:11:17 +02:00
Michael Chaly
4a66a7c9ca Do more aggressive pawn history updates
Tweak of recent patch that made pawn history to update for move that caused a fail low - and setting up default value of it to -900.  This patch makes it more aggressive - twice bigger updates and default value -1100.

Passed STC:
https://tests.stockfishchess.org/tests/view/6648c5d4308cceea45533b5d
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 235200 W: 61090 L: 60476 D: 113634
Ptnml(0-2): 763, 27952, 59651, 28376, 858

Passed LTC:
https://tests.stockfishchess.org/tests/view/664a1008ae57c1758ac5b523
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 20076 W: 5193 L: 4908 D: 9975
Ptnml(0-2): 7, 2105, 5534, 2380, 12

closes https://github.com/official-stockfish/Stockfish/pull/5268

Bench: 1590474
2024-05-21 08:07:22 +02:00
Stefan Geschwentner
a3bb7e626d Tweak continuation history bonus dependent on ply.
This patch is based on following tuning https://tests.stockfishchess.org/tests/view/6648b2eb308cceea45533abe by only using the tuned factors for the continuation history.

Passed STC:
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 99904 W: 25865 L: 25457 D: 48582
Ptnml(0-2): 281, 11705, 25578, 12101, 287
https://tests.stockfishchess.org/tests/view/6648c136308cceea45533af8

Passed LTC:
LLR: 2.96 (-2.94,2.94) <0.50,2.50>
Total: 36402 W: 9362 L: 9039 D: 18001
Ptnml(0-2): 20, 3952, 9951, 4241, 37
https://tests.stockfishchess.org/tests/view/6648ee3cb8fa20e74c39f3fd

closes https://github.com/official-stockfish/Stockfish/pull/5267

Bench: 1917762
2024-05-21 08:04:44 +02:00
cj5716
27eb49a221 Simplify ClippedReLU
Removes some max calls

Some speedup stats, courtesy of @AndyGrant (albeit measured in an alternate implementation)
Dev  749240 nps
Base 748495 nps
Gain 0.100%
289936 games

STC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 203040 W: 52213 L: 52179 D: 98648
Ptnml(0-2): 480, 20722, 59139, 20642, 537
https://tests.stockfishchess.org/tests/view/664805fe6dcff0d1d6b05f2c

closes #5261

No functional change
2024-05-21 07:58:16 +02:00
Viren6
2d32581623 Revert "Simplify Away Quadruple Extensions"
This reverts commit 4edd1a3

The unusual result of (combined) +12.0 +- 3.7 in the 2 VVLTC simplification SPRTs ran was the result of base having only 64MB of hash instead of 512MB (Asymmetric hash).
Vizvezdenec was the one to notice this.

closes https://github.com/official-stockfish/Stockfish/pull/5265

bench 1404295

Co-Authored-By: Michael Chaly <26898827+Vizvezdenec@users.noreply.github.com>
2024-05-19 09:37:22 +02:00
Muzhen Gaming
99f1bacfd6 VVLTC search tune
Tuned with 85k games at VVLTC.

VVLTC 1st sprt: https://tests.stockfishchess.org/tests/view/6648b836308cceea45533ad7
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 14880 W: 3890 L: 3652 D: 7338
Ptnml(0-2): 0, 1255, 4694, 1489, 2

VVLTC 2nd sprt: https://tests.stockfishchess.org/tests/view/6648c34f308cceea45533b4f
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 24984 W: 6502 L: 6235 D: 12247
Ptnml(0-2): 1, 2178, 7867, 2445, 1

closes https://github.com/official-stockfish/Stockfish/pull/5264

Bench: 1198142
2024-05-18 18:09:45 +02:00
Linmiao Xu
2694fce928 Simplify away adjustEval lambda
Now that only the shuffling constant differs between nets,
a lambda for adjusting eval is no longer needed.

Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/664806ca6dcff0d1d6b05f34
LLR: 2.99 (-2.94,2.94) <-1.75,0.25>
Total: 31552 W: 8175 L: 7959 D: 15418
Ptnml(0-2): 76, 3180, 9065, 3362, 93

closes https://github.com/official-stockfish/Stockfish/pull/5260

No functional change
2024-05-18 18:08:39 +02:00
Shawn Xu
4edd1a389e Simplify Away Quadruple Extensions
serendipitous gainer

Passed LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 95472 W: 24176 L: 24031 D: 47265
Ptnml(0-2): 52, 10533, 26414, 10692, 45
https://tests.stockfishchess.org/tests/live_elo/6647fa596dcff0d1d6b05efa

Passed VVLTC 70+7 th 7:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 6772 W: 1793 L: 1583 D: 3396
Ptnml(0-2): 0, 502, 2172, 712, 0
https://tests.stockfishchess.org/tests/live_elo/6648277a6dcff0d1d6b05ffb

Passed VVLTC 70+7 th 7 (2x):
https://tests.stockfishchess.org/tests/view/66484c896dcff0d1d6b0619d
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 5424 W: 1469 L: 1254 D: 2701
Ptnml(0-2): 0, 394, 1710, 607, 1

closes https://github.com/official-stockfish/Stockfish/pull/5259

Bench: 1441794
2024-05-18 09:32:21 +02:00
Linmiao Xu
99dfc63e03 Use one nnue pawn count multiplier
Switch to the value used by the main net.

Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/6647e8096dcff0d1d6b05e96
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 51040 W: 13249 L: 13044 D: 24747
Ptnml(0-2): 139, 6029, 13016, 6160, 176

Passed non-regression LTC:
https://tests.stockfishchess.org/tests/view/6647f4a46dcff0d1d6b05eea
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 20460 W: 5195 L: 4972 D: 10293
Ptnml(0-2): 8, 2178, 5637, 2397, 10

https://github.com/official-stockfish/Stockfish/pull/5258

bench 1887462
2024-05-18 09:29:26 +02:00
Shawn Xu
285f1d2a66 Tweak NMP Formula
Passed STC:
LLR: 2.99 (-2.94,2.94) <0.00,2.00>
Total: 241728 W: 62440 L: 61811 D: 117477
Ptnml(0-2): 914, 28467, 61458, 29126, 899
https://tests.stockfishchess.org/tests/live_elo/6645992993ce6da3e93b5b99

Passed LTC:
LLR: 2.96 (-2.94,2.94) <0.50,2.50>
Total: 167850 W: 42620 L: 42030 D: 83200
Ptnml(0-2): 82, 18412, 46354, 18988, 89
https://tests.stockfishchess.org/tests/live_elo/6647c5726dcff0d1d6b05dd3

closes https://github.com/official-stockfish/Stockfish/pull/5257

Bench: 1636018
2024-05-18 09:26:42 +02:00
FauziAkram
f5e15441b8 Early Exit in Bitboards::sliding_attack()
he original code checks for occupancy within the loop condition. By moving this check inside the loop and adding an early exit condition, we can avoid unnecessary iterations if a blocking piece is encountered.

Passed stc:
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 127200 W: 33129 L: 32700 D: 61371
Ptnml(0-2): 424, 13243, 35826, 13694, 413
https://tests.stockfishchess.org/tests/view/664646006dcff0d1d6b05bca

closes https://github.com/official-stockfish/Stockfish/pull/5256

No functional change
2024-05-18 09:24:23 +02:00
Linmiao Xu
d92d1f3180 Move smallnet threshold logic into a function
Now that the smallnet threshold is no longer a constant,
use a function to organize it with other eval code.

Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/66459fa093ce6da3e93b5ba2
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 217600 W: 56281 L: 56260 D: 105059
Ptnml(0-2): 756, 23787, 59729, 23736, 792

closes https://github.com/official-stockfish/Stockfish/pull/5255

No functional change
2024-05-18 09:21:00 +02:00
Linmiao Xu
1b7dea3f85 Update default main net to nn-c721dfca8cd3.nnue
Created by first retraining the spsa-tuned main net `nn-ae6a388e4a1a.nnue` with:
- using v6-dd data without bestmove captures removed
- addition of T80 mar2024 data
- increasing loss by 20% when Q is too high
- torch.compile changes for marginal training speed gains

And then SPSA tuning weights of epoch 899 following methods described in:
https://github.com/official-stockfish/Stockfish/pull/5149

This net was reached at 92k out of 120k steps in this 70+0.7 th 7 SPSA tuning run:
https://tests.stockfishchess.org/tests/view/66413b7df9f4e8fc783c9bbb
Thanks to @Viren6 for suggesting usage of:
- c value 4 for the weights
- c value 128 for the biases

Scripts for automating applying fishtest spsa params to exporting tuned .nnue are in:
https://github.com/linrock/nnue-tools/tree/master/spsa

Before spsa tuning, epoch 899 was nn-f85738aefa84.nnue
https://tests.stockfishchess.org/tests/view/663e5c893a2f9702074bc167

After initially training with max-epoch 800, training was resumed with max-epoch 1000.

```
experiment-name: 3072--S11--more-data-v6-dd-t80-mar2024--see-ge0-20p-more-loss-high-q-sk28-l8
nnue-pytorch-branch: linrock/nnue-pytorch/3072-r21-skip-more-wdl-see-ge0-20p-more-loss-high-q-torch-compile-more

start-from-engine-test-net: False
start-from-model: /data/config/apr2024-3072/nn-ae6a388e4a1a.nnue

early-fen-skipping: 28
training-dataset:
  /data/S11-mar2024/:
    - leela96.v2.min.binpack

    - test60-2021-11-12-novdec-12tb7p.v6-dd.min.binpack
    - test78-2022-01-to-05-jantomay-16tb7p.v6-dd.min.binpack

    - test80-2022-06-jun-16tb7p.v6-dd.min.binpack

    - test80-2022-08-aug-16tb7p.v6-dd.min.binpack
    - test80-2022-09-sep-16tb7p.v6-dd.min.binpack

    - test80-2023-01-jan-16tb7p.v6-sk20.min.binpack
    - test80-2023-02-feb-16tb7p.v6-sk20.min.binpack
    - test80-2023-03-mar-2tb7p.v6-sk16.min.binpack
    - test80-2023-04-apr-2tb7p.v6-sk16.min.binpack
    - test80-2023-05-may-2tb7p.v6.min.binpack

    # https://github.com/official-stockfish/Stockfish/pull/4782
    - test80-2023-06-jun-2tb7p.binpack
    - test80-2023-07-jul-2tb7p.binpack

    # https://github.com/official-stockfish/Stockfish/pull/4972
    - test80-2023-08-aug-2tb7p.v6.min.binpack
    - test80-2023-09-sep-2tb7p.binpack
    - test80-2023-10-oct-2tb7p.binpack

    # S9 new data: https://github.com/official-stockfish/Stockfish/pull/5056
    - test80-2023-11-nov-2tb7p.binpack
    - test80-2023-12-dec-2tb7p.binpack

    # S10 new data: https://github.com/official-stockfish/Stockfish/pull/5149
    - test80-2024-01-jan-2tb7p.binpack
    - test80-2024-02-feb-2tb7p.binpack

    # S11 new data
    - test80-2024-03-mar-2tb7p.binpack

  /data/filt-v6-dd/:
    - test77-dec2021-16tb7p-filter-v6-dd.binpack
    - test78-juntosep2022-16tb7p-filter-v6-dd.binpack
    - test79-apr2022-16tb7p-filter-v6-dd.binpack
    - test79-may2022-16tb7p-filter-v6-dd.binpack
    - test80-jul2022-16tb7p-filter-v6-dd.binpack
    - test80-oct2022-16tb7p-filter-v6-dd.binpack
    - test80-nov2022-16tb7p-filter-v6-dd.binpack

num-epochs: 1000

lr: 4.375e-4
gamma: 0.995
start-lambda: 0.8
end-lambda: 0.7
```

Training data can be found at:
https://robotmoon.com/nnue-training-data/

Local elo at 25k nodes per move:
nn-epoch899.nnue : 4.6 +/- 1.4

Passed STC:
https://tests.stockfishchess.org/tests/view/6645454893ce6da3e93b31ae
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 95232 W: 24598 L: 24194 D: 46440
Ptnml(0-2): 294, 11215, 24180, 11647, 280

Passed LTC:
https://tests.stockfishchess.org/tests/view/6645522d93ce6da3e93b31df
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 320544 W: 81432 L: 80524 D: 158588
Ptnml(0-2): 164, 35659, 87696, 36611, 142

closes https://github.com/official-stockfish/Stockfish/pull/5254

bench 1995552
2024-05-18 09:19:10 +02:00
Rak Laptudirm
e0227a6272 Improve comment
closes https://github.com/official-stockfish/Stockfish/pull/5249

No functional change
2024-05-18 09:18:14 +02:00
Linmiao Xu
47597641dc Lower smallnet threshold linearly as pawn count decreases
Passed STC:
https://tests.stockfishchess.org/tests/view/6644f677324e96f42f89d894
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 377920 W: 97135 L: 96322 D: 184463
Ptnml(0-2): 1044, 44259, 97588, 44978, 1091

Passed LTC:
https://tests.stockfishchess.org/tests/view/664548af93ce6da3e93b31b3
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 169056 W: 42901 L: 42312 D: 83843
Ptnml(0-2): 58, 18538, 46753, 19115, 64

closes https://github.com/official-stockfish/Stockfish/pull/5252

Bench: 1991750
2024-05-16 14:19:28 +02:00
Muzhen Gaming
e3c9ed77aa Revert "Reduce more when improving and ttvalue is lower than alpha"
The patch regressed significantly at longer time controls.

Passed VLTC:
https://tests.stockfishchess.org/tests/view/6644c7a2bc537f5619453096
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 43336 W: 11177 L: 10884 D: 21275
Ptnml(0-2): 3, 4432, 12507, 4721, 5

Passed VVLTC:
https://tests.stockfishchess.org/tests/view/66450c974aa4fa9a83b6d0b0
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 32394 W: 8350 L: 8072 D: 15972
Ptnml(0-2): 2, 2798, 10317, 3080, 0

closes https://github.com/official-stockfish/Stockfish/pull/5251

Bench: 1594188
2024-05-16 14:17:53 +02:00
Linmiao Xu
541406ab91 Use same nnue divisor for both nets
Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/6643ceeabc537f56194506f6
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 224800 W: 57910 L: 57896 D: 108994
Ptnml(0-2): 673, 26790, 57519, 26686, 732

Passed non-regression LTC:
https://tests.stockfishchess.org/tests/view/6643ff15bc537f5619451719
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 347658 W: 87574 L: 87688 D: 172396
Ptnml(0-2): 207, 39004, 95488, 38956, 174

closes https://github.com/official-stockfish/Stockfish/pull/5250

Bench: 1804704
2024-05-16 14:16:54 +02:00
FauziAkram
dcb0233784 Simplifying improving and worsening deduction formulas
Passed STC:
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 77696 W: 20052 L: 19878 D: 37766
Ptnml(0-2): 222, 9124, 19994, 9274, 234
https://tests.stockfishchess.org/tests/view/66440032bc537f561945171e

Passed LTC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 234414 W: 58874 L: 58871 D: 116669
Ptnml(0-2): 96, 26147, 64742, 26102, 120
https://tests.stockfishchess.org/tests/view/6644094cbc537f5619451735

closes https://github.com/official-stockfish/Stockfish/pull/5248

Bench: 1336738
2024-05-15 16:27:03 +02:00
Linmiao Xu
1f3a0fda2e Use same eval divisor for both nets
Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/66428f146577e9d2c8a29cf8
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 241024 W: 62173 L: 62177 D: 116674
Ptnml(0-2): 904, 28648, 61407, 28654, 899

Passed non-regression LTC:
https://tests.stockfishchess.org/tests/view/6643ae6f1f32a966da74977b
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 193710 W: 48762 L: 48717 D: 96231
Ptnml(0-2): 70, 21599, 53481, 21626, 79

closes https://github.com/official-stockfish/Stockfish/pull/5246

Bench: 1700680
2024-05-15 16:26:00 +02:00
Stefan Geschwentner
9b90cd88f0 Reduce more when improving and ttvalue is lower than alpha
More reduction if position is improving but value from TT doesn't
exceeds alpha but the tt move is excluded.

This idea is based on following LMR condition tuning
https://tests.stockfishchess.org/tests/view/66423a1bf9f4e8fc783cba37
by using only three of the four largest terms P[3], P[18] and P[12].

Passed STC:
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 27840 W: 7309 L: 7004 D: 13527
Ptnml(0-2): 85, 3219, 7018, 3502, 96
https://tests.stockfishchess.org/tests/view/6643dc1cbc537f56194508ba

Passed LTC:
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 191280 W: 48656 L: 48020 D: 94604
Ptnml(0-2): 78, 20979, 52903, 21589, 91
https://tests.stockfishchess.org/tests/view/6643e543bc537f5619451683

closes https://github.com/official-stockfish/Stockfish/pull/5245

Bench: 1430835
2024-05-15 16:20:14 +02:00
mstembera
09dba1f080 Call adjustEval with correct parameters after rescore
Set smallNet to false after rescoring so we call adjustEval() w/ correct
parameters.

STC:
https://tests.stockfishchess.org/tests/view/664308687134c82f3f7a4003
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 146912 W: 37856 L: 37756 D: 71300
Ptnml(0-2): 566, 17562, 37122, 17618, 588

LTC:
https://tests.stockfishchess.org/tests/view/6643a0821f32a966da7485d6
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 390414 W: 98015 L: 98173 D: 194226
Ptnml(0-2): 162, 43555, 107929, 43401, 160

closes https://github.com/official-stockfish/Stockfish/pull/5244

Bench: 1819318
2024-05-15 16:19:04 +02:00
Michael Chaly
9e45644c50 Add extra bonus to pawn history for a move that caused a fail low
Basically the same idea as it is for continuation/main history, but it
has some tweaks.
1) it has * 2 multiplier for bonus instead of full/half bonus - for
   whatever reason this seems to work better;
2) attempts with this type of big bonuses scaled somewhat poorly (or
   were unlucky at longer time controls), but after measuring the fact
   that average value of pawn history in LMR after adding this bonuses
   increased by substantial number (for multiplier 1,5 it increased by
   smth like 400~ from 8192 cap) attempts were made to make default pawn
   history negative to compensate it - and version with multiplier 2 and
   initial fill value -900 passed.

Passed STC:
https://tests.stockfishchess.org/tests/view/66424815f9f4e8fc783cba59
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 115008 W: 30001 L: 29564 D: 55443
Ptnml(0-2): 432, 13629, 28903, 14150, 390

Passed LTC:
https://tests.stockfishchess.org/tests/view/6642f5437134c82f3f7a3ffa
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 56448 W: 14432 L: 14067 D: 27949
Ptnml(0-2): 36, 6268, 15254, 6627, 39

Bench: 1857237
2024-05-15 16:15:15 +02:00
FauziAkram
fa114266fa Add extra bonus for high-depth condition
Passed STC:
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 54208 W: 14058 L: 13717 D: 26433
Ptnml(0-2): 166, 6277, 13885, 6602, 174
https://tests.stockfishchess.org/tests/view/664136d8f9f4e8fc783c9b82

Passed LTC:
LLR: 2.96 (-2.94,2.94) <0.50,2.50>
Total: 112548 W: 28492 L: 28018 D: 56038
Ptnml(0-2): 53, 12186, 31318, 12668, 49
https://tests.stockfishchess.org/tests/view/664143fef9f4e8fc783c9bf6

closes https://github.com/official-stockfish/Stockfish/pull/5242

Bench: 1725980
2024-05-15 16:13:43 +02:00
xoto10
2682c2127d Use 5% less time on first move
Stockfish appears to take too much time on the first move of a game and
then not enough on moves 2,3,4... Probably caused by most of the factors
that increase time usually applying on the first move.

Attempts to give more time to the subsequent moves have not worked so
far, but this change to simply reduce first move time by 5% worked.

STC 10+0.1 :
LLR: 2.96 (-2.94,2.94) <0.00,2.00>
Total: 78496 W: 20516 L: 20135 D: 37845
Ptnml(0-2): 340, 8859, 20456, 9266, 327
https://tests.stockfishchess.org/tests/view/663d47bf507ebe1c0e9200ba

LTC 60+0.6 :
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 94872 W: 24179 L: 23751 D: 46942
Ptnml(0-2): 61, 9743, 27405, 10161, 66
https://tests.stockfishchess.org/tests/view/663e779cbb28828150dd9089

closes https://github.com/official-stockfish/Stockfish/pull/5235

Bench: 1876282
2024-05-15 16:09:30 +02:00
mstembera
e608eab8dd Optimize update_accumulator_refresh_cache()
STC https://tests.stockfishchess.org/tests/view/664105df26ac5f9b286d30e6
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 178528 W: 46235 L: 45750 D: 86543
Ptnml(0-2): 505, 17792, 52142, 18363, 462

Combo of two yellow speedups
https://tests.stockfishchess.org/tests/view/6640abf9d163897c63214f5c
LLR: -2.93 (-2.94,2.94) <0.00,2.00>
Total: 355744 W: 91714 L: 91470 D: 172560
Ptnml(0-2): 913, 36233, 103384, 36381, 961

https://tests.stockfishchess.org/tests/view/6628ce073fe04ce4cefc739c
LLR: -2.93 (-2.94,2.94) <0.00,2.00>
Total: 627040 W: 162001 L: 161339 D: 303700
Ptnml(0-2): 2268, 72379, 163532, 73105, 2236

closes https://github.com/official-stockfish/Stockfish/pull/5239

No functional change
2024-05-13 07:32:32 +02:00
Linmiao Xu
0b08953174 Re-evaluate some small net positions for more accurate evals
Use main net evals when small net evals hint that higher eval
accuracy may be worth the slower eval speeds. With Finny caches,
re-evals with the main net are less expensive than before.

Original idea by mstembera who I've added as co-author to this PR.

Based on reEval tests by mstembera:
https://tests.stockfishchess.org/tests/view/65e69187b6345c1b934866e5
https://tests.stockfishchess.org/tests/view/65e863aa0ec64f0526c3e991

A few variants of this patch also passed LTC:
https://tests.stockfishchess.org/tests/view/663d2108507ebe1c0e91f407
https://tests.stockfishchess.org/tests/view/663e388c3a2f9702074bc152

Passed STC:
https://tests.stockfishchess.org/tests/view/663dadbd1a61d6377f190e2c
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 92320 W: 23941 L: 23531 D: 44848
Ptnml(0-2): 430, 10993, 22931, 11349, 457

Passed LTC:
https://tests.stockfishchess.org/tests/view/663ef48b2948bf9aa698690c
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 98934 W: 24907 L: 24457 D: 49570
Ptnml(0-2): 48, 10952, 27027, 11382, 58

closes https://github.com/official-stockfish/Stockfish/pull/5238

bench 1876282

Co-Authored-By: mstembera <5421953+mstembera@users.noreply.github.com>
2024-05-13 07:30:18 +02:00
Linmiao Xu
53f363041c Simplify npm constants when adjusting eval
Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/663d0c4f507ebe1c0e91ec8d
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 162784 W: 41987 L: 41906 D: 78891
Ptnml(0-2): 520, 19338, 41591, 19427, 516

Passed non-regression LTC:
https://tests.stockfishchess.org/tests/view/663d20fd507ebe1c0e91f405
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 457242 W: 115022 L: 115250 D: 226970
Ptnml(0-2): 271, 51566, 125179, 51330, 275

closes https://github.com/official-stockfish/Stockfish/pull/5237

Bench: 2238216
2024-05-13 07:25:22 +02:00
Michael Chaly
d3f081ed8a Adjust standpat return value in qsearch
Instead of returning value itself return value between it and beta for non pv nodes - analogous to what we do after actual search there.

Passed STC:
https://tests.stockfishchess.org/tests/view/663cb1b4c0b75d7f7b98188e
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 131552 W: 34131 L: 33673 D: 63748
Ptnml(0-2): 420, 15446, 33600, 15876, 434

Passed LTC:
https://tests.stockfishchess.org/tests/view/663cda5dc0b75d7f7b981c6f
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 282798 W: 71658 L: 70833 D: 140307
Ptnml(0-2): 112, 31187, 77979, 32006, 115

closes https://github.com/official-stockfish/Stockfish/pull/5233

Bench: 1606672
2024-05-13 07:22:11 +02:00
Muzhen Gaming
813c5aa532 VVLTC search tune
Tuned at 111k games of VVLTC.

Passed VVLTC 1st sprt: https://tests.stockfishchess.org/tests/view/664090c6d163897c63214324
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 83046 W: 21071 L: 20747 D: 41228
Ptnml(0-2): 2, 7574, 26048, 7896, 3

Passed VVLTC 2nd sprt: https://tests.stockfishchess.org/tests/view/6640cb2abaa6260a5688dc17
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 68630 W: 17620 L: 17270 D: 33740
Ptnml(0-2): 4, 6242, 21471, 6596, 2

closes https://github.com/official-stockfish/Stockfish/pull/5240

Bench: 1752471
2024-05-13 07:20:03 +02:00
Shawn Xu
540545d127 simplify away quietCheckEvasions pruning
simplifies away the pruning of quiet evasion moves in quiescent search.

Passed STC:
LLR: 2.98 (-2.94,2.94) <-1.75,0.25>
Total: 343520 W: 88356 L: 88470 D: 166694
Ptnml(0-2): 1061, 40073, 89706, 39759, 1161
https://tests.stockfishchess.org/tests/view/663c7ddfc0b75d7f7b980f3b

Passed LTC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 168744 W: 42454 L: 42384 D: 83906
Ptnml(0-2): 75, 18678, 46782, 18776, 61
https://tests.stockfishchess.org/tests/view/663ce34fc0b75d7f7b981ed9

closes https://github.com/official-stockfish/Stockfish/pull/5231

bench 3681552
2024-05-13 07:16:59 +02:00
xu-shawn
b8812138e8 Fix usage of abs vs std::abs
closes https://github.com/official-stockfish/Stockfish/pull/5229

no functional change
2024-05-13 07:15:25 +02:00
Shawn Xu
c43425b0b1 Simplify Away Negative Extension
This patch simplifies away the negative extension applied when the value returned by the transposition table is assumed to fail low over the value of reduced search.

Passed STC:
LLR: 2.99 (-2.94,2.94) <-1.75,0.25>
Total: 248736 W: 64293 L: 64302 D: 120141
Ptnml(0-2): 925, 29833, 62831, 29884, 895
https://tests.stockfishchess.org/tests/view/663bee3bca93dad645f7f64a

Passed LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 254970 W: 64289 L: 64308 D: 126373
Ptnml(0-2): 110, 28428, 70422, 28421, 104
https://tests.stockfishchess.org/tests/view/663c11f0c0b75d7f7b97d4bb

closes https://github.com/official-stockfish/Stockfish/pull/5226

Bench: 2353057
2024-05-09 09:02:57 +02:00
FauziAkram
574ad14b32 Simplify depth formula based on score improvement
Simplify depth formula based on score improvement.
This idea was first tried by cj5716

Passed STC:
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 347104 W: 89683 L: 89804 D: 167617
Ptnml(0-2): 1357, 38824, 93307, 38711, 1353
https://tests.stockfishchess.org/tests/view/66378edf9819650825aa75d0

Passed LTC:
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 63000 W: 15851 L: 15694 D: 31455
Ptnml(0-2): 22, 5396, 20499, 5569, 14
https://tests.stockfishchess.org/tests/view/663c04e5c0b75d7f7b97d461

closes https://github.com/official-stockfish/Stockfish/pull/5225

Bench: 2691699

Co-Authored-By: cj5716 <125858804+cj5716@users.noreply.github.com>
2024-05-09 09:00:32 +02:00
Michael Chaly
23439e4096 Remove conthist 3 from moves loop pruning
Followup to previous gainer that made it twice less impactful there - this patch removes it entirely as a simplification.

Passed STC:
https://tests.stockfishchess.org/tests/view/6637aa7e9819650825aa93e0
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 26208 W: 6930 L: 6694 D: 12584
Ptnml(0-2): 113, 2997, 6652, 3225, 117

Passed LTC:
https://tests.stockfishchess.org/tests/view/66383cba493aaaf4b7ea90c2
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 67866 W: 17294 L: 17118 D: 33454
Ptnml(0-2): 46, 7627, 18415, 7795, 50

closes https://github.com/official-stockfish/Stockfish/pull/5221

Bench: 2691699
2024-05-09 08:56:36 +02:00
Michael Chaly
3b4ddf4ae6 Simplify away conthist 3 from statscore
Following previous elo gainer that gained by making conthist 3 less important in pruning this patch simplifies away this history from calculation of statscore.

Passed STC:
https://tests.stockfishchess.org/tests/view/6637aa7e9819650825aa93e0
LLR: 3.00 (-2.94,2.94) <-1.75,0.25>
Total: 35392 W: 9352 L: 9120 D: 16920
Ptnml(0-2): 141, 4145, 8888, 4385, 137

Passed LTC:
https://tests.stockfishchess.org/tests/view/66383cd8493aaaf4b7ea90c5
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 33948 W: 8714 L: 8503 D: 16731
Ptnml(0-2): 39, 3701, 9270, 3938, 26

closes https://github.com/official-stockfish/Stockfish/pull/5220

Bench: 2508571
2024-05-09 08:52:06 +02:00
FauziAkram
9d6dab06a8 simplify moveCountPruning
no (significant) speedup upon renewed testing

Passed stc:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 88992 W: 22779 L: 22633 D: 43580
Ptnml(0-2): 137, 8706, 26681, 8818, 154
https://tests.stockfishchess.org/tests/view/6636c4844b68b70d85800dae

closes https://github.com/official-stockfish/Stockfish/pull/5213

No functional change.
2024-05-09 08:48:29 +02:00
MinetaS
2dbb44e28d Fix nodestime
1. The current time management system utilizes limits.inc and
limits.time, which can represent either milliseconds or node count,
depending on whether the nodestime option is active. There have been
several modifications which brought Elo gain for typical uses (i.e.
real-time matches), however some of these changes overlooked such
distinction. This patch adjusts constants and multiplication/division to
more accurately simulate real TC conditions when nodestime is used.

2. The advance_nodes_time function has a bug that can extend the time
limit when availableNodes reaches exact zero. This patch fixes the bug
by initializing the variable to -1 and make sure it does not go below
zero.

3. elapsed_time function is newly introduced to print PV in the UCI
output based on real time. This makes PV output more consistent with the
behavior of trivial use cases.

closes https://github.com/official-stockfish/Stockfish/pull/5186

No functional changes
2024-05-09 08:42:56 +02:00
rn5f107s2
db147fe258 IIR on cutnodes if there is a ttMove but the ttBound is upper
If there is an upper bound stored in the transposition table, but we still have a ttMove, the upperbound indicates that the last time the ttMove was tried, it failed low. This fail low indicates that the ttMove may not be good, so this patch introduces a depth reduction of one for cutnodes with such ttMoves.

Passed STC:
https://tests.stockfishchess.org/tests/view/663be4d1ca93dad645f7f45f
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 139424 W: 35900 L: 35433 D: 68091
Ptnml(0-2): 425, 16357, 35743, 16700, 487

Passed LTC:
https://tests.stockfishchess.org/tests/view/663bec95ca93dad645f7f5c8
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 129690 W: 32902 L: 32390 D: 64398
Ptnml(0-2): 63, 14304, 35610, 14794, 74

closes https://github.com/official-stockfish/Stockfish/pull/5227

bench 2257437
2024-05-09 08:38:04 +02:00
Michael Chaly
d1b8d8bab3 Refactor quiet moves pruning in qsearch
Make it formula more in line with what we use in search - current formula is more or less the one we used years ago for search but since then it was remade, this patch remakes qsearch formula to almost exactly the same as we use in search - with sum of conthist 0, 1 and pawn structure history.

Passed STC:
https://tests.stockfishchess.org/tests/view/6639c8421343f0cb16716206
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 84992 W: 22414 L: 22019 D: 40559
Ptnml(0-2): 358, 9992, 21440, 10309, 397

Passed LTC:
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 119136 W: 30407 L: 29916 D: 58813
Ptnml(0-2): 46, 13192, 32622, 13641, 67

closes https://github.com/official-stockfish/Stockfish/pull/5224

Bench: 2138659
2024-05-09 08:33:07 +02:00
FauziAkram
3bdfa0fb4a Depth dependent statscore based reductions
Test a modification of Fawzi's PR #5223, against that PR.

parameters locally tuned with nevergrad4sf.

passed STC:
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 1047424 W: 271478 L: 269649 D: 506297
Ptnml(0-2): 3851, 124543, 265290, 125982, 4046
https://tests.stockfishchess.org/tests/view/663b0889ca93dad645f7c58c

passed LTC:
LLR: 2.96 (-2.94,2.94) <0.50,2.50>
Total: 796236 W: 201712 L: 199825 D: 394699
Ptnml(0-2): 361, 88381, 218778, 90206, 392
https://tests.stockfishchess.org/tests/view/663be6adca93dad645f7f509

https://github.com/official-stockfish/Stockfish/pull/5228

Bench: 3346224
2024-05-09 08:29:33 +02:00
FauziAkram
2d5e248f58 Tweak reduction formula based on depth
The idea came to me by checking for trends from the megafauzi tunes, since the values of the divisor for this specific formula were as follows:
stc: 15990
mtc: 16117
ltc: 14805
vltc: 12719
new vltc passed by Muzhen: 12076

This shows a clear trend related to time control, the higher it is, the lower the optimum value for the divisor seems to be.
So I tried a simple formula, using educated guesses based on some calculations, tests show it works pretty fine, and it can still be further tuned at VLTC in the future to scale even better.

Passed STC:
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 431360 W: 110791 L: 109898 D: 210671
Ptnml(0-2): 1182, 50846, 110698, 51805, 1149
https://tests.stockfishchess.org/tests/view/663770409819650825aa269f

Passed LTC:
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 114114 W: 29109 L: 28625 D: 56380
Ptnml(0-2): 105, 12628, 31101, 13124, 99
https://tests.stockfishchess.org/tests/view/66378c099819650825aa73f6

https://github.com/official-stockfish/Stockfish/pull/5223

bench: 2273551
2024-05-09 08:26:35 +02:00
Muzhen Gaming
070e564c38 VVLTC search tune
This patch is the result of two tuning stages:
1. ~32k games at 60+0.6 th8:
   https://tests.stockfishchess.org/tests/view/662d9dea6115ff6764c7f817
2. ~193k games at 80+0.8 th6, based on PR #5211:
   https://tests.stockfishchess.org/tests/view/663587e273559a8aa857ca00.
   Based on extensive VVLTC tuning and testing both before and after
   #5211, it is observed that introduction of new extensions positively
   affected the search tune results.

Passed VVLTC 70+0.7 th7 1st sprt: https://tests.stockfishchess.org/tests/view/6636c6f04b68b70d85801409
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 18566 W: 4864 L: 4620 D: 9082
Ptnml(0-2): 0, 1608, 5827, 1844, 4

Passed VVLTC 70+0.7 th7 2nd sprt: https://tests.stockfishchess.org/tests/view/6636d4b84b68b70d85802ab7
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 43142 W: 11141 L: 10838 D: 21163
Ptnml(0-2): 4, 3915, 13427, 4224, 1

Passed VVLTC 70+0.7 3rd sprt: https://tests.stockfishchess.org/tests/view/66376b4f9819650825aa230b
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 40322 W: 10374 L: 10076 D: 19872
Ptnml(0-2): 1, 3660, 12544, 3952, 4

The first two sprts were run against passed #5211. The third sprt was
run against latest master.

closes https://github.com/official-stockfish/Stockfish/pull/5216

Bench: 2180675
2024-05-05 15:11:53 +02:00
cj5716
61f12a4c38 Simplify accumulator refreshes
Passed Non-Regression STC:
https://tests.stockfishchess.org/tests/view/6631f5d5d01fb9ac9bcdc7d0
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 57472 W: 14979 L: 14784 D: 27709
Ptnml(0-2): 185, 6486, 15192, 6695, 178

closes https://github.com/official-stockfish/Stockfish/pull/5207

No functional change
2024-05-05 15:11:37 +02:00
Michael Chaly
f161261245 Adjust history usage in moves loop pruning
After experiments with conthist 5 addition failed really bad divions by 2 passed as a gainer.

Passed STC:
https://tests.stockfishchess.org/tests/view/6636d7114b68b70d858035ce
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 35936 W: 9287 L: 8976 D: 17673
Ptnml(0-2): 81, 4129, 9234, 4446, 78

Passed LTC:
https://tests.stockfishchess.org/tests/view/6636ddb64b68b70d858040a8
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 82428 W: 21035 L: 20622 D: 40771
Ptnml(0-2): 29, 8985, 22775, 9394, 31

closes https://github.com/official-stockfish/Stockfish/pull/5217

Bench: 2309253
2024-05-05 13:06:22 +02:00
cj5716
6da1590de0 Some history fixes and tidy-up
This adds the functions `update_refutations` and `update_quiet_histories` to better distinguish the two. `update_quiet_stats` now just calls both of these functions.

The functional side of this patch is two-fold:
1. Stop refutations being updated when we carry out multicut
2. Update pawn history every time we update other quiet histories

Yellow STC:
LLR: -2.95 (-2.94,2.94) <0.00,2.00>
Total: 238976 W: 61506 L: 61415 D: 116055
Ptnml(0-2): 846, 28628, 60456, 28705, 853
https://tests.stockfishchess.org/tests/view/66321b5ed01fb9ac9bcdca83

However, it passed in <-1.75, 0.25> bounds:
$ python3 sprt.py --wins 61506 --losses 61415 --draws 116055 --elo0 -1.75 --elo1 0.25
ELO: 0.132 +- 0.998 [-0.865, 1.13]
LLR: 4.15 [-1.75, 0.25] (-2.94, 2.94)
H1 Accepted

Passed LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 399126 W: 100730 L: 100896 D: 197500
Ptnml(0-2): 116, 44328, 110843, 44158, 118
https://tests.stockfishchess.org/tests/view/66357b0473559a8aa857ba6f

closes #5215

Bench 2370967
2024-05-05 13:04:37 +02:00
FauziAkram
d712ed38d1 Simplify shuffling and optimism divisors to constants
Shuffling divisor and Optimism divisors passed STC & LTC separately:
shuf STC: https://tests.stockfishchess.org/tests/view/66356316b4e9bdbc7228b995
shuf LTC: https://tests.stockfishchess.org/tests/view/6635815a73559a8aa857c1dc
opt STC: https://tests.stockfishchess.org/tests/view/66356326b4e9bdbc7228b9a0
opt LTC: https://tests.stockfishchess.org/tests/view/663615c673559a8aa8589f8a

And then passed LTC together:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 178278 W: 45039 L: 44979 D: 88260
Ptnml(0-2): 43, 19776, 49460, 19798, 62
https://tests.stockfishchess.org/tests/view/66363f19cdb7cf5da64e22a3

closes https://github.com/official-stockfish/Stockfish/pull/5212

Bench: 2198243
2024-05-05 13:02:42 +02:00
Viren6
741aaf8a38 Introduce Quadruple Extensions
This patch introduces quadruple extensions, with the new condition of not ttPv. It also generalises all margins, so that extensions can still occur if conditions are only partially fulfilled, but with a stricter margin.

Failed STC:
LLR: -2.94 (-2.94,2.94) <0.00,2.00>
Total: 16096 W: 3984 L: 4228 D: 7884
Ptnml(0-2): 72, 2067, 4002, 1847, 60
https://tests.stockfishchess.org/tests/view/66316422d01fb9ac9bcdbdcd

Passed VVLTC 1:
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 96660 W: 24550 L: 24210 D: 47900
Ptnml(0-2): 5, 8776, 30426, 9120, 3
https://tests.stockfishchess.org/tests/view/66361f2c74fa3f41ef2ee091

Passed VVLTC 2:
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 80546 W: 20495 L: 20120 D: 39931
Ptnml(0-2): 6, 7477, 24929, 7858, 3
https://tests.stockfishchess.org/tests/view/66350cf739ba8e443112b3fa

closes https://github.com/official-stockfish/Stockfish/pull/5211

bench 2233743
2024-05-05 12:53:58 +02:00
Michael Chaly
351a2e22dd Add extra bonuses to some moves that forced a fail low
The previous patch on this idea was giving bonuses to this moves if best value of search is far below current static evaluation.
This patch does similar thing but adds extra bonus when best value of search is far below static evaluation before previous move.

Passed STC:
https://tests.stockfishchess.org/tests/view/66355fc819566d64b481d6a4
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 454144 W: 116575 L: 115656 D: 221913
Ptnml(0-2): 1060, 53410, 117215, 54325, 1062

Passed LTC:
https://tests.stockfishchess.org/tests/view/6635c61a73559a8aa858012d
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 136578 W: 34858 L: 34335 D: 67385

closes https://github.com/official-stockfish/Stockfish/pull/5209

Bench: 1614825
2024-05-05 12:42:30 +02:00
cj5716
8ee9905d8b Remove PSQT-only mode
Passed STC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 94208 W: 24270 L: 24112 D: 45826
Ptnml(0-2): 286, 11186, 24009, 11330, 293
https://tests.stockfishchess.org/tests/view/6635ddd773559a8aa8582826

Passed LTC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 114960 W: 29107 L: 28982 D: 56871
Ptnml(0-2): 37, 12683, 31924, 12790, 46
https://tests.stockfishchess.org/tests/view/663604a973559a8aa85881ed

closes #5214

Bench 1653939
2024-05-05 12:36:20 +02:00
Disservin
be026bdcb2 Clear Workers after changing the network
ensures internal state (e.g. accumulator cache) is consistent with network

closes https://github.com/official-stockfish/Stockfish/pull/5204

No functional change
2024-05-05 12:30:28 +02:00
mstembera
be142337d8 Accumulator cache bugfix and cleanup
STC:
https://tests.stockfishchess.org/tests/view/663068913a05f1bf7a511dc2
LLR: 2.98 (-2.94,2.94) <-1.75,0.25>
Total: 70304 W: 18211 L: 18026 D: 34067
Ptnml(0-2): 232, 7966, 18582, 8129, 243

1) Fixes a bug introduced in
   https://github.com/official-stockfish/Stockfish/pull/5194. Only one
   psqtOnly flag was used for two perspectives which was causing
   wrong entries to be cleared and marked.
2) The finny caches should be cleared like histories and not at the
   start of every search.

closes https://github.com/official-stockfish/Stockfish/pull/5203

No functional change
2024-05-01 14:17:32 +02:00
cj5716
6a9b8a0c7b Optimise NNUE Accumulator updates
Passed STC:
https://tests.stockfishchess.org/tests/view/662e3c6a5e9274400985a741
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 86176 W: 22284 L: 21905 D: 41987
Ptnml(0-2): 254, 9572, 23051, 9963, 248

closes https://github.com/official-stockfish/Stockfish/pull/5202

No functional change
2024-05-01 14:10:57 +02:00
Ciekce
eb20de36c0 Avoid unnecessary creation of accumulator cache
Saves a (currently) 800 KB allocation and deallocation when running
`eval`, not particularly significant and zero impact on play but not
necessary either.

closes https://github.com/official-stockfish/Stockfish/pull/5201

No functional change
2024-05-01 14:10:57 +02:00
Dubslow
5d72032559 Use capture history to better judge which sacrifices to explore
This idea has been bouncing around a while. @Vizvezdenec tried it a
couple years ago in Stockfish without results, but its recent arrival in
Ethereal inspired him and thence me to try it afresh in Stockfish.

(Also factor out the now-common code with futpruning for captures.)

STC:
https://tests.stockfishchess.org/tests/view/662355bc3fe04ce4cefc18ac
LLR: 2.92 (-2.94,2.94) <0.00,2.00>
Total: 45760 W: 11970 L: 11640 D: 22150
Ptnml(0-2): 124, 5371, 11625, 5571, 189

LTC:
https://tests.stockfishchess.org/tests/view/662dda396115ff6764c817c9
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 243828 W: 62042 L: 61287 D: 120499
Ptnml(0-2): 211, 27202, 66329, 27965, 207

closes https://github.com/official-stockfish/Stockfish/pull/5200

Bench: 1480008
2024-05-01 14:10:50 +02:00
Stefan Geschwentner
0fe6428645 More reduction at cut nodes which are not a former PV node
But the tt move and first killer are excluded.

This idea is based on following LMR condition tuning
https://tests.stockfishchess.org/tests/view/66228bed3fe04ce4cefc0c71 by
using only the two largest terms P[0] and P[1].

Passed STC:
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 173248 W: 45091 L: 44565 D: 83592
Ptnml(0-2): 693, 20534, 43673, 21002, 722
https://tests.stockfishchess.org/tests/view/6629603b3fe04ce4cefc7d37

Passed LTC:
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 722394 W: 183231 L: 181487 D: 357676
Ptnml(0-2): 462, 80650, 197252, 82348, 485
https://tests.stockfishchess.org/tests/view/662cbe45d46f72253dcff7bf

closes https://github.com/official-stockfish/Stockfish/pull/5199

Bench: 1619613
2024-04-28 21:46:45 +02:00
Stefan Geschwentner
48a3b7c0ee Simplify non-pawn material divisor to a constant
Passed STC:
https://tests.stockfishchess.org/tests/view/662942603fe04ce4cefc7aba
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 272832 W: 70456 L: 70497 D: 131879
Ptnml(0-2): 1020, 32619, 69154, 32628, 995

Passed LTC:
https://tests.stockfishchess.org/tests/view/662dfe3b6115ff6764c829eb
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 100254 W: 25446 L: 25303 D: 49505
Ptnml(0-2): 121, 11292, 27166, 11419, 129

closes https://github.com/official-stockfish/Stockfish/pull/5198

Bench: 1544645
2024-04-28 21:43:46 +02:00
cj5716
834e8ff619 Penalise the TT move in multicut
Passed STC:
LLR: 2.99 (-2.94,2.94) <0.00,2.00>
Total: 185504 W: 48079 L: 47533 D: 89892
Ptnml(0-2): 716, 21866, 46988, 22520, 662
https://tests.stockfishchess.org/tests/view/662d9e1d6115ff6764c7f83d

Passed LTC:
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 75612 W: 19351 L: 18948 D: 37313
Ptnml(0-2): 46, 8363, 20592, 8752, 53
https://tests.stockfishchess.org/tests/view/662dc9dc6115ff6764c80fea

closes https://github.com/official-stockfish/Stockfish/pull/5195

Bench: 1415435
2024-04-28 21:36:34 +02:00
mstembera
a129c0695b Combine remove and add in update_accumulator_refresh_cache()
Combine remove and add in update_accumulator_refresh_cache().
Move remove before add to match other parts of the code.

STC:
https://tests.stockfishchess.org/tests/view/662d96dc6115ff6764c7f4ca
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 364032 W: 94421 L: 93624 D: 175987
Ptnml(0-2): 1261, 41983, 94811, 42620, 1341

closes https://github.com/official-stockfish/Stockfish/pull/5194

Bench: 1836777
2024-04-28 21:35:48 +02:00
mstembera
940a3a7383 Cache small net w/ psqtOnly support
Caching the small net in the same way as the big net allows them to
share the same code path and completely removes
update_accumulator_refresh().

STC:
https://tests.stockfishchess.org/tests/view/662bfb5ed46f72253dcfed85
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 151712 W: 39252 L: 39158 D: 73302
Ptnml(0-2): 565, 17474, 39683, 17570, 564

closes https://github.com/official-stockfish/Stockfish/pull/5194

Bench: 1836777
2024-04-28 21:30:19 +02:00
Joost VandeVondele
bc45cbc820 Output some basic info about the used networks
Adds size in memory as well as layer sizes as in

info string NNUE evaluation using nn-ae6a388e4a1a.nnue (132MiB, (22528, 3072, 15, 32, 1))
info string NNUE evaluation using nn-baff1ede1f90.nnue (6MiB, (22528, 128, 15, 32, 1))

For example, the size in MiB is useful to keep the fishtest memory sizes up-to-date,
the L1-L3 sizes give a useful hint about the architecture used.

closes https://github.com/official-stockfish/Stockfish/pull/5193

No functional change
2024-04-28 21:27:28 +02:00
Disservin
3502c8ae42 Fix missing initialization of AccumulatorCaches in Eval::trace
Add a constructor to `AccumulatorCaches` instead of just calling
`clear(networks)` to prevent similar issues from appearing in the
future.

fixes https://github.com/official-stockfish/Stockfish/issues/5190

closes https://github.com/official-stockfish/Stockfish/pull/5191

No functional change
2024-04-28 21:26:36 +02:00
xoto10
886ed90ec3 Use less time on recaptures
Credit for the idea goes to peregrine on discord.

Passed STC 10+0.1:
https://tests.stockfishchess.org/tests/view/662652623fe04ce4cefc48cf
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 75712 W: 19793 L: 19423 D: 36496
Ptnml(0-2): 258, 8487, 20023, 8803, 285

Passed LTC 60+0.6:
https://tests.stockfishchess.org/tests/view/6627495e3fe04ce4cefc59b6
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 49788 W: 12743 L: 12404 D: 24641
Ptnml(0-2): 29, 5141, 14215, 5480, 29

The code was updated slightly and tested for non-regression against the
original code at STC:

LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 41952 W: 10912 L: 10698 D: 20342
Ptnml(0-2): 133, 4825, 10835, 5061, 122
https://tests.stockfishchess.org/tests/view/662d84f56115ff6764c7e438

closes https://github.com/official-stockfish/Stockfish/pull/5189

Bench: 1836777
2024-04-28 21:26:25 +02:00
gab8192
49ef4c935a Implement accumulator refresh table
For each thread persist an accumulator cache for the network, 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".

When the accumulator needs to be refreshed, instead of filling it with
biases and adding every piece from scratch, we...

1. Take the `AccumulatorRefreshEntry` associated with the new king bucket
2. Calculate the features to activate and deactivate (from differences
   between bitboards in the entry and bitboards of the actual position)
3. Apply the updates on the refresh entry
4. Copy the content of the refresh entry accumulator to the accumulator
   we were refreshing
5. Copy the bitboards from the position to the refresh entry, to match
   the newly updated accumulator

Results at STC:
https://tests.stockfishchess.org/tests/view/662301573fe04ce4cefc1386
(first version)
https://tests.stockfishchess.org/tests/view/6627fa063fe04ce4cefc6560
(final)

Non-Regression between first and final:
https://tests.stockfishchess.org/tests/view/662801e33fe04ce4cefc660a

STC SMP:
https://tests.stockfishchess.org/tests/view/662808133fe04ce4cefc667c

closes https://github.com/official-stockfish/Stockfish/pull/5183

No functional change
2024-04-24 18:38:20 +02:00
FauziAkram
fcba524793 Tune Search Parameters
Parameters Tune, adding also another tunable parameter (npmDiv) to be
variable for different nets (bignet, smallnet, psqtOnly smallnet). P.s:
The changed values are only the parameters where there is agreement
among the different time controls, so in other words, the tunings are
telling us that changing these specific values to this specific
direction is good in all time controls, so there shouldn't be a high
risk of regressing at longer time controls.

Passed STC:
LLR: 2.97 (-2.94,2.94) <0.00,2.00>
Total: 39552 W: 10329 L: 9999 D: 19224
Ptnml(0-2): 156, 4592, 9989, 4844, 195
https://tests.stockfishchess.org/tests/view/661be9a0bd68065432a088c0

Passed LTC:
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 56394 W: 14439 L: 14078 D: 27877
Ptnml(0-2): 30, 6152, 15480, 6497, 38
https://tests.stockfishchess.org/tests/view/661c746296961e72eb565406

closes https://github.com/official-stockfish/Stockfish/pull/5187

Bench: 1836777
2024-04-24 18:24:01 +02:00
Disservin
ddd250b9d6 Restore NPS output for Perft
Previously it was possible to also get the node counter after running a bench with perft, i.e.
`./stockfish bench 1 1 5 current perft`, caused by a small regression from the uci refactoring.

```
Nodes searched: 4865609

===========================
Total time (ms) : 18
Nodes searched  : 4865609
Nodes/second    : 270311611
````

closes https://github.com/official-stockfish/Stockfish/pull/5188

No functional change
2024-04-24 18:20:55 +02:00
cj5716
d47aa639bd Tweak TT aging and replacement strategies
We change the definition of "age" from "age of this position" to "age of this TT entry".
In this way, despite being on the same position, when we save into TT, we always prefer the new entry as compared to the old one.

Passed STC:
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 152256 W: 39597 L: 39110 D: 73549
Ptnml(0-2): 556, 17562, 39398, 18063, 549
https://tests.stockfishchess.org/tests/view/6620faee3fe04ce4cefbf215

Passed LTC:
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 51564 W: 13242 L: 12895 D: 25427
Ptnml(0-2): 24, 5464, 14463, 5803, 28
https://tests.stockfishchess.org/tests/view/66231ab53fe04ce4cefc153e

closes #5184

Bench 1479416
2024-04-21 14:50:04 +02:00
Disservin
56a9cc512e Move ALSR change to CI Workflow file
It makes more sense to not (potentially) change the developers alsr entropy setting to make the test run through. This should be an active choice even if the test then might fail locally for them.

closes https://github.com/official-stockfish/Stockfish/pull/5182

No functional change
2024-04-21 14:49:11 +02:00
Joost VandeVondele
1a8de45b8c Improve CI
the recent refactoring has shown some limitations of our testing, hence we add a couple of more tests including:
* expected mate score
* expected mated score
* expected in TB win score
* expected in TB loss score
* expected info line output
* expected info line output (wdl)

closes https://github.com/official-stockfish/Stockfish/pull/5181

No functional change
2024-04-21 14:46:01 +02:00
Robert Nurnberg @ elitebook
6fc7da44ad update the WDL model
The patch only changes the displayed cp and wdl values.

closes https://github.com/official-stockfish/Stockfish/pull/5178

No functional change
2024-04-21 14:40:02 +02:00
Gahtan Nahdi
d0e72c19fa fix clang compiler warning for avx512 build
Initialize variable in constexpr function to get rid of clang compiler warning for avx512 build.

closes https://github.com/official-stockfish/Stockfish/pull/5176

Non-functional change
2024-04-21 14:38:16 +02:00
Michael Chaly
9021a61807 Trivial cleanup
Make naming and declaration of futilityValue in search consistent between different places.

closes https://github.com/official-stockfish/Stockfish/pull/5165

No functional change.
2024-04-21 14:35:54 +02:00
Disservin
d3fc1d835e Refactor elapsed time checks in search
Small improvement of the elapsed time usage in search, makes the code easier to read overall.
Also Search::Worker::iterative_deepening() now only checks the elapsed time once, instead of 3 times in a row.

Non Regression STC:
https://tests.stockfishchess.org/tests/view/6617005d5a4693796d965c3c
LLR: 2.97 (-2.94,2.94) <-1.75,0.25>
Total: 61024 W: 16002 L: 15806 D: 29216
Ptnml(0-2): 243, 6874, 16102, 7030, 263

closes https://github.com/official-stockfish/Stockfish/pull/5163

No functional change
2024-04-21 14:35:01 +02:00
Disservin
432995ad82 Update outdated comments
closes https://github.com/official-stockfish/Stockfish/pull/5158

No functional change
2024-04-21 14:32:26 +02:00
Disservin
c55ae376f6 Fix wrong sign for 200 TB score
Fix another case of 9032c6cbe7

*    TB values can have a distance of 0, mainly when we are in a tb position but haven't found mate.
*    Add a missing whitespace to UCIEngine::on_update_no_moves()

Closes https://github.com/official-stockfish/Stockfish/pull/5172

No functional change
2024-04-13 22:05:19 +02:00
Disservin
4912f5b0b5 Remove duplicated Position object in UCIEngine
Also fixes searchmoves.

Drop the need of a Position object in uci.cpp.

A side note, it is still required for the static functions,
but these should be moved to a different namespace/class
later on, since sf kinda relies on them.

closes https://github.com/official-stockfish/Stockfish/pull/5169

No functional change
2024-04-12 19:37:39 +02:00
Shahin M. Shahin
14f6eab07d Fix some more UCI output
further fall-out of the refactoring, fixes:

* the position object in UCI is not never getting updated if position token is used
* duplicate string of " wdl "

See also:

https://discord.com/channels/435943710472011776/1032922913499783169/1228227522945351690
https://discord.com/channels/435943710472011776/813919248455827515/1228288106449338398

closes https://github.com/official-stockfish/Stockfish/pull/5168

No functional change

Co-Authored-By: disservin <45608332+disservin@users.noreply.github.com>
2024-04-12 18:11:54 +02:00
Robert Nurnberg @ elitebook
e58b3b4665 Fix wrong mate sign
introduced yesterday by the UCI refactoring 9032c6cbe

fixes #5166
closes https://github.com/official-stockfish/Stockfish/pull/5167

No functional change
2024-04-12 09:30:34 +02:00
FauziAkram
249eec6715 Simplify the depth-dependent part of the best value adjustment formula in main search
Passed STC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 139648 W: 36171 L: 36061 D: 67416
Ptnml(0-2): 545, 16685, 35282, 16739, 573
https://tests.stockfishchess.org/tests/view/660d953b8ff4a059828d625d

Passed LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 222894 W: 56519 L: 56505 D: 109870
Ptnml(0-2): 112, 25145, 60971, 25055, 164
https://tests.stockfishchess.org/tests/view/660fd4afbfeb43334bf7d558

closes https://github.com/official-stockfish/Stockfish/pull/5164

bench: 1479416
2024-04-11 22:47:40 +02:00
gab8192
d6bdcec52c Remove an useless assignment
The assignment (ss + 1)->excludedMove = Move::none() can be simplified away because when that line is reached, (ss + 1)->excludedMove is always already none. The only moment stack[x]->excludedMove is modified, is during singular search, but it is reset to none right after the singular search is finished.

closes https://github.com/official-stockfish/Stockfish/pull/5153

No functional change
2024-04-11 22:43:00 +02:00
Disservin
de2244284b Remove COMPILER from Makefile
The same functionality is available by using COMPCXX and having another variable which does the same is just confusing.
There was only one mention on Stockfish Wiki about this which has been changed to COMPCXX.

closes https://github.com/official-stockfish/Stockfish/pull/5154

No functional change
2024-04-11 22:41:35 +02:00
mstembera
94484db6e8 Avoid permuting inputs during transform()
Avoid permuting inputs during transform() and instead do it once at load time.
Affects AVX2 and newer Intel architectures only.

https://tests.stockfishchess.org/tests/view/661306613eb00c8ccc0033c7
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 108480 W: 28319 L: 27898 D: 52263
Ptnml(0-2): 436, 12259, 28438, 12662, 445

speedups measured such as e.g.

```
Result of 100 runs
==================
base (./stockfish.master       ) =    1241128  +/- 3757
test (./stockfish.patch        ) =    1247713  +/- 3689
diff                             =      +6585  +/- 2583

speedup        = +0.0053
P(speedup > 0) =  1.0000
```

closes https://github.com/official-stockfish/Stockfish/pull/5160

No functional change
2024-04-11 22:38:38 +02:00
Muzhen Gaming
1adf8e1ae6 VVLTC search tune
Parameters were tuned in 3 stages:

* Using an earlier L1-3072 net, and with triple extension margin manually set to 0: https://tests.stockfishchess.org/tests/view/65ffdf5d0ec64f0526c544f2 (~30k games)
* Continue tuning, but with the previous master net (L1-2560). https://tests.stockfishchess.org/tests/view/660663f00ec64f0526c59c41 (~27k games)
* Starting with the parameters from step 2, use the current L1-3072 net, and allow the triple extension margin to be tuned starting from 0: https://tests.stockfishchess.org/tests/view/660c16b8216a13d9498e7536 (40k games)

Passed VVLTC 1st sprt: https://tests.stockfishchess.org/tests/view/66115eacbfeb43334bf7eddd
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 27138 W: 7045 L: 6789 D: 13304
Ptnml(0-2): 1, 2421, 8471, 2673, 3

Passed VVLTC 2nd sprt: https://tests.stockfishchess.org/tests/view/661483623eb00c8ccc0049c1
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 26242 W: 6807 L: 6535 D: 12900
Ptnml(0-2): 0, 2353, 8143, 2625, 0

STC Elo estimate: https://tests.stockfishchess.org/tests/view/66175ca55a4693796d96608c
Elo: -10.53 ± 2.4 (95%) LOS: 0.0%
Total: 21584 W: 5294 L: 5948 D: 10342
Ptnml(0-2): 102, 2937, 5363, 2293, 97
nElo: -19.99 ± 4.7 (95%) PairsRatio: 0.79

closes https://github.com/official-stockfish/Stockfish/pull/5162

Bench: 1381387
2024-04-11 22:23:52 +02:00
Disservin
9032c6cbe7 Transform search output to engine callbacks
Part 2 of the Split UCI into UCIEngine and Engine refactor.
This creates function callbacks for search to use when an update should occur.
The benching in uci.cpp for example does this to extract the total nodes
searched.

No functional change
2024-04-05 21:03:58 +02:00
Disservin
299707d2c2 Split UCI into UCIEngine and Engine
This is another refactor which aims to decouple uci from stockfish. A new engine
class manages all engine related logic and uci is a "small" wrapper around it.

In the future we should also try to remove the need for the Position object in
the uci and replace the options with an actual options struct instead of using a
map. Also convert the std::string's in the Info structs a string_view.

closes #5147

No functional change
2024-04-04 00:15:17 +02:00
Viren6
0716b845fd Update NNUE architecture to SFNNv9 and net nn-ae6a388e4a1a.nnue
Part 1: PyTorch Training, linrock

Trained with a 10-stage sequence from scratch, starting in May 2023:
https://github.com/linrock/nnue-tools/blob/master/exp-sequences/3072-10stage-SFNNv9.yml

While the training methods were similar to the L1-2560 training sequence,
the last two stages introduced min-v2 binpacks,
where bestmove capture and in-check position scores were not zeroed during minimization,
for compatibility with skipping SEE >= 0 positions and future research.

Training data can be found at:
https://robotmoon.com/nnue-training-data

This net was tested at epoch 679 of the 10th training stage:
https://tests.stockfishchess.org/tests/view/65f32e460ec64f0526c48dbc

Part 2: SPSA Training, Viren6

The net was then SPSA tuned.
This consisted of the output weights (32 * 8) and biases (8)
as well as the L3 biases (32 * 8) and L2 biases (16 * 8), totalling 648 params in total.

The SPSA tune can be found here:
https://tests.stockfishchess.org/tests/view/65fc33ba0ec64f0526c512e3

With the help of Disservin , the initial weights were extracted with:
https://github.com/Viren6/Stockfish/tree/new228

The net was saved with the tuned weights using:
https://github.com/Viren6/Stockfish/tree/new241

Earlier nets of the SPSA failed STC compared to the base 3072 net of part 1:
https://tests.stockfishchess.org/tests/view/65ff356e0ec64f0526c53c98
Therefore it is suspected that the SPSA at VVLTC has
added extra scaling on top of the scaling of increasing the L1 size.

Passed VVLTC 1:
https://tests.stockfishchess.org/tests/view/6604a9020ec64f0526c583da
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 53042 W: 13554 L: 13256 D: 26232
Ptnml(0-2): 12, 5147, 15903, 5449, 10

Passed VVLTC 2:
https://tests.stockfishchess.org/tests/view/660ad1b60ec64f0526c5dd23
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 17506 W: 4574 L: 4315 D: 8617
Ptnml(0-2): 1, 1567, 5362, 1818, 5

STC Elo estimate:
https://tests.stockfishchess.org/tests/view/660b834d01aaec5069f87cb0
Elo: -7.66 ± 3.8 (95%) LOS: 0.0%
Total: 9618 W: 2440 L: 2652 D: 4526
Ptnml(0-2): 80, 1281, 2261, 1145, 42
nElo: -13.94 ± 6.9 (95%) PairsRatio: 0.87

closes https://tests.stockfishchess.org/tests/view/660b834d01aaec5069f87cb0

bench 1823302

Co-Authored-By: Linmiao Xu <lin@robotmoon.com>
2024-04-02 08:49:48 +02:00
Joost VandeVondele
c964942da2 Avoid a note related to an ABI change
current master triggers a gcc note:
parameter passing for argument of type 'std::pair<double, double>' when C++17 is enabled changed to match C++14 in GCC 10.1

while this is inconsequential, and just informative  https://gcc.gnu.org/bugzilla/show_bug.cgi?id=111516 we can easily avoid it.

closes https://github.com/official-stockfish/Stockfish/pull/5145

No functional change
2024-03-30 12:38:02 +01:00
Disservin
ec598b380d Improve prerelease creation workflow
In the last couple of months we sometimes saw duplicated prereleases uploaded to GitHub, possibly due to some racy behavior when concurrent jobs create a prerelease. This now creates an empty prerelease at the beginning of the CI and the binaries are later just attached to this one.

closes https://github.com/official-stockfish/Stockfish/pull/5144

No functional change
2024-03-29 13:13:07 +01:00
Joost VandeVondele
68d58d94da Fix usage of abs vs std::abs
close https://github.com/official-stockfish/Stockfish/pull/5143

No functional change
2024-03-29 13:12:20 +01:00
Shawn Xu
e13e4cfb83 Simplify NMP Condition
Remove eval >= ss->staticEval condition for Null Move Pruning.

Passed non-regression STC:
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 44000 W: 11420 L: 11202 D: 21378
Ptnml(0-2): 174, 5243, 10978, 5401, 204
https://tests.stockfishchess.org/tests/live_elo/6603ee490ec64f0526c57984

Passed non-regression LTC:
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 82956 W: 20978 L: 20818 D: 41160
Ptnml(0-2): 54, 9353, 22499, 9523, 49
https://tests.stockfishchess.org/tests/live_elo/660464b50ec64f0526c5804d

closes https://github.com/official-stockfish/Stockfish/pull/5142

Bench 1759189
2024-03-29 10:18:40 +01:00
Michael Chaly
0ef5d05102 Adjust best value after a pruned quiet move
Logic somewhat similar to how we adjust best value after pruned captures
in qsearch, but in search this patch does it after pruned quiet moves
and also to not full scale of futility value but to smth in between
best value and futility value.

Passed STC:
https://tests.stockfishchess.org/tests/view/6601cf900ec64f0526c55c30
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 59936 W: 15722 L: 15369 D: 28845
Ptnml(0-2): 182, 7097, 15112, 7340, 237

Passed LTC:
https://tests.stockfishchess.org/tests/view/66029b2d0ec64f0526c566f1
LLR: 2.96 (-2.94,2.94) <0.50,2.50>
Total: 118362 W: 29953 L: 29460 D: 58949
Ptnml(0-2): 68, 13159, 32249, 13622, 83

closes https://github.com/official-stockfish/Stockfish/pull/5141

bench 1772608
2024-03-29 10:15:17 +01:00
xoto10
e636f73ab8 Vary time use with eval
Adjust time use depending on the current eval.

Passed STC :
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 101696 W: 26651 L: 26238 D: 48807
Ptnml(0-2): 400, 11602, 26459, 11959, 428
https://tests.stockfishchess.org/tests/live_elo/660187a50ec64f0526c557f6

Passed LTC :
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 60648 W: 15550 L: 15187 D: 29911
Ptnml(0-2): 40, 6356, 17171, 6715, 42
https://tests.stockfishchess.org/tests/live_elo/660298ed0ec64f0526c566d0

Values were found using two tunes with the final values taken from the ltc tune after 62k games :
stc - https://tests.stockfishchess.org/tests/view/65fb526b0ec64f0526c50694
ltc - https://tests.stockfishchess.org/tests/view/65fd36e60ec64f0526c5214b

Ideas for future work;

  * tune these values with the other TM adjustments
  * try narrower bands
  * calculate adjustment for exact eval by interpolation

closes https://github.com/official-stockfish/Stockfish/pull/5138

No functional change
2024-03-29 10:09:42 +01:00
Gahtan Nahdi
ed24e3a0a6 Remove material imbalance from nnue eval
Passed non-reg STC:
https://tests.stockfishchess.org/tests/view/65fdf11f0ec64f0526c52b57
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 76480 W: 19893 L: 19712 D: 36875
Ptnml(0-2): 339, 9107, 19157, 9308, 329

Passed non-reg LTC:
https://tests.stockfishchess.org/tests/view/65fee22e0ec64f0526c53885
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 150948 W: 38078 L: 37988 D: 74882
Ptnml(0-2): 111, 16997, 41148, 17127, 91

closes https://github.com/official-stockfish/Stockfish/pull/5135

Bench: 2103324
2024-03-26 18:17:00 +01:00
FauziAkram
d49b3738bc Tweak the stats bonus and malus
For depth 1 we don't have a negative score anymore.

Passed STC:
https://tests.stockfishchess.org/tests/view/65fb055c0ec64f0526c5024f
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 117120 W: 30468 L: 30023 D: 56629
Ptnml(0-2): 526, 13759, 29539, 14216, 520

Passed LTC:
https://tests.stockfishchess.org/tests/view/65fdca4b0ec64f0526c5293f
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 54816 W: 13955 L: 13595 D: 27266
Ptnml(0-2): 30, 6046, 14897, 6404, 31

closes https://github.com/official-stockfish/Stockfish/pull/5134

Bench: 1876428
2024-03-26 18:17:00 +01:00
Disservin
7998570414 Add functionality to export small net
Usage
```
export_net <filenameBigNet> <filenameSmallNet>
```

closes https://github.com/official-stockfish/Stockfish/pull/5133

No functional change
2024-03-26 18:17:00 +01:00
mstembera
5001d49f42 Update nnue_feature_transformer.h
Unroll update_accumulator_refresh to process two
active indices simultaneously.

The compiler might not unroll effectively because
the number of active indices isn't known at
compile time.

STC https://tests.stockfishchess.org/tests/view/65faa8850ec64f0526c4fca9
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 130464 W: 33882 L: 33431 D: 63151
Ptnml(0-2): 539, 14591, 34501, 15082, 519

closes https://github.com/official-stockfish/Stockfish/pull/5125

No functional change
2024-03-26 18:06:49 +01:00
Muzhen Gaming
d99f89506b VVLTC search tune
This set of parameters was derived from 3 tuning attempts:

    https://tests.stockfishchess.org/tests/view/65d19ab61d8e83c78bfd8436 (80+0.8 x8, ~40k games)
    Then tuned with one of linrock's early L1-3072 nets:
    https://tests.stockfishchess.org/tests/view/65def7b04b19edc854ebdec8 (VVLTC, ~36k games)
    Starting from the result of this tuning, the parameters were then tuned with the current master net:
    https://tests.stockfishchess.org/tests/view/65f11c420ec64f0526c46fc4 (VVLTC, ~45k games)

Additionally, at the start of the third tuning phase, 2 parameters were manually changed:

    Notably, the triple extension margin was decreased from 78 to 22. This idea was given by Vizvezdenec:
    https://tests.stockfishchess.org/tests/view/65f0a2360ec64f0526c46752.
    The PvNode extension margin was also adjusted from 50 to 40.

This tune also differs from previous tuning attempts by tuning the evaluation thresholds for smallnet and psqt-only.
The former was increased through the tuning, and this is hypothesized to scale better at VVLTC,
although there is not much evidence of it.

Passed VVLTC 1st sprt: https://tests.stockfishchess.org/tests/view/65f6761d0ec64f0526c4be88
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 44688 W: 11421 L: 11140 D: 22127
Ptnml(0-2): 1, 4170, 13722, 4449, 2

Passed VVLTC 2nd sprt: https://tests.stockfishchess.org/tests/view/65fa31a30ec64f0526c4f611
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 27450 W: 7057 L: 6778 D: 13615
Ptnml(0-2): 4, 2545, 8346, 2828, 2

STC Elo estimate: https://tests.stockfishchess.org/tests/view/65fd3e540ec64f0526c521ae
Elo: -7.84 ± 1.8 (95%) LOS: 0.0%
Total: 40000 W: 9899 L: 10802 D: 19299
Ptnml(0-2): 203, 5221, 10025, 4378, 173
nElo: -14.91 ± 3.4 (95%) PairsRatio: 0.84

closes https://github.com/official-stockfish/Stockfish/pull/5130

Bench: 1876107
2024-03-22 16:44:06 +01:00
Disservin
7e427639ce Add cmath header to movepick.h
No functional change
2024-03-20 16:36:18 +01:00
Gahtan Nahdi
8e61d70499 Remove reduction increase on repetition
Passed non-reg STC:
https://tests.stockfishchess.org/tests/view/65f89ae30ec64f0526c4e0ff
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 173568 W: 45005 L: 44936 D: 83627
Ptnml(0-2): 684, 19878, 45628, 19873, 721

Passed non-reg LTC:
https://tests.stockfishchess.org/tests/view/65fa0f370ec64f0526c4f42d
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 21138 W: 5432 L: 5216 D: 10490
Ptnml(0-2): 13, 2107, 6112, 2325, 12

closes https://github.com/official-stockfish/Stockfish/pull/5123

Bench: 2109005
2024-03-20 16:29:35 +01:00
Gahtan Nahdi
1a6c22c511 Evaluation adjustment for different eval types
Gives different eval scaling parameters for the three different types
of evaluation (bignet, smallnet, psqtOnly).

Passed STC:
https://tests.stockfishchess.org/tests/view/65f4b0020ec64f0526c4a3bd
LLR: 2.96 (-2.94,2.94) <0.00,2.00>
Total: 168064 W: 43507 L: 42987 D: 81570
Ptnml(0-2): 662, 19871, 42445, 20393, 661

Passed LTC:
https://tests.stockfishchess.org/tests/view/65f6be1a0ec64f0526c4c361
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 162564 W: 41188 L: 40604 D: 80772
Ptnml(0-2): 120, 18112, 44216, 18732, 102

closes https://github.com/official-stockfish/Stockfish/pull/5122

Bench: 2113576
2024-03-20 16:29:35 +01:00
Robert Nurnberg
9b92ada935 Base WDL model on material count and normalize evals dynamically
This PR proposes to change the parameter dependence of Stockfish's
internal WDL model from full move counter to material count. In addition
it ensures that an evaluation of 100 centipawns always corresponds to a
50% win probability at fishtest LTC, whereas for master this holds only
at move number 32. See also
https://github.com/official-stockfish/Stockfish/pull/4920 and the
discussion therein.

The new model was fitted based on about 340M positions extracted from
5.6M fishtest LTC games from the last three weeks, involving SF versions
from e67cc979fd (SF 16.1) to current
master.

The involved commands are for
[WDL_model](https://github.com/official-stockfish/WDL_model) are:
```
./updateWDL.sh --firstrev e67cc979fd
python scoreWDL.py updateWDL.json --plot save --pgnName update_material.png --momType "material" --momTarget 58 --materialMin 10 --modelFitting optimizeProbability
```

The anchor `58` for the material count value was chosen to be as close
as possible to the observed average material count of fishtest LTC games
at move 32 (`43`), while not changing the value of
`NormalizeToPawnValue` compared to the move-based WDL model by more than
1.

The patch only affects the displayed cp and wdl values.

closes https://github.com/official-stockfish/Stockfish/pull/5121

No functional change
2024-03-20 16:29:35 +01:00
Disservin
117e08c264 Fix header name in Makefile
No functional change
2024-03-20 16:29:35 +01:00
Disservin
134e6d7bb4 Consistent use of anonymous namespace
Also change `bindThisThread` to match the current code style for function naming.

closes https://github.com/official-stockfish/Stockfish/pull/5118

No functional change
2024-03-20 16:15:37 +01:00
Michael Chaly
ed60460004 Clamp history bonus to stats range
Before, one always had to keep track of the bonus one assigns to a history to stop
the stats from overflowing. This is a quality of life improvement. Since this would often go unnoticed during benching.

Passed non-regression bounds:
https://tests.stockfishchess.org/tests/view/65ef2af40ec64f0526c44cbc
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 179232 W: 46513 L: 46450 D: 86269
Ptnml(0-2): 716, 20323, 47452, 20432, 693

closes https://github.com/official-stockfish/Stockfish/pull/5116

No functional change
2024-03-20 16:14:00 +01:00
Disservin
fb07281f55 Fix false positives from ThreadSanitizer
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

closes https://github.com/official-stockfish/Stockfish/pull/5115

No functional change
2024-03-14 22:14:11 +01:00
cj5716
abd82396a1 Make effort part of RootMove struct
Also includes several small cleanups.

Passed STC:
https://tests.stockfishchess.org/tests/view/65f15cfe0ec64f0526c473a0
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 71136 W: 18456 L: 18273 D: 34407
Ptnml(0-2): 311, 8014, 18708, 8251, 284

closes https://github.com/official-stockfish/Stockfish/pull/5114

No functional change
2024-03-14 22:13:14 +01:00
Lemmy
23493de082 Sudden Death - Improve TM
Due to the 50 estimated move horizon, once a sudden death game got below
1 second, the time allocation for optimumTime would go into the negative
and SF would start instamoving.

To counter this, once limits.time is below 1 second, the move horizon
will start decreasing, at a rate of 1 move per 20ms. This was just what
seemed a reasonable rate of decay.

Fishtest sudden death TC 5+0
https://tests.stockfishchess.org/tests/live_elo/65ee2cdf0ec64f0526c43bbb
LLR: 2.99 (-2.94,2.94) <0.00,2.00>
Total: 3348 W: 1070 L: 727 D:1551
Ptnml(0-2): 46, 277, 738, 514, 99

Fishtest SD TC 10+0
https://tests.stockfishchess.org/tests/live_elo/65ee401e0ec64f0526c43cf7
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 3780 W: 1097 L: 808 D: 1875
Ptnml(0-2): 11, 353, 919, 550, 57

Neutral Non-Regression STC 10+0.1
https://tests.stockfishchess.org/tests/live_elo/65ee45ff0ec64f0526c43d68
LLR: 2.95 (-2.94,2.94) <-1.75, 0.25>
Total: 123616 W: 32054 L: 31927 D:59635
Ptnml(0-2): 493, 14323, 32105, 14338, 549

Neutral Non-Regression LTC 60+0.6
https://tests.stockfishchess.org/tests/live_elo/65ef1eec0ec64f0526c44bc4
LLR: 2.95 (-2.94,2.94) <-1.75, 0.25>
Total: 130482 W: 32961 L: 32855 D:64666
Ptnml(0-2): 88, 13412, 38123, 13542, 76

closes https://github.com/official-stockfish/Stockfish/pull/5112

Bench: 2002517
2024-03-14 22:12:53 +01:00
Michael Chaly
ee2ee6bdc4 Give more bonuses to quiet move that caused a fail low
Give extra bonus if search result is far below static evaluation of
position.

Passed STC:
https://tests.stockfishchess.org/tests/view/65edf1250ec64f0526c43787
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 90816 W: 23713 L: 23307 D: 43796
Ptnml(0-2): 401, 10725, 22742, 11147, 393

Passed LTC:
https://tests.stockfishchess.org/tests/view/65ef5ed70ec64f0526c450af
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 66618 W: 16950 L: 16565 D: 33103
Ptnml(0-2): 35, 7372, 18139, 7699, 64

closes https://github.com/official-stockfish/Stockfish/pull/5111

Bench: 2002517
2024-03-14 22:08:48 +01:00
Disservin
55df0ee009 Fix Raspberry Pi Compilation
Reported by @Torom over discord.

> dev build fails on Raspberry Pi 5 with clang

```
clang++ -o stockfish benchmark.o bitboard.o evaluate.o main.o misc.o movegen.o movepick.o position.o search.o thread.o timeman.o tt.o uci.o ucioption.o tune.o tbprobe.o nnue_misc.o half_ka_v2_hm.o network.o  -fprofile-instr-generate -latomic -lpthread  -Wall -Wcast-qual -fno-exceptions -std=c++17 -fprofile-instr-generate  -pedantic -Wextra -Wshadow -Wmissing-prototypes -Wconditional-uninitialized -DUSE_PTHREADS -DNDEBUG -O3 -funroll-loops -DIS_64BIT -DUSE_POPCNT -DUSE_NEON=8 -march=armv8.2-a+dotprod -DUSE_NEON_DOTPROD -DGIT_SHA=627974c9 -DGIT_DATE=20240312 -DARCH=armv8-dotprod -flto=full
/tmp/lto-llvm-e9300e.o: in function `_GLOBAL__sub_I_network.cpp':
ld-temp.o:(.text.startup+0x704c): relocation truncated to fit: R_AARCH64_LDST64_ABS_LO12_NC against symbol `gEmbeddedNNUEBigEnd' defined in .rodata section in /tmp/lto-llvm-e9300e.o
/usr/bin/ld: ld-temp.o:(.text.startup+0x704c): warning: one possible cause of this error is that the symbol is being referenced in the indicated code as if it had a larger alignment than was declared where it was defined
ld-temp.o:(.text.startup+0x7068): relocation truncated to fit: R_AARCH64_LDST64_ABS_LO12_NC against symbol `gEmbeddedNNUESmallEnd' defined in .rodata section in /tmp/lto-llvm-e9300e.o
/usr/bin/ld: ld-temp.o:(.text.startup+0x7068): warning: one possible cause of this error is that the symbol is being referenced in the indicated code as if it had a larger alignment than was declared where it was defined
clang: error: linker command failed with exit code 1 (use -v to see invocation)
make[2]: *** [Makefile:1051: stockfish] Error 1
make[2]: Leaving directory '/home/torsten/chess/Stockfish_master/src'
make[1]: *** [Makefile:1058: clang-profile-make] Error 2
make[1]: Leaving directory '/home/torsten/chess/Stockfish_master/src'
make: *** [Makefile:886: profile-build] Error 2
```

closes https://github.com/official-stockfish/Stockfish/pull/5106

No functional change
2024-03-12 19:09:50 +01:00
FauziAkram
627974c99f Search + Eval + Movepick Tune
Passed STC:
https://tests.stockfishchess.org/tests/view/65ef15220ec64f0526c44b04
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 24480 W: 6459 L: 6153 D: 11868
Ptnml(0-2): 101, 2798, 6184, 3008, 149

Passed LTC:
https://tests.stockfishchess.org/tests/view/65ef4bac0ec64f0526c44f50
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 53316 W: 13561 L: 13203 D: 26552
Ptnml(0-2): 27, 5925, 14408, 6259, 39

closes https://github.com/official-stockfish/Stockfish/pull/5104

Bench: 1715522
2024-03-12 16:47:11 +01:00
FauziAkram
daa3ef9148 Simplify increaseDepth to boolean expression
Non-functional Simplification, maintaining the same logic as before. Big thanks
to @peregrineshahin for helping with the code.

Passed non-regression bounds:
https://tests.stockfishchess.org/tests/view/65ec93860ec64f0526c42375
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 101088 W: 26196 L: 26047 D: 48845
Ptnml(0-2): 405, 11580, 26473, 11633, 453

closes https://github.com/official-stockfish/Stockfish/pull/5103

No functional change
2024-03-12 16:43:10 +01:00
Disservin
1a26d698de Refactor Network Usage
Continuing from PR #4968, this update improves how Stockfish handles network
usage, making it easier to manage and modify networks in the future.

With the introduction of a dedicated Network class, creating networks has become
straightforward. See uci.cpp:
```cpp
NN::NetworkBig({EvalFileDefaultNameBig, "None", ""}, NN::embeddedNNUEBig)
```

The new `Network` encapsulates all network-related logic, significantly reducing
the complexity previously required to support multiple network types, such as
the distinction between small and big networks #4915.

Non-Regression STC:
https://tests.stockfishchess.org/tests/view/65edd26c0ec64f0526c43584
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 33760 W: 8887 L: 8661 D: 16212
Ptnml(0-2): 143, 3795, 8808, 3961, 173

Non-Regression SMP STC:
https://tests.stockfishchess.org/tests/view/65ed71970ec64f0526c42fdd
LLR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 59088 W: 15121 L: 14931 D: 29036
Ptnml(0-2): 110, 6640, 15829, 6880, 85

Compiled with `make -j profile-build`
```
bash ./bench_parallel.sh ./stockfish ./stockfish-nnue 13 50

sf_base =  1568540 +/-   7637 (95%)
sf_test =  1573129 +/-   7301 (95%)
diff    =     4589 +/-   8720 (95%)
speedup = 0.29260% +/- 0.556% (95%)
```

Compiled with `make -j build`
```
bash ./bench_parallel.sh ./stockfish ./stockfish-nnue 13 50

sf_base =  1472653 +/-   7293 (95%)
sf_test =  1491928 +/-   7661 (95%)
diff    =    19275 +/-   7154 (95%)
speedup = 1.30886% +/- 0.486% (95%)
```

closes https://github.com/official-stockfish/Stockfish/pull/5100

No functional change
2024-03-12 16:41:08 +01:00
Gahtan Nahdi
f072634e24 Simplify opponentWorsening condition
Passed non-reg STC:
https://tests.stockfishchess.org/tests/view/65ea18650ec64f0526c4033a
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 226624 W: 58601 L: 58589 D: 109434
Ptnml(0-2): 1030, 27193, 56819, 27275, 995

Passed non-reg LTC:
https://tests.stockfishchess.org/tests/view/65eb7a220ec64f0526c4161a
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 243882 W: 61462 L: 61469 D: 120951
Ptnml(0-2): 197, 27559, 66419, 27586, 180

closes https://github.com/official-stockfish/Stockfish/pull/5102

Bench: 1601012
2024-03-11 10:08:40 +01:00
Muzhen Gaming
10e2732978 VVLTC search tune
Result of 32k games of tuning at 60+0.6 8-thread. Link to the tuning
attempt:
https://tests.stockfishchess.org/tests/view/65def7b04b19edc854ebdec8

Passed VVLTC first SPRT:
https://tests.stockfishchess.org/tests/view/65e51b53416ecd92c162ab7f
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 37570 W: 9613 L: 9342 D: 18615
Ptnml(0-2): 2, 3454, 11601, 3727, 1

Passed VVLTC second SPRT:
https://tests.stockfishchess.org/tests/view/65e87d1c0ec64f0526c3eb39
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 123158 W: 31463 L: 31006 D: 60689
Ptnml(0-2): 5, 11589, 37935, 12044, 6

Note: The small net and psqt-only thresholds have been moved to
evaluate.h. The reasoning is that these values are used in both
`evaluate.cpp` and `evaluate_nnue.cpp`, and thus unifying their usage
avoids inconsistencies during testing, where one occurrence is changed
without the other (this happened during the search tune SPRT).

closes https://github.com/official-stockfish/Stockfish/pull/5101

Bench: 1741218
2024-03-11 10:04:37 +01:00
Disservin
b6dfd6bd54 Assorted cleanups
- fix naming convention for `workingDirectory`
- use type alias for `EvalFiles` everywhere
- move `ponderMode` into `LimitsType`
- move limits parsing into standalone static function

closes https://github.com/official-stockfish/Stockfish/pull/5098

No functional change
2024-03-11 09:02:13 +01:00
Robert Nurnberg @ elitebook
632f1c21cd Fix wrong constant usage in go mate
Fixes an oversight in https://github.com/official-stockfish/Stockfish/pull/5094

In theory, master could stop search when run with `go mate 247` and return a TB loss (not a mate score). Also fixes the spelling of opponenWorsening.

closes https://github.com/official-stockfish/Stockfish/pull/5096

No functional change
2024-03-07 21:10:33 +01:00
Muzhen Gaming
0f01a516d2 VLTC time management tune
Result of 35k games of SPSA tuning at 180+1.8. Tuning attempt can be
found here:
https://tests.stockfishchess.org/tests/view/65e40599f2ef6c733362b03b

Passed VLTC 180+1.8:
https://tests.stockfishchess.org/tests/view/65e5a6f5416ecd92c162b5d4
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 31950 W: 8225 L: 7949 D: 15776
Ptnml(0-2): 3, 3195, 9309, 3459, 9

Passed VLTC 240+2.4:
https://tests.stockfishchess.org/tests/view/65e714de0ec64f0526c3d1f1
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 65108 W: 16558 L: 16202 D: 32348
Ptnml(0-2): 7, 6366, 19449, 6728, 4

closes https://github.com/official-stockfish/Stockfish/pull/5095

Bench: 1714391
2024-03-07 20:08:00 +01:00
Shahin M. Shahin
748791f80d Fix go mate x in multithreading
Fixes two issues with master for go mate x:

- when running go mate x in losing positions, master always goes to the
  maximal depth, arguably against what the UCI protocol demands

- when running go mate x in winning positions with multiple
  threads, master may return non-mate scores from the search (this issue
  is present in stockfish since at least sf16) The issues are fixed by
  (a) also checking if score is mate -x and by (b) only letting
  mainthread stop the search for go mate x commands, and by not looking
  for a best thread but using mainthread as per the default. Related:
    niklasf/python-chess#1070

More diagnostics can be found here peregrineshahin#6 (comment)

closes https://github.com/official-stockfish/Stockfish/pull/5094

No functional change

Co-Authored-By: Robert Nürnberg <28635489+robertnurnberg@users.noreply.github.com>
2024-03-07 19:58:33 +01:00
Michael Chaly
6136d094c5 Introduce double extensions for PV nodes
Our double/triple extensions were allowed only for non-pv nodes. This
patch allows them to be done for PV nodes, with some stricter
conditions.

Passed STC:
https://tests.stockfishchess.org/tests/view/65d657ec1d8e83c78bfddab8
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 339424 W: 88097 L: 87318 D: 164009
Ptnml(0-2): 1573, 39935, 85729, 41090, 1385

Passed LTC:
https://tests.stockfishchess.org/tests/view/65dd63824b19edc854ebc433
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 459564 W: 115812 L: 114614 D: 229138
Ptnml(0-2): 248, 51441, 125173, 52705, 215

closes https://github.com/official-stockfish/Stockfish/pull/5093

Bench: 1714391
2024-03-07 19:56:30 +01:00
rn5f107s2
1db969e620 Reduce futility_margin if opponents last move was bad
This reduces the futiltiy_margin if our opponents last move was bad by
around ~1/3 when not improving and ~1/2.7 when improving, the idea being
to retroactively futility prune moves that were played, but turned out
to be bad.  A bad move is being defined as their staticEval before their
move being lower as our staticEval now is. If the depth is 2 and we are
improving the opponent worsening flag is not set, in order to not risk
having a too low futility_margin, due to the fact that when these
conditions are met the futility_margin already drops quite low.

Passed STC:
https://tests.stockfishchess.org/tests/live_elo/65e3977bf2ef6c733362aae3
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 122432 W: 31884 L: 31436 D: 59112
Ptnml(0-2): 467, 14404, 31035, 14834, 476

Passed LTC:
https://tests.stockfishchess.org/tests/live_elo/65e47f40f2ef6c733362b6d2
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 421692 W: 106572 L: 105452 D: 209668
Ptnml(0-2): 216, 47217, 114865, 48327, 221

closes https://github.com/official-stockfish/Stockfish/pull/5092

Bench: 1565939
2024-03-07 19:55:51 +01:00
Linmiao Xu
bd579ab5d1 Update default main net to nn-1ceb1ade0001.nnue
Created by retraining the previous main net `nn-b1a57edbea57.nnue` with:
- some of the same options as before:
  - ranger21, more WDL skipping, 15% more loss when Q is too high
- removal of the huge 514G pre-interleaved binpack
- removal of SF-generated dfrc data (dfrc99-16tb7p-filt-v2.min.binpack)
- interleaving many binpacks at training time
- training with some bestmove capture positions where SEE < 0
- increased usage of torch.compile to speed up training by up to 40%

```yaml
experiment-name: 2560--S10-dfrc0-to-dec2023-skip-more-wdl-15p-more-loss-high-q-see-ge0-sk28
nnue-pytorch-branch: linrock/nnue-pytorch/r21-more-wdl-skip-15p-more-loss-high-q-skip-see-ge0-torch-compile-more
start-from-engine-test-net: True

early-fen-skipping: 28
training-dataset:
  # similar, not the exact same as:
  # https://github.com/official-stockfish/Stockfish/pull/4635
  - /data/S5-5af/leela96.v2.min.binpack
  - /data/S5-5af/test60-2021-11-12-novdec-12tb7p.v6-dd.min.binpack
  - /data/S5-5af/test77-2021-12-dec-16tb7p.v6-dd.min.binpack
  - /data/S5-5af/test78-2022-01-to-05-jantomay-16tb7p.v6-dd.min.binpack
  - /data/S5-5af/test78-2022-06-to-09-juntosep-16tb7p.v6-dd.min.binpack
  - /data/S5-5af/test79-2022-04-apr-16tb7p.v6-dd.min.binpack
  - /data/S5-5af/test79-2022-05-may-16tb7p.v6-dd.min.binpack

  - /data/S5-5af/test80-2022-06-jun-16tb7p.v6-dd.min.unmin.binpack
  - /data/S5-5af/test80-2022-07-jul-16tb7p.v6-dd.min.binpack
  - /data/S5-5af/test80-2022-08-aug-16tb7p.v6-dd.min.binpack
  - /data/S5-5af/test80-2022-09-sep-16tb7p.v6-dd.min.unmin.binpack
  - /data/S5-5af/test80-2022-10-oct-16tb7p.v6-dd.min.binpack
  - /data/S5-5af/test80-2022-11-nov-16tb7p.v6-dd.min.binpack

  - /data/S5-5af/test80-2023-01-jan-16tb7p.v6-sk20.min.binpack
  - /data/S5-5af/test80-2023-02-feb-16tb7p.v6-dd.min.binpack
  - /data/S5-5af/test80-2023-03-mar-2tb7p.min.unmin.binpack
  - /data/S5-5af/test80-2023-04-apr-2tb7p.binpack
  - /data/S5-5af/test80-2023-05-may-2tb7p.min.dd.binpack

  # https://github.com/official-stockfish/Stockfish/pull/4782
  - /data/S6-1ee1aba5ed/test80-2023-06-jun-2tb7p.binpack
  - /data/S6-1ee1aba5ed/test80-2023-07-jul-2tb7p.min.binpack

  # https://github.com/official-stockfish/Stockfish/pull/4972
  - /data/S8-baff1edbea57/test80-2023-08-aug-2tb7p.v6.min.binpack
  - /data/S8-baff1edbea57/test80-2023-09-sep-2tb7p.binpack
  - /data/S8-baff1edbea57/test80-2023-10-oct-2tb7p.binpack

  # https://github.com/official-stockfish/Stockfish/pull/5056
  - /data/S9-b1a57edbea57/test80-2023-11-nov-2tb7p.binpack
  - /data/S9-b1a57edbea57/test80-2023-12-dec-2tb7p.binpack

num-epochs: 800
lr: 4.375e-4
gamma: 0.995
start-lambda: 1.0
end-lambda: 0.7
```

This particular net was reached at epoch 759. Use of more torch.compile decorators
in nnue-pytorch model.py than in the previous main net training run sped up training
by up to 40% on Tesla gpus when using recent pytorch compiled with cuda 12:
https://github.com/linrock/nnue-tools/blob/7fb9831/Dockerfile

Skipping positions with bestmove captures where static exchange evaluation is >= 0
is based on the implementation from Sopel's NNUE training & experimentation log:
https://docs.google.com/document/d/1gTlrr02qSNKiXNZ_SuO4-RjK4MXBiFlLE6jvNqqMkAY
Experiment 293 - only skip captures with see>=0

Positions with bestmove captures where score == 0 are always skipped for
compatibility with minimized binpacks, since the original minimizer sets
scores to 0 for slight improvements in compression.

The trainer branch used was:
https://github.com/linrock/nnue-pytorch/tree/r21-more-wdl-skip-15p-more-loss-high-q-skip-see-ge0-torch-compile-more

Binpacks were renamed to be sorted chronologically by default when sorted by name.
The binpack data are otherwise the same as binpacks with similar names in the prior
naming convention.

Training data can be found at:
https://robotmoon.com/nnue-training-data/

Passed STC:
https://tests.stockfishchess.org/tests/view/65e3ddd1f2ef6c733362ae5c
LLR: 2.92 (-2.94,2.94) <0.00,2.00>
Total: 149792 W: 39153 L: 38661 D: 71978
Ptnml(0-2): 675, 17586, 37905, 18032, 698

Passed LTC:
https://tests.stockfishchess.org/tests/view/65e4d91c416ecd92c162a69b
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 64416 W: 16517 L: 16135 D: 31764
Ptnml(0-2): 38, 7218, 17313, 7602, 37

closes https://github.com/official-stockfish/Stockfish/pull/5090

Bench: 1373183
2024-03-07 19:53:48 +01:00
FauziAkram
a96b0d4609 Update elo estimates
Tests used to change the elo worth of some functions:

https://tests.stockfishchess.org/tests/view/65c3f69dc865510db0283eef
https://tests.stockfishchess.org/tests/view/65c3f935c865510db0283f2a
https://tests.stockfishchess.org/tests/view/65d1489f1d8e83c78bfd7dbf
https://tests.stockfishchess.org/tests/view/65ce9d361d8e83c78bfd4951
https://tests.stockfishchess.org/tests/view/65cfcd901d8e83c78bfd6184

closes https://github.com/official-stockfish/Stockfish/pull/5089

No functional change
2024-03-07 19:53:48 +01:00
FauziAkram
a615efb19f Simplify Time Management
Instead of having a formula for using extra time with larger increments.
Simply set it to 1 when the increment is lower than 0.5s and to 1.1 when
the increment is higher.

The values can later on be further improved.

Passed STC:
https://tests.stockfishchess.org/tests/view/65d25d3c1d8e83c78bfd9293
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 27488 W: 7077 L: 6848 D: 13563
Ptnml(0-2): 96, 3041, 7267, 3218, 122

Passed LTC:
https://tests.stockfishchess.org/tests/view/65d2a72c1d8e83c78bfd97fa
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 137568 W: 34612 L: 34512 D: 68444
Ptnml(0-2): 60, 14672, 39221, 14770, 61

Passed VLTC:
https://tests.stockfishchess.org/tests/view/65d7d7d39b2da0226a5a205b
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 139650 W: 35229 L: 35134 D: 69287
Ptnml(0-2): 33, 14227, 41218, 14306, 41

Passed also the TCEC TC style suggested by vondele:
https://tests.stockfishchess.org/tests/view/65e4ca73416ecd92c162a57d
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 134150 W: 34278 L: 34163 D: 65709
Ptnml(0-2): 561, 15727, 34444, 15722, 621

closes https://github.com/official-stockfish/Stockfish/pull/5076

Bench: 1553115
2024-03-07 19:49:01 +01:00
Gahtan Nahdi
b0ac8a4e3b Simplify extension when ttMove is assumed to fail high over current beta
Simplify extension value to -3 when ttMove is assumed to fail high over current beta.

Passed non-reg STC:
https://tests.stockfishchess.org/tests/view/65d66ed81d8e83c78bfddcba
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 235136 W: 60711 L: 60708 D: 113717
Ptnml(0-2): 969, 27904, 59874, 27797, 1024

Passed non-reg LTC:
https://tests.stockfishchess.org/tests/view/65da2994944f2a78d4733107
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 662850 W: 166161 L: 166602 D: 330087
Ptnml(0-2): 394, 74895, 181274, 74482, 380

closes https://github.com/official-stockfish/Stockfish/pull/5088

Bench: 1553115
2024-03-03 15:45:13 +01:00
Gahtan Nahdi
6d0d430860 Simplify IIR
Simplified depth reduction for PV nodes without a ttMove to 3.

Passed STC non-reg:
https://tests.stockfishchess.org/tests/view/65d1a90a1d8e83c78bfd855a
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 363168 W: 93648 L: 93791 D: 175729
Ptnml(0-2): 1557, 43692, 91221, 43565, 1549

Passed LTC non-reg:
https://tests.stockfishchess.org/tests/view/65d5612d1d8e83c78bfdc8e2
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 58818 W: 14946 L: 14761 D: 29111
Ptnml(0-2): 36, 6595, 15962, 6780, 36

closes https://github.com/official-stockfish/Stockfish/pull/5062

Bench: 1505827
2024-03-03 15:42:17 +01:00
mstembera
7831131591 Only evaluate the PSQT part of the small net for large evals.
Thanks to Viren6 for suggesting to set complexity to 0.

STC https://tests.stockfishchess.org/tests/view/65d7d6709b2da0226a5a203f
LLR: 2.92 (-2.94,2.94) <0.00,2.00>
Total: 328384 W: 85316 L: 84554 D: 158514
Ptnml(0-2): 1414, 39076, 82486, 39766, 1450

LTC https://tests.stockfishchess.org/tests/view/65dce6d290f639b028a54d2e
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 165162 W: 41918 L: 41330 D: 81914
Ptnml(0-2): 102, 18332, 45124, 18922, 101

closes https://github.com/official-stockfish/Stockfish/pull/5083

bench: 1504003
2024-03-03 15:29:58 +01:00
Disservin
0a3eb1d8fa Document TT code more
Slight refactor of the TT code with the goal to make it easier to understand / tweak.

Passed Non-Regression STC:
https://tests.stockfishchess.org/tests/view/65d51e401d8e83c78bfdc427
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 56416 W: 14750 L: 14550 D: 27116
Ptnml(0-2): 227, 6386, 14796, 6558, 241

closes https://github.com/official-stockfish/Stockfish/pull/5061

No functional change
2024-03-03 15:21:57 +01:00
Gahtan Nahdi
f77eddfa2f Join conditions for move sorting heuristics
closes https://github.com/official-stockfish/Stockfish/pull/5078

No functional change.
2024-03-03 15:18:13 +01:00
Disservin
0c22d5bb1a Update Actions to Node20
ensure our CI continues to run after Node16 is obsolote on github.

closes https://github.com/official-stockfish/Stockfish/pull/5074

No functional change
2024-03-03 15:09:46 +01:00
Disservin
c83c7f4e71 Make binaries executable again in CI
closes https://github.com/official-stockfish/Stockfish/pull/5072

No functional change
2024-03-03 15:07:32 +01:00
Disservin
abcc090a62 Restore development
closes https://github.com/official-stockfish/Stockfish/pull/5073

No functional change
2024-03-03 15:01:29 +01:00
70 changed files with 6332 additions and 2909 deletions

View File

@@ -7,6 +7,7 @@
{ include: [ "<__fwd/sstream.h>", private, "<iosfwd>", public ] }, { include: [ "<__fwd/sstream.h>", private, "<iosfwd>", public ] },
{ include: [ "<__fwd/streambuf.h>", private, "<iosfwd>", public ] }, { include: [ "<__fwd/streambuf.h>", private, "<iosfwd>", public ] },
{ include: [ "<__fwd/string_view.h>", private, "<string_view>", 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 # Mappings for includes between public headers
{ include: [ "<ios>", public, "<iostream>", public ] }, { include: [ "<ios>", public, "<iostream>", public ] },

View File

@@ -10,7 +10,7 @@ jobs:
name: ${{ matrix.config.name }} ${{ matrix.binaries }} name: ${{ matrix.config.name }} ${{ matrix.binaries }}
runs-on: ${{ matrix.config.os }} runs-on: ${{ matrix.config.os }}
env: env:
COMPILER: ${{ matrix.config.compiler }} COMPCXX: ${{ matrix.config.compiler }}
COMP: ${{ matrix.config.comp }} COMP: ${{ matrix.config.comp }}
EMU: ${{ matrix.config.emu }} EMU: ${{ matrix.config.emu }}
EXT: ${{ matrix.config.ext }} EXT: ${{ matrix.config.ext }}
@@ -26,6 +26,7 @@ jobs:
- uses: actions/checkout@v4 - uses: actions/checkout@v4
with: with:
fetch-depth: 0 fetch-depth: 0
persist-credentials: false
- name: Download required linux packages - name: Download required linux packages
if: runner.os == 'Linux' if: runner.os == 'Linux'
@@ -62,7 +63,7 @@ jobs:
if [ $COMP == ndk ]; then if [ $COMP == ndk ]; then
export PATH=${{ env.ANDROID_NDK_BIN }}:$PATH export PATH=${{ env.ANDROID_NDK_BIN }}:$PATH
fi fi
$COMPILER -v $COMPCXX -v
- name: Test help target - name: Test help target
run: make help run: make help
@@ -91,4 +92,7 @@ jobs:
uses: actions/upload-artifact@v4 uses: actions/upload-artifact@v4
with: with:
name: ${{ matrix.config.simple_name }} ${{ matrix.binaries }} name: ${{ matrix.config.simple_name }} ${{ matrix.binaries }}
path: . path: |
.
!.git
!.output

View File

@@ -11,6 +11,10 @@ on:
paths: paths:
- "**.cpp" - "**.cpp"
- "**.h" - "**.h"
permissions:
pull-requests: write
jobs: jobs:
Clang-Format: Clang-Format:
name: Clang-Format name: Clang-Format
@@ -25,27 +29,29 @@ jobs:
id: clang-format id: clang-format
continue-on-error: true continue-on-error: true
with: with:
clang-format-version: "17" clang-format-version: "18"
exclude-regex: "incbin" exclude-regex: "incbin"
- name: Comment on PR - name: Comment on PR
if: steps.clang-format.outcome == 'failure' if: steps.clang-format.outcome == 'failure'
uses: thollander/actions-comment-pull-request@1d3973dc4b8e1399c0620d3f2b1aa5e795465308 # @v2.4.3 uses: thollander/actions-comment-pull-request@fabd468d3a1a0b97feee5f6b9e499eab0dd903f6 # @v2.5.0
with: with:
message: | message: |
clang-format 17 needs to be run on this PR. clang-format 18 needs to be run on this PR.
If you do not have clang-format installed, the maintainer will run it when merging. 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/mantic/clang-format-17. For the exact version please see https://packages.ubuntu.com/noble/clang-format-18.
_(execution **${{ github.run_id }}** / attempt **${{ github.run_attempt }}**)_ _(execution **${{ github.run_id }}** / attempt **${{ github.run_attempt }}**)_
comment_tag: execution comment_tag: execution
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Comment on PR - name: Comment on PR
if: steps.clang-format.outcome != 'failure' if: steps.clang-format.outcome != 'failure'
uses: thollander/actions-comment-pull-request@1d3973dc4b8e1399c0620d3f2b1aa5e795465308 # @v2.4.3 uses: thollander/actions-comment-pull-request@fabd468d3a1a0b97feee5f6b9e499eab0dd903f6 # @v2.5.0
with: with:
message: | message: |
_(execution **${{ github.run_id }}** / attempt **${{ github.run_attempt }}**)_ _(execution **${{ github.run_id }}** / attempt **${{ github.run_attempt }}**)_
create_if_not_exists: false create_if_not_exists: false
comment_tag: execution comment_tag: execution
mode: delete mode: delete
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

View File

@@ -30,6 +30,8 @@ jobs:
steps: steps:
- name: Checkout repository - name: Checkout repository
uses: actions/checkout@v4 uses: actions/checkout@v4
with:
persist-credentials: false
# Initializes the CodeQL tools for scanning. # Initializes the CodeQL tools for scanning.
- name: Initialize CodeQL - name: Initialize CodeQL

View File

@@ -10,7 +10,7 @@ jobs:
name: ${{ matrix.config.name }} ${{ matrix.binaries }} name: ${{ matrix.config.name }} ${{ matrix.binaries }}
runs-on: ${{ matrix.config.os }} runs-on: ${{ matrix.config.os }}
env: env:
COMPILER: ${{ matrix.config.compiler }} COMPCXX: ${{ matrix.config.compiler }}
COMP: ${{ matrix.config.comp }} COMP: ${{ matrix.config.comp }}
EXT: ${{ matrix.config.ext }} EXT: ${{ matrix.config.ext }}
NAME: ${{ matrix.config.simple_name }} NAME: ${{ matrix.config.simple_name }}
@@ -25,6 +25,8 @@ jobs:
shell: ${{ matrix.config.shell }} shell: ${{ matrix.config.shell }}
steps: steps:
- uses: actions/checkout@v4 - uses: actions/checkout@v4
with:
persist-credentials: false
- name: Install fixed GCC on Linux - name: Install fixed GCC on Linux
if: runner.os == 'Linux' if: runner.os == 'Linux'
@@ -50,7 +52,7 @@ jobs:
run: make net run: make net
- name: Check compiler - name: Check compiler
run: $COMPILER -v run: $COMPCXX -v
- name: Test help target - name: Test help target
run: make help run: make help
@@ -59,7 +61,7 @@ jobs:
run: git --version run: git --version
- name: Check compiler - name: Check compiler
run: $COMPILER -v run: $COMPCXX -v
- name: Show g++ cpu info - name: Show g++ cpu info
if: runner.os != 'macOS' if: runner.os != 'macOS'
@@ -86,4 +88,7 @@ jobs:
uses: actions/upload-artifact@v4 uses: actions/upload-artifact@v4
with: with:
name: ${{ matrix.config.simple_name }} ${{ matrix.binaries }} name: ${{ matrix.config.simple_name }} ${{ matrix.binaries }}
path: . path: |
.
!.git
!.output

43
.github/workflows/games.yml vendored Normal file
View File

@@ -0,0 +1,43 @@
# 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 fast-chess repo
uses: actions/checkout@v4
with:
repository: Disservin/fast-chess
path: fast-chess
ref: d54af1910d5479c669dc731f1f54f9108a251951
persist-credentials: false
- name: fast-chess build
working-directory: fast-chess
run: make -j
- name: Run games
working-directory: fast-chess
run: |
./fast-chess -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

View File

@@ -14,6 +14,7 @@ jobs:
uses: actions/checkout@v4 uses: actions/checkout@v4
with: with:
path: Stockfish path: Stockfish
persist-credentials: false
- name: Checkout include-what-you-use - name: Checkout include-what-you-use
uses: actions/checkout@v4 uses: actions/checkout@v4
@@ -21,6 +22,7 @@ jobs:
repository: include-what-you-use/include-what-you-use repository: include-what-you-use/include-what-you-use
ref: f25caa280dc3277c4086ec345ad279a2463fea0f ref: f25caa280dc3277c4086ec345ad279a2463fea0f
path: include-what-you-use path: include-what-you-use
persist-credentials: false
- name: Download required linux packages - name: Download required linux packages
run: | run: |

54
.github/workflows/matetrack.yml vendored Normal file
View File

@@ -0,0 +1,54 @@
# 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: 814160f82e6428ed2f6522dc06c2a6fa539cd413
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

View File

@@ -6,7 +6,7 @@ jobs:
name: ${{ matrix.sanitizers.name }} name: ${{ matrix.sanitizers.name }}
runs-on: ${{ matrix.config.os }} runs-on: ${{ matrix.config.os }}
env: env:
COMPILER: ${{ matrix.config.compiler }} COMPCXX: ${{ matrix.config.compiler }}
COMP: ${{ matrix.config.comp }} COMP: ${{ matrix.config.comp }}
CXXFLAGS: "-Werror" CXXFLAGS: "-Werror"
strategy: strategy:
@@ -31,12 +31,17 @@ jobs:
- name: Run under valgrind-thread - name: Run under valgrind-thread
make_option: "" make_option: ""
instrumented_option: valgrind-thread instrumented_option: valgrind-thread
- name: Run non-instrumented
make_option: ""
instrumented_option: none
defaults: defaults:
run: run:
working-directory: src working-directory: src
shell: ${{ matrix.config.shell }} shell: ${{ matrix.config.shell }}
steps: steps:
- uses: actions/checkout@v4 - uses: actions/checkout@v4
with:
persist-credentials: false
- name: Download required linux packages - name: Download required linux packages
run: | run: |
@@ -47,7 +52,7 @@ jobs:
run: make net run: make net
- name: Check compiler - name: Check compiler
run: $COMPILER -v run: $COMPCXX -v
- name: Test help target - name: Test help target
run: make help run: make help
@@ -55,6 +60,14 @@ jobs:
- name: Check git - name: Check git
run: git --version 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 # Sanitizers
- name: ${{ matrix.sanitizers.name }} - name: ${{ matrix.sanitizers.name }}

View File

@@ -15,7 +15,13 @@ jobs:
Prerelease: Prerelease:
if: github.repository == 'official-stockfish/Stockfish' && (github.ref == 'refs/heads/master' || (startsWith(github.ref_name, 'sf_') && github.ref_type == 'tag')) if: github.repository == 'official-stockfish/Stockfish' && (github.ref == 'refs/heads/master' || (startsWith(github.ref_name, 'sf_') && github.ref_type == 'tag'))
runs-on: ubuntu-latest runs-on: ubuntu-latest
permissions:
contents: write # For deleting/creating a prerelease
steps: steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
# returns null if no pre-release exists # returns null if no pre-release exists
- name: Get Commit SHA of Latest Pre-release - name: Get Commit SHA of Latest Pre-release
run: | run: |
@@ -23,14 +29,40 @@ jobs:
sudo apt-get update sudo apt-get update
sudo apt-get install -y curl jq sudo apt-get install -y curl jq
echo "COMMIT_SHA=$(jq -r 'map(select(.prerelease)) | first | .tag_name' <<< $(curl -s https://api.github.com/repos/${{ github.repository_owner }}/Stockfish/releases))" >> $GITHUB_ENV echo "COMMIT_SHA_TAG=$(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 # delete old previous pre-release and tag
- uses: actions/checkout@v4 - run: gh release delete ${{ env.COMMIT_SHA_TAG }} --cleanup-tag
- run: gh release delete ${{ env.COMMIT_SHA }} --cleanup-tag if: env.COMMIT_SHA_TAG != 'null'
if: env.COMMIT_SHA != 'null'
env: env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} 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: Matrix:
runs-on: ubuntu-latest runs-on: ubuntu-latest
outputs: outputs:
@@ -38,6 +70,8 @@ jobs:
arm_matrix: ${{ steps.set-arm-matrix.outputs.arm_matrix }} arm_matrix: ${{ steps.set-arm-matrix.outputs.arm_matrix }}
steps: steps:
- uses: actions/checkout@v4 - uses: actions/checkout@v4
with:
persist-credentials: false
- id: set-matrix - id: set-matrix
run: | run: |
TASKS=$(echo $(cat .github/ci/matrix.json) ) TASKS=$(echo $(cat .github/ci/matrix.json) )
@@ -62,15 +96,27 @@ jobs:
uses: ./.github/workflows/sanitizers.yml uses: ./.github/workflows/sanitizers.yml
Tests: Tests:
uses: ./.github/workflows/tests.yml uses: ./.github/workflows/tests.yml
Matetrack:
uses: ./.github/workflows/matetrack.yml
Games:
uses: ./.github/workflows/games.yml
Binaries: Binaries:
if: github.repository == 'official-stockfish/Stockfish' if: github.repository == 'official-stockfish/Stockfish'
needs: [Matrix, Prerelease, Compilation] needs: [Matrix, Prerelease, Compilation]
uses: ./.github/workflows/upload_binaries.yml uses: ./.github/workflows/upload_binaries.yml
with: with:
matrix: ${{ needs.Matrix.outputs.matrix }} matrix: ${{ needs.Matrix.outputs.matrix }}
permissions:
contents: write # For deleting/creating a (pre)release
secrets:
token: ${{ secrets.GITHUB_TOKEN }}
ARM_Binaries: ARM_Binaries:
if: github.repository == 'official-stockfish/Stockfish' if: github.repository == 'official-stockfish/Stockfish'
needs: [Matrix, Prerelease, ARMCompilation] needs: [Matrix, Prerelease, ARMCompilation]
uses: ./.github/workflows/upload_binaries.yml uses: ./.github/workflows/upload_binaries.yml
with: with:
matrix: ${{ needs.Matrix.outputs.arm_matrix }} matrix: ${{ needs.Matrix.outputs.arm_matrix }}
permissions:
contents: write # For deleting/creating a (pre)release
secrets:
token: ${{ secrets.GITHUB_TOKEN }}

View File

@@ -6,7 +6,7 @@ jobs:
name: ${{ matrix.config.name }} name: ${{ matrix.config.name }}
runs-on: ${{ matrix.config.os }} runs-on: ${{ matrix.config.os }}
env: env:
COMPILER: ${{ matrix.config.compiler }} COMPCXX: ${{ matrix.config.compiler }}
COMP: ${{ matrix.config.comp }} COMP: ${{ matrix.config.comp }}
CXXFLAGS: "-Werror" CXXFLAGS: "-Werror"
strategy: strategy:
@@ -106,6 +106,7 @@ jobs:
- uses: actions/checkout@v4 - uses: actions/checkout@v4
with: with:
fetch-depth: 0 fetch-depth: 0
persist-credentials: false
- name: Download required linux packages - name: Download required linux packages
if: runner.os == 'Linux' if: runner.os == 'Linux'
@@ -147,7 +148,7 @@ jobs:
- name: Download required macOS packages - name: Download required macOS packages
if: runner.os == 'macOS' if: runner.os == 'macOS'
run: brew install coreutils run: brew install coreutils gcc@11
- name: Setup msys and install required packages - name: Setup msys and install required packages
if: runner.os == 'Windows' if: runner.os == 'Windows'
@@ -172,9 +173,9 @@ jobs:
if [ $COMP == ndk ]; then if [ $COMP == ndk ]; then
export PATH=${{ env.ANDROID_NDK_BIN }}:$PATH export PATH=${{ env.ANDROID_NDK_BIN }}:$PATH
fi fi
$COMPILER -v $COMPCXX -v
else else
echo "$COMPILER -v" > script.sh echo "$COMPCXX -v" > script.sh
docker run --rm --platform ${{ matrix.config.platform }} -v ${{ github.workspace }}/src:/app sf_builder docker run --rm --platform ${{ matrix.config.platform }} -v ${{ github.workspace }}/src:/app sf_builder
fi fi

View File

@@ -5,13 +5,16 @@ on:
matrix: matrix:
type: string type: string
required: true required: true
secrets:
token:
required: true
jobs: jobs:
Artifacts: Artifacts:
name: ${{ matrix.config.name }} ${{ matrix.binaries }} name: ${{ matrix.config.name }} ${{ matrix.binaries }}
runs-on: ${{ matrix.config.os }} runs-on: ${{ matrix.config.os }}
env: env:
COMPILER: ${{ matrix.config.compiler }} COMPCXX: ${{ matrix.config.compiler }}
COMP: ${{ matrix.config.comp }} COMP: ${{ matrix.config.comp }}
EXT: ${{ matrix.config.ext }} EXT: ${{ matrix.config.ext }}
NAME: ${{ matrix.config.simple_name }} NAME: ${{ matrix.config.simple_name }}
@@ -25,6 +28,8 @@ jobs:
shell: ${{ matrix.config.shell }} shell: ${{ matrix.config.shell }}
steps: steps:
- uses: actions/checkout@v4 - uses: actions/checkout@v4
with:
persist-credentials: false
- name: Download artifact from compilation - name: Download artifact from compilation
uses: actions/download-artifact@v4 uses: actions/download-artifact@v4
@@ -65,6 +70,7 @@ jobs:
- name: Create tar - name: Create tar
if: runner.os != 'Windows' if: runner.os != 'Windows'
run: | run: |
chmod +x ./stockfish/stockfish-$NAME-$BINARY$EXT
tar -cvf stockfish-$NAME-$BINARY.tar stockfish tar -cvf stockfish-$NAME-$BINARY.tar stockfish
- name: Create zip - name: Create zip
@@ -77,6 +83,7 @@ jobs:
uses: softprops/action-gh-release@4634c16e79c963813287e889244c50009e7f0981 uses: softprops/action-gh-release@4634c16e79c963813287e889244c50009e7f0981
with: with:
files: stockfish-${{ matrix.config.simple_name }}-${{ matrix.binaries }}.${{ matrix.config.archive_ext }} files: stockfish-${{ matrix.config.simple_name }}-${{ matrix.binaries }}.${{ matrix.config.archive_ext }}
token: ${{ secrets.token }}
- name: Get last commit sha - name: Get last commit sha
id: last_commit id: last_commit
@@ -97,9 +104,10 @@ jobs:
- name: Prerelease - name: Prerelease
if: github.ref_name == 'master' && env.CHANGES == '0' if: github.ref_name == 'master' && env.CHANGES == '0'
continue-on-error: true continue-on-error: true
uses: softprops/action-gh-release@de2c0eb89ae2a093876385947365aca7b0e5f844 # @v1 uses: softprops/action-gh-release@4634c16e79c963813287e889244c50009e7f0981
with: with:
name: Stockfish dev-${{ env.COMMIT_DATE }}-${{ env.COMMIT_SHA }} name: Stockfish dev-${{ env.COMMIT_DATE }}-${{ env.COMMIT_SHA }}
tag_name: stockfish-dev-${{ env.COMMIT_DATE }}-${{ env.COMMIT_SHA }} tag_name: stockfish-dev-${{ env.COMMIT_DATE }}-${{ env.COMMIT_SHA }}
prerelease: true prerelease: true
files: stockfish-${{ matrix.config.simple_name }}-${{ matrix.binaries }}.${{ matrix.config.archive_ext }} files: stockfish-${{ matrix.config.simple_name }}-${{ matrix.binaries }}.${{ matrix.config.archive_ext }}
token: ${{ secrets.token }}

View File

@@ -20,6 +20,7 @@ Alexander Kure
Alexander Pagel (Lolligerhans) Alexander Pagel (Lolligerhans)
Alfredo Menezes (lonfom169) Alfredo Menezes (lonfom169)
Ali AlZhrani (Cooffe) Ali AlZhrani (Cooffe)
Andreas Jan van der Meulen (Andyson007)
Andreas Matthies (Matthies) Andreas Matthies (Matthies)
Andrei Vetrov (proukornew) Andrei Vetrov (proukornew)
Andrew Grant (AndyGrant) Andrew Grant (AndyGrant)
@@ -46,6 +47,7 @@ Bryan Cross (crossbr)
candirufish candirufish
Chess13234 Chess13234
Chris Cain (ceebo) Chris Cain (ceebo)
Ciekce
clefrks clefrks
Clemens L. (rn5f107s2) Clemens L. (rn5f107s2)
Cody Ho (aesrentai) Cody Ho (aesrentai)
@@ -67,9 +69,11 @@ Douglas Matos Gomes (dsmsgms)
Dubslow Dubslow
Eduardo Cáceres (eduherminio) Eduardo Cáceres (eduherminio)
Eelco de Groot (KingDefender) Eelco de Groot (KingDefender)
Ehsan Rashid (erashid)
Elvin Liu (solarlight2) Elvin Liu (solarlight2)
erbsenzaehler erbsenzaehler
Ernesto Gatti Ernesto Gatti
evqsx
Fabian Beuke (madnight) Fabian Beuke (madnight)
Fabian Fichter (ianfab) Fabian Fichter (ianfab)
Fanael Linithien (Fanael) Fanael Linithien (Fanael)
@@ -126,6 +130,7 @@ Kojirion
Krystian Kuzniarek (kuzkry) Krystian Kuzniarek (kuzkry)
Leonardo Ljubičić (ICCF World Champion) Leonardo Ljubičić (ICCF World Champion)
Leonid Pechenik (lp--) Leonid Pechenik (lp--)
Li Ying (yl25946)
Liam Keegan (lkeegan) Liam Keegan (lkeegan)
Linmiao Xu (linrock) Linmiao Xu (linrock)
Linus Arver (listx) Linus Arver (listx)
@@ -166,6 +171,7 @@ Niklas Fiekas (niklasf)
Nikolay Kostov (NikolayIT) Nikolay Kostov (NikolayIT)
Norman Schmidt (FireFather) Norman Schmidt (FireFather)
notruck notruck
Nour Berakdar (Nonlinear)
Ofek Shochat (OfekShochat, ghostway) Ofek Shochat (OfekShochat, ghostway)
Ondrej Mosnáček (WOnder93) Ondrej Mosnáček (WOnder93)
Ondřej Mišina (AndrovT) Ondřej Mišina (AndrovT)
@@ -204,6 +210,7 @@ sf-x
Shahin M. Shahin (peregrine) Shahin M. Shahin (peregrine)
Shane Booth (shane31) Shane Booth (shane31)
Shawn Varghese (xXH4CKST3RXx) Shawn Varghese (xXH4CKST3RXx)
Shawn Xu (xu-shawn)
Siad Daboul (Topologist) Siad Daboul (Topologist)
Stefan Geschwentner (locutus2) Stefan Geschwentner (locutus2)
Stefano Cardanobile (Stefano80) Stefano Cardanobile (Stefano80)

View File

@@ -59,7 +59,7 @@ discussion._
Changes to Stockfish C++ code should respect our coding style defined by Changes to Stockfish C++ code should respect our coding style defined by
[.clang-format](.clang-format). You can format your changes by running [.clang-format](.clang-format). You can format your changes by running
`make format`. This requires clang-format version 17 to be installed on your system. `make format`. This requires clang-format version 18 to be installed on your system.
## Navigate ## Navigate

View File

@@ -1,106 +1,109 @@
Contributors to Fishtest with >10,000 CPU hours, as of 2024-02-24. Contributors to Fishtest with >10,000 CPU hours, as of 2024-08-31.
Thank you! Thank you!
Username CPU Hours Games played Username CPU Hours Games played
------------------------------------------------------------------ ------------------------------------------------------------------
noobpwnftw 39302472 3055513453 noobpwnftw 40428649 3164740143
technologov 20845762 994893444 technologov 23581394 1076895482
linrock 8616428 560281417 vdv 19425375 718302718
linrock 10034115 643194527
mlang 3026000 200065824 mlang 3026000 200065824
okrout 2332151 222639518 okrout 2572676 237511408
pemo 1800019 60274069 pemo 1836785 62226157
dew 1689162 100033738 dew 1689162 100033738
TueRens 1474943 75121774 TueRens 1648780 77891164
grandphish2 1463002 91616949 sebastronomy 1468328 60859092
JojoM 1109702 72927902 grandphish2 1466110 91776075
olafm 978631 71037944 JojoM 1130625 73666098
sebastronomy 939955 44920556 olafm 1067009 74807270
tvijlbrief 796125 51897690 tvijlbrief 796125 51897690
gvreuls 711320 49142318 oz 781847 53910686
rpngn 768460 49812975
gvreuls 751085 52177668
mibere 703840 46867607 mibere 703840 46867607
oz 646268 46293638 leszek 566598 42024615
rpngn 572571 38928563 cw 519601 34988161
leszek 531858 39316505
cw 518116 34894291
fastgm 503862 30260818 fastgm 503862 30260818
CSU_Dynasty 468784 31385034 CSU_Dynasty 468784 31385034
ctoks 434591 28520597 maximmasiutin 439192 27893522
maximmasiutin 429983 27066286 ctoks 435148 28541909
crunchy 427414 27371625 crunchy 427414 27371625
bcross 415724 29061187 bcross 415724 29061187
robal 371112 24642270
mgrabiak 367963 26464704
velislav 342588 22140902 velislav 342588 22140902
mgrabiak 338763 23999170 ncfish1 329039 20624527
Fisherman 327231 21829379 Fisherman 327231 21829379
robal 299836 20213182
Dantist 296386 18031762 Dantist 296386 18031762
ncfish1 267604 17881149 tolkki963 262050 22049676
Sylvain27 255595 8864404
nordlandia 249322 16420192 nordlandia 249322 16420192
Fifis 237657 13065577
marrco 234581 17714473 marrco 234581 17714473
tolkki963 233490 19773930 Calis007 217537 14450582
glinscott 208125 13277240 glinscott 208125 13277240
drabel 204167 13930674 drabel 204167 13930674
mhoram 202894 12601997 mhoram 202894 12601997
bking_US 198894 11876016 bking_US 198894 11876016
Calis007 188631 12795784
Thanar 179852 12365359 Thanar 179852 12365359
Fifis 176209 10638245 javran 169679 13481966
vdv 175544 9904472 armo9494 162863 10937118
spams 157128 10319326 spams 157128 10319326
DesolatedDodo 156659 10210328 DesolatedDodo 156683 10211206
armo9494 155355 10566898 Wencey 152308 8375444
sqrt2 147963 9724586 sqrt2 147963 9724586
vdbergh 140311 9225125
jcAEie 140086 10603658 jcAEie 140086 10603658
vdbergh 139746 9172061
CoffeeOne 137100 5024116 CoffeeOne 137100 5024116
malala 136182 8002293 malala 136182 8002293
xoto 133759 9159372 xoto 133759 9159372
Dubslow 129614 8519312
davar 129023 8376525 davar 129023 8376525
DMBK 122960 8980062 DMBK 122960 8980062
dsmith 122059 7570238 dsmith 122059 7570238
javran 121564 10144656 CypressChess 120784 8672620
sschnee 120526 7547722
maposora 119734 10749710
amicic 119661 7938029 amicic 119661 7938029
sschnee 118107 7389266 Wolfgang 115713 8159062
Wolfgang 114616 8070494
Data 113305 8220352 Data 113305 8220352
BrunoBanani 112960 7436849 BrunoBanani 112960 7436849
Wencey 111502 5991676 markkulix 112897 9133168
cuistot 108503 7006992 cuistot 109802 7121030
CypressChess 108331 7759788
skiminki 107583 7218170 skiminki 107583 7218170
sterni1971 104431 5938282
MaZePallas 102823 6633619 MaZePallas 102823 6633619
sterni1971 100532 5880772
sunu 100167 7040199 sunu 100167 7040199
zeryl 99331 6221261 zeryl 99331 6221261
thirdlife 99156 2245320 thirdlife 99156 2245320
ElbertoOne 99028 7023771 ElbertoOne 99028 7023771
Dubslow 98600 6903242 megaman7de 98456 6675076
markkulix 97010 7643900 Goatminola 96765 8257832
bigpen0r 94809 6529203 bigpen0r 94825 6529241
brabos 92118 6186135 brabos 92118 6186135
Maxim 90818 3283364 Maxim 90818 3283364
psk 89957 5984901 psk 89957 5984901
megaman7de 88822 6052132
racerschmacer 85805 6122790 racerschmacer 85805 6122790
maposora 85710 7778146
Vizvezdenec 83761 5344740 Vizvezdenec 83761 5344740
0x3C33 82614 5271253 0x3C33 82614 5271253
szupaw 82495 7151686
BRAVONE 81239 5054681 BRAVONE 81239 5054681
nssy 76497 5259388 nssy 76497 5259388
cody 76126 4492126
jromang 76106 5236025 jromang 76106 5236025
MarcusTullius 76103 5061991
woutboat 76072 6022922
Spprtr 75977 5252287
teddybaer 75125 5407666 teddybaer 75125 5407666
Pking_cda 73776 5293873 Pking_cda 73776 5293873
yurikvelo 73516 5036928 yurikvelo 73611 5046822
MarcusTullius 71053 4803477 Mineta 71130 4711422
Bobo1239 70579 4794999 Bobo1239 70579 4794999
solarlight 70517 5028306 solarlight 70517 5028306
dv8silencer 70287 3883992 dv8silencer 70287 3883992
Spprtr 69646 4806763
Mineta 66325 4537742
manap 66273 4121774 manap 66273 4121774
szupaw 65468 5669742
tinker 64333 4268790 tinker 64333 4268790
qurashee 61208 3429862 qurashee 61208 3429862
woutboat 59496 4906352
AGI 58195 4329580 AGI 58195 4329580
robnjr 57262 4053117 robnjr 57262 4053117
Freja 56938 3733019 Freja 56938 3733019
@@ -108,39 +111,45 @@ MaxKlaxxMiner 56879 3423958
ttruscott 56010 3680085 ttruscott 56010 3680085
rkl 55132 4164467 rkl 55132 4164467
jmdana 54697 4012593 jmdana 54697 4012593
notchris 53936 4184018
renouve 53811 3501516 renouve 53811 3501516
notchris 52433 4044590
finfish 51360 3370515 finfish 51360 3370515
eva42 51272 3599691 eva42 51272 3599691
eastorwest 51117 3454811 eastorwest 51117 3454811
Goatminola 51004 4432492
rap 49985 3219146 rap 49985 3219146
pb00067 49733 3298934 pb00067 49733 3298934
GPUex 48686 3684998 GPUex 48686 3684998
OuaisBla 48626 3445134 OuaisBla 48626 3445134
ronaldjerum 47654 3240695 ronaldjerum 47654 3240695
biffhero 46564 3111352 biffhero 46564 3111352
oryx 45533 3539290 oryx 45639 3546530
VoyagerOne 45476 3452465 VoyagerOne 45476 3452465
speedycpu 43842 3003273 speedycpu 43842 3003273
jbwiebe 43305 2805433 jbwiebe 43305 2805433
Antihistamine 41788 2761312 Antihistamine 41788 2761312
mhunt 41735 2691355 mhunt 41735 2691355
jibarbosa 41640 4145702
homyur 39893 2850481 homyur 39893 2850481
gri 39871 2515779 gri 39871 2515779
DeepnessFulled 39020 3323102
Garf 37741 2999686 Garf 37741 2999686
SC 37299 2731694 SC 37299 2731694
Sylvain27 36520 1467082 Gaster319 37118 3279678
naclosagc 36562 1279618
csnodgrass 36207 2688994 csnodgrass 36207 2688994
Gaster319 35655 3149442
strelock 34716 2074055 strelock 34716 2074055
gopeto 33717 2245606
EthanOConnor 33370 2090311 EthanOConnor 33370 2090311
slakovv 32915 2021889 slakovv 32915 2021889
gopeto 31884 2076712 jojo2357 32890 2826662
shawnxu 32019 2802552
Gelma 31771 1551204 Gelma 31771 1551204
vidar808 31560 1351810
kdave 31157 2198362 kdave 31157 2198362
manapbk 30987 1810399 manapbk 30987 1810399
ZacHFX 30551 2238078 ZacHFX 30966 2272416
TataneSan 30713 1513402
votoanthuan 30691 2460856
Prcuvu 30377 2170122 Prcuvu 30377 2170122
anst 30301 2190091 anst 30301 2190091
jkiiski 30136 1904470 jkiiski 30136 1904470
@@ -149,14 +158,15 @@ hyperbolic.tom 29840 2017394
chuckstablers 29659 2093438 chuckstablers 29659 2093438
Pyafue 29650 1902349 Pyafue 29650 1902349
belzedar94 28846 1811530 belzedar94 28846 1811530
votoanthuan 27978 2285818 mecevdimitar 27610 1721382
shawnxu 27438 2465810
chriswk 26902 1868317 chriswk 26902 1868317
xwziegtm 26897 2124586 xwziegtm 26897 2124586
achambord 26582 1767323 achambord 26582 1767323
somethingintheshadows 26496 2186404
Patrick_G 26276 1801617 Patrick_G 26276 1801617
yorkman 26193 1992080 yorkman 26193 1992080
Ulysses 25397 1701264 srowen 25743 1490684
Ulysses 25413 1702830
Jopo12321 25227 1652482 Jopo12321 25227 1652482
SFTUser 25182 1675689 SFTUser 25182 1675689
nabildanial 25068 1531665 nabildanial 25068 1531665
@@ -164,66 +174,69 @@ Sharaf_DG 24765 1786697
rodneyc 24376 1416402 rodneyc 24376 1416402
jsys14 24297 1721230 jsys14 24297 1721230
agg177 23890 1395014 agg177 23890 1395014
srowen 23842 1342508 AndreasKrug 23754 1890115
Ente 23752 1678188 Ente 23752 1678188
jojo2357 23479 2061238
JanErik 23408 1703875 JanErik 23408 1703875
Isidor 23388 1680691 Isidor 23388 1680691
Norabor 23371 1603244 Norabor 23371 1603244
WoodMan777 23253 2023048
Nullvalue 23155 2022752
cisco2015 22920 1763301 cisco2015 22920 1763301
Zirie 22542 1472937 Zirie 22542 1472937
Nullvalue 22490 1970374
AndreasKrug 22485 1769491
team-oh 22272 1636708 team-oh 22272 1636708
Roady 22220 1465606 Roady 22220 1465606
MazeOfGalious 21978 1629593 MazeOfGalious 21978 1629593
sg4032 21947 1643353 sg4032 21950 1643373
tsim67 21747 1330880
ianh2105 21725 1632562 ianh2105 21725 1632562
Skiff84 21711 1014212
xor12 21628 1680365 xor12 21628 1680365
dex 21612 1467203 dex 21612 1467203
nesoneg 21494 1463031 nesoneg 21494 1463031
user213718 21454 1404128 user213718 21454 1404128
Serpensin 21452 1790510
sphinx 21211 1384728 sphinx 21211 1384728
qoo_charly_cai 21135 1514907 qoo_charly_cai 21136 1514927
IslandLambda 21062 1220838
jjoshua2 21001 1423089 jjoshua2 21001 1423089
Zake9298 20938 1565848 Zake9298 20938 1565848
horst.prack 20878 1465656 horst.prack 20878 1465656
fishtester 20729 1348888
0xB00B1ES 20590 1208666 0xB00B1ES 20590 1208666
Serpensin 20487 1729674 ols 20477 1195945
Dinde 20440 1292390 Dinde 20459 1292774
j3corre 20405 941444 j3corre 20405 941444
Adrian.Schmidt123 20316 1281436 Adrian.Schmidt123 20316 1281436
wei 19973 1745989 wei 19973 1745989
fishtester 19617 1257388 teenychess 19819 1762006
rstoesser 19569 1293588 rstoesser 19569 1293588
eudhan 19274 1283717 eudhan 19274 1283717
vulcan 18871 1729392 vulcan 18871 1729392
wizardassassin 18795 1376884
Karpovbot 18766 1053178 Karpovbot 18766 1053178
WoodMan777 18556 1628264
jundery 18445 1115855 jundery 18445 1115855
mkstockfishtester 18350 1690676
ville 17883 1384026 ville 17883 1384026
chris 17698 1487385 chris 17698 1487385
purplefishies 17595 1092533 purplefishies 17595 1092533
dju 17414 981289 dju 17414 981289
ols 17291 1042003
iisiraider 17275 1049015 iisiraider 17275 1049015
Skiff84 17111 950248
DragonLord 17014 1162790 DragonLord 17014 1162790
Karby 17008 1013160
pirt 16965 1271519
redstone59 16842 1461780 redstone59 16842 1461780
Karby 16839 1010124
Alb11747 16787 1213990 Alb11747 16787 1213990
pirt 16493 1237199
Naven94 16414 951718 Naven94 16414 951718
wizardassassin 16392 1148672 scuzzi 16115 994341
IgorLeMasson 16064 1147232 IgorLeMasson 16064 1147232
scuzzi 15757 968735
ako027ako 15671 1173203 ako027ako 15671 1173203
infinigon 15285 965966
Nikolay.IT 15154 1068349 Nikolay.IT 15154 1068349
Andrew Grant 15114 895539 Andrew Grant 15114 895539
OssumOpossum 14857 1007129 OssumOpossum 14857 1007129
LunaticBFF57 14525 1190310 LunaticBFF57 14525 1190310
enedene 14476 905279 enedene 14476 905279
IslandLambda 14393 958196 Hjax 14394 1005013
bpfliegel 14233 882523 bpfliegel 14233 882523
YELNAMRON 14230 1128094 YELNAMRON 14230 1128094
mpx86 14019 759568 mpx86 14019 759568
@@ -233,54 +246,56 @@ Nesa92 13806 1116101
crocogoat 13803 1117422 crocogoat 13803 1117422
joster 13710 946160 joster 13710 946160
mbeier 13650 1044928 mbeier 13650 1044928
Hjax 13535 915487 Pablohn26 13552 1088532
wxt9861 13550 1312306
Dark_wizzie 13422 1007152 Dark_wizzie 13422 1007152
Rudolphous 13244 883140 Rudolphous 13244 883140
Machariel 13010 863104 Machariel 13010 863104
infinigon 12991 943216 nalanzeyu 12996 232590
mabichito 12903 749391 mabichito 12903 749391
Jackfish 12895 868928
thijsk 12886 722107 thijsk 12886 722107
AdrianSA 12860 804972 AdrianSA 12860 804972
Flopzee 12698 894821 Flopzee 12698 894821
whelanh 12682 266404
mschmidt 12644 863193 mschmidt 12644 863193
korposzczur 12606 838168 korposzczur 12606 838168
tsim67 12570 890180
Jackfish 12553 836958
fatmurphy 12547 853210 fatmurphy 12547 853210
Oakwen 12503 853105 Oakwen 12532 855759
icewulf 12447 854878
SapphireBrand 12416 969604 SapphireBrand 12416 969604
deflectooor 12386 579392 deflectooor 12386 579392
modolief 12386 896470 modolief 12386 896470
TataneSan 12358 609332
Farseer 12249 694108 Farseer 12249 694108
Hongildong 12201 648712
pgontarz 12151 848794 pgontarz 12151 848794
dbernier 12103 860824 dbernier 12103 860824
FormazChar 11989 907809 szczur90 12035 942376
FormazChar 12019 910409
rensonthemove 11999 971993
stocky 11954 699440 stocky 11954 699440
somethingintheshadows 11940 989472 MooTheCow 11923 779432
MooTheCow 11892 776126
3cho 11842 1036786 3cho 11842 1036786
whelanh 11557 245188 ckaz 11792 732276
infinity 11470 727027 infinity 11470 727027
aga 11412 695127 aga 11412 695127
torbjo 11395 729145 torbjo 11395 729145
Thomas A. Anderson 11372 732094 Thomas A. Anderson 11372 732094
savage84 11358 670860 savage84 11358 670860
Def9Infinity 11345 696552
d64 11263 789184 d64 11263 789184
ali-al-zhrani 11245 779246 ali-al-zhrani 11245 779246
ckaz 11170 680866 ImperiumAeternum 11155 952000
snicolet 11106 869170 snicolet 11106 869170
dapper 11032 771402 dapper 11032 771402
Ethnikoi 10993 945906 Ethnikoi 10993 945906
Snuuka 10938 435504 Snuuka 10938 435504
Karmatron 10859 678058 Karmatron 10871 678306
basepi 10637 744851 basepi 10637 744851
jibarbosa 10628 857100
Cubox 10621 826448 Cubox 10621 826448
mecevdimitar 10609 787318 gerbil 10519 971688
michaelrpg 10509 739239 michaelrpg 10509 739239
Def9Infinity 10427 686978
OIVAS7572 10420 995586 OIVAS7572 10420 995586
wxt9861 10412 1013864
Garruk 10365 706465 Garruk 10365 706465
dzjp 10343 732529 dzjp 10343 732529
RickGroszkiewicz 10263 990798

View File

@@ -55,15 +55,15 @@ PGOBENCH = $(WINE_PATH) ./$(EXE) bench
SRCS = benchmark.cpp bitboard.cpp evaluate.cpp main.cpp \ SRCS = benchmark.cpp bitboard.cpp evaluate.cpp main.cpp \
misc.cpp movegen.cpp movepick.cpp position.cpp \ misc.cpp movegen.cpp movepick.cpp position.cpp \
search.cpp thread.cpp timeman.cpp tt.cpp uci.cpp ucioption.cpp tune.cpp syzygy/tbprobe.cpp \ search.cpp thread.cpp timeman.cpp tt.cpp uci.cpp ucioption.cpp tune.cpp syzygy/tbprobe.cpp \
nnue/evaluate_nnue.cpp nnue/features/half_ka_v2_hm.cpp nnue/nnue_misc.cpp nnue/features/half_ka_v2_hm.cpp nnue/network.cpp engine.cpp score.cpp memory.cpp
HEADERS = benchmark.h bitboard.h evaluate.h misc.h movegen.h movepick.h \ HEADERS = benchmark.h bitboard.h evaluate.h misc.h movegen.h movepick.h \
nnue/evaluate_nnue.h nnue/features/half_ka_v2_hm.h nnue/layers/affine_transform.h \ nnue/nnue_misc.h nnue/features/half_ka_v2_hm.h nnue/layers/affine_transform.h \
nnue/layers/affine_transform_sparse_input.h nnue/layers/clipped_relu.h nnue/layers/simd.h \ nnue/layers/affine_transform_sparse_input.h nnue/layers/clipped_relu.h nnue/layers/simd.h \
nnue/layers/sqr_clipped_relu.h nnue/nnue_accumulator.h nnue/nnue_architecture.h \ nnue/layers/sqr_clipped_relu.h nnue/nnue_accumulator.h nnue/nnue_architecture.h \
nnue/nnue_common.h nnue/nnue_feature_transformer.h position.h \ nnue/nnue_common.h nnue/nnue_feature_transformer.h position.h \
search.h syzygy/tbprobe.h thread.h thread_win32_osx.h timeman.h \ search.h syzygy/tbprobe.h thread.h thread_win32_osx.h timeman.h \
tt.h tune.h types.h uci.h ucioption.h perft.h tt.h tune.h types.h uci.h ucioption.h perft.h nnue/network.h engine.h score.h numa.h memory.h
OBJS = $(notdir $(SRCS:.cpp=.o)) OBJS = $(notdir $(SRCS:.cpp=.o))
@@ -153,8 +153,8 @@ dotprod = no
arm_version = 0 arm_version = 0
STRIP = strip STRIP = strip
ifneq ($(shell which clang-format-17 2> /dev/null),) ifneq ($(shell which clang-format-18 2> /dev/null),)
CLANG-FORMAT = clang-format-17 CLANG-FORMAT = clang-format-18
else else
CLANG-FORMAT = clang-format CLANG-FORMAT = clang-format
endif endif
@@ -489,8 +489,8 @@ ifeq ($(COMP),clang)
endif endif
ifeq ($(KERNEL),Darwin) ifeq ($(KERNEL),Darwin)
CXXFLAGS += -mmacosx-version-min=10.14 CXXFLAGS += -mmacosx-version-min=10.15
LDFLAGS += -mmacosx-version-min=10.14 LDFLAGS += -mmacosx-version-min=10.15
ifneq ($(arch),any) ifneq ($(arch),any)
CXXFLAGS += -arch $(arch) CXXFLAGS += -arch $(arch)
LDFLAGS += -arch $(arch) LDFLAGS += -arch $(arch)
@@ -546,11 +546,6 @@ else
endif endif
endif endif
### Travis CI script uses COMPILER to overwrite CXX
ifdef COMPILER
COMPCXX=$(COMPILER)
endif
### Allow overwriting CXX from command line ### Allow overwriting CXX from command line
ifdef COMPCXX ifdef COMPCXX
CXX=$(COMPCXX) CXX=$(COMPCXX)
@@ -1056,14 +1051,14 @@ FORCE:
clang-profile-make: clang-profile-make:
$(MAKE) ARCH=$(ARCH) COMP=$(COMP) \ $(MAKE) ARCH=$(ARCH) COMP=$(COMP) \
EXTRACXXFLAGS='-fprofile-instr-generate ' \ EXTRACXXFLAGS='-fprofile-generate ' \
EXTRALDFLAGS=' -fprofile-instr-generate' \ EXTRALDFLAGS=' -fprofile-generate' \
all all
clang-profile-use: clang-profile-use:
$(XCRUN) llvm-profdata merge -output=stockfish.profdata *.profraw $(XCRUN) llvm-profdata merge -output=stockfish.profdata *.profraw
$(MAKE) ARCH=$(ARCH) COMP=$(COMP) \ $(MAKE) ARCH=$(ARCH) COMP=$(COMP) \
EXTRACXXFLAGS='-fprofile-instr-use=stockfish.profdata' \ EXTRACXXFLAGS='-fprofile-use=stockfish.profdata' \
EXTRALDFLAGS='-fprofile-use ' \ EXTRALDFLAGS='-fprofile-use ' \
all all

View File

@@ -23,8 +23,6 @@
#include <iostream> #include <iostream>
#include <vector> #include <vector>
#include "position.h"
namespace { namespace {
// clang-format off // clang-format off
@@ -95,7 +93,7 @@ const std::vector<std::string> Defaults = {
} // namespace } // namespace
namespace Stockfish { namespace Stockfish::Benchmark {
// Builds a list of UCI commands to be run by bench. There // Builds a list of UCI commands to be run by bench. There
// are five parameters: TT size in MB, number of search threads that // are five parameters: TT size in MB, number of search threads that
@@ -108,7 +106,7 @@ namespace Stockfish {
// bench 64 1 100000 default nodes : search default positions for 100K nodes each // 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 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" // bench 16 1 5 blah perft : run a perft 5 on positions in file "blah"
std::vector<std::string> setup_bench(const Position& current, std::istream& is) { std::vector<std::string> setup_bench(const std::string& currentFen, std::istream& is) {
std::vector<std::string> fens, list; std::vector<std::string> fens, list;
std::string go, token; std::string go, token;
@@ -126,7 +124,7 @@ std::vector<std::string> setup_bench(const Position& current, std::istream& is)
fens = Defaults; fens = Defaults;
else if (fenFile == "current") else if (fenFile == "current")
fens.push_back(current.fen()); fens.push_back(currentFen);
else else
{ {

View File

@@ -23,11 +23,9 @@
#include <string> #include <string>
#include <vector> #include <vector>
namespace Stockfish { namespace Stockfish::Benchmark {
class Position; std::vector<std::string> setup_bench(const std::string&, std::istream&);
std::vector<std::string> setup_bench(const Position&, std::istream&);
} // namespace Stockfish } // namespace Stockfish

View File

@@ -124,8 +124,14 @@ Bitboard sliding_attack(PieceType pt, Square sq, Bitboard occupied) {
for (Direction d : (pt == ROOK ? RookDirections : BishopDirections)) for (Direction d : (pt == ROOK ? RookDirections : BishopDirections))
{ {
Square s = sq; Square s = sq;
while (safe_destination(s, d) && !(occupied & s)) while (safe_destination(s, d))
{
attacks |= (s += d); attacks |= (s += d);
if (occupied & s)
{
break;
}
}
} }
return attacks; return attacks;

335
src/engine.cpp Normal file
View File

@@ -0,0 +1,335 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2024 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 <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 "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;
Engine::Engine(std::string path) :
binaryDirectory(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());
capSq = SQ_NONE;
options["Debug Log File"] << Option("", [](const Option& o) {
start_logger(o);
return std::nullopt;
});
options["NumaPolicy"] << Option("auto", [this](const Option& o) {
set_numa_config_from_option(o);
return numa_config_information_as_string() + "\n" + thread_binding_information_as_string();
});
options["Threads"] << Option(1, 1, 1024, [this](const Option&) {
resize_threads();
return thread_binding_information_as_string();
});
options["Hash"] << Option(16, 1, MaxHashMB, [this](const Option& o) {
set_tt_size(o);
return std::nullopt;
});
options["Clear Hash"] << Option([this](const Option&) {
search_clear();
return std::nullopt;
});
options["Ponder"] << Option(false);
options["MultiPV"] << Option(1, 1, MAX_MOVES);
options["Skill Level"] << Option(20, 0, 20);
options["Move Overhead"] << Option(10, 0, 5000);
options["nodestime"] << Option(0, 0, 10000);
options["UCI_Chess960"] << Option(false);
options["UCI_LimitStrength"] << Option(false);
options["UCI_Elo"] << Option(Stockfish::Search::Skill::LowestElo,
Stockfish::Search::Skill::LowestElo,
Stockfish::Search::Skill::HighestElo);
options["UCI_ShowWDL"] << Option(false);
options["SyzygyPath"] << Option("", [](const Option& o) {
Tablebases::init(o);
return std::nullopt;
});
options["SyzygyProbeDepth"] << Option(1, 1, 100);
options["Syzygy50MoveRule"] << Option(true);
options["SyzygyProbeLimit"] << Option(7, 0, 7);
options["EvalFile"] << Option(EvalFileDefaultNameBig, [this](const Option& o) {
load_big_network(o);
return std::nullopt;
});
options["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();
limits.capSq = capSq;
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::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());
capSq = SQ_NONE;
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());
capSq = SQ_NONE;
DirtyPiece& dp = states->back().dirtyPiece;
if (dp.dirty_num > 1 && dp.to[1] == SQ_NONE)
capSq = m.to_sq();
}
}
// 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"]);
networks->small.verify(options["EvalFileSmall"]);
}
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();
}
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;
size_t threadsSize = threads.size();
ss << "Using " << threadsSize << (threadsSize > 1 ? " threads" : " thread");
if (boundThreadsByNode.empty())
return ss.str();
ss << " with NUMA node thread binding: ";
bool isFirst = true;
for (auto&& [current, total] : boundThreadsByNode)
{
if (!isFirst)
ss << ":";
ss << current << "/" << total;
isFirst = false;
}
return ss.str();
}
}

128
src/engine.h Normal file
View File

@@ -0,0 +1,128 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2024 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 {
enum Square : int;
class Engine {
public:
using InfoShort = Search::InfoShort;
using InfoFull = Search::InfoFull;
using InfoIter = Search::InfoIteration;
Engine(std::string path = "");
// 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)>&&);
// 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();
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_binding_information_as_string() const;
private:
const std::string binaryDirectory;
NumaReplicationContext numaContext;
Position pos;
StateListPtr states;
Square capSq;
OptionsMap options;
ThreadPool threads;
TranspositionTable tt;
LazyNumaReplicated<Eval::NNUE::Networks> networks;
Search::SearchManager::UpdateContext updateContext;
};
} // namespace Stockfish
#endif // #ifndef ENGINE_H_INCLUDED

View File

@@ -22,161 +22,21 @@
#include <cassert> #include <cassert>
#include <cmath> #include <cmath>
#include <cstdlib> #include <cstdlib>
#include <fstream>
#include <iomanip> #include <iomanip>
#include <iostream> #include <iostream>
#include <optional> #include <memory>
#include <sstream> #include <sstream>
#include <unordered_map> #include <tuple>
#include <vector>
#include "incbin/incbin.h" #include "nnue/network.h"
#include "misc.h" #include "nnue/nnue_misc.h"
#include "nnue/evaluate_nnue.h"
#include "nnue/nnue_architecture.h"
#include "position.h" #include "position.h"
#include "types.h" #include "types.h"
#include "uci.h" #include "uci.h"
#include "ucioption.h" #include "nnue/nnue_accumulator.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 Stockfish { namespace Stockfish {
namespace Eval {
// Tries to load a NNUE network at startup time, or when the engine
// receives a UCI command "setoption name EvalFile value nn-[a-z0-9]{12}.nnue"
// The name of the NNUE network is always retrieved from the EvalFile option.
// We search the given network in three locations: internally (the default
// network may be embedded in the binary), in the active working directory and
// in the engine directory. Distro packagers may define the DEFAULT_NNUE_DIRECTORY
// variable to have the engine search in a special directory in their distro.
NNUE::EvalFiles NNUE::load_networks(const std::string& rootDirectory,
const OptionsMap& options,
NNUE::EvalFiles evalFiles) {
for (auto& [netSize, evalFile] : evalFiles)
{
std::string user_eval_file = options[evalFile.optionName];
if (user_eval_file.empty())
user_eval_file = evalFile.defaultName;
#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
for (const std::string& directory : dirs)
{
if (evalFile.current != user_eval_file)
{
if (directory != "<internal>")
{
std::ifstream stream(directory + user_eval_file, std::ios::binary);
auto description = NNUE::load_eval(stream, netSize);
if (description.has_value())
{
evalFile.current = user_eval_file;
evalFile.netDescription = description.value();
}
}
if (directory == "<internal>" && user_eval_file == evalFile.defaultName)
{
// 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);
}
};
MemoryBuffer buffer(
const_cast<char*>(reinterpret_cast<const char*>(
netSize == Small ? gEmbeddedNNUESmallData : gEmbeddedNNUEBigData)),
size_t(netSize == Small ? gEmbeddedNNUESmallSize : gEmbeddedNNUEBigSize));
(void) gEmbeddedNNUEBigEnd; // Silence warning on unused variable
(void) gEmbeddedNNUESmallEnd;
std::istream stream(&buffer);
auto description = NNUE::load_eval(stream, netSize);
if (description.has_value())
{
evalFile.current = user_eval_file;
evalFile.netDescription = description.value();
}
}
}
}
}
return evalFiles;
}
// Verifies that the last net used was loaded successfully
void NNUE::verify(const OptionsMap& options,
const std::unordered_map<Eval::NNUE::NetSize, EvalFile>& evalFiles) {
for (const auto& [netSize, evalFile] : evalFiles)
{
std::string user_eval_file = options[evalFile.optionName];
if (user_eval_file.empty())
user_eval_file = evalFile.defaultName;
if (evalFile.current != user_eval_file)
{
std::string msg1 =
"Network evaluation parameters compatible with the engine must be available.";
std::string msg2 =
"The network file " + user_eval_file + " 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.";
sync_cout << "info string ERROR: " << msg1 << sync_endl;
sync_cout << "info string ERROR: " << msg2 << sync_endl;
sync_cout << "info string ERROR: " << msg3 << sync_endl;
sync_cout << "info string ERROR: " << msg4 << sync_endl;
sync_cout << "info string ERROR: " << msg5 << sync_endl;
exit(EXIT_FAILURE);
}
sync_cout << "info string NNUE evaluation using " << user_eval_file << sync_endl;
}
}
}
// Returns a static, purely materialistic evaluation of the position from // Returns a static, purely materialistic evaluation of the position from
// the point of view of the given color. It can be divided by PawnValue to get // the point of view of the given color. It can be divided by PawnValue to get
// an approximation of the material advantage on the board in terms of pawns. // an approximation of the material advantage on the board in terms of pawns.
@@ -185,31 +45,49 @@ int Eval::simple_eval(const Position& pos, Color c) {
+ (pos.non_pawn_material(c) - pos.non_pawn_material(~c)); + (pos.non_pawn_material(c) - pos.non_pawn_material(~c));
} }
bool Eval::use_smallnet(const Position& pos) {
int simpleEval = simple_eval(pos, pos.side_to_move());
return std::abs(simpleEval) > 962;
}
// Evaluate is the evaluator for the outer world. It returns a static evaluation // Evaluate is the evaluator for the outer world. It returns a static evaluation
// of the position from the point of view of the side to move. // of the position from the point of view of the side to move.
Value Eval::evaluate(const Position& pos, int optimism) { Value Eval::evaluate(const Eval::NNUE::Networks& networks,
const Position& pos,
Eval::NNUE::AccumulatorCaches& caches,
int optimism) {
assert(!pos.checkers()); assert(!pos.checkers());
int simpleEval = simple_eval(pos, pos.side_to_move()); bool smallNet = use_smallnet(pos);
bool smallNet = std::abs(simpleEval) > 1050; int v;
int nnueComplexity; auto [psqt, positional] = smallNet ? networks.small.evaluate(pos, &caches.small)
: networks.big.evaluate(pos, &caches.big);
Value nnue = smallNet ? NNUE::evaluate<NNUE::Small>(pos, true, &nnueComplexity) Value nnue = (125 * psqt + 131 * positional) / 128;
: NNUE::evaluate<NNUE::Big>(pos, true, &nnueComplexity);
// Blend optimism and eval with nnue complexity and material imbalance // Re-evaluate the position when higher eval accuracy is worth the time spent
optimism += optimism * (nnueComplexity + std::abs(simpleEval - nnue)) / 512; if (smallNet && (nnue * psqt < 0 || std::abs(nnue) < 227))
nnue -= nnue * (nnueComplexity + std::abs(simpleEval - nnue)) / 32768; {
std::tie(psqt, positional) = networks.big.evaluate(pos, &caches.big);
nnue = (125 * psqt + 131 * positional) / 128;
smallNet = false;
}
int npm = pos.non_pawn_material() / 64; // Blend optimism and eval with nnue complexity
int v = (nnue * (915 + npm + 9 * pos.count<PAWN>()) + optimism * (154 + npm)) / 1024; int nnueComplexity = std::abs(psqt - positional);
optimism += optimism * nnueComplexity / (smallNet ? 433 : 453);
nnue -= nnue * nnueComplexity / (smallNet ? 18815 : 17864);
int material = (smallNet ? 553 : 532) * pos.count<PAWN>() + pos.non_pawn_material();
v = (nnue * (73921 + material) + optimism * (8112 + material)) / (smallNet ? 68104 : 74715);
// Evaluation grain (to get more alpha-beta cuts) with randomization (for robustness)
v = (v / 16) * 16 - 1 + (pos.key() & 0x2);
// Damp down the evaluation linearly when shuffling // Damp down the evaluation linearly when shuffling
int shuffling = pos.rule50_count(); v -= v * pos.rule50_count() / 212;
v = v * (200 - shuffling) / 214;
// Guarantee evaluation does not hit the tablebase range // Guarantee evaluation does not hit the tablebase range
v = std::clamp(v, VALUE_TB_LOSS_IN_MAX_PLY + 1, VALUE_TB_WIN_IN_MAX_PLY - 1); v = std::clamp(v, VALUE_TB_LOSS_IN_MAX_PLY + 1, VALUE_TB_WIN_IN_MAX_PLY - 1);
@@ -221,25 +99,27 @@ Value Eval::evaluate(const Position& pos, int optimism) {
// a string (suitable for outputting to stdout) that contains the detailed // a string (suitable for outputting to stdout) that contains the detailed
// descriptions and values of each evaluation term. Useful for debugging. // descriptions and values of each evaluation term. Useful for debugging.
// Trace scores are from white's point of view // Trace scores are from white's point of view
std::string Eval::trace(Position& pos) { std::string Eval::trace(Position& pos, const Eval::NNUE::Networks& networks) {
if (pos.checkers()) if (pos.checkers())
return "Final evaluation: none (in check)"; return "Final evaluation: none (in check)";
auto caches = std::make_unique<Eval::NNUE::AccumulatorCaches>(networks);
std::stringstream ss; std::stringstream ss;
ss << std::showpoint << std::noshowpos << std::fixed << std::setprecision(2); ss << std::showpoint << std::noshowpos << std::fixed << std::setprecision(2);
ss << '\n' << NNUE::trace(pos) << '\n'; ss << '\n' << NNUE::trace(pos, networks, *caches) << '\n';
ss << std::showpoint << std::showpos << std::fixed << std::setprecision(2) << std::setw(15); ss << std::showpoint << std::showpos << std::fixed << std::setprecision(2) << std::setw(15);
Value v; auto [psqt, positional] = networks.big.evaluate(pos, &caches->big);
v = NNUE::evaluate<NNUE::Big>(pos, false); Value v = psqt + positional;
v = pos.side_to_move() == WHITE ? v : -v; v = pos.side_to_move() == WHITE ? v : -v;
ss << "NNUE evaluation " << 0.01 * UCI::to_cp(v) << " (white side)\n"; ss << "NNUE evaluation " << 0.01 * UCIEngine::to_cp(v, pos) << " (white side)\n";
v = evaluate(pos, VALUE_ZERO); v = evaluate(networks, pos, *caches, VALUE_ZERO);
v = pos.side_to_move() == WHITE ? v : -v; v = pos.side_to_move() == WHITE ? v : -v;
ss << "Final evaluation " << 0.01 * UCI::to_cp(v) << " (white side)"; ss << "Final evaluation " << 0.01 * UCIEngine::to_cp(v, pos) << " (white side)";
ss << " [with scaled NNUE, ...]"; ss << " [with scaled NNUE, ...]";
ss << "\n"; ss << "\n";

View File

@@ -20,50 +20,35 @@
#define EVALUATE_H_INCLUDED #define EVALUATE_H_INCLUDED
#include <string> #include <string>
#include <unordered_map>
#include "types.h" #include "types.h"
namespace Stockfish { namespace Stockfish {
class Position; class Position;
class OptionsMap;
namespace Eval { namespace Eval {
std::string trace(Position& pos);
int simple_eval(const Position& pos, Color c);
Value evaluate(const Position& pos, int optimism);
// The default net name MUST follow the format nn-[SHA256 first 12 digits].nnue // 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 // for the build process (profile-build and fishtest) to work. Do not change the
// name of the macro, as it is used in the Makefile. // name of the macro or the location where this macro is defined, as it is used
#define EvalFileDefaultNameBig "nn-b1a57edbea57.nnue" // in the Makefile/Fishtest.
#define EvalFileDefaultNameSmall "nn-baff1ede1f90.nnue" #define EvalFileDefaultNameBig "nn-1111cefa1111.nnue"
#define EvalFileDefaultNameSmall "nn-37f18f62d772.nnue"
struct EvalFile {
// UCI option name
std::string optionName;
// Default net name, will use one of the macros above
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;
};
namespace NNUE { namespace NNUE {
struct Networks;
struct AccumulatorCaches;
}
enum NetSize : int; std::string trace(Position& pos, const Eval::NNUE::Networks& networks);
using EvalFiles = std::unordered_map<Eval::NNUE::NetSize, EvalFile>;
EvalFiles load_networks(const std::string&, const OptionsMap&, EvalFiles);
void verify(const OptionsMap&, const EvalFiles&);
} // namespace NNUE
int simple_eval(const Position& pos, Color c);
bool use_smallnet(const Position& pos);
Value evaluate(const NNUE::Networks& networks,
const Position& pos,
Eval::NNUE::AccumulatorCaches& caches,
int optimism);
} // namespace Eval } // namespace Eval
} // namespace Stockfish } // namespace Stockfish

View File

@@ -17,15 +17,13 @@
*/ */
#include <iostream> #include <iostream>
#include <unordered_map>
#include "bitboard.h" #include "bitboard.h"
#include "evaluate.h"
#include "misc.h" #include "misc.h"
#include "position.h" #include "position.h"
#include "tune.h"
#include "types.h" #include "types.h"
#include "uci.h" #include "uci.h"
#include "tune.h"
using namespace Stockfish; using namespace Stockfish;
@@ -36,11 +34,9 @@ int main(int argc, char* argv[]) {
Bitboards::init(); Bitboards::init();
Position::init(); Position::init();
UCI uci(argc, argv); UCIEngine uci(argc, argv);
Tune::init(uci.options); Tune::init(uci.engine_options());
uci.evalFiles = Eval::NNUE::load_networks(uci.workingDirectory(), uci.options, uci.evalFiles);
uci.loop(); uci.loop();

237
src/memory.cpp Normal file
View File

@@ -0,0 +1,237 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2024 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
// 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

216
src/memory.h Normal file
View File

@@ -0,0 +1,216 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2024 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);
// 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);
return;
}
// 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

@@ -18,64 +18,27 @@
#include "misc.h" #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" {
using fun1_t = bool (*)(LOGICAL_PROCESSOR_RELATIONSHIP,
PSYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX,
PDWORD);
using fun2_t = bool (*)(USHORT, PGROUP_AFFINITY);
using fun3_t = bool (*)(HANDLE, CONST GROUP_AFFINITY*, PGROUP_AFFINITY);
using fun4_t = bool (*)(USHORT, PGROUP_AFFINITY, USHORT, PUSHORT);
using fun5_t = WORD (*)();
using fun6_t = bool (*)(HANDLE, DWORD, PHANDLE);
using fun7_t = bool (*)(LPCSTR, LPCSTR, PLUID);
using fun8_t = bool (*)(HANDLE, BOOL, PTOKEN_PRIVILEGES, DWORD, PTOKEN_PRIVILEGES, PDWORD);
}
#endif
#include <atomic> #include <atomic>
#include <cctype>
#include <cmath> #include <cmath>
#include <cstdlib> #include <cstdlib>
#include <fstream> #include <fstream>
#include <iomanip> #include <iomanip>
#include <iostream> #include <iostream>
#include <iterator>
#include <limits>
#include <mutex> #include <mutex>
#include <sstream> #include <sstream>
#include <string_view> #include <string_view>
#include "types.h" #include "types.h"
#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
namespace Stockfish { namespace Stockfish {
namespace { namespace {
// Version number or dev. // Version number or dev.
constexpr std::string_view version = "16.1"; constexpr std::string_view version = "17";
// Our fancy logging facility. The trick here is to replace cin.rdbuf() and // 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 // cout.rdbuf() with two Tie objects that tie cin and cout to a file stream. We
@@ -149,14 +112,16 @@ class Logger {
// Returns the full name of the current Stockfish version. // 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: // For local dev compiles we try to append the commit SHA and
// Stockfish dev-YYYYMMDD-SHA // commit date from git. If that fails only the local compilation
// or // date is set and "nogit" is specified:
// Stockfish dev-YYYYMMDD-nogit // Stockfish dev-YYYYMMDD-SHA
// or
// Stockfish dev-YYYYMMDD-nogit
// //
// For releases (non-dev builds) we only include the version number: // For releases (non-dev builds) we only include the version number:
// Stockfish version // Stockfish version
std::string engine_info(bool to_uci) { std::string engine_info(bool to_uci) {
std::stringstream ss; std::stringstream ss;
ss << "Stockfish " << version << std::setfill('0'); ss << "Stockfish " << version << std::setfill('0');
@@ -168,8 +133,9 @@ std::string engine_info(bool to_uci) {
ss << stringify(GIT_DATE); ss << stringify(GIT_DATE);
#else #else
constexpr std::string_view months("Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec"); constexpr std::string_view months("Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec");
std::string month, day, year;
std::stringstream date(__DATE__); // From compiler, format is "Sep 21 2008" std::string month, day, year;
std::stringstream date(__DATE__); // From compiler, format is "Sep 21 2008"
date >> month >> day >> year; date >> month >> day >> year;
ss << year << std::setw(2) << std::setfill('0') << (1 + months.find(month) / 4) ss << year << std::setw(2) << std::setfill('0') << (1 + months.find(month) / 4)
@@ -318,13 +284,21 @@ template<size_t N>
struct DebugInfo { struct DebugInfo {
std::atomic<int64_t> data[N] = {0}; std::atomic<int64_t> data[N] = {0};
constexpr inline std::atomic<int64_t>& operator[](int index) { return data[index]; } constexpr std::atomic<int64_t>& operator[](int index) { return data[index]; }
}; };
DebugInfo<2> hit[MaxDebugSlots]; struct DebugExtremes: public DebugInfo<3> {
DebugInfo<2> mean[MaxDebugSlots]; DebugExtremes() {
DebugInfo<3> stdev[MaxDebugSlots]; data[1] = std::numeric_limits<int64_t>::min();
DebugInfo<6> correl[MaxDebugSlots]; data[2] = std::numeric_limits<int64_t>::max();
}
};
DebugInfo<2> hit[MaxDebugSlots];
DebugInfo<2> mean[MaxDebugSlots];
DebugInfo<3> stdev[MaxDebugSlots];
DebugInfo<6> correl[MaxDebugSlots];
DebugExtremes extremes[MaxDebugSlots];
} // namespace } // namespace
@@ -348,6 +322,18 @@ void dbg_stdev_of(int64_t value, int slot) {
stdev[slot][2] += value * value; stdev[slot][2] += value * value;
} }
void dbg_extremes_of(int64_t value, int slot) {
++extremes[slot][0];
int64_t current_max = extremes[slot][1].load();
while (current_max < value && !extremes[slot][1].compare_exchange_weak(current_max, value))
{}
int64_t current_min = extremes[slot][2].load();
while (current_min > value && !extremes[slot][2].compare_exchange_weak(current_min, value))
{}
}
void dbg_correl_of(int64_t value1, int64_t value2, int slot) { void dbg_correl_of(int64_t value1, int64_t value2, int slot) {
++correl[slot][0]; ++correl[slot][0];
@@ -382,6 +368,13 @@ void dbg_print() {
std::cerr << "Stdev #" << i << ": Total " << n << " Stdev " << r << std::endl; 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) for (int i = 0; i < MaxDebugSlots; ++i)
if ((n = correl[i][0])) if ((n = correl[i][0]))
{ {
@@ -408,6 +401,8 @@ std::ostream& operator<<(std::ostream& os, SyncCout sc) {
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); } void start_logger(const std::string& fname) { Logger::start(fname); }
@@ -415,14 +410,14 @@ void start_logger(const std::string& fname) { Logger::start(fname); }
#ifdef NO_PREFETCH #ifdef NO_PREFETCH
void prefetch(void*) {} void prefetch(const void*) {}
#else #else
void prefetch(void* addr) { void prefetch(const void* addr) {
#if defined(_MSC_VER) #if defined(_MSC_VER)
_mm_prefetch((char*) addr, _MM_HINT_T0); _mm_prefetch((char const*) addr, _MM_HINT_T0);
#else #else
__builtin_prefetch(addr); __builtin_prefetch(addr);
#endif #endif
@@ -430,289 +425,6 @@ void prefetch(void* addr) {
#endif #endif
// Wrapper 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(POSIXALIGNEDALLOC)
void* mem;
return posix_memalign(&mem, alignment, size) ? nullptr : 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 fun6 = fun6_t((void (*)()) GetProcAddress(hAdvapi32, "OpenProcessToken"));
if (!fun6)
return nullptr;
auto fun7 = fun7_t((void (*)()) GetProcAddress(hAdvapi32, "LookupPrivilegeValueA"));
if (!fun7)
return nullptr;
auto fun8 = fun8_t((void (*)()) GetProcAddress(hAdvapi32, "AdjustTokenPrivileges"));
if (!fun8)
return nullptr;
// We need SeLockMemoryPrivilege, so try to enable it for the process
if (!fun6( // OpenProcessToken()
GetCurrentProcess(), TOKEN_ADJUST_PRIVILEGES | TOKEN_QUERY, &hProcessToken))
return nullptr;
if (fun7( // LookupPrivilegeValue(nullptr, SE_LOCK_MEMORY_NAME, &luid)
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 (fun8( // 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(nullptr, allocSize, MEM_RESERVE | MEM_COMMIT | MEM_LARGE_PAGES,
PAGE_READWRITE);
// Privilege no longer needed, restore previous state
fun8( // AdjustTokenPrivileges ()
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; // assumed 2MB page size
#else
constexpr size_t alignment = 4096; // assumed small page size
#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
// aligned_large_pages_free() will free the previously allocated ttmem
#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 WinProcGroup {
#ifndef _WIN32
void bindThisThread(size_t) {}
#else
// Retrieves logical processor information using Windows-specific
// API and returns the best node id for the thread with index idx. Original
// code from Texel by Peter Österlund.
static int best_node(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(TEXT("Kernel32.dll"));
auto fun1 = (fun1_t) (void (*)()) GetProcAddress(k32, "GetLogicalProcessorInformationEx");
if (!fun1)
return -1;
// First call to GetLogicalProcessorInformationEx() to get returnLength.
// We expect the call 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 to GetLogicalProcessorInformationEx(), 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 the core limit is
// reached, then move on to 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
// still have threads to allocate, 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;
}
// Sets the group affinity of the current thread
void bindThisThread(size_t idx) {
// Use only local variables to be thread-safe
int node = best_node(idx);
if (node == -1)
return;
// Early exit if the needed API are not available at runtime
HMODULE k32 = GetModuleHandle(TEXT("Kernel32.dll"));
auto fun2 = fun2_t((void (*)()) GetProcAddress(k32, "GetNumaNodeProcessorMaskEx"));
auto fun3 = fun3_t((void (*)()) GetProcAddress(k32, "SetThreadGroupAffinity"));
auto fun4 = fun4_t((void (*)()) GetProcAddress(k32, "GetNumaNodeProcessorMask2"));
auto fun5 = fun5_t((void (*)()) GetProcAddress(k32, "GetMaximumProcessorGroupCount"));
if (!fun2 || !fun3)
return;
if (!fun4 || !fun5)
{
GROUP_AFFINITY affinity;
if (fun2(node, &affinity)) // GetNumaNodeProcessorMaskEx
fun3(GetCurrentThread(), &affinity, nullptr); // SetThreadGroupAffinity
}
else
{
// If a numa node has more than one processor group, we assume they are
// sized equal and we spread threads evenly across the groups.
USHORT elements, returnedElements;
elements = fun5(); // GetMaximumProcessorGroupCount
GROUP_AFFINITY* affinity = (GROUP_AFFINITY*) malloc(elements * sizeof(GROUP_AFFINITY));
if (fun4(node, affinity, elements, &returnedElements)) // GetNumaNodeProcessorMask2
fun3(GetCurrentThread(), &affinity[idx % returnedElements],
nullptr); // SetThreadGroupAffinity
free(affinity);
}
}
#endif
} // namespace WinProcGroup
#ifdef _WIN32 #ifdef _WIN32
#include <direct.h> #include <direct.h>
#define GETCWD _getcwd #define GETCWD _getcwd
@@ -721,13 +433,30 @@ void bindThisThread(size_t idx) {
#define GETCWD getcwd #define GETCWD getcwd
#endif #endif
CommandLine::CommandLine(int _argc, char** _argv) : size_t str_to_size_t(const std::string& s) {
argc(_argc), unsigned long long value = std::stoull(s);
argv(_argv) { if (value > std::numeric_limits<size_t>::max())
std::string pathSeparator; std::exit(EXIT_FAILURE);
return static_cast<size_t>(value);
}
// Extract the path+name of the executable binary std::optional<std::string> read_file_to_string(const std::string& path) {
std::string argv0 = argv[0]; 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(const std::string& 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 #ifdef _WIN32
pathSeparator = "\\"; pathSeparator = "\\";
@@ -743,15 +472,11 @@ CommandLine::CommandLine(int _argc, char** _argv) :
#endif #endif
// Extract the working directory // Extract the working directory
workingDirectory = ""; auto workingDirectory = CommandLine::get_working_directory();
char buff[40000];
char* cwd = GETCWD(buff, 40000);
if (cwd)
workingDirectory = cwd;
// Extract the binary directory path from argv0 // Extract the binary directory path from argv0
binaryDirectory = argv0; auto binaryDirectory = argv0;
size_t pos = binaryDirectory.find_last_of("\\/"); size_t pos = binaryDirectory.find_last_of("\\/");
if (pos == std::string::npos) if (pos == std::string::npos)
binaryDirectory = "." + pathSeparator; binaryDirectory = "." + pathSeparator;
else else
@@ -760,6 +485,19 @@ CommandLine::CommandLine(int _argc, char** _argv) :
// Pattern replacement: "./" at the start of path is replaced by the working directory // Pattern replacement: "./" at the start of path is replaced by the working directory
if (binaryDirectory.find("." + pathSeparator) == 0) if (binaryDirectory.find("." + pathSeparator) == 0)
binaryDirectory.replace(0, 1, workingDirectory); binaryDirectory.replace(0, 1, workingDirectory);
return binaryDirectory;
} }
std::string CommandLine::get_working_directory() {
std::string workingDirectory = "";
char buff[40000];
char* cwd = GETCWD(buff, 40000);
if (cwd)
workingDirectory = cwd;
return workingDirectory;
}
} // namespace Stockfish } // namespace Stockfish

View File

@@ -24,7 +24,9 @@
#include <chrono> #include <chrono>
#include <cstddef> #include <cstddef>
#include <cstdint> #include <cstdint>
#include <cstdio>
#include <iosfwd> #include <iosfwd>
#include <optional>
#include <string> #include <string>
#include <vector> #include <vector>
@@ -39,19 +41,33 @@ std::string compiler_info();
// Preloads the given address in L1/L2 cache. This is a non-blocking // 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, // function that doesn't stall the CPU waiting for data to be loaded from memory,
// which can be quite slow. // which can be quite slow.
void prefetch(void* addr); void prefetch(const void* addr);
void start_logger(const std::string& fname); void start_logger(const std::string& fname);
void* std_aligned_alloc(size_t alignment, size_t size);
void std_aligned_free(void* ptr); size_t str_to_size_t(const std::string& s);
// memory aligned by page size, min alignment: 4096 bytes
void* aligned_large_pages_alloc(size_t size); #if defined(__linux__)
// nop if mem == nullptr
void aligned_large_pages_free(void* mem); 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_hit_on(bool cond, int slot = 0);
void dbg_mean_of(int64_t value, 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_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_correl_of(int64_t value1, int64_t value2, int slot = 0);
void dbg_print(); void dbg_print();
@@ -63,6 +79,30 @@ inline TimePoint now() {
.count(); .count();
} }
inline std::vector<std::string> split(const std::string& s, const std::string& delimiter) {
std::vector<std::string> res;
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(const std::string& s);
enum SyncCout { enum SyncCout {
IO_LOCK, IO_LOCK,
@@ -73,19 +113,8 @@ std::ostream& operator<<(std::ostream&, SyncCout);
#define sync_cout std::cout << IO_LOCK #define sync_cout std::cout << IO_LOCK
#define sync_endl std::endl << IO_UNLOCK #define sync_endl std::endl << IO_UNLOCK
void sync_cout_start();
// Get the first aligned element of an array. void sync_cout_end();
// 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));
}
// True if and only if the binary is compiled on a little-endian machine // True if and only if the binary is compiled on a little-endian machine
static inline const union { static inline const union {
@@ -169,25 +198,18 @@ inline uint64_t mul_hi64(uint64_t a, uint64_t b) {
#endif #endif
} }
// Under Windows it is not possible for a process to run on more than one
// logical processor group. This usually means being limited to using 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.
namespace WinProcGroup {
void bindThisThread(size_t idx);
}
struct CommandLine { struct CommandLine {
public: public:
CommandLine(int, char**); 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; int argc;
char** argv; char** argv;
std::string binaryDirectory; // path of the executable directory
std::string workingDirectory; // path of the working directory
}; };
namespace Utility { namespace Utility {

View File

@@ -75,17 +75,6 @@ ExtMove* generate_pawn_moves(const Position& pos, ExtMove* moveList, Bitboard ta
b2 &= target; b2 &= target;
} }
if constexpr (Type == QUIET_CHECKS)
{
// To make a quiet check, you either make a direct check by pushing a pawn
// or push a blocker pawn that is not on the same file as the enemy king.
// Discovered check promotion has been already generated amongst the captures.
Square ksq = pos.square<KING>(Them);
Bitboard dcCandidatePawns = pos.blockers_for_king(Them) & ~file_bb(ksq);
b1 &= pawn_attacks_bb(Them, ksq) | shift<Up>(dcCandidatePawns);
b2 &= pawn_attacks_bb(Them, ksq) | shift<Up + Up>(dcCandidatePawns);
}
while (b1) while (b1)
{ {
Square to = pop_lsb(b1); Square to = pop_lsb(b1);
@@ -158,7 +147,7 @@ ExtMove* generate_pawn_moves(const Position& pos, ExtMove* moveList, Bitboard ta
} }
template<Color Us, PieceType Pt, bool Checks> template<Color Us, PieceType Pt>
ExtMove* generate_moves(const Position& pos, ExtMove* moveList, Bitboard target) { ExtMove* generate_moves(const Position& pos, ExtMove* moveList, Bitboard target) {
static_assert(Pt != KING && Pt != PAWN, "Unsupported piece type in generate_moves()"); static_assert(Pt != KING && Pt != PAWN, "Unsupported piece type in generate_moves()");
@@ -170,10 +159,6 @@ ExtMove* generate_moves(const Position& pos, ExtMove* moveList, Bitboard target)
Square from = pop_lsb(bb); Square from = pop_lsb(bb);
Bitboard b = attacks_bb<Pt>(from, pos.pieces()) & target; Bitboard b = attacks_bb<Pt>(from, pos.pieces()) & target;
// To check, you either move freely a blocker or make a direct check.
if (Checks && (Pt == QUEEN || !(pos.blockers_for_king(~Us) & from)))
b &= pos.check_squares(Pt);
while (b) while (b)
*moveList++ = Move(from, pop_lsb(b)); *moveList++ = Move(from, pop_lsb(b));
} }
@@ -187,9 +172,8 @@ ExtMove* generate_all(const Position& pos, ExtMove* moveList) {
static_assert(Type != LEGAL, "Unsupported type in generate_all()"); static_assert(Type != LEGAL, "Unsupported type in generate_all()");
constexpr bool Checks = Type == QUIET_CHECKS; // Reduce template instantiations const Square ksq = pos.square<KING>(Us);
const Square ksq = pos.square<KING>(Us); Bitboard target;
Bitboard target;
// Skip generating non-king moves when in double check // Skip generating non-king moves when in double check
if (Type != EVASIONS || !more_than_one(pos.checkers())) if (Type != EVASIONS || !more_than_one(pos.checkers()))
@@ -197,29 +181,24 @@ ExtMove* generate_all(const Position& pos, ExtMove* moveList) {
target = Type == EVASIONS ? between_bb(ksq, lsb(pos.checkers())) target = Type == EVASIONS ? between_bb(ksq, lsb(pos.checkers()))
: Type == NON_EVASIONS ? ~pos.pieces(Us) : Type == NON_EVASIONS ? ~pos.pieces(Us)
: Type == CAPTURES ? pos.pieces(~Us) : Type == CAPTURES ? pos.pieces(~Us)
: ~pos.pieces(); // QUIETS || QUIET_CHECKS : ~pos.pieces(); // QUIETS
moveList = generate_pawn_moves<Us, Type>(pos, moveList, target); moveList = generate_pawn_moves<Us, Type>(pos, moveList, target);
moveList = generate_moves<Us, KNIGHT, Checks>(pos, moveList, target); moveList = generate_moves<Us, KNIGHT>(pos, moveList, target);
moveList = generate_moves<Us, BISHOP, Checks>(pos, moveList, target); moveList = generate_moves<Us, BISHOP>(pos, moveList, target);
moveList = generate_moves<Us, ROOK, Checks>(pos, moveList, target); moveList = generate_moves<Us, ROOK>(pos, moveList, target);
moveList = generate_moves<Us, QUEEN, Checks>(pos, moveList, target); moveList = generate_moves<Us, QUEEN>(pos, moveList, target);
} }
if (!Checks || pos.blockers_for_king(~Us) & ksq) Bitboard b = attacks_bb<KING>(ksq) & (Type == EVASIONS ? ~pos.pieces(Us) : target);
{
Bitboard b = attacks_bb<KING>(ksq) & (Type == EVASIONS ? ~pos.pieces(Us) : target);
if (Checks)
b &= ~attacks_bb<QUEEN>(pos.square<KING>(~Us));
while (b) while (b)
*moveList++ = Move(ksq, pop_lsb(b)); *moveList++ = Move(ksq, pop_lsb(b));
if ((Type == QUIETS || Type == NON_EVASIONS) && pos.can_castle(Us & ANY_CASTLING)) if ((Type == QUIETS || Type == NON_EVASIONS) && pos.can_castle(Us & ANY_CASTLING))
for (CastlingRights cr : {Us & KING_SIDE, Us & QUEEN_SIDE}) for (CastlingRights cr : {Us & KING_SIDE, Us & QUEEN_SIDE})
if (!pos.castling_impeded(cr) && pos.can_castle(cr)) if (!pos.castling_impeded(cr) && pos.can_castle(cr))
*moveList++ = Move::make<CASTLING>(ksq, pos.castling_rook_square(cr)); *moveList++ = Move::make<CASTLING>(ksq, pos.castling_rook_square(cr));
}
return moveList; return moveList;
} }
@@ -231,8 +210,6 @@ ExtMove* generate_all(const Position& pos, ExtMove* moveList) {
// <QUIETS> Generates all pseudo-legal non-captures and underpromotions // <QUIETS> Generates all pseudo-legal non-captures and underpromotions
// <EVASIONS> Generates all pseudo-legal check evasions // <EVASIONS> Generates all pseudo-legal check evasions
// <NON_EVASIONS> Generates all pseudo-legal captures and non-captures // <NON_EVASIONS> Generates all pseudo-legal captures and non-captures
// <QUIET_CHECKS> Generates all pseudo-legal non-captures giving check,
// except castling and promotions
// //
// Returns a pointer to the end of the move list. // Returns a pointer to the end of the move list.
template<GenType Type> template<GenType Type>
@@ -251,7 +228,6 @@ ExtMove* generate(const Position& pos, ExtMove* moveList) {
template ExtMove* generate<CAPTURES>(const Position&, ExtMove*); template ExtMove* generate<CAPTURES>(const Position&, ExtMove*);
template ExtMove* generate<QUIETS>(const Position&, ExtMove*); template ExtMove* generate<QUIETS>(const Position&, ExtMove*);
template ExtMove* generate<EVASIONS>(const Position&, ExtMove*); template ExtMove* generate<EVASIONS>(const Position&, ExtMove*);
template ExtMove* generate<QUIET_CHECKS>(const Position&, ExtMove*);
template ExtMove* generate<NON_EVASIONS>(const Position&, ExtMove*); template ExtMove* generate<NON_EVASIONS>(const Position&, ExtMove*);

View File

@@ -31,7 +31,6 @@ class Position;
enum GenType { enum GenType {
CAPTURES, CAPTURES,
QUIETS, QUIETS,
QUIET_CHECKS,
EVASIONS, EVASIONS,
NON_EVASIONS, NON_EVASIONS,
LEGAL LEGAL

View File

@@ -20,7 +20,6 @@
#include <algorithm> #include <algorithm>
#include <cassert> #include <cassert>
#include <iterator>
#include <utility> #include <utility>
#include "bitboard.h" #include "bitboard.h"
@@ -35,7 +34,6 @@ enum Stages {
MAIN_TT, MAIN_TT,
CAPTURE_INIT, CAPTURE_INIT,
GOOD_CAPTURE, GOOD_CAPTURE,
REFUTATION,
QUIET_INIT, QUIET_INIT,
GOOD_QUIET, GOOD_QUIET,
BAD_CAPTURE, BAD_CAPTURE,
@@ -54,13 +52,11 @@ enum Stages {
// generate qsearch moves // generate qsearch moves
QSEARCH_TT, QSEARCH_TT,
QCAPTURE_INIT, QCAPTURE_INIT,
QCAPTURE, QCAPTURE
QCHECK_INIT,
QCHECK
}; };
// Sort moves in descending order up to and including // Sort moves in descending order up to and including a given limit.
// a given limit. The order of moves smaller than the limit is left unspecified. // The order of moves smaller than the limit is left unspecified.
void partial_insertion_sort(ExtMove* begin, ExtMove* end, int limit) { void partial_insertion_sort(ExtMove* begin, ExtMove* end, int limit) {
for (ExtMove *sortedEnd = begin, *p = begin + 1; p < end; ++p) for (ExtMove *sortedEnd = begin, *p = begin + 1; p < end; ++p)
@@ -78,35 +74,10 @@ void partial_insertion_sort(ExtMove* begin, ExtMove* end, int limit) {
// Constructors of the MovePicker class. As arguments, we pass information // Constructors of the MovePicker class. As arguments, we pass information
// to help it return the (presumably) good moves first, to decide which // to decide which class of moves to emit, to help sorting the (presumably)
// moves to return (in the quiescence search, for instance, we only want to // good moves first, and how important move ordering is at the current node.
// search captures, promotions, and some checks) and how important a good
// move ordering is at the current node.
// MovePicker constructor for the main search // MovePicker constructor for the main search and for the quiescence search
MovePicker::MovePicker(const Position& p,
Move ttm,
Depth d,
const ButterflyHistory* mh,
const CapturePieceToHistory* cph,
const PieceToHistory** ch,
const PawnHistory* ph,
Move cm,
const Move* killers) :
pos(p),
mainHistory(mh),
captureHistory(cph),
continuationHistory(ch),
pawnHistory(ph),
ttMove(ttm),
refutations{{killers[0], 0}, {killers[1], 0}, {cm, 0}},
depth(d) {
assert(d > 0);
stage = (pos.checkers() ? EVASION_TT : MAIN_TT) + !(ttm && pos.pseudo_legal(ttm));
}
// Constructor for quiescence search
MovePicker::MovePicker(const Position& p, MovePicker::MovePicker(const Position& p,
Move ttm, Move ttm,
Depth d, Depth d,
@@ -121,13 +92,16 @@ MovePicker::MovePicker(const Position& p,
pawnHistory(ph), pawnHistory(ph),
ttMove(ttm), ttMove(ttm),
depth(d) { depth(d) {
assert(d <= 0);
stage = (pos.checkers() ? EVASION_TT : QSEARCH_TT) + !(ttm && pos.pseudo_legal(ttm)); if (pos.checkers())
stage = EVASION_TT + !(ttm && pos.pseudo_legal(ttm));
else
stage = (depth > 0 ? MAIN_TT : QSEARCH_TT) + !(ttm && pos.pseudo_legal(ttm));
} }
// Constructor for ProbCut: we generate captures with SEE greater // MovePicker constructor for ProbCut: we generate captures with Static Exchange
// than or equal to the given threshold. // Evaluation (SEE) greater than or equal to the given threshold.
MovePicker::MovePicker(const Position& p, Move ttm, int th, const CapturePieceToHistory* cph) : MovePicker::MovePicker(const Position& p, Move ttm, int th, const CapturePieceToHistory* cph) :
pos(p), pos(p),
captureHistory(cph), captureHistory(cph),
@@ -139,9 +113,9 @@ MovePicker::MovePicker(const Position& p, Move ttm, int th, const CapturePieceTo
+ !(ttm && pos.capture_stage(ttm) && pos.pseudo_legal(ttm) && pos.see_ge(ttm, threshold)); + !(ttm && pos.capture_stage(ttm) && pos.pseudo_legal(ttm) && pos.see_ge(ttm, threshold));
} }
// Assigns a numerical value to each move in a list, used // Assigns a numerical value to each move in a list, used for sorting.
// for sorting. Captures are ordered by Most Valuable Victim (MVV), preferring // Captures are ordered by Most Valuable Victim (MVV), preferring captures
// captures with a good history. Quiets moves are ordered using the history tables. // with a good history. Quiets moves are ordered using the history tables.
template<GenType Type> template<GenType Type>
void MovePicker::score() { void MovePicker::score() {
@@ -178,11 +152,11 @@ void MovePicker::score() {
Square to = m.to_sq(); Square to = m.to_sq();
// histories // histories
m.value = 2 * (*mainHistory)[pos.side_to_move()][m.from_to()]; m.value = (*mainHistory)[pos.side_to_move()][m.from_to()];
m.value += 2 * (*pawnHistory)[pawn_structure_index(pos)][pc][to]; m.value += 2 * (*pawnHistory)[pawn_structure_index(pos)][pc][to];
m.value += 2 * (*continuationHistory[0])[pc][to]; m.value += 2 * (*continuationHistory[0])[pc][to];
m.value += (*continuationHistory[1])[pc][to]; m.value += (*continuationHistory[1])[pc][to];
m.value += (*continuationHistory[2])[pc][to] / 4; m.value += (*continuationHistory[2])[pc][to] / 3;
m.value += (*continuationHistory[3])[pc][to]; m.value += (*continuationHistory[3])[pc][to];
m.value += (*continuationHistory[5])[pc][to]; m.value += (*continuationHistory[5])[pc][to];
@@ -190,20 +164,16 @@ void MovePicker::score() {
m.value += bool(pos.check_squares(pt) & to) * 16384; m.value += bool(pos.check_squares(pt) & to) * 16384;
// bonus for escaping from capture // bonus for escaping from capture
m.value += threatenedPieces & from ? (pt == QUEEN && !(to & threatenedByRook) ? 50000 m.value += threatenedPieces & from ? (pt == QUEEN && !(to & threatenedByRook) ? 51700
: pt == ROOK && !(to & threatenedByMinor) ? 25000 : pt == ROOK && !(to & threatenedByMinor) ? 25600
: !(to & threatenedByPawn) ? 15000 : !(to & threatenedByPawn) ? 14450
: 0) : 0)
: 0; : 0;
// malus for putting piece en prise // malus for putting piece en prise
m.value -= !(threatenedPieces & from) m.value -= (pt == QUEEN ? bool(to & threatenedByRook) * 49000
? (pt == QUEEN ? bool(to & threatenedByRook) * 50000 : pt == ROOK ? bool(to & threatenedByMinor) * 24335
+ bool(to & threatenedByMinor) * 10000 : bool(to & threatenedByPawn) * 14900);
: pt == ROOK ? bool(to & threatenedByMinor) * 25000
: pt != PAWN ? bool(to & threatenedByPawn) * 15000
: 0)
: 0;
} }
else // Type == EVASIONS else // Type == EVASIONS
@@ -219,7 +189,7 @@ void MovePicker::score() {
} }
// Returns the next move satisfying a predicate function. // Returns the next move satisfying a predicate function.
// It never returns the TT move. // This never returns the TT move, as it was emitted before.
template<MovePicker::PickType T, typename Pred> template<MovePicker::PickType T, typename Pred>
Move MovePicker::select(Pred filter) { Move MovePicker::select(Pred filter) {
@@ -236,12 +206,12 @@ Move MovePicker::select(Pred filter) {
return Move::none(); return Move::none();
} }
// Most important method of the MovePicker class. It // This is the most important method of the MovePicker class. We emit one
// returns a new pseudo-legal move every time it is called until there are no more // new pseudo-legal move on every call until there are no more moves left,
// moves left, picking the move with the highest score from a list of generated moves. // picking the move with the highest score from a list of generated moves.
Move MovePicker::next_move(bool skipQuiets) { Move MovePicker::next_move(bool skipQuiets) {
auto quiet_threshold = [](Depth d) { return -3330 * d; }; auto quiet_threshold = [](Depth d) { return -3560 * d; };
top: top:
switch (stage) switch (stage)
@@ -273,22 +243,6 @@ top:
})) }))
return *(cur - 1); return *(cur - 1);
// Prepare the pointers to loop over the refutations array
cur = std::begin(refutations);
endMoves = std::end(refutations);
// If the countermove is the same as a killer, skip it
if (refutations[0] == refutations[2] || refutations[1] == refutations[2])
--endMoves;
++stage;
[[fallthrough]];
case REFUTATION :
if (select<Next>([&]() {
return *cur != Move::none() && !pos.capture_stage(*cur) && pos.pseudo_legal(*cur);
}))
return *(cur - 1);
++stage; ++stage;
[[fallthrough]]; [[fallthrough]];
@@ -306,11 +260,9 @@ top:
[[fallthrough]]; [[fallthrough]];
case GOOD_QUIET : case GOOD_QUIET :
if (!skipQuiets && select<Next>([&]() { if (!skipQuiets && select<Next>([]() { return true; }))
return *cur != refutations[0] && *cur != refutations[1] && *cur != refutations[2];
}))
{ {
if ((cur - 1)->value > -8000 || (cur - 1)->value <= quiet_threshold(depth)) if ((cur - 1)->value > -7998 || (cur - 1)->value <= quiet_threshold(depth))
return *(cur - 1); return *(cur - 1);
// Remaining quiets are bad // Remaining quiets are bad
@@ -337,9 +289,7 @@ top:
case BAD_QUIET : case BAD_QUIET :
if (!skipQuiets) if (!skipQuiets)
return select<Next>([&]() { return select<Next>([]() { return true; });
return *cur != refutations[0] && *cur != refutations[1] && *cur != refutations[2];
});
return Move::none(); return Move::none();
@@ -358,24 +308,6 @@ top:
return select<Next>([&]() { return pos.see_ge(*cur, threshold); }); return select<Next>([&]() { return pos.see_ge(*cur, threshold); });
case QCAPTURE : case QCAPTURE :
if (select<Next>([]() { return true; }))
return *(cur - 1);
// 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; }); return select<Next>([]() { return true; });
} }

View File

@@ -19,6 +19,7 @@
#ifndef MOVEPICK_H_INCLUDED #ifndef MOVEPICK_H_INCLUDED
#define MOVEPICK_H_INCLUDED #define MOVEPICK_H_INCLUDED
#include <algorithm>
#include <array> #include <array>
#include <cassert> #include <cassert>
#include <cmath> #include <cmath>
@@ -28,8 +29,8 @@
#include <type_traits> // IWYU pragma: keep #include <type_traits> // IWYU pragma: keep
#include "movegen.h" #include "movegen.h"
#include "types.h"
#include "position.h" #include "position.h"
#include "types.h"
namespace Stockfish { namespace Stockfish {
@@ -69,10 +70,11 @@ class StatsEntry {
operator const T&() const { return entry; } operator const T&() const { return entry; }
void operator<<(int bonus) { void operator<<(int bonus) {
assert(std::abs(bonus) <= D); // Ensure range is [-D, D]
static_assert(D <= std::numeric_limits<T>::max(), "D overflows T"); static_assert(D <= std::numeric_limits<T>::max(), "D overflows T");
entry += bonus - entry * std::abs(bonus) / D; // 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); assert(std::abs(entry) <= D);
} }
@@ -116,10 +118,6 @@ enum StatsType {
// see www.chessprogramming.org/Butterfly_Boards (~11 elo) // see www.chessprogramming.org/Butterfly_Boards (~11 elo)
using ButterflyHistory = Stats<int16_t, 7183, COLOR_NB, int(SQUARE_NB) * int(SQUARE_NB)>; using ButterflyHistory = Stats<int16_t, 7183, COLOR_NB, int(SQUARE_NB) * int(SQUARE_NB)>;
// CounterMoveHistory stores counter moves indexed by [piece][to] of the previous
// move, see www.chessprogramming.org/Countermove_Heuristic
using CounterMoveHistory = Stats<Move, NOT_USED, PIECE_NB, SQUARE_NB>;
// CapturePieceToHistory is addressed by a move's [piece][to][captured piece type] // CapturePieceToHistory is addressed by a move's [piece][to][captured piece type]
using CapturePieceToHistory = Stats<int16_t, 10692, PIECE_NB, SQUARE_NB, PIECE_TYPE_NB>; using CapturePieceToHistory = Stats<int16_t, 10692, PIECE_NB, SQUARE_NB, PIECE_TYPE_NB>;
@@ -139,12 +137,12 @@ using PawnHistory = Stats<int16_t, 8192, PAWN_HISTORY_SIZE, PIECE_NB, SQUARE_NB>
using CorrectionHistory = using CorrectionHistory =
Stats<int16_t, CORRECTION_HISTORY_LIMIT, COLOR_NB, CORRECTION_HISTORY_SIZE>; Stats<int16_t, CORRECTION_HISTORY_LIMIT, COLOR_NB, CORRECTION_HISTORY_SIZE>;
// MovePicker class is used to pick one pseudo-legal move at a time from the // 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 returns a // current position. The most important method is next_move(), which emits one
// new pseudo-legal move each time it is called, until there are no moves left, // new pseudo-legal move on every call, until there are no moves left, when
// when Move::none() is returned. In order to improve the efficiency of the // Move::none() is returned. In order to improve the efficiency of the alpha-beta
// alpha-beta algorithm, MovePicker attempts to return the moves which are most // algorithm, MovePicker attempts to return the moves which are most likely to get
// likely to get a cut-off first. // a cut-off first.
class MovePicker { class MovePicker {
enum PickType { enum PickType {
@@ -155,15 +153,6 @@ class MovePicker {
public: public:
MovePicker(const MovePicker&) = delete; MovePicker(const MovePicker&) = delete;
MovePicker& operator=(const MovePicker&) = delete; MovePicker& operator=(const MovePicker&) = delete;
MovePicker(const Position&,
Move,
Depth,
const ButterflyHistory*,
const CapturePieceToHistory*,
const PieceToHistory**,
const PawnHistory*,
Move,
const Move*);
MovePicker(const Position&, MovePicker(const Position&,
Move, Move,
Depth, Depth,
@@ -188,11 +177,11 @@ class MovePicker {
const PieceToHistory** continuationHistory; const PieceToHistory** continuationHistory;
const PawnHistory* pawnHistory; const PawnHistory* pawnHistory;
Move ttMove; Move ttMove;
ExtMove refutations[3], *cur, *endMoves, *endBadCaptures, *beginBadQuiets, *endBadQuiets; ExtMove * cur, *endMoves, *endBadCaptures, *beginBadQuiets, *endBadQuiets;
int stage; int stage;
int threshold; int threshold;
Depth depth; Depth depth;
ExtMove moves[MAX_MOVES]; ExtMove moves[MAX_MOVES];
}; };
} // namespace Stockfish } // namespace Stockfish

View File

@@ -1,482 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2024 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 "evaluate_nnue.h"
#include <cmath>
#include <cstdlib>
#include <cstring>
#include <fstream>
#include <iomanip>
#include <iostream>
#include <optional>
#include <sstream>
#include <string_view>
#include <type_traits>
#include <unordered_map>
#include "../evaluate.h"
#include "../misc.h"
#include "../position.h"
#include "../types.h"
#include "../uci.h"
#include "nnue_accumulator.h"
#include "nnue_common.h"
namespace Stockfish::Eval::NNUE {
// Input feature converter
LargePagePtr<FeatureTransformer<TransformedFeatureDimensionsBig, &StateInfo::accumulatorBig>>
featureTransformerBig;
LargePagePtr<FeatureTransformer<TransformedFeatureDimensionsSmall, &StateInfo::accumulatorSmall>>
featureTransformerSmall;
// Evaluation function
AlignedPtr<Network<TransformedFeatureDimensionsBig, L2Big, L3Big>> networkBig[LayerStacks];
AlignedPtr<Network<TransformedFeatureDimensionsSmall, L2Small, L3Small>> networkSmall[LayerStacks];
// Evaluation function file names
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));
}
template<typename T>
void initialize(LargePagePtr<T>& pointer) {
static_assert(alignof(T) <= 4096,
"aligned_large_pages_alloc() may fail for such a big alignment requirement of T");
pointer.reset(reinterpret_cast<T*>(aligned_large_pages_alloc(sizeof(T))));
std::memset(pointer.get(), 0, sizeof(T));
}
// 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, const T& reference) {
write_little_endian<std::uint32_t>(stream, T::get_hash_value());
return reference.write_parameters(stream);
}
} // namespace Detail
// Initialize the evaluation function parameters
static void initialize(NetSize netSize) {
if (netSize == Small)
{
Detail::initialize(featureTransformerSmall);
for (std::size_t i = 0; i < LayerStacks; ++i)
Detail::initialize(networkSmall[i]);
}
else
{
Detail::initialize(featureTransformerBig);
for (std::size_t i = 0; i < LayerStacks; ++i)
Detail::initialize(networkBig[i]);
}
}
// Read network header
static bool read_header(std::istream& stream, std::uint32_t* hashValue, std::string* desc) {
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
static bool write_header(std::ostream& stream, std::uint32_t hashValue, const std::string& desc) {
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();
}
// Read network parameters
static bool read_parameters(std::istream& stream, NetSize netSize, std::string& netDescription) {
std::uint32_t hashValue;
if (!read_header(stream, &hashValue, &netDescription))
return false;
if (hashValue != HashValue[netSize])
return false;
if (netSize == Big && !Detail::read_parameters(stream, *featureTransformerBig))
return false;
if (netSize == Small && !Detail::read_parameters(stream, *featureTransformerSmall))
return false;
for (std::size_t i = 0; i < LayerStacks; ++i)
{
if (netSize == Big && !Detail::read_parameters(stream, *(networkBig[i])))
return false;
if (netSize == Small && !Detail::read_parameters(stream, *(networkSmall[i])))
return false;
}
return stream && stream.peek() == std::ios::traits_type::eof();
}
// Write network parameters
static bool
write_parameters(std::ostream& stream, NetSize netSize, const std::string& netDescription) {
if (!write_header(stream, HashValue[netSize], netDescription))
return false;
if (netSize == Big && !Detail::write_parameters(stream, *featureTransformerBig))
return false;
if (netSize == Small && !Detail::write_parameters(stream, *featureTransformerSmall))
return false;
for (std::size_t i = 0; i < LayerStacks; ++i)
{
if (netSize == Big && !Detail::write_parameters(stream, *(networkBig[i])))
return false;
if (netSize == Small && !Detail::write_parameters(stream, *(networkSmall[i])))
return false;
}
return bool(stream);
}
void hint_common_parent_position(const Position& pos) {
int simpleEval = simple_eval(pos, pos.side_to_move());
if (std::abs(simpleEval) > 1050)
featureTransformerSmall->hint_common_access(pos);
else
featureTransformerBig->hint_common_access(pos);
}
// Evaluation function. Perform differential calculation.
template<NetSize Net_Size>
Value evaluate(const Position& pos, bool adjusted, int* complexity) {
// We manually align the arrays on the stack because with gcc < 9.3
// overaligning stack variables with alignas() doesn't work correctly.
constexpr uint64_t alignment = CacheLineSize;
constexpr int delta = 24;
#if defined(ALIGNAS_ON_STACK_VARIABLES_BROKEN)
TransformedFeatureType transformedFeaturesUnaligned
[FeatureTransformer < Net_Size == Small ? TransformedFeatureDimensionsSmall
: TransformedFeatureDimensionsBig,
nullptr > ::BufferSize + alignment / sizeof(TransformedFeatureType)];
auto* transformedFeatures = align_ptr_up<alignment>(&transformedFeaturesUnaligned[0]);
#else
alignas(alignment) TransformedFeatureType
transformedFeatures[FeatureTransformer < Net_Size == Small ? TransformedFeatureDimensionsSmall
: TransformedFeatureDimensionsBig,
nullptr > ::BufferSize];
#endif
ASSERT_ALIGNED(transformedFeatures, alignment);
const int bucket = (pos.count<ALL_PIECES>() - 1) / 4;
const auto psqt = Net_Size == Small
? featureTransformerSmall->transform(pos, transformedFeatures, bucket)
: featureTransformerBig->transform(pos, transformedFeatures, bucket);
const auto positional = Net_Size == Small ? networkSmall[bucket]->propagate(transformedFeatures)
: networkBig[bucket]->propagate(transformedFeatures);
if (complexity)
*complexity = std::abs(psqt - positional) / OutputScale;
// Give more value to positional evaluation when adjusted flag is set
if (adjusted)
return static_cast<Value>(((1024 - delta) * psqt + (1024 + delta) * positional)
/ (1024 * OutputScale));
else
return static_cast<Value>((psqt + positional) / OutputScale);
}
template Value evaluate<Big>(const Position& pos, bool adjusted, int* complexity);
template Value evaluate<Small>(const Position& pos, bool adjusted, int* complexity);
struct NnueEvalTrace {
static_assert(LayerStacks == PSQTBuckets);
Value psqt[LayerStacks];
Value positional[LayerStacks];
std::size_t correctBucket;
};
static NnueEvalTrace trace_evaluate(const Position& pos) {
// We manually align the arrays on the stack because with gcc < 9.3
// overaligning stack variables with alignas() doesn't work correctly.
constexpr uint64_t alignment = CacheLineSize;
#if defined(ALIGNAS_ON_STACK_VARIABLES_BROKEN)
TransformedFeatureType transformedFeaturesUnaligned
[FeatureTransformer<TransformedFeatureDimensionsBig, nullptr>::BufferSize
+ alignment / sizeof(TransformedFeatureType)];
auto* transformedFeatures = align_ptr_up<alignment>(&transformedFeaturesUnaligned[0]);
#else
alignas(alignment) TransformedFeatureType
transformedFeatures[FeatureTransformer<TransformedFeatureDimensionsBig, nullptr>::BufferSize];
#endif
ASSERT_ALIGNED(transformedFeatures, alignment);
NnueEvalTrace t{};
t.correctBucket = (pos.count<ALL_PIECES>() - 1) / 4;
for (IndexType bucket = 0; bucket < LayerStacks; ++bucket)
{
const auto materialist = featureTransformerBig->transform(pos, transformedFeatures, bucket);
const auto positional = networkBig[bucket]->propagate(transformedFeatures);
t.psqt[bucket] = static_cast<Value>(materialist / OutputScale);
t.positional[bucket] = static_cast<Value>(positional / OutputScale);
}
return t;
}
constexpr std::string_view PieceToChar(" PNBRQK pnbrqk");
// Converts a Value into (centi)pawns and writes it in a buffer.
// The buffer must have capacity for at least 5 chars.
static void format_cp_compact(Value v, char* buffer) {
buffer[0] = (v < 0 ? '-' : v > 0 ? '+' : ' ');
int cp = std::abs(UCI::to_cp(v));
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
static void format_cp_aligned_dot(Value v, std::stringstream& stream) {
const double pawns = std::abs(0.01 * UCI::to_cp(v));
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) {
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](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 (value != VALUE_NONE)
format_cp_compact(value, &board[y + 2][x + 2]);
};
// 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.
Value base = evaluate<NNUE::Big>(pos);
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)
{
auto st = pos.state();
pos.remove_piece(sq);
st->accumulatorBig.computed[WHITE] = false;
st->accumulatorBig.computed[BLACK] = false;
Value eval = evaluate<NNUE::Big>(pos);
eval = pos.side_to_move() == WHITE ? eval : -eval;
v = base - eval;
pos.put_piece(pc, sq);
st->accumulatorBig.computed[WHITE] = false;
st->accumulatorBig.computed[BLACK] = false;
}
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';
auto t = trace_evaluate(pos);
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 << " ";
ss << " | ";
format_cp_aligned_dot(t.psqt[bucket], ss);
ss << " "
<< " | ";
format_cp_aligned_dot(t.positional[bucket], ss);
ss << " "
<< " | ";
format_cp_aligned_dot(t.psqt[bucket] + t.positional[bucket], ss);
ss << " "
<< " |";
if (bucket == t.correctBucket)
ss << " <-- this bucket is used";
ss << '\n';
}
ss << "+------------+------------+------------+------------+\n";
return ss.str();
}
// Load eval, from a file stream or a memory stream
std::optional<std::string> load_eval(std::istream& stream, NetSize netSize) {
initialize(netSize);
std::string netDescription;
return read_parameters(stream, netSize, netDescription) ? std::make_optional(netDescription)
: std::nullopt;
}
// Save eval, to a file stream or a memory stream
bool save_eval(std::ostream& stream,
NetSize netSize,
const std::string& name,
const std::string& netDescription) {
if (name.empty() || name == "None")
return false;
return write_parameters(stream, netSize, netDescription);
}
// Save eval, to a file given by its name
bool save_eval(const std::optional<std::string>& filename,
NetSize netSize,
const std::unordered_map<Eval::NNUE::NetSize, Eval::EvalFile>& evalFiles) {
std::string actualFilename;
std::string msg;
if (filename.has_value())
actualFilename = filename.value();
else
{
if (evalFiles.at(netSize).current
!= (netSize == Small ? EvalFileDefaultNameSmall : EvalFileDefaultNameBig))
{
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 = (netSize == Small ? EvalFileDefaultNameSmall : EvalFileDefaultNameBig);
}
std::ofstream stream(actualFilename, std::ios_base::binary);
bool saved = save_eval(stream, netSize, evalFiles.at(netSize).current,
evalFiles.at(netSize).netDescription);
msg = saved ? "Network saved successfully to " + actualFilename : "Failed to export a net";
sync_cout << msg << sync_endl;
return saved;
}
} // namespace Stockfish::Eval::NNUE

View File

@@ -1,93 +0,0 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2024 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 <cstdint>
#include <iosfwd>
#include <memory>
#include <optional>
#include <string>
#include <unordered_map>
#include "../misc.h"
#include "../types.h"
#include "nnue_architecture.h"
#include "nnue_feature_transformer.h"
namespace Stockfish {
class Position;
namespace Eval {
struct EvalFile;
}
}
namespace Stockfish::Eval::NNUE {
// Hash value of evaluation function structure
constexpr std::uint32_t HashValue[2] = {
FeatureTransformer<TransformedFeatureDimensionsBig, nullptr>::get_hash_value()
^ Network<TransformedFeatureDimensionsBig, L2Big, L3Big>::get_hash_value(),
FeatureTransformer<TransformedFeatureDimensionsSmall, nullptr>::get_hash_value()
^ Network<TransformedFeatureDimensionsSmall, L2Small, L3Small>::get_hash_value()};
// 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>
struct LargePageDeleter {
void operator()(T* ptr) const {
ptr->~T();
aligned_large_pages_free(ptr);
}
};
template<typename T>
using AlignedPtr = std::unique_ptr<T, AlignedDeleter<T>>;
template<typename T>
using LargePagePtr = std::unique_ptr<T, LargePageDeleter<T>>;
std::string trace(Position& pos);
template<NetSize Net_Size>
Value evaluate(const Position& pos, bool adjusted = false, int* complexity = nullptr);
void hint_common_parent_position(const Position& pos);
std::optional<std::string> load_eval(std::istream& stream, NetSize netSize);
bool save_eval(std::ostream& stream,
NetSize netSize,
const std::string& name,
const std::string& netDescription);
bool save_eval(const std::optional<std::string>& filename,
NetSize netSize,
const std::unordered_map<Eval::NNUE::NetSize, Eval::EvalFile>&);
} // namespace Stockfish::Eval::NNUE
#endif // #ifndef NNUE_EVALUATE_NNUE_H_INCLUDED

View File

@@ -23,7 +23,7 @@
#include "../../bitboard.h" #include "../../bitboard.h"
#include "../../position.h" #include "../../position.h"
#include "../../types.h" #include "../../types.h"
#include "../nnue_common.h" #include "../nnue_accumulator.h"
namespace Stockfish::Eval::NNUE::Features { namespace Stockfish::Eval::NNUE::Features {
@@ -49,6 +49,8 @@ void HalfKAv2_hm::append_active_indices(const Position& pos, IndexList& active)
// Explicit template instantiations // Explicit template instantiations
template void HalfKAv2_hm::append_active_indices<WHITE>(const Position& pos, IndexList& active); 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 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 // Get a list of indices for recently changed features
template<Color Perspective> template<Color Perspective>

View File

@@ -63,10 +63,6 @@ class HalfKAv2_hm {
{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}}; PS_NONE, PS_W_PAWN, PS_W_KNIGHT, PS_W_BISHOP, PS_W_ROOK, PS_W_QUEEN, PS_KING, PS_NONE}};
// 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);
public: public:
// Feature name // Feature name
static constexpr const char* Name = "HalfKAv2_hm(Friend)"; static constexpr const char* Name = "HalfKAv2_hm(Friend)";
@@ -126,6 +122,10 @@ class HalfKAv2_hm {
static constexpr IndexType MaxActiveDimensions = 32; static constexpr IndexType MaxActiveDimensions = 32;
using IndexList = ValueList<IndexType, MaxActiveDimensions>; 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 // Get a list of indices for active features
template<Color Perspective> template<Color Perspective>
static void append_active_indices(const Position& pos, IndexList& active); static void append_active_indices(const Position& pos, IndexList& active);

View File

@@ -39,25 +39,26 @@
namespace Stockfish::Eval::NNUE::Layers { namespace Stockfish::Eval::NNUE::Layers {
#if defined(USE_SSSE3) || defined(USE_NEON_DOTPROD)
#define ENABLE_SEQ_OPT
#endif
// Fallback implementation for older/other architectures. // Fallback implementation for older/other architectures.
// Requires the input to be padded to at least 16 values. // Requires the input to be padded to at least 16 values.
#if !defined(USE_SSSE3) #ifndef ENABLE_SEQ_OPT
template<IndexType InputDimensions, IndexType PaddedInputDimensions, IndexType OutputDimensions> template<IndexType InputDimensions, IndexType PaddedInputDimensions, IndexType OutputDimensions>
static void affine_transform_non_ssse3(std::int32_t* output, static void affine_transform_non_ssse3(std::int32_t* output,
const std::int8_t* weights, const std::int8_t* weights,
const std::int32_t* biases, const std::int32_t* biases,
const std::uint8_t* input) { const std::uint8_t* input) {
#if defined(USE_SSE2) || defined(USE_NEON_DOTPROD) || defined(USE_NEON) #if defined(USE_SSE2) || defined(USE_NEON)
#if defined(USE_SSE2) #if defined(USE_SSE2)
// At least a multiple of 16, with SSE2. // At least a multiple of 16, with SSE2.
constexpr IndexType NumChunks = ceil_to_multiple<IndexType>(InputDimensions, 16) / 16; constexpr IndexType NumChunks = ceil_to_multiple<IndexType>(InputDimensions, 16) / 16;
const __m128i Zeros = _mm_setzero_si128(); const __m128i Zeros = _mm_setzero_si128();
const auto inputVector = reinterpret_cast<const __m128i*>(input); const auto inputVector = reinterpret_cast<const __m128i*>(input);
#elif defined(USE_NEON_DOTPROD)
constexpr IndexType NumChunks = ceil_to_multiple<IndexType>(InputDimensions, 16) / 16;
const auto inputVector = reinterpret_cast<const int8x16_t*>(input);
#elif defined(USE_NEON) #elif defined(USE_NEON)
constexpr IndexType NumChunks = ceil_to_multiple<IndexType>(InputDimensions, 16) / 16; constexpr IndexType NumChunks = ceil_to_multiple<IndexType>(InputDimensions, 16) / 16;
const auto inputVector = reinterpret_cast<const int8x8_t*>(input); const auto inputVector = reinterpret_cast<const int8x8_t*>(input);
@@ -91,16 +92,8 @@ static void affine_transform_non_ssse3(std::int32_t* output,
sum = _mm_add_epi32(sum, sum_second_32); sum = _mm_add_epi32(sum, sum_second_32);
output[i] = _mm_cvtsi128_si32(sum); output[i] = _mm_cvtsi128_si32(sum);
#elif defined(USE_NEON_DOTPROD)
int32x4_t sum = {biases[i]};
const auto row = reinterpret_cast<const int8x16_t*>(&weights[offset]);
for (IndexType j = 0; j < NumChunks; ++j)
{
sum = vdotq_s32(sum, inputVector[j], row[j]);
}
output[i] = vaddvq_s32(sum);
#elif defined(USE_NEON) #elif defined(USE_NEON)
int32x4_t sum = {biases[i]}; int32x4_t sum = {biases[i]};
const auto row = reinterpret_cast<const int8x8_t*>(&weights[offset]); const auto row = reinterpret_cast<const int8x8_t*>(&weights[offset]);
for (IndexType j = 0; j < NumChunks; ++j) for (IndexType j = 0; j < NumChunks; ++j)
@@ -127,7 +120,8 @@ static void affine_transform_non_ssse3(std::int32_t* output,
} }
#endif #endif
} }
#endif
#endif // !ENABLE_SEQ_OPT
template<IndexType InDims, IndexType OutDims> template<IndexType InDims, IndexType OutDims>
class AffineTransform { class AffineTransform {
@@ -162,7 +156,7 @@ class AffineTransform {
} }
static constexpr IndexType get_weight_index(IndexType i) { static constexpr IndexType get_weight_index(IndexType i) {
#if defined(USE_SSSE3) #ifdef ENABLE_SEQ_OPT
return get_weight_index_scrambled(i); return get_weight_index_scrambled(i);
#else #else
return i; return i;
@@ -190,29 +184,28 @@ class AffineTransform {
// Forward propagation // Forward propagation
void propagate(const InputType* input, OutputType* output) const { void propagate(const InputType* input, OutputType* output) const {
#if defined(USE_SSSE3) #ifdef ENABLE_SEQ_OPT
if constexpr (OutputDimensions > 1) if constexpr (OutputDimensions > 1)
{ {
#if defined(USE_AVX512) #if defined(USE_AVX512)
using vec_t = __m512i; using vec_t = __m512i;
#define vec_setzero _mm512_setzero_si512
#define vec_set_32 _mm512_set1_epi32 #define vec_set_32 _mm512_set1_epi32
#define vec_add_dpbusd_32 Simd::m512_add_dpbusd_epi32 #define vec_add_dpbusd_32 Simd::m512_add_dpbusd_epi32
#define vec_hadd Simd::m512_hadd
#elif defined(USE_AVX2) #elif defined(USE_AVX2)
using vec_t = __m256i; using vec_t = __m256i;
#define vec_setzero _mm256_setzero_si256
#define vec_set_32 _mm256_set1_epi32 #define vec_set_32 _mm256_set1_epi32
#define vec_add_dpbusd_32 Simd::m256_add_dpbusd_epi32 #define vec_add_dpbusd_32 Simd::m256_add_dpbusd_epi32
#define vec_hadd Simd::m256_hadd
#elif defined(USE_SSSE3) #elif defined(USE_SSSE3)
using vec_t = __m128i; using vec_t = __m128i;
#define vec_setzero _mm_setzero_si128
#define vec_set_32 _mm_set1_epi32 #define vec_set_32 _mm_set1_epi32
#define vec_add_dpbusd_32 Simd::m128_add_dpbusd_epi32 #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_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 #endif
static constexpr IndexType OutputSimdWidth = sizeof(vec_t) / sizeof(OutputType); static constexpr IndexType OutputSimdWidth = sizeof(vec_t) / sizeof(OutputType);
@@ -242,28 +235,33 @@ class AffineTransform {
for (IndexType k = 0; k < NumRegs; ++k) for (IndexType k = 0; k < NumRegs; ++k)
outptr[k] = acc[k]; outptr[k] = acc[k];
#undef vec_setzero
#undef vec_set_32 #undef vec_set_32
#undef vec_add_dpbusd_32 #undef vec_add_dpbusd_32
#undef vec_hadd
} }
else if constexpr (OutputDimensions == 1) else if constexpr (OutputDimensions == 1)
{ {
// We cannot use AVX512 for the last layer because there are only 32 inputs // We cannot use AVX512 for the last layer because there are only 32 inputs
// and the buffer is not padded to 64 elements. // and the buffer is not padded to 64 elements.
#if defined(USE_AVX2) #if defined(USE_AVX2)
using vec_t = __m256i; using vec_t = __m256i;
#define vec_setzero _mm256_setzero_si256 #define vec_setzero() _mm256_setzero_si256()
#define vec_set_32 _mm256_set1_epi32 #define vec_set_32 _mm256_set1_epi32
#define vec_add_dpbusd_32 Simd::m256_add_dpbusd_epi32 #define vec_add_dpbusd_32 Simd::m256_add_dpbusd_epi32
#define vec_hadd Simd::m256_hadd #define vec_hadd Simd::m256_hadd
#elif defined(USE_SSSE3) #elif defined(USE_SSSE3)
using vec_t = __m128i; using vec_t = __m128i;
#define vec_setzero _mm_setzero_si128 #define vec_setzero() _mm_setzero_si128()
#define vec_set_32 _mm_set1_epi32 #define vec_set_32 _mm_set1_epi32
#define vec_add_dpbusd_32 Simd::m128_add_dpbusd_epi32 #define vec_add_dpbusd_32 Simd::m128_add_dpbusd_epi32
#define vec_hadd Simd::m128_hadd #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_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))
#define vec_hadd Simd::neon_m128_hadd
#endif #endif
const auto inputVector = reinterpret_cast<const vec_t*>(input); const auto inputVector = reinterpret_cast<const vec_t*>(input);

View File

@@ -65,41 +65,37 @@ class ClippedReLU {
if constexpr (InputDimensions % SimdWidth == 0) if constexpr (InputDimensions % SimdWidth == 0)
{ {
constexpr IndexType NumChunks = InputDimensions / SimdWidth; constexpr IndexType NumChunks = InputDimensions / SimdWidth;
const __m256i Zero = _mm256_setzero_si256();
const __m256i Offsets = _mm256_set_epi32(7, 3, 6, 2, 5, 1, 4, 0); const __m256i Offsets = _mm256_set_epi32(7, 3, 6, 2, 5, 1, 4, 0);
const auto in = reinterpret_cast<const __m256i*>(input); const auto in = reinterpret_cast<const __m256i*>(input);
const auto out = reinterpret_cast<__m256i*>(output); const auto out = reinterpret_cast<__m256i*>(output);
for (IndexType i = 0; i < NumChunks; ++i) for (IndexType i = 0; i < NumChunks; ++i)
{ {
const __m256i words0 = const __m256i words0 =
_mm256_srai_epi16(_mm256_packs_epi32(_mm256_load_si256(&in[i * 4 + 0]), _mm256_srli_epi16(_mm256_packus_epi32(_mm256_load_si256(&in[i * 4 + 0]),
_mm256_load_si256(&in[i * 4 + 1])), _mm256_load_si256(&in[i * 4 + 1])),
WeightScaleBits); WeightScaleBits);
const __m256i words1 = const __m256i words1 =
_mm256_srai_epi16(_mm256_packs_epi32(_mm256_load_si256(&in[i * 4 + 2]), _mm256_srli_epi16(_mm256_packus_epi32(_mm256_load_si256(&in[i * 4 + 2]),
_mm256_load_si256(&in[i * 4 + 3])), _mm256_load_si256(&in[i * 4 + 3])),
WeightScaleBits); WeightScaleBits);
_mm256_store_si256( _mm256_store_si256(&out[i], _mm256_permutevar8x32_epi32(
&out[i], _mm256_permutevar8x32_epi32( _mm256_packs_epi16(words0, words1), Offsets));
_mm256_max_epi8(_mm256_packs_epi16(words0, words1), Zero), Offsets));
} }
} }
else else
{ {
constexpr IndexType NumChunks = InputDimensions / (SimdWidth / 2); constexpr IndexType NumChunks = InputDimensions / (SimdWidth / 2);
const __m128i Zero = _mm_setzero_si128();
const auto in = reinterpret_cast<const __m128i*>(input); const auto in = reinterpret_cast<const __m128i*>(input);
const auto out = reinterpret_cast<__m128i*>(output); const auto out = reinterpret_cast<__m128i*>(output);
for (IndexType i = 0; i < NumChunks; ++i) for (IndexType i = 0; i < NumChunks; ++i)
{ {
const __m128i words0 = _mm_srai_epi16( const __m128i words0 = _mm_srli_epi16(
_mm_packs_epi32(_mm_load_si128(&in[i * 4 + 0]), _mm_load_si128(&in[i * 4 + 1])), _mm_packus_epi32(_mm_load_si128(&in[i * 4 + 0]), _mm_load_si128(&in[i * 4 + 1])),
WeightScaleBits); WeightScaleBits);
const __m128i words1 = _mm_srai_epi16( const __m128i words1 = _mm_srli_epi16(
_mm_packs_epi32(_mm_load_si128(&in[i * 4 + 2]), _mm_load_si128(&in[i * 4 + 3])), _mm_packus_epi32(_mm_load_si128(&in[i * 4 + 2]), _mm_load_si128(&in[i * 4 + 3])),
WeightScaleBits); WeightScaleBits);
const __m128i packedbytes = _mm_packs_epi16(words0, words1); _mm_store_si128(&out[i], _mm_packs_epi16(words0, words1));
_mm_store_si128(&out[i], _mm_max_epi8(packedbytes, Zero));
} }
} }
constexpr IndexType Start = InputDimensions % SimdWidth == 0 constexpr IndexType Start = InputDimensions % SimdWidth == 0
@@ -109,9 +105,7 @@ class ClippedReLU {
#elif defined(USE_SSE2) #elif defined(USE_SSE2)
constexpr IndexType NumChunks = InputDimensions / SimdWidth; constexpr IndexType NumChunks = InputDimensions / SimdWidth;
#ifdef USE_SSE41 #ifndef USE_SSE41
const __m128i Zero = _mm_setzero_si128();
#else
const __m128i k0x80s = _mm_set1_epi8(-128); const __m128i k0x80s = _mm_set1_epi8(-128);
#endif #endif
@@ -119,6 +113,15 @@ class ClippedReLU {
const auto out = reinterpret_cast<__m128i*>(output); const auto out = reinterpret_cast<__m128i*>(output);
for (IndexType i = 0; i < NumChunks; ++i) 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( const __m128i words0 = _mm_srai_epi16(
_mm_packs_epi32(_mm_load_si128(&in[i * 4 + 0]), _mm_load_si128(&in[i * 4 + 1])), _mm_packs_epi32(_mm_load_si128(&in[i * 4 + 0]), _mm_load_si128(&in[i * 4 + 1])),
WeightScaleBits); WeightScaleBits);
@@ -126,15 +129,8 @@ class ClippedReLU {
_mm_packs_epi32(_mm_load_si128(&in[i * 4 + 2]), _mm_load_si128(&in[i * 4 + 3])), _mm_packs_epi32(_mm_load_si128(&in[i * 4 + 2]), _mm_load_si128(&in[i * 4 + 3])),
WeightScaleBits); WeightScaleBits);
const __m128i packedbytes = _mm_packs_epi16(words0, words1); const __m128i packedbytes = _mm_packs_epi16(words0, words1);
_mm_store_si128(&out[i], _mm_store_si128(&out[i], _mm_subs_epi8(_mm_adds_epi8(packedbytes, k0x80s), k0x80s));
#ifdef USE_SSE41
_mm_max_epi8(packedbytes, Zero)
#else
_mm_subs_epi8(_mm_adds_epi8(packedbytes, k0x80s), k0x80s)
#endif #endif
);
} }
constexpr IndexType Start = NumChunks * SimdWidth; constexpr IndexType Start = NumChunks * SimdWidth;

View File

@@ -43,39 +43,6 @@ namespace Stockfish::Simd {
return _mm512_reduce_add_epi32(sum) + bias; return _mm512_reduce_add_epi32(sum) + bias;
} }
/*
Parameters:
sum0 = [zmm0.i128[0], zmm0.i128[1], zmm0.i128[2], zmm0.i128[3]]
sum1 = [zmm1.i128[0], zmm1.i128[1], zmm1.i128[2], zmm1.i128[3]]
sum2 = [zmm2.i128[0], zmm2.i128[1], zmm2.i128[2], zmm2.i128[3]]
sum3 = [zmm3.i128[0], zmm3.i128[1], zmm3.i128[2], zmm3.i128[3]]
Returns:
ret = [
reduce_add_epi32(zmm0.i128[0]), reduce_add_epi32(zmm1.i128[0]), reduce_add_epi32(zmm2.i128[0]), reduce_add_epi32(zmm3.i128[0]),
reduce_add_epi32(zmm0.i128[1]), reduce_add_epi32(zmm1.i128[1]), reduce_add_epi32(zmm2.i128[1]), reduce_add_epi32(zmm3.i128[1]),
reduce_add_epi32(zmm0.i128[2]), reduce_add_epi32(zmm1.i128[2]), reduce_add_epi32(zmm2.i128[2]), reduce_add_epi32(zmm3.i128[2]),
reduce_add_epi32(zmm0.i128[3]), reduce_add_epi32(zmm1.i128[3]), reduce_add_epi32(zmm2.i128[3]), reduce_add_epi32(zmm3.i128[3])
]
*/
[[maybe_unused]] static __m512i
m512_hadd128x16_interleave(__m512i sum0, __m512i sum1, __m512i sum2, __m512i sum3) {
__m512i sum01a = _mm512_unpacklo_epi32(sum0, sum1);
__m512i sum01b = _mm512_unpackhi_epi32(sum0, sum1);
__m512i sum23a = _mm512_unpacklo_epi32(sum2, sum3);
__m512i sum23b = _mm512_unpackhi_epi32(sum2, sum3);
__m512i sum01 = _mm512_add_epi32(sum01a, sum01b);
__m512i sum23 = _mm512_add_epi32(sum23a, sum23b);
__m512i sum0123a = _mm512_unpacklo_epi64(sum01, sum23);
__m512i sum0123b = _mm512_unpackhi_epi64(sum01, sum23);
return _mm512_add_epi32(sum0123a, sum0123b);
}
[[maybe_unused]] static void m512_add_dpbusd_epi32(__m512i& acc, __m512i a, __m512i b) { [[maybe_unused]] static void m512_add_dpbusd_epi32(__m512i& acc, __m512i a, __m512i b) {
#if defined(USE_VNNI) #if defined(USE_VNNI)

455
src/nnue/network.cpp Normal file
View File

@@ -0,0 +1,455 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2024 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>
#include "../evaluate.h"
#include "../incbin/incbin.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"
namespace {
// 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
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, const 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,
AccumulatorCaches::Cache<FTDimensions>* cache) const {
// We manually align the arrays on the stack because with gcc < 9.3
// overaligning stack variables with alignas() doesn't work correctly.
constexpr uint64_t alignment = CacheLineSize;
#if defined(ALIGNAS_ON_STACK_VARIABLES_BROKEN)
TransformedFeatureType
transformedFeaturesUnaligned[FeatureTransformer<FTDimensions, nullptr>::BufferSize
+ alignment / sizeof(TransformedFeatureType)];
auto* transformedFeatures = align_ptr_up<alignment>(&transformedFeaturesUnaligned[0]);
#else
alignas(alignment) TransformedFeatureType
transformedFeatures[FeatureTransformer<FTDimensions, nullptr>::BufferSize];
#endif
ASSERT_ALIGNED(transformedFeatures, alignment);
const int bucket = (pos.count<ALL_PIECES>() - 1) / 4;
const auto psqt = featureTransformer->transform(pos, 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 {
if (evalfilePath.empty())
evalfilePath = evalFile.defaultName;
if (evalFile.current != evalfilePath)
{
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.";
sync_cout << "info string ERROR: " << msg1 << sync_endl;
sync_cout << "info string ERROR: " << msg2 << sync_endl;
sync_cout << "info string ERROR: " << msg3 << sync_endl;
sync_cout << "info string ERROR: " << msg4 << sync_endl;
sync_cout << "info string ERROR: " << msg5 << sync_endl;
exit(EXIT_FAILURE);
}
size_t size = sizeof(*featureTransformer) + sizeof(Arch) * LayerStacks;
sync_cout << "info string NNUE evaluation using " << evalfilePath << " ("
<< size / (1024 * 1024) << "MiB, (" << featureTransformer->InputDimensions << ", "
<< network[0].TransformedFeatureDimensions << ", " << network[0].FC_0_OUTPUTS << ", "
<< network[0].FC_1_OUTPUTS << ", 1))" << sync_endl;
}
template<typename Arch, typename Transformer>
void Network<Arch, Transformer>::hint_common_access(
const Position& pos, AccumulatorCaches::Cache<FTDimensions>* cache) const {
featureTransformer->hint_common_access(pos, cache);
}
template<typename Arch, typename Transformer>
NnueEvalTrace
Network<Arch, Transformer>::trace_evaluate(const Position& pos,
AccumulatorCaches::Cache<FTDimensions>* cache) const {
// We manually align the arrays on the stack because with gcc < 9.3
// overaligning stack variables with alignas() doesn't work correctly.
constexpr uint64_t alignment = CacheLineSize;
#if defined(ALIGNAS_ON_STACK_VARIABLES_BROKEN)
TransformedFeatureType
transformedFeaturesUnaligned[FeatureTransformer<FTDimensions, nullptr>::BufferSize
+ alignment / sizeof(TransformedFeatureType)];
auto* transformedFeatures = align_ptr_up<alignment>(&transformedFeaturesUnaligned[0]);
#else
alignas(alignment) TransformedFeatureType
transformedFeatures[FeatureTransformer<FTDimensions, nullptr>::BufferSize];
#endif
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, 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 instantiation
template class Network<
NetworkArchitecture<TransformedFeatureDimensionsBig, L2Big, L3Big>,
FeatureTransformer<TransformedFeatureDimensionsBig, &StateInfo::accumulatorBig>>;
template class Network<
NetworkArchitecture<TransformedFeatureDimensionsSmall, L2Small, L3Small>,
FeatureTransformer<TransformedFeatureDimensionsSmall, &StateInfo::accumulatorSmall>>;
} // namespace Stockfish::Eval::NNUE

132
src/nnue/network.h Normal file
View File

@@ -0,0 +1,132 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2024 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 <iostream>
#include <optional>
#include <string>
#include <tuple>
#include <utility>
#include "../memory.h"
#include "../position.h"
#include "../types.h"
#include "nnue_accumulator.h"
#include "nnue_architecture.h"
#include "nnue_feature_transformer.h"
#include "nnue_misc.h"
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,
AccumulatorCaches::Cache<FTDimensions>* cache) const;
void hint_common_access(const Position& pos,
AccumulatorCaches::Cache<FTDimensions>* cache) const;
void verify(std::string evalfilePath) const;
NnueEvalTrace trace_evaluate(const Position& pos,
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;
};
// Definitions of the network types
using SmallFeatureTransformer =
FeatureTransformer<TransformedFeatureDimensionsSmall, &StateInfo::accumulatorSmall>;
using SmallNetworkArchitecture =
NetworkArchitecture<TransformedFeatureDimensionsSmall, L2Small, L3Small>;
using BigFeatureTransformer =
FeatureTransformer<TransformedFeatureDimensionsBig, &StateInfo::accumulatorBig>;
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

@@ -28,12 +28,76 @@
namespace Stockfish::Eval::NNUE { namespace Stockfish::Eval::NNUE {
using BiasType = std::int16_t;
using PSQTWeightType = std::int32_t;
using IndexType = std::uint32_t;
// Class that holds the result of affine transformation of input features // Class that holds the result of affine transformation of input features
template<IndexType Size> template<IndexType Size>
struct alignas(CacheLineSize) Accumulator { struct alignas(CacheLineSize) Accumulator {
std::int16_t accumulation[2][Size]; std::int16_t accumulation[COLOR_NB][Size];
std::int32_t psqtAccumulation[2][PSQTBuckets]; std::int32_t psqtAccumulation[COLOR_NB][PSQTBuckets];
bool computed[2]; bool computed[COLOR_NB];
};
// 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);
}
void clear(const BiasType* biases) {
for (auto& entry : entries)
entry.clear(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;
}; };
} // namespace Stockfish::Eval::NNUE } // namespace Stockfish::Eval::NNUE

View File

@@ -37,13 +37,8 @@ namespace Stockfish::Eval::NNUE {
// Input features used in evaluation function // Input features used in evaluation function
using FeatureSet = Features::HalfKAv2_hm; using FeatureSet = Features::HalfKAv2_hm;
enum NetSize : int {
Big,
Small
};
// Number of input feature dimensions after conversion // Number of input feature dimensions after conversion
constexpr IndexType TransformedFeatureDimensionsBig = 2560; constexpr IndexType TransformedFeatureDimensionsBig = 3072;
constexpr int L2Big = 15; constexpr int L2Big = 15;
constexpr int L3Big = 32; constexpr int L3Big = 32;
@@ -55,7 +50,7 @@ constexpr IndexType PSQTBuckets = 8;
constexpr IndexType LayerStacks = 8; constexpr IndexType LayerStacks = 8;
template<IndexType L1, int L2, int L3> template<IndexType L1, int L2, int L3>
struct Network { struct NetworkArchitecture {
static constexpr IndexType TransformedFeatureDimensions = L1; static constexpr IndexType TransformedFeatureDimensions = L1;
static constexpr int FC_0_OUTPUTS = L2; static constexpr int FC_0_OUTPUTS = L2;
static constexpr int FC_1_OUTPUTS = L3; static constexpr int FC_1_OUTPUTS = L3;

View File

@@ -55,15 +55,14 @@ using psqt_vec_t = __m256i;
#define vec_store(a, b) _mm512_store_si512(a, b) #define vec_store(a, b) _mm512_store_si512(a, b)
#define vec_add_16(a, b) _mm512_add_epi16(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_sub_16(a, b) _mm512_sub_epi16(a, b)
#define vec_mul_16(a, b) _mm512_mullo_epi16(a, b) #define vec_mulhi_16(a, b) _mm512_mulhi_epi16(a, b)
#define vec_zero() _mm512_setzero_epi32() #define vec_zero() _mm512_setzero_epi32()
#define vec_set_16(a) _mm512_set1_epi16(a) #define vec_set_16(a) _mm512_set1_epi16(a)
#define vec_max_16(a, b) _mm512_max_epi16(a, b) #define vec_max_16(a, b) _mm512_max_epi16(a, b)
#define vec_min_16(a, b) _mm512_min_epi16(a, b) #define vec_min_16(a, b) _mm512_min_epi16(a, b)
inline vec_t vec_msb_pack_16(vec_t a, vec_t b) { #define vec_slli_16(a, b) _mm512_slli_epi16(a, b)
vec_t compacted = _mm512_packs_epi16(_mm512_srli_epi16(a, 7), _mm512_srli_epi16(b, 7)); // Inverse permuted at load time
return _mm512_permutexvar_epi64(_mm512_setr_epi64(0, 2, 4, 6, 1, 3, 5, 7), compacted); #define vec_packus_16(a, b) _mm512_packus_epi16(a, b)
}
#define vec_load_psqt(a) _mm256_load_si256(a) #define vec_load_psqt(a) _mm256_load_si256(a)
#define vec_store_psqt(a, b) _mm256_store_si256(a, b) #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_add_psqt_32(a, b) _mm256_add_epi32(a, b)
@@ -79,15 +78,14 @@ using psqt_vec_t = __m256i;
#define vec_store(a, b) _mm256_store_si256(a, b) #define vec_store(a, b) _mm256_store_si256(a, b)
#define vec_add_16(a, b) _mm256_add_epi16(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_sub_16(a, b) _mm256_sub_epi16(a, b)
#define vec_mul_16(a, b) _mm256_mullo_epi16(a, b) #define vec_mulhi_16(a, b) _mm256_mulhi_epi16(a, b)
#define vec_zero() _mm256_setzero_si256() #define vec_zero() _mm256_setzero_si256()
#define vec_set_16(a) _mm256_set1_epi16(a) #define vec_set_16(a) _mm256_set1_epi16(a)
#define vec_max_16(a, b) _mm256_max_epi16(a, b) #define vec_max_16(a, b) _mm256_max_epi16(a, b)
#define vec_min_16(a, b) _mm256_min_epi16(a, b) #define vec_min_16(a, b) _mm256_min_epi16(a, b)
inline vec_t vec_msb_pack_16(vec_t a, vec_t b) { #define vec_slli_16(a, b) _mm256_slli_epi16(a, b)
vec_t compacted = _mm256_packs_epi16(_mm256_srli_epi16(a, 7), _mm256_srli_epi16(b, 7)); // Inverse permuted at load time
return _mm256_permute4x64_epi64(compacted, 0b11011000); #define vec_packus_16(a, b) _mm256_packus_epi16(a, b)
}
#define vec_load_psqt(a) _mm256_load_si256(a) #define vec_load_psqt(a) _mm256_load_si256(a)
#define vec_store_psqt(a, b) _mm256_store_si256(a, b) #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_add_psqt_32(a, b) _mm256_add_epi32(a, b)
@@ -103,12 +101,13 @@ using psqt_vec_t = __m128i;
#define vec_store(a, b) *(a) = (b) #define vec_store(a, b) *(a) = (b)
#define vec_add_16(a, b) _mm_add_epi16(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_sub_16(a, b) _mm_sub_epi16(a, b)
#define vec_mul_16(a, b) _mm_mullo_epi16(a, b) #define vec_mulhi_16(a, b) _mm_mulhi_epi16(a, b)
#define vec_zero() _mm_setzero_si128() #define vec_zero() _mm_setzero_si128()
#define vec_set_16(a) _mm_set1_epi16(a) #define vec_set_16(a) _mm_set1_epi16(a)
#define vec_max_16(a, b) _mm_max_epi16(a, b) #define vec_max_16(a, b) _mm_max_epi16(a, b)
#define vec_min_16(a, b) _mm_min_epi16(a, b) #define vec_min_16(a, b) _mm_min_epi16(a, b)
#define vec_msb_pack_16(a, b) _mm_packs_epi16(_mm_srli_epi16(a, 7), _mm_srli_epi16(b, 7)) #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_load_psqt(a) (*(a))
#define vec_store_psqt(a, b) *(a) = (b) #define vec_store_psqt(a, b) *(a) = (b)
#define vec_add_psqt_32(a, b) _mm_add_epi32(a, b) #define vec_add_psqt_32(a, b) _mm_add_epi32(a, b)
@@ -124,18 +123,14 @@ using psqt_vec_t = int32x4_t;
#define vec_store(a, b) *(a) = (b) #define vec_store(a, b) *(a) = (b)
#define vec_add_16(a, b) vaddq_s16(a, b) #define vec_add_16(a, b) vaddq_s16(a, b)
#define vec_sub_16(a, b) vsubq_s16(a, b) #define vec_sub_16(a, b) vsubq_s16(a, b)
#define vec_mul_16(a, b) vmulq_s16(a, b) #define vec_mulhi_16(a, b) vqdmulhq_s16(a, b)
#define vec_zero() \ #define vec_zero() \
vec_t { 0 } vec_t { 0 }
#define vec_set_16(a) vdupq_n_s16(a) #define vec_set_16(a) vdupq_n_s16(a)
#define vec_max_16(a, b) vmaxq_s16(a, b) #define vec_max_16(a, b) vmaxq_s16(a, b)
#define vec_min_16(a, b) vminq_s16(a, b) #define vec_min_16(a, b) vminq_s16(a, b)
inline vec_t vec_msb_pack_16(vec_t a, vec_t b) { #define vec_slli_16(a, b) vshlq_s16(a, vec_set_16(b))
const int8x8_t shifta = vshrn_n_s16(a, 7); #define vec_packus_16(a, b) reinterpret_cast<vec_t>(vcombine_u8(vqmovun_s16(a), vqmovun_s16(b)))
const int8x8_t shiftb = vshrn_n_s16(b, 7);
const int8x16_t compacted = vcombine_s8(shifta, shiftb);
return *reinterpret_cast<const vec_t*>(&compacted);
}
#define vec_load_psqt(a) (*(a)) #define vec_load_psqt(a) (*(a))
#define vec_store_psqt(a, b) *(a) = (b) #define vec_store_psqt(a, b) *(a) = (b)
#define vec_add_psqt_32(a, b) vaddq_s32(a, b) #define vec_add_psqt_32(a, b) vaddq_s32(a, b)
@@ -197,10 +192,10 @@ template<IndexType TransformedFeatureDimensions,
Accumulator<TransformedFeatureDimensions> StateInfo::*accPtr> Accumulator<TransformedFeatureDimensions> StateInfo::*accPtr>
class FeatureTransformer { class FeatureTransformer {
private:
// Number of output dimensions for one side // Number of output dimensions for one side
static constexpr IndexType HalfDimensions = TransformedFeatureDimensions; static constexpr IndexType HalfDimensions = TransformedFeatureDimensions;
private:
#ifdef VECTOR #ifdef VECTOR
static constexpr int NumRegs = static constexpr int NumRegs =
BestRegisterCount<vec_t, WeightType, TransformedFeatureDimensions, NumRegistersSIMD>(); BestRegisterCount<vec_t, WeightType, TransformedFeatureDimensions, NumRegistersSIMD>();
@@ -229,6 +224,73 @@ class FeatureTransformer {
return FeatureSet::HashValue ^ (OutputDimensions * 2); return FeatureSet::HashValue ^ (OutputDimensions * 2);
} }
static constexpr void order_packs([[maybe_unused]] uint64_t* v) {
#if defined(USE_AVX512) // _mm512_packs_epi16 ordering
uint64_t tmp0 = v[2], tmp1 = v[3];
v[2] = v[8], v[3] = v[9];
v[8] = v[4], v[9] = v[5];
v[4] = tmp0, v[5] = tmp1;
tmp0 = v[6], tmp1 = v[7];
v[6] = v[10], v[7] = v[11];
v[10] = v[12], v[11] = v[13];
v[12] = tmp0, v[13] = tmp1;
#elif defined(USE_AVX2) // _mm256_packs_epi16 ordering
std::swap(v[2], v[4]);
std::swap(v[3], v[5]);
#endif
}
static constexpr void inverse_order_packs([[maybe_unused]] uint64_t* v) {
#if defined(USE_AVX512) // Inverse _mm512_packs_epi16 ordering
uint64_t tmp0 = v[2], tmp1 = v[3];
v[2] = v[4], v[3] = v[5];
v[4] = v[8], v[5] = v[9];
v[8] = tmp0, v[9] = tmp1;
tmp0 = v[6], tmp1 = v[7];
v[6] = v[12], v[7] = v[13];
v[12] = v[10], v[13] = v[11];
v[10] = tmp0, v[11] = tmp1;
#elif defined(USE_AVX2) // Inverse _mm256_packs_epi16 ordering
std::swap(v[2], v[4]);
std::swap(v[3], v[5]);
#endif
}
void permute_weights([[maybe_unused]] void (*order_fn)(uint64_t*)) const {
#if defined(USE_AVX2)
#if defined(USE_AVX512)
constexpr IndexType di = 16;
#else
constexpr IndexType di = 8;
#endif
uint64_t* b = reinterpret_cast<uint64_t*>(const_cast<BiasType*>(&biases[0]));
for (IndexType i = 0; i < HalfDimensions * sizeof(BiasType) / sizeof(uint64_t); i += di)
order_fn(&b[i]);
for (IndexType j = 0; j < InputDimensions; ++j)
{
uint64_t* w =
reinterpret_cast<uint64_t*>(const_cast<WeightType*>(&weights[j * HalfDimensions]));
for (IndexType i = 0; i < HalfDimensions * sizeof(WeightType) / sizeof(uint64_t);
i += di)
order_fn(&w[i]);
}
#endif
}
inline void scale_weights(bool read) const {
for (IndexType j = 0; j < InputDimensions; ++j)
{
WeightType* w = const_cast<WeightType*>(&weights[j * HalfDimensions]);
for (IndexType i = 0; i < HalfDimensions; ++i)
w[i] = read ? w[i] * 2 : w[i] / 2;
}
BiasType* b = const_cast<BiasType*>(biases);
for (IndexType i = 0; i < HalfDimensions; ++i)
b[i] = read ? b[i] * 2 : b[i] / 2;
}
// Read network parameters // Read network parameters
bool read_parameters(std::istream& stream) { bool read_parameters(std::istream& stream) {
@@ -236,32 +298,41 @@ class FeatureTransformer {
read_leb_128<WeightType>(stream, weights, HalfDimensions * InputDimensions); read_leb_128<WeightType>(stream, weights, HalfDimensions * InputDimensions);
read_leb_128<PSQTWeightType>(stream, psqtWeights, PSQTBuckets * InputDimensions); read_leb_128<PSQTWeightType>(stream, psqtWeights, PSQTBuckets * InputDimensions);
permute_weights(inverse_order_packs);
scale_weights(true);
return !stream.fail(); return !stream.fail();
} }
// Write network parameters // Write network parameters
bool write_parameters(std::ostream& stream) const { bool write_parameters(std::ostream& stream) const {
permute_weights(order_packs);
scale_weights(false);
write_leb_128<BiasType>(stream, biases, HalfDimensions); write_leb_128<BiasType>(stream, biases, HalfDimensions);
write_leb_128<WeightType>(stream, weights, HalfDimensions * InputDimensions); write_leb_128<WeightType>(stream, weights, HalfDimensions * InputDimensions);
write_leb_128<PSQTWeightType>(stream, psqtWeights, PSQTBuckets * InputDimensions); write_leb_128<PSQTWeightType>(stream, psqtWeights, PSQTBuckets * InputDimensions);
permute_weights(inverse_order_packs);
scale_weights(true);
return !stream.fail(); return !stream.fail();
} }
// Convert input features // Convert input features
std::int32_t transform(const Position& pos, OutputType* output, int bucket) const { std::int32_t transform(const Position& pos,
update_accumulator<WHITE>(pos); AccumulatorCaches::Cache<HalfDimensions>* cache,
update_accumulator<BLACK>(pos); OutputType* output,
int bucket) const {
update_accumulator<WHITE>(pos, cache);
update_accumulator<BLACK>(pos, cache);
const Color perspectives[2] = {pos.side_to_move(), ~pos.side_to_move()}; const Color perspectives[2] = {pos.side_to_move(), ~pos.side_to_move()};
const auto& accumulation = (pos.state()->*accPtr).accumulation;
const auto& psqtAccumulation = (pos.state()->*accPtr).psqtAccumulation; const auto& psqtAccumulation = (pos.state()->*accPtr).psqtAccumulation;
const auto psqt =
const auto psqt =
(psqtAccumulation[perspectives[0]][bucket] - psqtAccumulation[perspectives[1]][bucket]) (psqtAccumulation[perspectives[0]][bucket] - psqtAccumulation[perspectives[1]][bucket])
/ 2; / 2;
const auto& accumulation = (pos.state()->*accPtr).accumulation;
for (IndexType p = 0; p < 2; ++p) for (IndexType p = 0; p < 2; ++p)
{ {
@@ -273,25 +344,87 @@ class FeatureTransformer {
static_assert((HalfDimensions / 2) % OutputChunkSize == 0); static_assert((HalfDimensions / 2) % OutputChunkSize == 0);
constexpr IndexType NumOutputChunks = HalfDimensions / 2 / OutputChunkSize; constexpr IndexType NumOutputChunks = HalfDimensions / 2 / OutputChunkSize;
vec_t Zero = vec_zero(); const vec_t Zero = vec_zero();
vec_t One = vec_set_16(127); const vec_t One = vec_set_16(127 * 2);
const vec_t* in0 = reinterpret_cast<const vec_t*>(&(accumulation[perspectives[p]][0])); const vec_t* in0 = reinterpret_cast<const vec_t*>(&(accumulation[perspectives[p]][0]));
const vec_t* in1 = const vec_t* in1 =
reinterpret_cast<const vec_t*>(&(accumulation[perspectives[p]][HalfDimensions / 2])); reinterpret_cast<const vec_t*>(&(accumulation[perspectives[p]][HalfDimensions / 2]));
vec_t* out = reinterpret_cast<vec_t*>(output + offset); vec_t* out = reinterpret_cast<vec_t*>(output + offset);
// 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.
// 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.
// 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) for (IndexType j = 0; j < NumOutputChunks; ++j)
{ {
const vec_t sum0a = vec_max_16(vec_min_16(in0[j * 2 + 0], One), Zero); const vec_t sum0a =
const vec_t sum0b = vec_max_16(vec_min_16(in0[j * 2 + 1], One), Zero); vec_slli_16(vec_max_16(vec_min_16(in0[j * 2 + 0], One), Zero), shift);
const vec_t sum1a = vec_max_16(vec_min_16(in1[j * 2 + 0], One), Zero); const vec_t sum0b =
const vec_t sum1b = vec_max_16(vec_min_16(in1[j * 2 + 1], One), Zero); 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_mul_16(sum0a, sum1a); const vec_t pa = vec_mulhi_16(sum0a, sum1a);
const vec_t pb = vec_mul_16(sum0b, sum1b); const vec_t pb = vec_mulhi_16(sum0b, sum1b);
out[j] = vec_msb_pack_16(pa, pb); out[j] = vec_packus_16(pa, pb);
} }
#else #else
@@ -301,9 +434,9 @@ class FeatureTransformer {
BiasType sum0 = accumulation[static_cast<int>(perspectives[p])][j + 0]; BiasType sum0 = accumulation[static_cast<int>(perspectives[p])][j + 0];
BiasType sum1 = BiasType sum1 =
accumulation[static_cast<int>(perspectives[p])][j + HalfDimensions / 2]; accumulation[static_cast<int>(perspectives[p])][j + HalfDimensions / 2];
sum0 = std::clamp<BiasType>(sum0, 0, 127); sum0 = std::clamp<BiasType>(sum0, 0, 127 * 2);
sum1 = std::clamp<BiasType>(sum1, 0, 127); sum1 = std::clamp<BiasType>(sum1, 0, 127 * 2);
output[offset + j] = static_cast<OutputType>(unsigned(sum0 * sum1) / 128); output[offset + j] = static_cast<OutputType>(unsigned(sum0 * sum1) / 512);
} }
#endif #endif
@@ -312,9 +445,10 @@ class FeatureTransformer {
return psqt; return psqt;
} // end of function transform() } // end of function transform()
void hint_common_access(const Position& pos) const { void hint_common_access(const Position& pos,
hint_common_access_for_perspective<WHITE>(pos); AccumulatorCaches::Cache<HalfDimensions>* cache) const {
hint_common_access_for_perspective<BLACK>(pos); hint_common_access_for_perspective<WHITE>(pos, cache);
hint_common_access_for_perspective<BLACK>(pos, cache);
} }
private: private:
@@ -338,31 +472,33 @@ class FeatureTransformer {
return {st, next}; return {st, next};
} }
// NOTE: The parameter states_to_update is an array of position states, ending with nullptr. // NOTE: The parameter states_to_update is an array of position states.
// All states must be sequential, that is states_to_update[i] must either be reachable // All states must be sequential, that is states_to_update[i] must
// by repeatedly applying ->previous from states_to_update[i+1] or // either be reachable by repeatedly applying ->previous from
// states_to_update[i] == nullptr. // states_to_update[i+1], and computed_st must be reachable by
// computed_st must be reachable by repeatedly applying ->previous on // repeatedly applying ->previous on states_to_update[0].
// states_to_update[0], if not nullptr.
template<Color Perspective, size_t N> template<Color Perspective, size_t N>
void update_accumulator_incremental(const Position& pos, void update_accumulator_incremental(const Position& pos,
StateInfo* computed_st, StateInfo* computed_st,
StateInfo* states_to_update[N]) const { StateInfo* states_to_update[N]) const {
static_assert(N > 0); static_assert(N > 0);
assert(states_to_update[N - 1] == nullptr); assert([&]() {
for (size_t i = 0; i < N; ++i)
{
if (states_to_update[i] == nullptr)
return false;
}
return true;
}());
#ifdef VECTOR #ifdef VECTOR
// Gcc-10.2 unnecessarily spills AVX2 registers if this array // Gcc-10.2 unnecessarily spills AVX2 registers if this array
// is defined in the VECTOR code below, once in each branch // is defined in the VECTOR code below, once in each branch.
vec_t acc[NumRegs]; vec_t acc[NumRegs];
psqt_vec_t psqt[NumPsqtRegs]; psqt_vec_t psqt[NumPsqtRegs];
#endif #endif
if (states_to_update[0] == nullptr)
return;
// Update incrementally going back through states_to_update. // Update incrementally going back through states_to_update.
// Gather all features to be updated. // Gather all features to be updated.
const Square ksq = pos.square<KING>(Perspective); const Square ksq = pos.square<KING>(Perspective);
@@ -370,36 +506,26 @@ class FeatureTransformer {
// That might depend on the feature set and generally relies on the // That might depend on the feature set and generally relies on the
// feature set's update cost calculation to be correct and never allow // feature set's update cost calculation to be correct and never allow
// updates with more added/removed features than MaxActiveDimensions. // updates with more added/removed features than MaxActiveDimensions.
FeatureSet::IndexList removed[N - 1], added[N - 1]; FeatureSet::IndexList removed[N], added[N];
for (int i = N - 1; i >= 0; --i)
{ {
int i = (states_to_update[i]->*accPtr).computed[Perspective] = true;
N
- 2; // Last potential state to update. Skip last element because it must be nullptr.
while (states_to_update[i] == nullptr)
--i;
StateInfo* st2 = states_to_update[i]; const StateInfo* end_state = i == 0 ? computed_st : states_to_update[i - 1];
for (; i >= 0; --i) for (StateInfo* st2 = states_to_update[i]; st2 != end_state; st2 = st2->previous)
{ FeatureSet::append_changed_indices<Perspective>(ksq, st2->dirtyPiece, removed[i],
(states_to_update[i]->*accPtr).computed[Perspective] = true; added[i]);
const StateInfo* end_state = i == 0 ? computed_st : states_to_update[i - 1];
for (; st2 != end_state; st2 = st2->previous)
FeatureSet::append_changed_indices<Perspective>(ksq, st2->dirtyPiece,
removed[i], added[i]);
}
} }
StateInfo* st = computed_st; StateInfo* st = computed_st;
// Now update the accumulators listed in states_to_update[], where the last element is a sentinel. // Now update the accumulators listed in states_to_update[],
// where the last element is a sentinel.
#ifdef VECTOR #ifdef VECTOR
if (states_to_update[1] == nullptr && (removed[0].size() == 1 || removed[0].size() == 2) if (N == 1 && (removed[0].size() == 1 || removed[0].size() == 2) && added[0].size() == 1)
&& added[0].size() == 1)
{ {
assert(states_to_update[0]); assert(states_to_update[0]);
@@ -469,7 +595,7 @@ class FeatureTransformer {
for (IndexType k = 0; k < NumRegs; ++k) for (IndexType k = 0; k < NumRegs; ++k)
acc[k] = vec_load(&accTileIn[k]); acc[k] = vec_load(&accTileIn[k]);
for (IndexType i = 0; states_to_update[i]; ++i) for (IndexType i = 0; i < N; ++i)
{ {
// Difference calculation for the deactivated features // Difference calculation for the deactivated features
for (const auto index : removed[i]) for (const auto index : removed[i])
@@ -505,7 +631,7 @@ class FeatureTransformer {
for (std::size_t k = 0; k < NumPsqtRegs; ++k) for (std::size_t k = 0; k < NumPsqtRegs; ++k)
psqt[k] = vec_load_psqt(&accTilePsqtIn[k]); psqt[k] = vec_load_psqt(&accTilePsqtIn[k]);
for (IndexType i = 0; states_to_update[i]; ++i) for (IndexType i = 0; i < N; ++i)
{ {
// Difference calculation for the deactivated features // Difference calculation for the deactivated features
for (const auto index : removed[i]) for (const auto index : removed[i])
@@ -535,7 +661,7 @@ class FeatureTransformer {
} }
} }
#else #else
for (IndexType i = 0; states_to_update[i]; ++i) for (IndexType i = 0; i < N; ++i)
{ {
std::memcpy((states_to_update[i]->*accPtr).accumulation[Perspective], std::memcpy((states_to_update[i]->*accPtr).accumulation[Perspective],
(st->*accPtr).accumulation[Perspective], HalfDimensions * sizeof(BiasType)); (st->*accPtr).accumulation[Perspective], HalfDimensions * sizeof(BiasType));
@@ -550,7 +676,6 @@ class FeatureTransformer {
for (const auto index : removed[i]) for (const auto index : removed[i])
{ {
const IndexType offset = HalfDimensions * index; const IndexType offset = HalfDimensions * index;
for (IndexType j = 0; j < HalfDimensions; ++j) for (IndexType j = 0; j < HalfDimensions; ++j)
(st->*accPtr).accumulation[Perspective][j] -= weights[offset + j]; (st->*accPtr).accumulation[Perspective][j] -= weights[offset + j];
@@ -563,7 +688,6 @@ class FeatureTransformer {
for (const auto index : added[i]) for (const auto index : added[i])
{ {
const IndexType offset = HalfDimensions * index; const IndexType offset = HalfDimensions * index;
for (IndexType j = 0; j < HalfDimensions; ++j) for (IndexType j = 0; j < HalfDimensions; ++j)
(st->*accPtr).accumulation[Perspective][j] += weights[offset + j]; (st->*accPtr).accumulation[Perspective][j] += weights[offset + j];
@@ -576,31 +700,78 @@ class FeatureTransformer {
} }
template<Color Perspective> template<Color Perspective>
void update_accumulator_refresh(const Position& pos) const { void update_accumulator_refresh_cache(const Position& pos,
#ifdef VECTOR AccumulatorCaches::Cache<HalfDimensions>* cache) const {
// Gcc-10.2 unnecessarily spills AVX2 registers if this array assert(cache != nullptr);
// is defined in the VECTOR code below, once in each branch
vec_t acc[NumRegs]; Square ksq = pos.square<KING>(Perspective);
psqt_vec_t psqt[NumPsqtRegs]; auto& entry = (*cache)[ksq][Perspective];
#endif 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));
}
}
}
// Refresh the accumulator
// Could be extracted to a separate function because it's done in 2 places,
// but it's unclear if compilers would correctly handle register allocation.
auto& accumulator = pos.state()->*accPtr; auto& accumulator = pos.state()->*accPtr;
accumulator.computed[Perspective] = true; accumulator.computed[Perspective] = true;
FeatureSet::IndexList active;
FeatureSet::append_active_indices<Perspective>(pos, active);
#ifdef VECTOR #ifdef VECTOR
vec_t acc[NumRegs];
psqt_vec_t psqt[NumPsqtRegs];
for (IndexType j = 0; j < HalfDimensions / TileHeight; ++j) for (IndexType j = 0; j < HalfDimensions / TileHeight; ++j)
{ {
auto biasesTile = reinterpret_cast<const vec_t*>(&biases[j * TileHeight]); auto accTile =
for (IndexType k = 0; k < NumRegs; ++k) reinterpret_cast<vec_t*>(&accumulator.accumulation[Perspective][j * TileHeight]);
acc[k] = biasesTile[k]; auto entryTile = reinterpret_cast<vec_t*>(&entry.accumulation[j * TileHeight]);
for (const auto index : active) for (IndexType k = 0; k < NumRegs; ++k)
acc[k] = entryTile[k];
int i = 0;
for (; i < int(std::min(removed.size(), added.size())); ++i)
{ {
IndexType indexR = removed[i];
const IndexType offsetR = HalfDimensions * indexR + j * TileHeight;
auto columnR = reinterpret_cast<const vec_t*>(&weights[offsetR]);
IndexType indexA = added[i];
const IndexType offsetA = HalfDimensions * indexA + j * TileHeight;
auto columnA = reinterpret_cast<const vec_t*>(&weights[offsetA]);
for (unsigned k = 0; k < NumRegs; ++k)
acc[k] = vec_add_16(acc[k], vec_sub_16(columnA[k], columnR[k]));
}
for (; i < int(removed.size()); ++i)
{
IndexType index = removed[i];
const IndexType offset = HalfDimensions * index + j * TileHeight;
auto column = reinterpret_cast<const vec_t*>(&weights[offset]);
for (unsigned k = 0; k < NumRegs; ++k)
acc[k] = vec_sub_16(acc[k], column[k]);
}
for (; i < int(added.size()); ++i)
{
IndexType index = added[i];
const IndexType offset = HalfDimensions * index + j * TileHeight; const IndexType offset = HalfDimensions * index + j * TileHeight;
auto column = reinterpret_cast<const vec_t*>(&weights[offset]); auto column = reinterpret_cast<const vec_t*>(&weights[offset]);
@@ -608,19 +779,34 @@ class FeatureTransformer {
acc[k] = vec_add_16(acc[k], column[k]); acc[k] = vec_add_16(acc[k], column[k]);
} }
auto accTile = for (IndexType k = 0; k < NumRegs; k++)
reinterpret_cast<vec_t*>(&accumulator.accumulation[Perspective][j * TileHeight]); vec_store(&entryTile[k], acc[k]);
for (unsigned k = 0; k < NumRegs; k++) for (IndexType k = 0; k < NumRegs; k++)
vec_store(&accTile[k], acc[k]); vec_store(&accTile[k], acc[k]);
} }
for (IndexType j = 0; j < PSQTBuckets / PsqtTileHeight; ++j) for (IndexType j = 0; j < PSQTBuckets / PsqtTileHeight; ++j)
{ {
for (std::size_t k = 0; k < NumPsqtRegs; ++k) auto accTilePsqt = reinterpret_cast<psqt_vec_t*>(
psqt[k] = vec_zero_psqt(); &accumulator.psqtAccumulation[Perspective][j * PsqtTileHeight]);
auto entryTilePsqt =
reinterpret_cast<psqt_vec_t*>(&entry.psqtAccumulation[j * PsqtTileHeight]);
for (const auto index : active) for (std::size_t k = 0; k < NumPsqtRegs; ++k)
psqt[k] = entryTilePsqt[k];
for (int i = 0; i < int(removed.size()); ++i)
{ {
IndexType index = removed[i];
const IndexType offset = PSQTBuckets * index + j * PsqtTileHeight;
auto columnPsqt = reinterpret_cast<const psqt_vec_t*>(&psqtWeights[offset]);
for (std::size_t k = 0; k < NumPsqtRegs; ++k)
psqt[k] = vec_sub_psqt_32(psqt[k], columnPsqt[k]);
}
for (int i = 0; i < int(added.size()); ++i)
{
IndexType index = added[i];
const IndexType offset = PSQTBuckets * index + j * PsqtTileHeight; const IndexType offset = PSQTBuckets * index + j * PsqtTileHeight;
auto columnPsqt = reinterpret_cast<const psqt_vec_t*>(&psqtWeights[offset]); auto columnPsqt = reinterpret_cast<const psqt_vec_t*>(&psqtWeights[offset]);
@@ -628,35 +814,53 @@ class FeatureTransformer {
psqt[k] = vec_add_psqt_32(psqt[k], columnPsqt[k]); psqt[k] = vec_add_psqt_32(psqt[k], columnPsqt[k]);
} }
auto accTilePsqt = reinterpret_cast<psqt_vec_t*>( for (std::size_t k = 0; k < NumPsqtRegs; ++k)
&accumulator.psqtAccumulation[Perspective][j * PsqtTileHeight]); vec_store_psqt(&entryTilePsqt[k], psqt[k]);
for (std::size_t k = 0; k < NumPsqtRegs; ++k) for (std::size_t k = 0; k < NumPsqtRegs; ++k)
vec_store_psqt(&accTilePsqt[k], psqt[k]); vec_store_psqt(&accTilePsqt[k], psqt[k]);
} }
#else #else
std::memcpy(accumulator.accumulation[Perspective], biases,
HalfDimensions * sizeof(BiasType));
for (std::size_t k = 0; k < PSQTBuckets; ++k) for (const auto index : removed)
accumulator.psqtAccumulation[Perspective][k] = 0;
for (const auto index : active)
{ {
const IndexType offset = HalfDimensions * index; const IndexType offset = HalfDimensions * index;
for (IndexType j = 0; j < HalfDimensions; ++j) for (IndexType j = 0; j < HalfDimensions; ++j)
accumulator.accumulation[Perspective][j] += weights[offset + j]; entry.accumulation[j] -= weights[offset + j];
for (std::size_t k = 0; k < PSQTBuckets; ++k) for (std::size_t k = 0; k < PSQTBuckets; ++k)
accumulator.psqtAccumulation[Perspective][k] += entry.psqtAccumulation[k] -= psqtWeights[index * PSQTBuckets + k];
psqtWeights[index * PSQTBuckets + k];
} }
for (const auto index : added)
{
const IndexType offset = HalfDimensions * index;
for (IndexType j = 0; j < HalfDimensions; ++j)
entry.accumulation[j] += weights[offset + j];
for (std::size_t k = 0; k < PSQTBuckets; ++k)
entry.psqtAccumulation[k] += 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) * HalfDimensions);
std::memcpy(accumulator.psqtAccumulation[Perspective], entry.psqtAccumulation,
sizeof(int32_t) * PSQTBuckets);
#endif #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);
} }
template<Color Perspective> template<Color Perspective>
void hint_common_access_for_perspective(const Position& pos) const { void hint_common_access_for_perspective(const Position& pos,
AccumulatorCaches::Cache<HalfDimensions>* cache) const {
// Works like update_accumulator, but performs less work. // Works like update_accumulator, but performs less work.
// Updates ONLY the accumulator for pos. // Updates ONLY the accumulator for pos.
@@ -671,16 +875,17 @@ class FeatureTransformer {
if ((oldest_st->*accPtr).computed[Perspective]) if ((oldest_st->*accPtr).computed[Perspective])
{ {
// Only update current position accumulator to minimize work. // Only update current position accumulator to minimize work
StateInfo* states_to_update[2] = {pos.state(), nullptr}; StateInfo* states_to_update[1] = {pos.state()};
update_accumulator_incremental<Perspective, 2>(pos, oldest_st, states_to_update); update_accumulator_incremental<Perspective, 1>(pos, oldest_st, states_to_update);
} }
else else
update_accumulator_refresh<Perspective>(pos); update_accumulator_refresh_cache<Perspective>(pos, cache);
} }
template<Color Perspective> template<Color Perspective>
void update_accumulator(const Position& pos) const { void update_accumulator(const Position& pos,
AccumulatorCaches::Cache<HalfDimensions>* cache) const {
auto [oldest_st, next] = try_find_computed_accumulator<Perspective>(pos); auto [oldest_st, next] = try_find_computed_accumulator<Perspective>(pos);
@@ -689,22 +894,31 @@ class FeatureTransformer {
if (next == nullptr) if (next == nullptr)
return; return;
// Now update the accumulators listed in states_to_update[], where the last element is a sentinel. // Now update the accumulators listed in states_to_update[], where
// Currently we update 2 accumulators. // the last element is a sentinel. Currently we update two accumulators:
// 1. for the current position // 1. for the current position
// 2. the next accumulator after the computed one // 2. the next accumulator after the computed one
// The heuristic may change in the future. // The heuristic may change in the future.
StateInfo* states_to_update[3] = {next, next == pos.state() ? nullptr : pos.state(), if (next == pos.state())
nullptr}; {
StateInfo* states_to_update[1] = {next};
update_accumulator_incremental<Perspective, 3>(pos, oldest_st, states_to_update); update_accumulator_incremental<Perspective, 1>(pos, oldest_st, states_to_update);
}
else
{
StateInfo* states_to_update[2] = {next, pos.state()};
update_accumulator_incremental<Perspective, 2>(pos, oldest_st, states_to_update);
}
} }
else else
{ update_accumulator_refresh_cache<Perspective>(pos, cache);
update_accumulator_refresh<Perspective>(pos);
}
} }
template<IndexType Size>
friend struct AccumulatorCaches::Cache;
alignas(CacheLineSize) BiasType biases[HalfDimensions]; alignas(CacheLineSize) BiasType biases[HalfDimensions];
alignas(CacheLineSize) WeightType weights[HalfDimensions * InputDimensions]; alignas(CacheLineSize) WeightType weights[HalfDimensions * InputDimensions];
alignas(CacheLineSize) PSQTWeightType psqtWeights[InputDimensions * PSQTBuckets]; alignas(CacheLineSize) PSQTWeightType psqtWeights[InputDimensions * PSQTBuckets];

203
src/nnue/nnue_misc.cpp Normal file
View File

@@ -0,0 +1,203 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2024 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 "../evaluate.h"
#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");
void hint_common_parent_position(const Position& pos,
const Networks& networks,
AccumulatorCaches& caches) {
if (Eval::use_smallnet(pos))
networks.small.hint_common_access(pos, &caches.small);
else
networks.big.hint_common_access(pos, &caches.big);
}
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 (value != VALUE_NONE)
format_cp_compact(value, &board[y + 2][x + 2], pos);
};
// 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, &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)
{
auto st = pos.state();
pos.remove_piece(sq);
st->accumulatorBig.computed[WHITE] = st->accumulatorBig.computed[BLACK] = false;
std::tie(psqt, positional) = networks.big.evaluate(pos, &caches.big);
Value eval = psqt + positional;
eval = pos.side_to_move() == WHITE ? eval : -eval;
v = base - eval;
pos.put_piece(pc, sq);
st->accumulatorBig.computed[WHITE] = st->accumulatorBig.computed[BLACK] = false;
}
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';
auto t = networks.big.trace_evaluate(pos, &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

64
src/nnue/nnue_misc.h Normal file
View File

@@ -0,0 +1,64 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2024 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);
void hint_common_parent_position(const Position& pos,
const Networks& networks,
AccumulatorCaches& caches);
} // namespace Stockfish::Eval::NNUE
} // namespace Stockfish
#endif // #ifndef NNUE_MISC_H_INCLUDED

1345
src/numa.h Normal file

File diff suppressed because it is too large Load Diff

View File

@@ -26,7 +26,7 @@
#include "types.h" #include "types.h"
#include "uci.h" #include "uci.h"
namespace Stockfish { namespace Stockfish::Benchmark {
// Utility to verify move generation. All the leaf nodes up // Utility to verify move generation. All the leaf nodes up
// to the given depth are generated and counted, and the sum is returned. // to the given depth are generated and counted, and the sum is returned.
@@ -51,18 +51,17 @@ uint64_t perft(Position& pos, Depth depth) {
pos.undo_move(m); pos.undo_move(m);
} }
if (Root) if (Root)
sync_cout << UCI::move(m, pos.is_chess960()) << ": " << cnt << sync_endl; sync_cout << UCIEngine::move(m, pos.is_chess960()) << ": " << cnt << sync_endl;
} }
return nodes; return nodes;
} }
inline void perft(const std::string& fen, Depth depth, bool isChess960) { inline uint64_t perft(const std::string& fen, Depth depth, bool isChess960) {
StateListPtr states(new std::deque<StateInfo>(1)); StateListPtr states(new std::deque<StateInfo>(1));
Position p; Position p;
p.set(fen, isChess960, &states->back()); p.set(fen, isChess960, &states->back());
uint64_t nodes = perft<true>(p, depth); return perft<true>(p, depth);
sync_cout << "\nNodes searched: " << nodes << "\n" << sync_endl;
} }
} }

View File

@@ -78,7 +78,7 @@ std::ostream& operator<<(std::ostream& os, const Position& pos) {
<< std::setw(16) << pos.key() << std::setfill(' ') << std::dec << "\nCheckers: "; << std::setw(16) << pos.key() << std::setfill(' ') << std::dec << "\nCheckers: ";
for (Bitboard b = pos.checkers(); b;) for (Bitboard b = pos.checkers(); b;)
os << UCI::square(pop_lsb(b)) << " "; os << UCIEngine::square(pop_lsb(b)) << " ";
if (int(Tablebases::MaxCardinality) >= popcount(pos.pieces()) && !pos.can_castle(ANY_CASTLING)) if (int(Tablebases::MaxCardinality) >= popcount(pos.pieces()) && !pos.can_castle(ANY_CASTLING))
{ {
@@ -431,8 +431,8 @@ string Position::fen() const {
if (!can_castle(ANY_CASTLING)) if (!can_castle(ANY_CASTLING))
ss << '-'; ss << '-';
ss << (ep_square() == SQ_NONE ? " - " : " " + UCI::square(ep_square()) + " ") << st->rule50 ss << (ep_square() == SQ_NONE ? " - " : " " + UCIEngine::square(ep_square()) + " ")
<< " " << 1 + (gamePly - (sideToMove == BLACK)) / 2; << st->rule50 << " " << 1 + (gamePly - (sideToMove == BLACK)) / 2;
return ss.str(); return ss.str();
} }
@@ -682,8 +682,9 @@ void Position::do_move(Move m, StateInfo& newSt, bool givesCheck) {
// Used by NNUE // Used by NNUE
st->accumulatorBig.computed[WHITE] = st->accumulatorBig.computed[BLACK] = st->accumulatorBig.computed[WHITE] = st->accumulatorBig.computed[BLACK] =
st->accumulatorSmall.computed[WHITE] = st->accumulatorSmall.computed[BLACK] = false; st->accumulatorSmall.computed[WHITE] = st->accumulatorSmall.computed[BLACK] = false;
auto& dp = st->dirtyPiece;
dp.dirty_num = 1; auto& dp = st->dirtyPiece;
dp.dirty_num = 1;
Color us = sideToMove; Color us = sideToMove;
Color them = ~us; Color them = ~us;
@@ -740,7 +741,6 @@ void Position::do_move(Move m, StateInfo& newSt, bool givesCheck) {
// Update board and piece lists // Update board and piece lists
remove_piece(capsq); remove_piece(capsq);
// Update material hash key and prefetch access to materialTable
k ^= Zobrist::psq[captured][capsq]; k ^= Zobrist::psq[captured][capsq];
st->materialKey ^= Zobrist::psq[captured][pieceCount[captured]]; st->materialKey ^= Zobrist::psq[captured][pieceCount[captured]];
@@ -1156,9 +1156,9 @@ bool Position::has_repeated() const {
} }
// Tests if the position has a move which draws by repetition, // Tests if the position has a move which draws by repetition.
// or an earlier position has a move that directly reaches the current position. // This function accurately matches the outcome of is_draw() over all legal moves.
bool Position::has_game_cycle(int ply) const { bool Position::upcoming_repetition(int ply) const {
int j; int j;
@@ -1169,10 +1169,16 @@ bool Position::has_game_cycle(int ply) const {
Key originalKey = st->key; Key originalKey = st->key;
StateInfo* stp = st->previous; StateInfo* stp = st->previous;
Key other = originalKey ^ stp->key ^ Zobrist::side;
for (int i = 3; i <= end; i += 2) for (int i = 3; i <= end; i += 2)
{ {
stp = stp->previous->previous; stp = stp->previous;
other ^= stp->key ^ stp->previous->key ^ Zobrist::side;
stp = stp->previous;
if (other != 0)
continue;
Key moveKey = originalKey ^ stp->key; Key moveKey = originalKey ^ stp->key;
if ((j = H1(moveKey), cuckoo[j] == moveKey) || (j = H2(moveKey), cuckoo[j] == moveKey)) if ((j = H1(moveKey), cuckoo[j] == moveKey) || (j = H2(moveKey), cuckoo[j] == moveKey))
@@ -1188,12 +1194,6 @@ bool Position::has_game_cycle(int ply) const {
// For nodes before or at the root, check that the move is a // For nodes before or at the root, check that the move is a
// repetition rather than a move to the current position. // repetition rather than a move to the current position.
// In the cuckoo table, both moves Rc1c5 and Rc5c1 are stored in
// the same location, so we have to select which square to check.
if (color_of(piece_on(empty(s1) ? s2 : s1)) != side_to_move())
continue;
// For repetitions before or at the root, require one more
if (stp->repetition) if (stp->repetition)
return true; return true;
} }

View File

@@ -156,7 +156,7 @@ class Position {
int game_ply() const; int game_ply() const;
bool is_chess960() const; bool is_chess960() const;
bool is_draw(int ply) const; bool is_draw(int ply) const;
bool has_game_cycle(int ply) const; bool upcoming_repetition(int ply) const;
bool has_repeated() const; bool has_repeated() const;
int rule50_count() const; int rule50_count() const;
Value non_pawn_material(Color c) const; Value non_pawn_material(Color c) const;
@@ -315,8 +315,8 @@ inline bool Position::capture(Move m) const {
} }
// Returns true if a move is generated from the capture stage, having also // 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 // queen promotions covered, i.e. consistency with the capture stage move
// is needed to avoid the generation of duplicate moves. // generation is needed to avoid the generation of duplicate moves.
inline bool Position::capture_stage(Move m) const { inline bool Position::capture_stage(Move m) const {
assert(m.is_ok()); assert(m.is_ok());
return capture(m) || m.promotion_type() == QUEEN; return capture(m) || m.promotion_type() == QUEEN;

48
src/score.cpp Normal file
View File

@@ -0,0 +1,48 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2024 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 (std::abs(v) < VALUE_TB_WIN_IN_MAX_PLY)
{
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};
}
}
}

70
src/score.h Normal file
View File

@@ -0,0 +1,70 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2024 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

File diff suppressed because it is too large Load Diff

View File

@@ -19,18 +19,25 @@
#ifndef SEARCH_H_INCLUDED #ifndef SEARCH_H_INCLUDED
#define SEARCH_H_INCLUDED #define SEARCH_H_INCLUDED
#include <algorithm>
#include <array> #include <array>
#include <atomic> #include <atomic>
#include <cassert> #include <cassert>
#include <cstddef> #include <cstddef>
#include <cstdint> #include <cstdint>
#include <functional>
#include <memory> #include <memory>
#include <vector>
#include <string> #include <string>
#include <string_view>
#include <vector>
#include "misc.h" #include "misc.h"
#include "movepick.h" #include "movepick.h"
#include "nnue/network.h"
#include "nnue/nnue_accumulator.h"
#include "numa.h"
#include "position.h" #include "position.h"
#include "score.h"
#include "syzygy/tbprobe.h" #include "syzygy/tbprobe.h"
#include "timeman.h" #include "timeman.h"
#include "types.h" #include "types.h"
@@ -59,14 +66,12 @@ struct Stack {
int ply; int ply;
Move currentMove; Move currentMove;
Move excludedMove; Move excludedMove;
Move killers[2];
Value staticEval; Value staticEval;
int statScore; int statScore;
int moveCount; int moveCount;
bool inCheck; bool inCheck;
bool ttPv; bool ttPv;
bool ttHit; bool ttHit;
int multipleExtensions;
int cutoffCnt; int cutoffCnt;
}; };
@@ -85,6 +90,7 @@ struct RootMove {
return m.score != score ? m.score < score : m.previousScore < previousScore; return m.score != score ? m.score < score : m.previousScore < previousScore;
} }
uint64_t effort = 0;
Value score = -VALUE_INFINITE; Value score = -VALUE_INFINITE;
Value previousScore = -VALUE_INFINITE; Value previousScore = -VALUE_INFINITE;
Value averageScore = -VALUE_INFINITE; Value averageScore = -VALUE_INFINITE;
@@ -100,8 +106,7 @@ struct RootMove {
using RootMoves = std::vector<RootMove>; using RootMoves = std::vector<RootMove>;
// LimitsType struct stores information sent by GUI about available time to // LimitsType struct stores information sent by the caller about the analysis required.
// search the current move, maximum depth/time, or if we are in analysis mode.
struct LimitsType { struct LimitsType {
// Init explicitly due to broken value-initialization of non POD in MSVC // Init explicitly due to broken value-initialization of non POD in MSVC
@@ -109,30 +114,36 @@ struct LimitsType {
time[WHITE] = time[BLACK] = inc[WHITE] = inc[BLACK] = npmsec = movetime = TimePoint(0); time[WHITE] = time[BLACK] = inc[WHITE] = inc[BLACK] = npmsec = movetime = TimePoint(0);
movestogo = depth = mate = perft = infinite = 0; movestogo = depth = mate = perft = infinite = 0;
nodes = 0; nodes = 0;
ponderMode = false;
} }
bool use_time_management() const { return time[WHITE] || time[BLACK]; } bool use_time_management() const { return time[WHITE] || time[BLACK]; }
std::vector<Move> searchmoves; std::vector<std::string> searchmoves;
TimePoint time[COLOR_NB], inc[COLOR_NB], npmsec, movetime, startTime; TimePoint time[COLOR_NB], inc[COLOR_NB], npmsec, movetime, startTime;
int movestogo, depth, mate, perft, infinite; int movestogo, depth, mate, perft, infinite;
uint64_t nodes; uint64_t nodes;
bool ponderMode;
Square capSq;
}; };
// The UCI stores the uci options, thread pool, and transposition table. // The UCI stores the uci options, thread pool, and transposition table.
// This struct is used to easily forward data to the Search::Worker class. // This struct is used to easily forward data to the Search::Worker class.
struct SharedState { struct SharedState {
SharedState(const OptionsMap& optionsMap, SharedState(const OptionsMap& optionsMap,
ThreadPool& threadPool, ThreadPool& threadPool,
TranspositionTable& transpositionTable) : TranspositionTable& transpositionTable,
const LazyNumaReplicated<Eval::NNUE::Networks>& nets) :
options(optionsMap), options(optionsMap),
threads(threadPool), threads(threadPool),
tt(transpositionTable) {} tt(transpositionTable),
networks(nets) {}
const OptionsMap& options; const OptionsMap& options;
ThreadPool& threads; ThreadPool& threads;
TranspositionTable& tt; TranspositionTable& tt;
const LazyNumaReplicated<Eval::NNUE::Networks>& networks;
}; };
class Worker; class Worker;
@@ -145,18 +156,87 @@ class ISearchManager {
virtual void check_time(Search::Worker&) = 0; 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 // 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. // keeping track of the time, and storing data strictly related to the main thread.
class SearchManager: public ISearchManager { class SearchManager: public ISearchManager {
public: 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 check_time(Search::Worker& worker) override;
std::string pv(const Search::Worker& worker, void pv(Search::Worker& worker,
const ThreadPool& threads, const ThreadPool& threads,
const TranspositionTable& tt, const TranspositionTable& tt,
Depth depth) const; Depth depth);
Stockfish::TimeManagement tm; Stockfish::TimeManagement tm;
double originalTimeAdjust;
int callsCnt; int callsCnt;
std::atomic_bool ponder; std::atomic_bool ponder;
@@ -167,6 +247,8 @@ class SearchManager: public ISearchManager {
bool stopOnPonderhit; bool stopOnPonderhit;
size_t id; size_t id;
const UpdateContext& updates;
}; };
class NullSearchManager: public ISearchManager { class NullSearchManager: public ISearchManager {
@@ -174,25 +256,27 @@ class NullSearchManager: public ISearchManager {
void check_time(Search::Worker&) override {} void check_time(Search::Worker&) override {}
}; };
// Search::Worker is the class that does the actual search. // Search::Worker is the class that does the actual search.
// It is instantiated once per thread, and it is responsible for keeping track // It is instantiated once per thread, and it is responsible for keeping track
// of the search history, and storing data required for the search. // of the search history, and storing data required for the search.
class Worker { class Worker {
public: public:
Worker(SharedState&, std::unique_ptr<ISearchManager>, size_t); Worker(SharedState&, std::unique_ptr<ISearchManager>, size_t, NumaReplicatedAccessToken);
// Called at instantiation to initialize Reductions tables // Called at instantiation to initialize reductions tables.
// Reset histories, usually before a new game // Reset histories, usually before a new game.
void clear(); void clear();
// Called when the program receives the UCI 'go' command. // Called when the program receives the UCI 'go' command.
// It searches from the root position and outputs the "bestmove". // It searches from the root position and outputs the "bestmove".
void start_searching(); void start_searching();
bool is_mainthread() const { return thread_idx == 0; } bool is_mainthread() const { return threadIdx == 0; }
void ensure_network_replicated();
// Public because they need to be updatable by the stats // Public because they need to be updatable by the stats
CounterMoveHistory counterMoves;
ButterflyHistory mainHistory; ButterflyHistory mainHistory;
CapturePieceToHistory captureHistory; CapturePieceToHistory captureHistory;
ContinuationHistory continuationHistory[2][2]; ContinuationHistory continuationHistory[2][2];
@@ -202,24 +286,24 @@ class Worker {
private: private:
void iterative_deepening(); void iterative_deepening();
// Main search function for both PV and non-PV nodes // This is the main search function, for both PV and non-PV nodes
template<NodeType nodeType> template<NodeType nodeType>
Value search(Position& pos, Stack* ss, Value alpha, Value beta, Depth depth, bool cutNode); Value search(Position& pos, Stack* ss, Value alpha, Value beta, Depth depth, bool cutNode);
// Quiescence search function, which is called by the main search // Quiescence search function, which is called by the main search
template<NodeType nodeType> template<NodeType nodeType>
Value qsearch(Position& pos, Stack* ss, Value alpha, Value beta, Depth depth = 0); Value qsearch(Position& pos, Stack* ss, Value alpha, Value beta);
Depth reduction(bool i, Depth d, int mn, int delta); Depth reduction(bool i, Depth d, int mn, int delta) const;
// Get a pointer to the search manager, only allowed to be called by the // Pointer to the search manager, only allowed to be called by the main thread
// main thread.
SearchManager* main_manager() const { SearchManager* main_manager() const {
assert(thread_idx == 0); assert(threadIdx == 0);
return static_cast<SearchManager*>(manager.get()); return static_cast<SearchManager*>(manager.get());
} }
std::array<std::array<uint64_t, SQUARE_NB>, SQUARE_NB> effort; TimePoint elapsed() const;
TimePoint elapsed_time() const;
LimitsType limits; LimitsType limits;
@@ -235,7 +319,8 @@ class Worker {
Depth rootDepth, completedDepth; Depth rootDepth, completedDepth;
Value rootDelta; Value rootDelta;
size_t thread_idx; size_t threadIdx;
NumaReplicatedAccessToken numaAccessToken;
// Reductions lookup table initialized at startup // Reductions lookup table initialized at startup
std::array<int, MAX_MOVES> reductions; // [depth or moveNumber] std::array<int, MAX_MOVES> reductions; // [depth or moveNumber]
@@ -245,9 +330,13 @@ class Worker {
Tablebases::Config tbConfig; Tablebases::Config tbConfig;
const OptionsMap& options; const OptionsMap& options;
ThreadPool& threads; ThreadPool& threads;
TranspositionTable& tt; TranspositionTable& tt;
const LazyNumaReplicated<Eval::NNUE::Networks>& networks;
// Used by NNUE
Eval::NNUE::AccumulatorCaches refreshTable;
friend class Stockfish::ThreadPool; friend class Stockfish::ThreadPool;
friend class SearchManager; friend class SearchManager;

View File

@@ -66,7 +66,7 @@ namespace {
constexpr int TBPIECES = 7; // Max number of supported pieces constexpr int TBPIECES = 7; // Max number of supported pieces
constexpr int MAX_DTZ = constexpr int MAX_DTZ =
1 << 18; // Max DTZ supported, large enough to deal with the syzygy TB limit. 1 << 18; // Max DTZ supported times 2, large enough to deal with the syzygy TB limit.
enum { enum {
BigEndian, BigEndian,
@@ -443,6 +443,8 @@ class TBTables {
std::deque<TBTable<WDL>> wdlTable; std::deque<TBTable<WDL>> wdlTable;
std::deque<TBTable<DTZ>> dtzTable; std::deque<TBTable<DTZ>> dtzTable;
size_t foundDTZFiles = 0;
size_t foundWDLFiles = 0;
void insert(Key key, TBTable<WDL>* wdl, TBTable<DTZ>* dtz) { void insert(Key key, TBTable<WDL>* wdl, TBTable<DTZ>* dtz) {
uint32_t homeBucket = uint32_t(key) & (Size - 1); uint32_t homeBucket = uint32_t(key) & (Size - 1);
@@ -486,9 +488,16 @@ class TBTables {
memset(hashTable, 0, sizeof(hashTable)); memset(hashTable, 0, sizeof(hashTable));
wdlTable.clear(); wdlTable.clear();
dtzTable.clear(); dtzTable.clear();
foundDTZFiles = 0;
foundWDLFiles = 0;
} }
size_t size() const { return wdlTable.size(); }
void add(const std::vector<PieceType>& pieces); void info() const {
sync_cout << "info string Found " << foundWDLFiles << " WDL and " << foundDTZFiles
<< " DTZ tablebase files (up to " << MaxCardinality << "-man)." << sync_endl;
}
void add(const std::vector<PieceType>& pieces);
}; };
TBTables TBTables; TBTables TBTables;
@@ -501,13 +510,22 @@ void TBTables::add(const std::vector<PieceType>& pieces) {
for (PieceType pt : pieces) for (PieceType pt : pieces)
code += PieceToChar[pt]; code += PieceToChar[pt];
code.insert(code.find('K', 1), "v");
TBFile file(code.insert(code.find('K', 1), "v") + ".rtbw"); // KRK -> KRvK TBFile file_dtz(code + ".rtbz"); // KRK -> KRvK
if (file_dtz.is_open())
{
file_dtz.close();
foundDTZFiles++;
}
TBFile file(code + ".rtbw"); // KRK -> KRvK
if (!file.is_open()) // Only WDL file is checked if (!file.is_open()) // Only WDL file is checked
return; return;
file.close(); file.close();
foundWDLFiles++;
MaxCardinality = std::max(int(pieces.size()), MaxCardinality); MaxCardinality = std::max(int(pieces.size()), MaxCardinality);
@@ -1326,7 +1344,7 @@ void Tablebases::init(const std::string& paths) {
MaxCardinality = 0; MaxCardinality = 0;
TBFile::Paths = paths; TBFile::Paths = paths;
if (paths.empty() || paths == "<empty>") if (paths.empty())
return; return;
// MapB1H1H7[] encodes a square below a1-h8 diagonal to 0..27 // MapB1H1H7[] encodes a square below a1-h8 diagonal to 0..27
@@ -1466,7 +1484,7 @@ void Tablebases::init(const std::string& paths) {
} }
} }
sync_cout << "info string Found " << TBTables.size() << " tablebases" << sync_endl; TBTables.info();
} }
// Probe the WDL table for a particular position. // Probe the WDL table for a particular position.
@@ -1574,7 +1592,10 @@ int Tablebases::probe_dtz(Position& pos, ProbeState* result) {
// Use the DTZ tables to rank root moves. // Use the DTZ tables to rank root moves.
// //
// A return value false indicates that not all probes were successful. // A return value false indicates that not all probes were successful.
bool Tablebases::root_probe(Position& pos, Search::RootMoves& rootMoves, bool rule50) { bool Tablebases::root_probe(Position& pos,
Search::RootMoves& rootMoves,
bool rule50,
bool rankDTZ) {
ProbeState result = OK; ProbeState result = OK;
StateInfo st; StateInfo st;
@@ -1585,7 +1606,7 @@ bool Tablebases::root_probe(Position& pos, Search::RootMoves& rootMoves, bool ru
// Check whether a position was repeated since the last zeroing move. // Check whether a position was repeated since the last zeroing move.
bool rep = pos.has_repeated(); bool rep = pos.has_repeated();
int dtz, bound = rule50 ? (MAX_DTZ - 100) : 1; int dtz, bound = rule50 ? (MAX_DTZ / 2 - 100) : 1;
// Probe and rank each move // Probe and rank each move
for (auto& m : rootMoves) for (auto& m : rootMoves)
@@ -1624,8 +1645,10 @@ bool Tablebases::root_probe(Position& pos, Search::RootMoves& rootMoves, bool ru
// Better moves are ranked higher. Certain wins are ranked equally. // Better moves are ranked higher. Certain wins are ranked equally.
// Losing moves are ranked equally unless a 50-move draw is in sight. // Losing moves are ranked equally unless a 50-move draw is in sight.
int r = dtz > 0 ? (dtz + cnt50 <= 99 && !rep ? MAX_DTZ : MAX_DTZ - (dtz + cnt50)) int r = dtz > 0 ? (dtz + cnt50 <= 99 && !rep ? MAX_DTZ - (rankDTZ ? dtz : 0)
: dtz < 0 ? (-dtz * 2 + cnt50 < 100 ? -MAX_DTZ : -MAX_DTZ + (-dtz + cnt50)) : MAX_DTZ / 2 - (dtz + cnt50))
: dtz < 0 ? (-dtz * 2 + cnt50 < 100 ? -MAX_DTZ - (rankDTZ ? dtz : 0)
: -MAX_DTZ / 2 + (-dtz + cnt50))
: 0; : 0;
m.tbRank = r; m.tbRank = r;
@@ -1633,10 +1656,11 @@ bool Tablebases::root_probe(Position& pos, Search::RootMoves& rootMoves, bool ru
// 1 cp to cursed wins and let it grow to 49 cp as the positions gets // 1 cp to cursed wins and let it grow to 49 cp as the positions gets
// closer to a real win. // closer to a real win.
m.tbScore = r >= bound ? VALUE_MATE - MAX_PLY - 1 m.tbScore = r >= bound ? VALUE_MATE - MAX_PLY - 1
: r > 0 ? Value((std::max(3, r - (MAX_DTZ - 200)) * int(PawnValue)) / 200) : r > 0 ? Value((std::max(3, r - (MAX_DTZ / 2 - 200)) * int(PawnValue)) / 200)
: r == 0 ? VALUE_DRAW : r == 0 ? VALUE_DRAW
: r > -bound ? Value((std::min(-3, r + (MAX_DTZ - 200)) * int(PawnValue)) / 200) : r > -bound
: -VALUE_MATE + MAX_PLY + 1; ? Value((std::min(-3, r + (MAX_DTZ / 2 - 200)) * int(PawnValue)) / 200)
: -VALUE_MATE + MAX_PLY + 1;
} }
return true; return true;
@@ -1683,7 +1707,8 @@ bool Tablebases::root_probe_wdl(Position& pos, Search::RootMoves& rootMoves, boo
Config Tablebases::rank_root_moves(const OptionsMap& options, Config Tablebases::rank_root_moves(const OptionsMap& options,
Position& pos, Position& pos,
Search::RootMoves& rootMoves) { Search::RootMoves& rootMoves,
bool rankDTZ) {
Config config; Config config;
if (rootMoves.empty()) if (rootMoves.empty())
@@ -1707,7 +1732,7 @@ Config Tablebases::rank_root_moves(const OptionsMap& options,
if (config.cardinality >= popcount(pos.pieces()) && !pos.can_castle(ANY_CASTLING)) if (config.cardinality >= popcount(pos.pieces()) && !pos.can_castle(ANY_CASTLING))
{ {
// Rank moves using DTZ tables // Rank moves using DTZ tables
config.rootInTB = root_probe(pos, rootMoves, options["Syzygy50MoveRule"]); config.rootInTB = root_probe(pos, rootMoves, options["Syzygy50MoveRule"], rankDTZ);
if (!config.rootInTB) if (!config.rootInTB)
{ {

View File

@@ -66,9 +66,12 @@ extern int MaxCardinality;
void init(const std::string& paths); void init(const std::string& paths);
WDLScore probe_wdl(Position& pos, ProbeState* result); WDLScore probe_wdl(Position& pos, ProbeState* result);
int probe_dtz(Position& pos, ProbeState* result); int probe_dtz(Position& pos, ProbeState* result);
bool root_probe(Position& pos, Search::RootMoves& rootMoves, bool rule50); bool root_probe(Position& pos, Search::RootMoves& rootMoves, bool rule50, bool rankDTZ);
bool root_probe_wdl(Position& pos, Search::RootMoves& rootMoves, bool rule50); bool root_probe_wdl(Position& pos, Search::RootMoves& rootMoves, bool rule50);
Config rank_root_moves(const OptionsMap& options, Position& pos, Search::RootMoves& rootMoves); Config rank_root_moves(const OptionsMap& options,
Position& pos,
Search::RootMoves& rootMoves,
bool rankDTZ = false);
} // namespace Stockfish::Tablebases } // namespace Stockfish::Tablebases

View File

@@ -22,17 +22,16 @@
#include <cassert> #include <cassert>
#include <deque> #include <deque>
#include <memory> #include <memory>
#include <string>
#include <unordered_map> #include <unordered_map>
#include <utility> #include <utility>
#include <array>
#include "misc.h"
#include "movegen.h" #include "movegen.h"
#include "search.h" #include "search.h"
#include "syzygy/tbprobe.h" #include "syzygy/tbprobe.h"
#include "timeman.h" #include "timeman.h"
#include "tt.h"
#include "types.h" #include "types.h"
#include "uci.h"
#include "ucioption.h" #include "ucioption.h"
namespace Stockfish { namespace Stockfish {
@@ -41,13 +40,24 @@ namespace Stockfish {
// in idle_loop(). Note that 'searching' and 'exit' should be already set. // in idle_loop(). Note that 'searching' and 'exit' should be already set.
Thread::Thread(Search::SharedState& sharedState, Thread::Thread(Search::SharedState& sharedState,
std::unique_ptr<Search::ISearchManager> sm, std::unique_ptr<Search::ISearchManager> sm,
size_t n) : size_t n,
worker(std::make_unique<Search::Worker>(sharedState, std::move(sm), n)), OptionalThreadToNumaNodeBinder binder) :
idx(n), idx(n),
nthreads(sharedState.options["Threads"]), nthreads(sharedState.options["Threads"]),
stdThread(&Thread::idle_loop, this) { stdThread(&Thread::idle_loop, this) {
wait_for_search_finished(); wait_for_search_finished();
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);
});
wait_for_search_finished();
} }
@@ -64,35 +74,40 @@ Thread::~Thread() {
// Wakes up the thread that will start the search // Wakes up the thread that will start the search
void Thread::start_searching() { void Thread::start_searching() {
mutex.lock(); assert(worker != nullptr);
searching = true; run_custom_job([this]() { worker->start_searching(); });
mutex.unlock(); // Unlock before notifying saves a few CPU-cycles
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 // Blocks on the condition variable until the thread has finished searching
// until the thread has finished searching.
void Thread::wait_for_search_finished() { void Thread::wait_for_search_finished() {
std::unique_lock<std::mutex> lk(mutex); std::unique_lock<std::mutex> lk(mutex);
cv.wait(lk, [&] { return !searching; }); 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();
}
// Thread gets parked here, blocked on the void Thread::ensure_network_replicated() { worker->ensure_network_replicated(); }
// condition variable, when it has no work to do.
// Thread gets parked here, blocked on the condition variable
// when the thread has no work to do.
void Thread::idle_loop() { void Thread::idle_loop() {
// 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 (nthreads > 8)
WinProcGroup::bindThisThread(idx);
while (true) while (true)
{ {
std::unique_lock<std::mutex> lk(mutex); std::unique_lock<std::mutex> lk(mutex);
@@ -103,81 +118,150 @@ void Thread::idle_loop() {
if (exit) if (exit)
return; return;
std::function<void()> job = std::move(jobFunc);
jobFunc = nullptr;
lk.unlock(); lk.unlock();
worker->start_searching(); if (job)
job();
} }
} }
Search::SearchManager* ThreadPool::main_manager() { return main_thread()->worker->main_manager(); }
uint64_t ThreadPool::nodes_searched() const { return accumulate(&Search::Worker::nodes); }
uint64_t ThreadPool::tb_hits() const { return accumulate(&Search::Worker::tbHits); }
// Creates/destroys threads to match the requested number. // Creates/destroys threads to match the requested number.
// Created and launched threads will immediately go to sleep in idle_loop. // Created and launched threads will immediately go to sleep in idle_loop.
// Upon resizing, threads are recreated to allow for binding if necessary. // Upon resizing, threads are recreated to allow for binding if necessary.
void ThreadPool::set(Search::SharedState sharedState) { void ThreadPool::set(const NumaConfig& numaConfig,
Search::SharedState sharedState,
const Search::SearchManager::UpdateContext& updateContext) {
if (threads.size() > 0) // destroy any existing thread(s) if (threads.size() > 0) // destroy any existing thread(s)
{ {
main_thread()->wait_for_search_finished(); main_thread()->wait_for_search_finished();
while (threads.size() > 0) threads.clear();
delete threads.back(), threads.pop_back();
boundThreadToNumaNode.clear();
} }
const size_t requested = sharedState.options["Threads"]; const size_t requested = sharedState.options["Threads"];
if (requested > 0) // create new thread(s) if (requested > 0) // create new thread(s)
{ {
threads.push_back(new Thread( // Binding threads may be problematic when there's multiple NUMA nodes and
sharedState, std::unique_ptr<Search::ISearchManager>(new Search::SearchManager()), 0)); // 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) while (threads.size() < requested)
threads.push_back(new Thread( {
sharedState, std::unique_ptr<Search::ISearchManager>(new Search::NullSearchManager()), const size_t threadId = threads.size();
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(); clear();
main_thread()->wait_for_search_finished(); main_thread()->wait_for_search_finished();
// Reallocate the hash with the new threadpool size
sharedState.tt.resize(sharedState.options["Hash"], requested);
} }
} }
// Sets threadPool data to initial values // Sets threadPool data to initial values
void ThreadPool::clear() { void ThreadPool::clear() {
if (threads.size() == 0)
return;
for (Thread* th : threads) for (auto&& th : threads)
th->worker->clear(); th->clear_worker();
main_manager()->callsCnt = 0; for (auto&& th : threads)
main_manager()->bestPreviousScore = VALUE_INFINITE; 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()->bestPreviousAverageScore = VALUE_INFINITE;
main_manager()->previousTimeReduction = 1.0; main_manager()->previousTimeReduction = 0.85;
main_manager()->callsCnt = 0;
main_manager()->bestPreviousScore = VALUE_INFINITE;
main_manager()->originalTimeAdjust = -1;
main_manager()->tm.clear(); main_manager()->tm.clear();
} }
void ThreadPool::run_on_thread(size_t threadId, std::function<void()> f) {
assert(threads.size() > threadId);
threads[threadId]->run_custom_job(std::move(f));
}
// Wakes up main thread waiting in idle_loop() and void ThreadPool::wait_on_thread(size_t threadId) {
// returns immediately. Main thread will wake up other threads and start the search. assert(threads.size() > threadId);
threads[threadId]->wait_for_search_finished();
}
size_t ThreadPool::num_threads() const { return threads.size(); }
// 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, void ThreadPool::start_thinking(const OptionsMap& options,
Position& pos, Position& pos,
StateListPtr& states, StateListPtr& states,
Search::LimitsType limits, Search::LimitsType limits) {
bool ponderMode) {
main_thread()->wait_for_search_finished(); main_thread()->wait_for_search_finished();
main_manager()->stopOnPonderhit = stop = abortedSearch = false; main_manager()->stopOnPonderhit = stop = abortedSearch = false;
main_manager()->ponder = ponderMode; main_manager()->ponder = limits.ponderMode;
increaseDepth = true; increaseDepth = true;
Search::RootMoves rootMoves; Search::RootMoves rootMoves;
const auto legalmoves = MoveList<LEGAL>(pos);
for (const auto& m : MoveList<LEGAL>(pos)) for (const auto& uciMove : limits.searchmoves)
if (limits.searchmoves.empty() {
|| std::count(limits.searchmoves.begin(), limits.searchmoves.end(), m)) auto move = UCIEngine::to_move(pos, uciMove);
if (std::find(legalmoves.begin(), legalmoves.end(), move) != legalmoves.end())
rootMoves.emplace_back(move);
}
if (rootMoves.empty())
for (const auto& m : legalmoves)
rootMoves.emplace_back(m); rootMoves.emplace_back(m);
Tablebases::Config tbConfig = Tablebases::rank_root_moves(options, pos, rootMoves); Tablebases::Config tbConfig = Tablebases::rank_root_moves(options, pos, rootMoves);
@@ -192,34 +276,38 @@ void ThreadPool::start_thinking(const OptionsMap& options,
// We use Position::set() to set root position across threads. But there are // We use Position::set() to set root position across threads. But there are
// some StateInfo fields (previous, pliesFromNull, capturedPiece) that cannot // some StateInfo fields (previous, pliesFromNull, capturedPiece) that cannot
// be deduced from a fen string, so set() clears them and they are set from // 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 // setupStates->back() later. The rootState is per thread, earlier states are
// since they are read-only. // shared since they are read-only.
for (Thread* th : threads) for (auto&& th : threads)
{ {
th->worker->limits = limits; th->run_custom_job([&]() {
th->worker->nodes = th->worker->tbHits = th->worker->nmpMinPly = th->worker->limits = limits;
th->worker->bestMoveChanges = 0; th->worker->nodes = th->worker->tbHits = th->worker->nmpMinPly =
th->worker->rootDepth = th->worker->completedDepth = 0; th->worker->bestMoveChanges = 0;
th->worker->rootMoves = rootMoves; th->worker->rootDepth = th->worker->completedDepth = 0;
th->worker->rootPos.set(pos.fen(), pos.is_chess960(), &th->worker->rootState); th->worker->rootMoves = rootMoves;
th->worker->rootState = setupStates->back(); th->worker->rootPos.set(pos.fen(), pos.is_chess960(), &th->worker->rootState);
th->worker->tbConfig = tbConfig; th->worker->rootState = setupStates->back();
th->worker->effort = {}; th->worker->tbConfig = tbConfig;
});
} }
for (auto&& th : threads)
th->wait_for_search_finished();
main_thread()->start_searching(); main_thread()->start_searching();
} }
Thread* ThreadPool::get_best_thread() const { Thread* ThreadPool::get_best_thread() const {
Thread* bestThread = threads.front(); Thread* bestThread = threads.front().get();
Value minScore = VALUE_NONE; Value minScore = VALUE_NONE;
std::unordered_map<Move, int64_t, Move::MoveHash> votes( std::unordered_map<Move, int64_t, Move::MoveHash> votes(
2 * std::min(size(), bestThread->worker->rootMoves.size())); 2 * std::min(size(), bestThread->worker->rootMoves.size()));
// Find the minimum score of all threads // Find the minimum score of all threads
for (Thread* th : threads) for (auto&& th : threads)
minScore = std::min(minScore, th->worker->rootMoves[0].score); minScore = std::min(minScore, th->worker->rootMoves[0].score);
// Vote according to score and depth, and select the best thread // Vote according to score and depth, and select the best thread
@@ -227,10 +315,10 @@ Thread* ThreadPool::get_best_thread() const {
return (th->worker->rootMoves[0].score - minScore + 14) * int(th->worker->completedDepth); return (th->worker->rootMoves[0].score - minScore + 14) * int(th->worker->completedDepth);
}; };
for (Thread* th : threads) for (auto&& th : threads)
votes[th->worker->rootMoves[0].pv[0]] += thread_voting_value(th); votes[th->worker->rootMoves[0].pv[0]] += thread_voting_value(th.get());
for (Thread* th : threads) for (auto&& th : threads)
{ {
const auto bestThreadScore = bestThread->worker->rootMoves[0].score; const auto bestThreadScore = bestThread->worker->rootMoves[0].score;
const auto newThreadScore = th->worker->rootMoves[0].score; const auto newThreadScore = th->worker->rootMoves[0].score;
@@ -249,51 +337,74 @@ Thread* ThreadPool::get_best_thread() const {
const bool newThreadInProvenLoss = const bool newThreadInProvenLoss =
newThreadScore != -VALUE_INFINITE && newThreadScore <= VALUE_TB_LOSS_IN_MAX_PLY; newThreadScore != -VALUE_INFINITE && newThreadScore <= VALUE_TB_LOSS_IN_MAX_PLY;
// Note that we make sure not to pick a thread with truncated-PV for better viewer experience. // We make sure not to pick a thread with truncated principal variation
const bool betterVotingValue = const bool betterVotingValue =
thread_voting_value(th) * int(newThreadPV.size() > 2) thread_voting_value(th.get()) * int(newThreadPV.size() > 2)
> thread_voting_value(bestThread) * int(bestThreadPV.size() > 2); > thread_voting_value(bestThread) * int(bestThreadPV.size() > 2);
if (bestThreadInProvenWin) if (bestThreadInProvenWin)
{ {
// Make sure we pick the shortest mate / TB conversion // Make sure we pick the shortest mate / TB conversion
if (newThreadScore > bestThreadScore) if (newThreadScore > bestThreadScore)
bestThread = th; bestThread = th.get();
} }
else if (bestThreadInProvenLoss) else if (bestThreadInProvenLoss)
{ {
// Make sure we pick the shortest mated / TB conversion // Make sure we pick the shortest mated / TB conversion
if (newThreadInProvenLoss && newThreadScore < bestThreadScore) if (newThreadInProvenLoss && newThreadScore < bestThreadScore)
bestThread = th; bestThread = th.get();
} }
else if (newThreadInProvenWin || newThreadInProvenLoss else if (newThreadInProvenWin || newThreadInProvenLoss
|| (newThreadScore > VALUE_TB_LOSS_IN_MAX_PLY || (newThreadScore > VALUE_TB_LOSS_IN_MAX_PLY
&& (newThreadMoveVote > bestThreadMoveVote && (newThreadMoveVote > bestThreadMoveVote
|| (newThreadMoveVote == bestThreadMoveVote && betterVotingValue)))) || (newThreadMoveVote == bestThreadMoveVote && betterVotingValue))))
bestThread = th; bestThread = th.get();
} }
return bestThread; return bestThread;
} }
// Start non-main threads // Start non-main threads.
// Will be invoked by main thread after it has started searching // Will be invoked by main thread after it has started searching.
void ThreadPool::start_searching() { void ThreadPool::start_searching() {
for (Thread* th : threads) for (auto&& th : threads)
if (th != threads.front()) if (th != threads.front())
th->start_searching(); th->start_searching();
} }
// Wait for non-main threads // Wait for non-main threads
void ThreadPool::wait_for_search_finished() const { void ThreadPool::wait_for_search_finished() const {
for (Thread* th : threads) for (auto&& th : threads)
if (th != threads.front()) if (th != threads.front())
th->wait_for_search_finished(); 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 } // namespace Stockfish

View File

@@ -23,19 +23,48 @@
#include <condition_variable> #include <condition_variable>
#include <cstddef> #include <cstddef>
#include <cstdint> #include <cstdint>
#include <functional>
#include <memory> #include <memory>
#include <mutex> #include <mutex>
#include <vector> #include <vector>
#include "numa.h"
#include "position.h" #include "position.h"
#include "search.h" #include "search.h"
#include "thread_win32_osx.h" #include "thread_win32_osx.h"
namespace Stockfish { namespace Stockfish {
class OptionsMap; class OptionsMap;
using Value = int; 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. // 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() // After construction, the native thread is started with idle_loop()
// waiting for a signal to start searching. // waiting for a signal to start searching.
@@ -43,22 +72,37 @@ using Value = int;
// the search is finished, it goes back to idle_loop() waiting for a new signal. // the search is finished, it goes back to idle_loop() waiting for a new signal.
class Thread { class Thread {
public: public:
Thread(Search::SharedState&, std::unique_ptr<Search::ISearchManager>, size_t); Thread(Search::SharedState&,
std::unique_ptr<Search::ISearchManager>,
size_t,
OptionalThreadToNumaNodeBinder);
virtual ~Thread(); virtual ~Thread();
void idle_loop(); void idle_loop();
void start_searching(); void start_searching();
void clear_worker();
void run_custom_job(std::function<void()> f);
void ensure_network_replicated();
// 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(); void wait_for_search_finished();
size_t id() const { return idx; } size_t id() const { return idx; }
std::unique_ptr<Search::Worker> worker; std::unique_ptr<Search::Worker> worker;
std::function<void()> jobFunc;
private: private:
std::mutex mutex; std::mutex mutex;
std::condition_variable cv; std::condition_variable cv;
size_t idx, nthreads; size_t idx, nthreads;
bool exit = false, searching = true; // Set before starting std::thread bool exit = false, searching = true; // Set before starting std::thread
NativeThread stdThread; NativeThread stdThread;
NumaReplicatedAccessToken numaAccessToken;
}; };
@@ -66,33 +110,45 @@ class Thread {
// parking and, most importantly, launching a thread. All the access to threads // parking and, most importantly, launching a thread. All the access to threads
// is done through this class. // is done through this class.
class ThreadPool { class ThreadPool {
public: public:
ThreadPool() {}
~ThreadPool() { ~ThreadPool() {
// destroy any existing thread(s) // destroy any existing thread(s)
if (threads.size() > 0) if (threads.size() > 0)
{ {
main_thread()->wait_for_search_finished(); main_thread()->wait_for_search_finished();
while (threads.size() > 0) threads.clear();
delete threads.back(), threads.pop_back();
} }
} }
void ThreadPool(const ThreadPool&) = delete;
start_thinking(const OptionsMap&, Position&, StateListPtr&, Search::LimitsType, bool = false); ThreadPool(ThreadPool&&) = delete;
void clear();
void set(Search::SharedState);
Search::SearchManager* main_manager() const { ThreadPool& operator=(const ThreadPool&) = delete;
return static_cast<Search::SearchManager*>(main_thread()->worker.get()->manager.get()); ThreadPool& operator=(ThreadPool&&) = delete;
};
Thread* main_thread() const { return threads.front(); } void start_thinking(const OptionsMap&, Position&, StateListPtr&, Search::LimitsType);
uint64_t nodes_searched() const { return accumulate(&Search::Worker::nodes); } void run_on_thread(size_t threadId, std::function<void()> f);
uint64_t tb_hits() const { return accumulate(&Search::Worker::tbHits); } void wait_on_thread(size_t threadId);
Thread* get_best_thread() const; size_t num_threads() const;
void start_searching(); void clear();
void wait_for_search_finished() const; 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; std::atomic_bool stop, abortedSearch, increaseDepth;
@@ -104,13 +160,14 @@ class ThreadPool {
auto empty() const noexcept { return threads.empty(); } auto empty() const noexcept { return threads.empty(); }
private: private:
StateListPtr setupStates; StateListPtr setupStates;
std::vector<Thread*> threads; std::vector<std::unique_ptr<Thread>> threads;
std::vector<NumaIndex> boundThreadToNumaNode;
uint64_t accumulate(std::atomic<uint64_t> Search::Worker::*member) const { uint64_t accumulate(std::atomic<uint64_t> Search::Worker::*member) const {
uint64_t sum = 0; uint64_t sum = 0;
for (Thread* th : threads) for (auto&& th : threads)
sum += (th->worker.get()->*member).load(std::memory_order_relaxed); sum += (th->worker.get()->*member).load(std::memory_order_relaxed);
return sum; return sum;
} }

View File

@@ -30,17 +30,14 @@ namespace Stockfish {
TimePoint TimeManagement::optimum() const { return optimumTime; } TimePoint TimeManagement::optimum() const { return optimumTime; }
TimePoint TimeManagement::maximum() const { return maximumTime; } TimePoint TimeManagement::maximum() const { return maximumTime; }
TimePoint TimeManagement::elapsed(size_t nodes) const {
return useNodesTime ? TimePoint(nodes) : now() - startTime;
}
void TimeManagement::clear() { void TimeManagement::clear() {
availableNodes = 0; // When in 'nodes as time' mode availableNodes = -1; // When in 'nodes as time' mode
} }
void TimeManagement::advance_nodes_time(std::int64_t nodes) { void TimeManagement::advance_nodes_time(std::int64_t nodes) {
assert(useNodesTime); assert(useNodesTime);
availableNodes += nodes; availableNodes = std::max(int64_t(0), availableNodes - nodes);
} }
// Called at the beginning of the search and calculates // Called at the beginning of the search and calculates
@@ -50,15 +47,19 @@ void TimeManagement::advance_nodes_time(std::int64_t nodes) {
void TimeManagement::init(Search::LimitsType& limits, void TimeManagement::init(Search::LimitsType& limits,
Color us, Color us,
int ply, int ply,
const OptionsMap& options) { const OptionsMap& options,
// If we have no time, no need to initialize TM, except for the start time, double& originalTimeAdjust) {
// which is used by movetime. TimePoint npmsec = TimePoint(options["nodestime"]);
startTime = limits.startTime;
// 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;
if (limits.time[us] == 0) if (limits.time[us] == 0)
return; return;
TimePoint moveOverhead = TimePoint(options["Move Overhead"]); TimePoint moveOverhead = TimePoint(options["Move Overhead"]);
TimePoint npmsec = TimePoint(options["nodestime"]);
// optScale is a percentage of available time to use for the current move. // optScale is a percentage of available time to use for the current move.
// maxScale is a multiplier applied to optimumTime. // maxScale is a multiplier applied to optimumTime.
@@ -68,56 +69,69 @@ void TimeManagement::init(Search::LimitsType& limits,
// to nodes, and use resulting values in time management formulas. // to nodes, and use resulting values in time management formulas.
// WARNING: to avoid time losses, the given npmsec (nodes per millisecond) // WARNING: to avoid time losses, the given npmsec (nodes per millisecond)
// must be much lower than the real engine speed. // must be much lower than the real engine speed.
if (npmsec) if (useNodesTime)
{ {
useNodesTime = true; if (availableNodes == -1) // Only once at game start
if (!availableNodes) // Only once at game start
availableNodes = npmsec * limits.time[us]; // Time is in msec availableNodes = npmsec * limits.time[us]; // Time is in msec
// Convert from milliseconds to nodes // Convert from milliseconds to nodes
limits.time[us] = TimePoint(availableNodes); limits.time[us] = TimePoint(availableNodes);
limits.inc[us] *= npmsec; limits.inc[us] *= npmsec;
limits.npmsec = npmsec; limits.npmsec = npmsec;
moveOverhead *= npmsec;
} }
// 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;
const TimePoint scaledInc = limits.inc[us] / scaleFactor;
// Maximum move horizon of 50 moves // Maximum move horizon of 50 moves
int mtg = limits.movestogo ? std::min(limits.movestogo, 50) : 50; int mtg = limits.movestogo ? std::min(limits.movestogo, 50) : 50;
// If less than one second, gradually reduce mtg
if (scaledTime < 1000 && double(mtg) / scaledInc > 0.05)
{
mtg = scaledTime * 0.05;
}
// Make sure timeLeft is > 0 since we may use it as a divisor // 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) TimePoint timeLeft = std::max(TimePoint(1), limits.time[us] + limits.inc[us] * (mtg - 1)
- moveOverhead * (2 + mtg)); - moveOverhead * (2 + mtg));
// x basetime (+ z increment) // x basetime (+ z increment)
// If there is a healthy increment, timeLeft can exceed actual available // If there is a healthy increment, timeLeft can exceed the actual available
// game time for the current move, so also cap to 20% of available game time. // game time for the current move, so also cap to a percentage of available game time.
if (limits.movestogo == 0) if (limits.movestogo == 0)
{ {
// Use extra time with larger increments // Extra time according to timeLeft
double optExtra = std::clamp(1.0 + 12.5 * limits.inc[us] / limits.time[us], 1.0, 1.11); if (originalTimeAdjust < 0)
originalTimeAdjust = 0.3285 * std::log10(timeLeft) - 0.4830;
// Calculate time constants based on current time left. // Calculate time constants based on current time left.
double optConstant = double logTimeInSec = std::log10(scaledTime / 1000.0);
std::min(0.00334 + 0.0003 * std::log10(limits.time[us] / 1000.0), 0.0049); double optConstant = std::min(0.00308 + 0.000319 * logTimeInSec, 0.00506);
double maxConstant = std::max(3.4 + 3.0 * std::log10(limits.time[us] / 1000.0), 2.76); double maxConstant = std::max(3.39 + 3.01 * logTimeInSec, 2.93);
optScale = std::min(0.0120 + std::pow(ply + 3.1, 0.44) * optConstant, optScale = std::min(0.0122 + std::pow(ply + 2.95, 0.462) * optConstant,
0.21 * limits.time[us] / double(timeLeft)) 0.213 * limits.time[us] / timeLeft)
* optExtra; * originalTimeAdjust;
maxScale = std::min(6.9, maxConstant + ply / 12.2);
maxScale = std::min(6.64, maxConstant + ply / 12.0);
} }
// x moves in y seconds (+ z increment) // x moves in y seconds (+ z increment)
else else
{ {
optScale = std::min((0.88 + ply / 116.4) / mtg, 0.88 * limits.time[us] / double(timeLeft)); optScale = std::min((0.88 + ply / 116.4) / mtg, 0.88 * limits.time[us] / timeLeft);
maxScale = std::min(6.3, 1.5 + 0.11 * mtg); maxScale = std::min(6.3, 1.5 + 0.11 * mtg);
} }
// Limit the maximum possible time for this move // Limit the maximum possible time for this move
optimumTime = TimePoint(optScale * timeLeft); optimumTime = TimePoint(optScale * timeLeft);
maximumTime = maximumTime =
TimePoint(std::min(0.84 * limits.time[us] - moveOverhead, maxScale * optimumTime)) - 10; TimePoint(std::min(0.825 * limits.time[us] - moveOverhead, maxScale * optimumTime)) - 10;
if (options["Ponder"]) if (options["Ponder"])
optimumTime += optimumTime / 4; optimumTime += optimumTime / 4;

View File

@@ -19,7 +19,6 @@
#ifndef TIMEMAN_H_INCLUDED #ifndef TIMEMAN_H_INCLUDED
#define TIMEMAN_H_INCLUDED #define TIMEMAN_H_INCLUDED
#include <cstddef>
#include <cstdint> #include <cstdint>
#include "misc.h" #include "misc.h"
@@ -37,11 +36,19 @@ struct LimitsType;
// the maximum available time, the game move number, and other parameters. // the maximum available time, the game move number, and other parameters.
class TimeManagement { class TimeManagement {
public: public:
void init(Search::LimitsType& limits, Color us, int ply, const OptionsMap& options); void init(Search::LimitsType& limits,
Color us,
int ply,
const OptionsMap& options,
double& originalTimeAdjust);
TimePoint optimum() const; TimePoint optimum() const;
TimePoint maximum() const; TimePoint maximum() const;
TimePoint elapsed(std::size_t nodes) const; template<typename FUNC>
TimePoint elapsed(FUNC nodes) const {
return useNodesTime ? TimePoint(nodes()) : elapsed_time();
}
TimePoint elapsed_time() const { return now() - startTime; };
void clear(); void clear();
void advance_nodes_time(std::int64_t nodes); void advance_nodes_time(std::int64_t nodes);
@@ -51,7 +58,7 @@ class TimeManagement {
TimePoint optimumTime; TimePoint optimumTime;
TimePoint maximumTime; TimePoint maximumTime;
std::int64_t availableNodes = 0; // When in 'nodes as time' mode std::int64_t availableNodes = -1; // When in 'nodes as time' mode
bool useNodesTime = false; // True if we are in 'nodes as time' mode bool useNodesTime = false; // True if we are in 'nodes as time' mode
}; };

View File

@@ -19,33 +19,93 @@
#include "tt.h" #include "tt.h"
#include <cassert> #include <cassert>
#include <cstdint>
#include <cstdlib> #include <cstdlib>
#include <cstring> #include <cstring>
#include <iostream> #include <iostream>
#include <thread>
#include <vector>
#include "memory.h"
#include "misc.h" #include "misc.h"
#include "syzygy/tbprobe.h"
#include "thread.h"
namespace Stockfish { namespace Stockfish {
// 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.
struct TTEntry {
// 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)};
}
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 // Populates the TTEntry with a new node's data, possibly
// overwriting an old position. The update is not atomic and can be racy. // overwriting an old position. The update is not atomic and can be racy.
void TTEntry::save( void TTEntry::save(
Key k, Value v, bool pv, Bound b, Depth d, Move m, Value ev, uint8_t generation8) { Key k, Value v, bool pv, Bound b, Depth d, Move m, Value ev, uint8_t generation8) {
// Preserve any existing move for the same position // Preserve the old ttmove if we don't have a new one
if (m || uint16_t(k) != key16) if (m || uint16_t(k) != key16)
move16 = m; move16 = m;
// Overwrite less valuable entries (cheapest checks first) // Overwrite less valuable entries (cheapest checks first)
if (b == BOUND_EXACT || uint16_t(k) != key16 || d - DEPTH_OFFSET + 2 * pv > depth8 - 4) if (b == BOUND_EXACT || uint16_t(k) != key16 || d - DEPTH_ENTRY_OFFSET + 2 * pv > depth8 - 4
|| relative_age(generation8))
{ {
assert(d > DEPTH_OFFSET); assert(d > DEPTH_ENTRY_OFFSET);
assert(d < 256 + DEPTH_OFFSET); assert(d < 256 + DEPTH_ENTRY_OFFSET);
key16 = uint16_t(k); key16 = uint16_t(k);
depth8 = uint8_t(d - DEPTH_OFFSET); depth8 = uint8_t(d - DEPTH_ENTRY_OFFSET);
genBound8 = uint8_t(generation8 | uint8_t(pv) << 2 | b); genBound8 = uint8_t(generation8 | uint8_t(pv) << 2 | b);
value16 = int16_t(v); value16 = int16_t(v);
eval16 = int16_t(ev); eval16 = int16_t(ev);
@@ -53,100 +113,137 @@ void TTEntry::save(
} }
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;
}
// TTWriter is but a very thin wrapper around the pointer
TTWriter::TTWriter(TTEntry* tte) :
entry(tte) {}
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);
}
// 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.
static constexpr int ClusterSize = 3;
struct Cluster {
TTEntry entry[ClusterSize];
char padding[2]; // Pad to 32 bytes
};
static_assert(sizeof(Cluster) == 32, "Suboptimal Cluster size");
// Sets the size of the transposition table, // Sets the size of the transposition table,
// measured in megabytes. Transposition table consists of a power of 2 number // measured in megabytes. Transposition table consists
// of clusters and each cluster consists of ClusterSize number of TTEntry. // of clusters and each cluster consists of ClusterSize number of TTEntry.
void TranspositionTable::resize(size_t mbSize, int threadCount) { void TranspositionTable::resize(size_t mbSize, ThreadPool& threads) {
aligned_large_pages_free(table); aligned_large_pages_free(table);
clusterCount = mbSize * 1024 * 1024 / sizeof(Cluster); clusterCount = mbSize * 1024 * 1024 / sizeof(Cluster);
table = static_cast<Cluster*>(aligned_large_pages_alloc(clusterCount * sizeof(Cluster))); table = static_cast<Cluster*>(aligned_large_pages_alloc(clusterCount * sizeof(Cluster)));
if (!table) if (!table)
{ {
std::cerr << "Failed to allocate " << mbSize << "MB for transposition table." << std::endl; std::cerr << "Failed to allocate " << mbSize << "MB for transposition table." << std::endl;
exit(EXIT_FAILURE); exit(EXIT_FAILURE);
} }
clear(threadCount); clear(threads);
} }
// Initializes the entire transposition table to zero, // Initializes the entire transposition table to zero,
// in a multi-threaded way. // in a multi-threaded way.
void TranspositionTable::clear(size_t threadCount) { void TranspositionTable::clear(ThreadPool& threads) {
std::vector<std::thread> threads; generation8 = 0;
const size_t threadCount = threads.num_threads();
for (size_t idx = 0; idx < size_t(threadCount); ++idx) for (size_t i = 0; i < threadCount; ++i)
{ {
threads.emplace_back([this, idx, threadCount]() { threads.run_on_thread(i, [this, i, threadCount]() {
// Thread binding gives faster search on systems with a first-touch policy
if (threadCount > 8)
WinProcGroup::bindThisThread(idx);
// Each thread will zero its part of the hash table // Each thread will zero its part of the hash table
const size_t stride = size_t(clusterCount / threadCount), start = size_t(stride * idx), const size_t stride = clusterCount / threadCount;
len = idx != size_t(threadCount) - 1 ? stride : clusterCount - start; const size_t start = stride * i;
const size_t len = i + 1 != threadCount ? stride : clusterCount - start;
std::memset(&table[start], 0, len * sizeof(Cluster)); std::memset(&table[start], 0, len * sizeof(Cluster));
}); });
} }
for (std::thread& th : threads) for (size_t i = 0; i < threadCount; ++i)
th.join(); threads.wait_on_thread(i);
}
// 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.
TTEntry* TranspositionTable::probe(const Key key, bool& found) 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 || !tte[i].depth8)
{
tte[i].genBound8 =
uint8_t(generation8 | (tte[i].genBound8 & (GENERATION_DELTA - 1))); // Refresh
return found = bool(tte[i].depth8), &tte[i];
}
// 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 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.
if (replace->depth8
- ((GENERATION_CYCLE + generation8 - replace->genBound8) & GENERATION_MASK)
> tte[i].depth8
- ((GENERATION_CYCLE + generation8 - tte[i].genBound8) & GENERATION_MASK))
replace = &tte[i];
return found = false, replace;
} }
// Returns an approximation of the hashtable // Returns an approximation of the hashtable
// occupation during a search. The hash is x permill full, as per UCI protocol. // 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() const { int TranspositionTable::hashfull() const {
int cnt = 0; int cnt = 0;
for (int i = 0; i < 1000; ++i) for (int i = 0; i < 1000; ++i)
for (int j = 0; j < ClusterSize; ++j) for (int j = 0; j < ClusterSize; ++j)
cnt += table[i].entry[j].depth8 cnt += table[i].entry[j].is_occupied()
&& (table[i].entry[j].genBound8 & GENERATION_MASK) == generation8; && (table[i].entry[j].genBound8 & GENERATION_MASK) == generation8;
return cnt / ClusterSize; 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) * 2
> tte[i].depth8 - tte[i].relative_age(generation8) * 2)
replace = &tte[i];
return {false, TTData(), TTWriter(replace)};
}
TTEntry* TranspositionTable::first_entry(const Key key) const {
return &table[mul_hi64(key, clusterCount)].entry[0];
}
} // namespace Stockfish } // namespace Stockfish

108
src/tt.h
View File

@@ -21,88 +21,76 @@
#include <cstddef> #include <cstddef>
#include <cstdint> #include <cstdint>
#include <tuple>
#include "misc.h" #include "memory.h"
#include "types.h" #include "types.h"
namespace Stockfish { namespace Stockfish {
// TTEntry struct is the 10 bytes transposition table entry, defined as below: class ThreadPool;
struct TTEntry;
struct Cluster;
// 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.
// //
// key 16 bit // `probe` is the primary method: given a board position, we lookup its entry in the table, and return a tuple of:
// depth 8 bit // 1) whether the entry already has this position
// generation 5 bit // 2) a copy of the prior data (if any) (may be inconsistent due to read races)
// pv node 1 bit // 3) a writer object to this entry
// bound type 2 bit // The copied data and the writer are separated to maintain clear boundaries between local vs global objects.
// move 16 bit
// value 16 bit
// eval value 16 bit
struct TTEntry {
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, uint8_t generation8);
private: // A copy of the data already in the entry (possibly collided). `probe` may be racy, resulting in inconsistent data.
friend class TranspositionTable; struct TTData {
Move move;
uint16_t key16; Value value, eval;
uint8_t depth8; Depth depth;
uint8_t genBound8; Bound bound;
Move move16; bool is_pv;
int16_t value16; };
int16_t eval16;
// 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 { class TranspositionTable {
static constexpr int ClusterSize = 3;
struct Cluster {
TTEntry entry[ClusterSize];
char padding[2]; // Pad to 32 bytes
};
static_assert(sizeof(Cluster) == 32, "Unexpected Cluster size");
// Constants used to refresh the hash table periodically
static constexpr unsigned GENERATION_BITS = 3; // nb of bits reserved for other things
static constexpr int GENERATION_DELTA =
(1 << GENERATION_BITS); // increment for generation field
static constexpr int GENERATION_CYCLE = 255 + (1 << GENERATION_BITS); // cycle length
static constexpr int GENERATION_MASK =
(0xFF << GENERATION_BITS) & 0xFF; // mask to pull out generation number
public: public:
~TranspositionTable() { aligned_large_pages_free(table); } ~TranspositionTable() { aligned_large_pages_free(table); }
void new_search() { generation8 += GENERATION_DELTA; } // Lower bits are used for other things
TTEntry* probe(const Key key, bool& found) const;
int hashfull() const;
void resize(size_t mbSize, int threadCount);
void clear(size_t threadCount);
TTEntry* first_entry(const Key key) const { void resize(size_t mbSize, ThreadPool& threads); // Set TT size
return &table[mul_hi64(key, clusterCount)].entry[0]; void clear(ThreadPool& threads); // Re-initialize memory, multithreaded
} int hashfull()
const; // Approximate what fraction of entries (permille) have been written to during this root search
uint8_t generation() const { return generation8; } 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.
private: private:
friend struct TTEntry; friend struct TTEntry;
size_t clusterCount; size_t clusterCount;
Cluster* table = nullptr; Cluster* table = nullptr;
uint8_t generation8 = 0; // Size must be not bigger than TTEntry::genBound8
uint8_t generation8 = 0; // Size must be not bigger than TTEntry::genBound8
}; };
} // namespace Stockfish } // namespace Stockfish

View File

@@ -21,6 +21,7 @@
#include <algorithm> #include <algorithm>
#include <iostream> #include <iostream>
#include <map> #include <map>
#include <optional>
#include <sstream> #include <sstream>
#include <string> #include <string>
@@ -30,10 +31,41 @@ using std::string;
namespace Stockfish { namespace Stockfish {
bool Tune::update_on_last; bool Tune::update_on_last;
const Option* LastOption = nullptr; const Option* LastOption = nullptr;
OptionsMap* Tune::options; OptionsMap* Tune::options;
static std::map<std::string, int> TuneResults; namespace {
std::map<std::string, int> TuneResults;
std::optional<std::string> on_tune(const Option& o) {
if (!Tune::update_on_last || LastOption == &o)
Tune::read_options();
return std::nullopt;
}
}
void Tune::make_option(OptionsMap* opts, const string& n, int v, const SetRange& r) {
// Do not generate option when there is nothing to tune (ie. min = max)
if (r(v).first == r(v).second)
return;
if (TuneResults.count(n))
v = TuneResults[n];
(*opts)[n] << Option(v, r(v).first, r(v).second, on_tune);
LastOption = &((*opts)[n]);
// Print formatted parameters, ready to be copy-pasted in Fishtest
std::cout << n << "," //
<< v << "," //
<< r(v).first << "," //
<< r(v).second << "," //
<< (r(v).second - r(v).first) / 20.0 << "," //
<< "0.0020" << std::endl;
}
string Tune::next(string& names, bool pop) { string Tune::next(string& names, bool pop) {
@@ -54,29 +86,6 @@ string Tune::next(string& names, bool pop) {
return name; return name;
} }
static void on_tune(const Option& o) {
if (!Tune::update_on_last || LastOption == &o)
Tune::read_options();
}
static void make_option(OptionsMap* options, const string& n, int v, const SetRange& r) {
// Do not generate option when there is nothing to tune (ie. min = max)
if (r(v).first == r(v).second)
return;
if (TuneResults.count(n))
v = TuneResults[n];
(*options)[n] << Option(v, r(v).first, r(v).second, on_tune);
LastOption = &((*options)[n]);
// Print formatted parameters, ready to be copy-pasted in Fishtest
std::cout << n << "," << v << "," << r(v).first << "," << r(v).second << ","
<< (r(v).second - r(v).first) / 20.0 << ","
<< "0.0020" << std::endl;
}
template<> template<>
void Tune::Entry<int>::init_option() { void Tune::Entry<int>::init_option() {
@@ -112,7 +121,6 @@ void Tune::Entry<Tune::PostUpdate>::read_option() {
namespace Stockfish { namespace Stockfish {
void Tune::read_results() { /* ...insert your values here... */ void Tune::read_results() { /* ...insert your values here... */ }
}
} // namespace Stockfish } // namespace Stockfish

View File

@@ -145,6 +145,8 @@ class Tune {
return add(value, (next(names), std::move(names)), args...); return add(value, (next(names), std::move(names)), args...);
} }
static void make_option(OptionsMap* options, const std::string& n, int v, const SetRange& r);
std::vector<std::unique_ptr<EntryBase>> list; std::vector<std::unique_ptr<EntryBase>> list;
public: public:
@@ -158,7 +160,7 @@ class Tune {
for (auto& e : instance().list) for (auto& e : instance().list)
e->init_option(); e->init_option();
read_options(); read_options();
} // Deferred, due to UCI::Options access } // Deferred, due to UCIEngine::Options access
static void read_options() { static void read_options() {
for (auto& e : instance().list) for (auto& e : instance().list)
e->read_option(); e->read_option();

View File

@@ -137,9 +137,9 @@ enum Bound {
BOUND_EXACT = BOUND_UPPER | BOUND_LOWER BOUND_EXACT = BOUND_UPPER | BOUND_LOWER
}; };
// Value is used as an alias for int16_t, this is done to differentiate between // Value is used as an alias for int, this is done to differentiate between a search
// a search value and any other integer value. The values used in search are always // value and any other integer value. The values used in search are always supposed
// supposed to be in the range (-VALUE_NONE, VALUE_NONE] and should not exceed this range. // to be in the range (-VALUE_NONE, VALUE_NONE] and should not exceed this range.
using Value = int; using Value = int;
constexpr Value VALUE_ZERO = 0; constexpr Value VALUE_ZERO = 0;
@@ -187,12 +187,21 @@ constexpr Value PieceValue[PIECE_NB] = {
using Depth = int; using Depth = int;
enum : int { enum : int {
DEPTH_QS_CHECKS = 0, // The following DEPTH_ constants are used for transposition table entries
DEPTH_QS_NO_CHECKS = -1, // and quiescence search move generation stages. In regular search, the
// depth stored in the transposition table is literal: the search depth
DEPTH_NONE = -6, // (effort) used to make the corresponding transposition table value. In
// quiescence search, however, the transposition table entries only store
DEPTH_OFFSET = -7 // value used only for TT entry occupancy check // the current quiescence move generation stage (which should thus compare
// lower than any regular search depth).
DEPTH_QS = 0,
// For transposition table entries where no searching at all was done
// (whether regular or qsearch) we use DEPTH_UNSEARCHED, which should thus
// compare lower than any quiescence or regular depth. DEPTH_ENTRY_OFFSET
// is used only for the transposition table entry occupancy check (see tt.cpp),
// and should thus be lower than DEPTH_UNSEARCHED.
DEPTH_UNSEARCHED = -2,
DEPTH_ENTRY_OFFSET = -3
}; };
// clang-format off // clang-format off
@@ -351,9 +360,10 @@ enum MoveType {
// bit 14-15: special move flag: promotion (1), en passant (2), castling (3) // bit 14-15: special move flag: promotion (1), en passant (2), castling (3)
// NOTE: en passant bit is set only when a pawn can be captured // NOTE: en passant bit is set only when a pawn can be captured
// //
// Special cases are Move::none() and Move::null(). We can sneak these in because in // Special cases are Move::none() and Move::null(). We can sneak these in because
// any normal move destination square is always different from origin square // in any normal move the destination square and origin square are always different,
// while Move::none() and Move::null() have the same origin and destination square. // but Move::none() and Move::null() have the same origin and destination square.
class Move { class Move {
public: public:
Move() = default; Move() = default;

View File

@@ -19,86 +19,65 @@
#include "uci.h" #include "uci.h"
#include <algorithm> #include <algorithm>
#include <cassert>
#include <cctype> #include <cctype>
#include <cmath> #include <cmath>
#include <cstdlib> #include <cstdint>
#include <deque>
#include <memory>
#include <optional> #include <optional>
#include <sstream> #include <sstream>
#include <string_view>
#include <utility>
#include <vector> #include <vector>
#include <cstdint>
#include "benchmark.h" #include "benchmark.h"
#include "evaluate.h" #include "engine.h"
#include "movegen.h" #include "movegen.h"
#include "nnue/evaluate_nnue.h"
#include "nnue/nnue_architecture.h"
#include "position.h" #include "position.h"
#include "score.h"
#include "search.h" #include "search.h"
#include "syzygy/tbprobe.h"
#include "types.h" #include "types.h"
#include "ucioption.h" #include "ucioption.h"
#include "perft.h"
namespace Stockfish { namespace Stockfish {
constexpr auto StartFEN = "rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1"; constexpr auto StartFEN = "rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1";
constexpr int NormalizeToPawnValue = 356; template<typename... Ts>
constexpr int MaxHashMB = Is64Bit ? 33554432 : 2048; struct overload: Ts... {
using Ts::operator()...;
};
UCI::UCI(int argc, char** argv) : template<typename... Ts>
cli(argc, argv) { overload(Ts...) -> overload<Ts...>;
evalFiles = {{Eval::NNUE::Big, {"EvalFile", EvalFileDefaultNameBig, "None", ""}}, void UCIEngine::print_info_string(const std::string& str) {
{Eval::NNUE::Small, {"EvalFileSmall", EvalFileDefaultNameSmall, "None", ""}}}; sync_cout_start();
for (auto& line : split(str, "\n"))
{
options["Debug Log File"] << Option("", [](const Option& o) { start_logger(o); }); if (!is_whitespace(line))
{
options["Threads"] << Option(1, 1, 1024, [this](const Option&) { std::cout << "info string " << line << '\n';
threads.set({options, threads, tt}); }
}); }
sync_cout_end();
options["Hash"] << Option(16, 1, MaxHashMB, [this](const Option& o) {
threads.main_thread()->wait_for_search_finished();
tt.resize(o, options["Threads"]);
});
options["Clear Hash"] << Option([this](const Option&) { search_clear(); });
options["Ponder"] << Option(false);
options["MultiPV"] << Option(1, 1, MAX_MOVES);
options["Skill Level"] << Option(20, 0, 20);
options["Move Overhead"] << Option(10, 0, 5000);
options["nodestime"] << Option(0, 0, 10000);
options["UCI_Chess960"] << Option(false);
options["UCI_LimitStrength"] << Option(false);
options["UCI_Elo"] << Option(1320, 1320, 3190);
options["UCI_ShowWDL"] << Option(false);
options["SyzygyPath"] << Option("<empty>", [](const Option& o) { Tablebases::init(o); });
options["SyzygyProbeDepth"] << Option(1, 1, 100);
options["Syzygy50MoveRule"] << Option(true);
options["SyzygyProbeLimit"] << Option(7, 0, 7);
options["EvalFile"] << Option(EvalFileDefaultNameBig, [this](const Option&) {
evalFiles = Eval::NNUE::load_networks(cli.binaryDirectory, options, evalFiles);
});
options["EvalFileSmall"] << Option(EvalFileDefaultNameSmall, [this](const Option&) {
evalFiles = Eval::NNUE::load_networks(cli.binaryDirectory, options, evalFiles);
});
threads.set({options, threads, tt});
search_clear(); // After threads are up
} }
void UCI::loop() { UCIEngine::UCIEngine(int argc, char** argv) :
engine(argv[0]),
cli(argc, argv) {
Position pos; engine.get_options().add_info_listener([](const std::optional<std::string>& str) {
std::string token, cmd; if (str.has_value())
StateListPtr states(new std::deque<StateInfo>(1)); print_info_string(*str);
});
pos.set(StartFEN, false, &states->back()); engine.set_on_iter([](const auto& i) { on_iter(i); });
engine.set_on_update_no_moves([](const auto& i) { on_update_no_moves(i); });
engine.set_on_update_full(
[this](const auto& i) { on_update_full(i, engine.get_options()["UCI_ShowWDL"]); });
engine.set_on_bestmove([](const auto& bm, const auto& p) { on_bestmove(bm, p); });
}
void UCIEngine::loop() {
std::string token, cmd;
for (int i = 1; i < cli.argc; ++i) for (int i = 1; i < cli.argc; ++i)
cmd += std::string(cli.argv[i]) + " "; cmd += std::string(cli.argv[i]) + " ";
@@ -115,49 +94,62 @@ void UCI::loop() {
is >> std::skipws >> token; is >> std::skipws >> token;
if (token == "quit" || token == "stop") if (token == "quit" || token == "stop")
threads.stop = true; engine.stop();
// The GUI sends 'ponderhit' to tell that the user has played the expected move. // The GUI sends 'ponderhit' to tell that the user has played the expected move.
// So, 'ponderhit' is sent if pondering was done on the same move that the user // So, 'ponderhit' is sent if pondering was done on the same move that the user
// has played. The search should continue, but should also switch from pondering // has played. The search should continue, but should also switch from pondering
// to the normal search. // to the normal search.
else if (token == "ponderhit") else if (token == "ponderhit")
threads.main_manager()->ponder = false; // Switch to the normal search engine.set_ponderhit(false);
else if (token == "uci") else if (token == "uci")
{
sync_cout << "id name " << engine_info(true) << "\n" sync_cout << "id name " << engine_info(true) << "\n"
<< options << "\nuciok" << sync_endl; << engine.get_options() << sync_endl;
sync_cout << "uciok" << sync_endl;
}
else if (token == "setoption") else if (token == "setoption")
setoption(is); setoption(is);
else if (token == "go") else if (token == "go")
go(pos, is, states); {
// send info strings after the go command is sent for old GUIs and python-chess
print_info_string(engine.numa_config_information_as_string());
print_info_string(engine.thread_binding_information_as_string());
go(is);
}
else if (token == "position") else if (token == "position")
position(pos, is, states); position(is);
else if (token == "ucinewgame") else if (token == "ucinewgame")
search_clear(); engine.search_clear();
else if (token == "isready") else if (token == "isready")
sync_cout << "readyok" << sync_endl; sync_cout << "readyok" << sync_endl;
// Add custom non-UCI commands, mainly for debugging purposes. // Add custom non-UCI commands, mainly for debugging purposes.
// These commands must not be used during a search! // These commands must not be used during a search!
else if (token == "flip") else if (token == "flip")
pos.flip(); engine.flip();
else if (token == "bench") else if (token == "bench")
bench(pos, is, states); bench(is);
else if (token == "d") else if (token == "d")
sync_cout << pos << sync_endl; sync_cout << engine.visualize() << sync_endl;
else if (token == "eval") else if (token == "eval")
trace_eval(pos); engine.trace_eval();
else if (token == "compiler") else if (token == "compiler")
sync_cout << compiler_info() << sync_endl; sync_cout << compiler_info() << sync_endl;
else if (token == "export_net") else if (token == "export_net")
{ {
std::optional<std::string> filename; std::pair<std::optional<std::string>, std::string> files[2];
std::string f;
if (is >> std::skipws >> f) if (is >> std::skipws >> files[0].second)
filename = f; files[0].first = files[0].second;
Eval::NNUE::save_eval(filename, Eval::NNUE::Big, evalFiles);
if (is >> std::skipws >> files[1].second)
files[1].first = files[1].second;
engine.save_network(files);
} }
else if (token == "--help" || token == "help" || token == "--license" || token == "license") else if (token == "--help" || token == "help" || token == "--license" || token == "license")
sync_cout sync_cout
@@ -175,18 +167,16 @@ void UCI::loop() {
} while (token != "quit" && cli.argc == 1); // The command-line arguments are one-shot } while (token != "quit" && cli.argc == 1); // The command-line arguments are one-shot
} }
void UCI::go(Position& pos, std::istringstream& is, StateListPtr& states) { Search::LimitsType UCIEngine::parse_limits(std::istream& is) {
Search::LimitsType limits; Search::LimitsType limits;
std::string token; std::string token;
bool ponderMode = false;
limits.startTime = now(); // The search starts as early as possible limits.startTime = now(); // The search starts as early as possible
while (is >> token) while (is >> token)
if (token == "searchmoves") // Needs to be the last command on the line if (token == "searchmoves") // Needs to be the last command on the line
while (is >> token) while (is >> token)
limits.searchmoves.push_back(to_move(pos, token)); limits.searchmoves.push_back(to_lower(token));
else if (token == "wtime") else if (token == "wtime")
is >> limits.time[WHITE]; is >> limits.time[WHITE];
@@ -211,24 +201,33 @@ void UCI::go(Position& pos, std::istringstream& is, StateListPtr& states) {
else if (token == "infinite") else if (token == "infinite")
limits.infinite = 1; limits.infinite = 1;
else if (token == "ponder") else if (token == "ponder")
ponderMode = true; limits.ponderMode = true;
Eval::NNUE::verify(options, evalFiles); return limits;
if (limits.perft)
{
perft(pos.fen(), limits.perft, options["UCI_Chess960"]);
return;
}
threads.start_thinking(options, pos, states, limits, ponderMode);
} }
void UCI::bench(Position& pos, std::istream& args, StateListPtr& states) { void UCIEngine::go(std::istringstream& is) {
Search::LimitsType limits = parse_limits(is);
if (limits.perft)
perft(limits);
else
engine.go(limits);
}
void UCIEngine::bench(std::istream& args) {
std::string token; std::string token;
uint64_t num, nodes = 0, cnt = 1; uint64_t num, nodes = 0, cnt = 1;
uint64_t nodesSearched = 0;
const auto& options = engine.get_options();
std::vector<std::string> list = setup_bench(pos, args); engine.set_on_update_full([&](const auto& i) {
nodesSearched = i.nodes;
on_update_full(i, options["UCI_ShowWDL"]);
});
std::vector<std::string> list = Benchmark::setup_bench(engine.fen(), args);
num = count_if(list.begin(), list.end(), num = count_if(list.begin(), list.end(),
[](const std::string& s) { return s.find("go ") == 0 || s.find("eval") == 0; }); [](const std::string& s) { return s.find("go ") == 0 || s.find("eval") == 0; });
@@ -242,24 +241,33 @@ void UCI::bench(Position& pos, std::istream& args, StateListPtr& states) {
if (token == "go" || token == "eval") if (token == "go" || token == "eval")
{ {
std::cerr << "\nPosition: " << cnt++ << '/' << num << " (" << pos.fen() << ")" std::cerr << "\nPosition: " << cnt++ << '/' << num << " (" << engine.fen() << ")"
<< std::endl; << std::endl;
if (token == "go") if (token == "go")
{ {
go(pos, is, states); Search::LimitsType limits = parse_limits(is);
threads.main_thread()->wait_for_search_finished();
nodes += threads.nodes_searched(); if (limits.perft)
nodesSearched = perft(limits);
else
{
engine.go(limits);
engine.wait_for_search_finished();
}
nodes += nodesSearched;
nodesSearched = 0;
} }
else else
trace_eval(pos); engine.trace_eval();
} }
else if (token == "setoption") else if (token == "setoption")
setoption(is); setoption(is);
else if (token == "position") else if (token == "position")
position(pos, is, states); position(is);
else if (token == "ucinewgame") else if (token == "ucinewgame")
{ {
search_clear(); // Search::clear() may take a while engine.search_clear(); // search_clear may take a while
elapsed = now(); elapsed = now();
} }
} }
@@ -268,36 +276,28 @@ void UCI::bench(Position& pos, std::istream& args, StateListPtr& states) {
dbg_print(); dbg_print();
std::cerr << "\n===========================" std::cerr << "\n===========================" //
<< "\nTotal time (ms) : " << elapsed << "\nNodes searched : " << nodes << "\nTotal time (ms) : " << elapsed //
<< "\nNodes searched : " << nodes //
<< "\nNodes/second : " << 1000 * nodes / elapsed << std::endl; << "\nNodes/second : " << 1000 * nodes / elapsed << std::endl;
// reset callback, to not capture a dangling reference to nodesSearched
engine.set_on_update_full([&](const auto& i) { on_update_full(i, options["UCI_ShowWDL"]); });
} }
void UCI::trace_eval(Position& pos) {
StateListPtr states(new std::deque<StateInfo>(1));
Position p;
p.set(pos.fen(), options["UCI_Chess960"], &states->back());
Eval::NNUE::verify(options, evalFiles); void UCIEngine::setoption(std::istringstream& is) {
engine.wait_for_search_finished();
sync_cout << "\n" << Eval::trace(p) << sync_endl; engine.get_options().setoption(is);
} }
void UCI::search_clear() { std::uint64_t UCIEngine::perft(const Search::LimitsType& limits) {
threads.main_thread()->wait_for_search_finished(); auto nodes = engine.perft(engine.fen(), limits.perft, engine.get_options()["UCI_Chess960"]);
sync_cout << "\nNodes searched: " << nodes << "\n" << sync_endl;
tt.clear(options["Threads"]); return nodes;
threads.clear();
Tablebases::init(options["SyzygyPath"]); // Free mapped files
} }
void UCI::setoption(std::istringstream& is) { void UCIEngine::position(std::istringstream& is) {
threads.main_thread()->wait_for_search_finished();
options.setoption(is);
}
void UCI::position(Position& pos, std::istringstream& is, StateListPtr& states) {
Move m;
std::string token, fen; std::string token, fen;
is >> token; is >> token;
@@ -313,42 +313,99 @@ void UCI::position(Position& pos, std::istringstream& is, StateListPtr& states)
else else
return; return;
states = StateListPtr(new std::deque<StateInfo>(1)); // Drop the old state and create a new one std::vector<std::string> moves;
pos.set(fen, options["UCI_Chess960"], &states->back());
// Parse the move list, if any while (is >> token)
while (is >> token && (m = to_move(pos, token)) != Move::none())
{ {
states->emplace_back(); moves.push_back(token);
pos.do_move(m, states->back());
} }
engine.set_position(fen, moves);
} }
int UCI::to_cp(Value v) { return 100 * v / NormalizeToPawnValue; } namespace {
std::string UCI::value(Value v) { struct WinRateParams {
assert(-VALUE_INFINITE < v && v < VALUE_INFINITE); double a;
double b;
};
WinRateParams win_rate_params(const Position& pos) {
int material = pos.count<PAWN>() + 3 * pos.count<KNIGHT>() + 3 * pos.count<BISHOP>()
+ 5 * pos.count<ROOK>() + 9 * pos.count<QUEEN>();
// The fitted model only uses data for material counts in [17, 78], and is anchored at count 58.
double m = std::clamp(material, 17, 78) / 58.0;
// Return a = p_a(material) and b = p_b(material), see github.com/official-stockfish/WDL_model
constexpr double as[] = {-37.45051876, 121.19101539, -132.78783573, 420.70576692};
constexpr double bs[] = {90.26261072, -137.26549898, 71.10130540, 51.35259597};
double a = (((as[0] * m + as[1]) * m + as[2]) * m) + as[3];
double b = (((bs[0] * m + bs[1]) * m + bs[2]) * m) + bs[3];
return {a, b};
}
// The win rate model is 1 / (1 + exp((a - eval) / b)), where a = p_a(material) and b = p_b(material).
// It fits the LTC fishtest statistics rather accurately.
int win_rate_model(Value v, const Position& pos) {
auto [a, b] = win_rate_params(pos);
// Return the win rate in per mille units, rounded to the nearest integer.
return int(0.5 + 1000 / (1 + std::exp((a - double(v)) / b)));
}
}
std::string UCIEngine::format_score(const Score& s) {
constexpr int TB_CP = 20000;
const auto format =
overload{[](Score::Mate mate) -> std::string {
auto m = (mate.plies > 0 ? (mate.plies + 1) : mate.plies) / 2;
return std::string("mate ") + std::to_string(m);
},
[](Score::Tablebase tb) -> std::string {
return std::string("cp ")
+ std::to_string((tb.win ? TB_CP - tb.plies : -TB_CP - tb.plies));
},
[](Score::InternalUnits units) -> std::string {
return std::string("cp ") + std::to_string(units.value);
}};
return s.visit(format);
}
// Turns a Value to an integer centipawn number,
// without treatment of mate and similar special scores.
int UCIEngine::to_cp(Value v, const Position& pos) {
// In general, the score can be defined via the WDL as
// (log(1/L - 1) - log(1/W - 1)) / (log(1/L - 1) + log(1/W - 1)).
// Based on our win_rate_model, this simply yields v / a.
auto [a, b] = win_rate_params(pos);
return std::round(100 * int(v) / a);
}
std::string UCIEngine::wdl(Value v, const Position& pos) {
std::stringstream ss; std::stringstream ss;
if (std::abs(v) < VALUE_TB_WIN_IN_MAX_PLY) int wdl_w = win_rate_model(v, pos);
ss << "cp " << to_cp(v); int wdl_l = win_rate_model(-v, pos);
else if (std::abs(v) <= VALUE_TB) int wdl_d = 1000 - wdl_w - wdl_l;
{ ss << wdl_w << " " << wdl_d << " " << wdl_l;
const int ply = VALUE_TB - std::abs(v); // recompute ss->ply
ss << "cp " << (v > 0 ? 20000 - ply : -20000 + ply);
}
else
ss << "mate " << (v > 0 ? VALUE_MATE - v + 1 : -VALUE_MATE - v) / 2;
return ss.str(); return ss.str();
} }
std::string UCI::square(Square s) { std::string UCIEngine::square(Square s) {
return std::string{char('a' + file_of(s)), char('1' + rank_of(s))}; return std::string{char('a' + file_of(s)), char('1' + rank_of(s))};
} }
std::string UCI::move(Move m, bool chess960) { std::string UCIEngine::move(Move m, bool chess960) {
if (m == Move::none()) if (m == Move::none())
return "(none)"; return "(none)";
@@ -369,45 +426,15 @@ std::string UCI::move(Move m, bool chess960) {
return move; return move;
} }
namespace {
// The win rate model returns the probability of winning (in per mille units) given an
// eval and a game ply. It fits the LTC fishtest statistics rather accurately.
int win_rate_model(Value v, int ply) {
// The fitted model only uses data for moves in [8, 120], and is anchored at move 32. std::string UCIEngine::to_lower(std::string str) {
double m = std::clamp(ply / 2 + 1, 8, 120) / 32.0; std::transform(str.begin(), str.end(), str.begin(), [](auto c) { return std::tolower(c); });
// The coefficients of a third-order polynomial fit is based on the fishtest data return str;
// for two parameters that need to transform eval to the argument of a logistic
// function.
constexpr double as[] = {-1.06249702, 7.42016937, 0.89425629, 348.60356174};
constexpr double bs[] = {-5.33122190, 39.57831533, -90.84473771, 123.40620748};
// Enforce that NormalizeToPawnValue corresponds to a 50% win rate at move 32.
static_assert(NormalizeToPawnValue == int(0.5 + as[0] + as[1] + as[2] + as[3]));
double a = (((as[0] * m + as[1]) * m + as[2]) * m) + as[3];
double b = (((bs[0] * m + bs[1]) * m + bs[2]) * m) + bs[3];
// Return the win rate in per mille units, rounded to the nearest integer.
return int(0.5 + 1000 / (1 + std::exp((a - double(v)) / b)));
}
} }
std::string UCI::wdl(Value v, int ply) { Move UCIEngine::to_move(const Position& pos, std::string str) {
std::stringstream ss; str = to_lower(str);
int wdl_w = win_rate_model(v, ply);
int wdl_l = win_rate_model(-v, ply);
int wdl_d = 1000 - wdl_w - wdl_l;
ss << " wdl " << wdl_w << " " << wdl_d << " " << wdl_l;
return ss.str();
}
Move UCI::to_move(const Position& pos, std::string& str) {
if (str.length() == 5)
str[4] = char(tolower(str[4])); // The promotion piece character must be lowercased
for (const auto& m : MoveList<LEGAL>(pos)) for (const auto& m : MoveList<LEGAL>(pos))
if (str == move(m, pos.is_chess960())) if (str == move(m, pos.is_chess960()))
@@ -416,4 +443,51 @@ Move UCI::to_move(const Position& pos, std::string& str) {
return Move::none(); return Move::none();
} }
void UCIEngine::on_update_no_moves(const Engine::InfoShort& info) {
sync_cout << "info depth " << info.depth << " score " << format_score(info.score) << sync_endl;
}
void UCIEngine::on_update_full(const Engine::InfoFull& info, bool showWDL) {
std::stringstream ss;
ss << "info";
ss << " depth " << info.depth //
<< " seldepth " << info.selDepth //
<< " multipv " << info.multiPV //
<< " score " << format_score(info.score); //
if (showWDL)
ss << " wdl " << info.wdl;
if (!info.bound.empty())
ss << " " << info.bound;
ss << " nodes " << info.nodes //
<< " nps " << info.nps //
<< " hashfull " << info.hashfull //
<< " tbhits " << info.tbHits //
<< " time " << info.timeMs //
<< " pv " << info.pv; //
sync_cout << ss.str() << sync_endl;
}
void UCIEngine::on_iter(const Engine::InfoIter& info) {
std::stringstream ss;
ss << "info";
ss << " depth " << info.depth //
<< " currmove " << info.currmove //
<< " currmovenumber " << info.currmovenumber; //
sync_cout << ss.str() << sync_endl;
}
void UCIEngine::on_bestmove(std::string_view bestmove, std::string_view ponder) {
sync_cout << "bestmove " << bestmove;
if (!ponder.empty())
std::cout << " ponder " << ponder;
std::cout << sync_endl;
}
} // namespace Stockfish } // namespace Stockfish

View File

@@ -19,57 +19,57 @@
#ifndef UCI_H_INCLUDED #ifndef UCI_H_INCLUDED
#define UCI_H_INCLUDED #define UCI_H_INCLUDED
#include <cstdint>
#include <iostream> #include <iostream>
#include <string> #include <string>
#include <unordered_map> #include <string_view>
#include "evaluate.h" #include "engine.h"
#include "misc.h" #include "misc.h"
#include "position.h" #include "search.h"
#include "thread.h"
#include "tt.h"
#include "ucioption.h"
namespace Stockfish { namespace Stockfish {
namespace Eval::NNUE { class Position;
enum NetSize : int;
}
class Move; class Move;
class Score;
enum Square : int; enum Square : int;
using Value = int; using Value = int;
class UCI { class UCIEngine {
public: public:
UCI(int argc, char** argv); UCIEngine(int argc, char** argv);
void loop(); void loop();
static int to_cp(Value v); static int to_cp(Value v, const Position& pos);
static std::string value(Value v); static std::string format_score(const Score& s);
static std::string square(Square s); static std::string square(Square s);
static std::string move(Move m, bool chess960); static std::string move(Move m, bool chess960);
static std::string wdl(Value v, int ply); static std::string wdl(Value v, const Position& pos);
static Move to_move(const Position& pos, std::string& str); static std::string to_lower(std::string str);
static Move to_move(const Position& pos, std::string str);
const std::string& workingDirectory() const { return cli.workingDirectory; } static Search::LimitsType parse_limits(std::istream& is);
OptionsMap options; auto& engine_options() { return engine.get_options(); }
std::unordered_map<Eval::NNUE::NetSize, Eval::EvalFile> evalFiles;
private: private:
TranspositionTable tt; Engine engine;
ThreadPool threads; CommandLine cli;
CommandLine cli;
void go(Position& pos, std::istringstream& is, StateListPtr& states); static void print_info_string(const std::string& str);
void bench(Position& pos, std::istream& args, StateListPtr& states);
void position(Position& pos, std::istringstream& is, StateListPtr& states); void go(std::istringstream& is);
void trace_eval(Position& pos); void bench(std::istream& args);
void search_clear(); void position(std::istringstream& is);
void setoption(std::istringstream& is); void setoption(std::istringstream& is);
std::uint64_t perft(const Search::LimitsType&);
static void on_update_no_moves(const Engine::InfoShort& info);
static void on_update_full(const Engine::InfoFull& info, bool showWDL);
static void on_iter(const Engine::InfoIter& info);
static void on_bestmove(std::string_view bestmove, std::string_view ponder);
}; };
} // namespace Stockfish } // namespace Stockfish

View File

@@ -36,6 +36,8 @@ bool CaseInsensitiveLess::operator()(const std::string& s1, const std::string& s
[](char c1, char c2) { return std::tolower(c1) < std::tolower(c2); }); [](char c1, char c2) { return std::tolower(c1) < std::tolower(c2); });
} }
void OptionsMap::add_info_listener(InfoListener&& message_func) { info = std::move(message_func); }
void OptionsMap::setoption(std::istringstream& is) { void OptionsMap::setoption(std::istringstream& is) {
std::string token, name, value; std::string token, name, value;
@@ -57,13 +59,20 @@ void OptionsMap::setoption(std::istringstream& is) {
Option OptionsMap::operator[](const std::string& name) const { Option OptionsMap::operator[](const std::string& name) const {
auto it = options_map.find(name); auto it = options_map.find(name);
return it != options_map.end() ? it->second : Option(); return it != options_map.end() ? it->second : Option(this);
} }
Option& OptionsMap::operator[](const std::string& name) { return options_map[name]; } Option& OptionsMap::operator[](const std::string& name) {
if (!options_map.count(name))
options_map[name] = Option(this);
return options_map[name];
}
std::size_t OptionsMap::count(const std::string& name) const { return options_map.count(name); } std::size_t OptionsMap::count(const std::string& name) const { return options_map.count(name); }
Option::Option(const OptionsMap* map) :
parent(map) {}
Option::Option(const char* v, OnChange f) : Option::Option(const char* v, OnChange f) :
type("string"), type("string"),
min(0), min(0),
@@ -118,6 +127,8 @@ bool Option::operator==(const char* s) const {
return !CaseInsensitiveLess()(currentValue, s) && !CaseInsensitiveLess()(s, currentValue); return !CaseInsensitiveLess()(currentValue, s) && !CaseInsensitiveLess()(s, currentValue);
} }
bool Option::operator!=(const char* s) const { return !(*this == s); }
// Inits options and assigns idx in the correct printing order // Inits options and assigns idx in the correct printing order
@@ -125,10 +136,12 @@ void Option::operator<<(const Option& o) {
static size_t insert_order = 0; static size_t insert_order = 0;
*this = o; auto p = this->parent;
idx = insert_order++; *this = o;
}
this->parent = p;
idx = insert_order++;
}
// Updates currentValue and triggers on_change() action. It's up to // Updates currentValue and triggers on_change() action. It's up to
// the GUI to check for option's limits, but we could receive the new value // the GUI to check for option's limits, but we could receive the new value
@@ -153,11 +166,18 @@ Option& Option::operator=(const std::string& v) {
return *this; return *this;
} }
if (type != "button") if (type == "string")
currentValue = v == "<empty>" ? "" : v;
else if (type != "button")
currentValue = v; currentValue = v;
if (on_change) if (on_change)
on_change(*this); {
const auto ret = on_change(*this);
if (ret && parent != nullptr && parent->info != nullptr)
parent->info(ret);
}
return *this; return *this;
} }
@@ -170,10 +190,16 @@ std::ostream& operator<<(std::ostream& os, const OptionsMap& om) {
const Option& o = it.second; const Option& o = it.second;
os << "\noption name " << it.first << " type " << o.type; os << "\noption name " << it.first << " type " << o.type;
if (o.type == "string" || o.type == "check" || o.type == "combo") if (o.type == "check" || o.type == "combo")
os << " default " << o.defaultValue; os << " default " << o.defaultValue;
if (o.type == "spin") else if (o.type == "string")
{
std::string defaultValue = o.defaultValue.empty() ? "<empty>" : o.defaultValue;
os << " default " << defaultValue;
}
else if (o.type == "spin")
os << " default " << int(stof(o.defaultValue)) << " min " << o.min << " max " os << " default " << int(stof(o.defaultValue)) << " min " << o.min << " max "
<< o.max; << o.max;

View File

@@ -23,6 +23,7 @@
#include <functional> #include <functional>
#include <iosfwd> #include <iosfwd>
#include <map> #include <map>
#include <optional>
#include <string> #include <string>
namespace Stockfish { namespace Stockfish {
@@ -31,31 +32,14 @@ struct CaseInsensitiveLess {
bool operator()(const std::string&, const std::string&) const; bool operator()(const std::string&, const std::string&) const;
}; };
class Option; class OptionsMap;
class OptionsMap {
public:
void setoption(std::istringstream&);
friend std::ostream& operator<<(std::ostream&, const OptionsMap&);
Option operator[](const std::string&) const;
Option& operator[](const std::string&);
std::size_t count(const std::string&) const;
private:
// The options container is defined as a std::map
using OptionsStore = std::map<std::string, Option, CaseInsensitiveLess>;
OptionsStore options_map;
};
// The Option class implements each option as specified by the UCI protocol // The Option class implements each option as specified by the UCI protocol
class Option { class Option {
public: public:
using OnChange = std::function<void(const Option&)>; using OnChange = std::function<std::optional<std::string>(const Option&)>;
Option(const OptionsMap*);
Option(OnChange = nullptr); Option(OnChange = nullptr);
Option(bool v, OnChange = nullptr); Option(bool v, OnChange = nullptr);
Option(const char* v, OnChange = nullptr); Option(const char* v, OnChange = nullptr);
@@ -63,18 +47,57 @@ class Option {
Option(const char* v, const char* cur, OnChange = nullptr); Option(const char* v, const char* cur, OnChange = nullptr);
Option& operator=(const std::string&); Option& operator=(const std::string&);
void operator<<(const Option&);
operator int() const; operator int() const;
operator std::string() const; operator std::string() const;
bool operator==(const char*) const; bool operator==(const char*) const;
bool operator!=(const char*) const;
friend std::ostream& operator<<(std::ostream&, const OptionsMap&); friend std::ostream& operator<<(std::ostream&, const OptionsMap&);
private: private:
std::string defaultValue, currentValue, type; friend class OptionsMap;
int min, max; friend class Engine;
size_t idx; friend class Tune;
OnChange on_change;
void operator<<(const Option&);
std::string defaultValue, currentValue, type;
int min, max;
size_t idx;
OnChange on_change;
const OptionsMap* parent = nullptr;
};
class OptionsMap {
public:
using InfoListener = std::function<void(std::optional<std::string>)>;
OptionsMap() = default;
OptionsMap(const OptionsMap&) = delete;
OptionsMap(OptionsMap&&) = delete;
OptionsMap& operator=(const OptionsMap&) = delete;
OptionsMap& operator=(OptionsMap&&) = delete;
void add_info_listener(InfoListener&&);
void setoption(std::istringstream&);
Option operator[](const std::string&) const;
Option& operator[](const std::string&);
std::size_t count(const std::string&) const;
private:
friend class Engine;
friend class Option;
friend std::ostream& operator<<(std::ostream&, const OptionsMap&);
// The options container is defined as a std::map
using OptionsStore = std::map<std::string, Option, CaseInsensitiveLess>;
OptionsStore options_map;
InfoListener info;
}; };
} }

View File

@@ -14,14 +14,14 @@ case $1 in
echo "valgrind testing started" echo "valgrind testing started"
prefix='' prefix=''
exeprefix='valgrind --error-exitcode=42 --errors-for-leak-kinds=all --leak-check=full' exeprefix='valgrind --error-exitcode=42 --errors-for-leak-kinds=all --leak-check=full'
postfix='1>/dev/null' postfix=''
threads="1" threads="1"
;; ;;
--valgrind-thread) --valgrind-thread)
echo "valgrind-thread testing started" echo "valgrind-thread testing started"
prefix='' prefix=''
exeprefix='valgrind --fair-sched=try --error-exitcode=42' exeprefix='valgrind --fair-sched=try --error-exitcode=42'
postfix='1>/dev/null' postfix=''
threads="2" threads="2"
;; ;;
--sanitizer-undefined) --sanitizer-undefined)
@@ -39,13 +39,8 @@ case $1 in
threads="2" threads="2"
cat << EOF > tsan.supp cat << EOF > tsan.supp
race:Stockfish::TTEntry::move race:Stockfish::TTEntry::read
race:Stockfish::TTEntry::depth
race:Stockfish::TTEntry::bound
race:Stockfish::TTEntry::save race:Stockfish::TTEntry::save
race:Stockfish::TTEntry::value
race:Stockfish::TTEntry::eval
race:Stockfish::TTEntry::is_pv
race:Stockfish::TranspositionTable::probe race:Stockfish::TranspositionTable::probe
race:Stockfish::TranspositionTable::hashfull race:Stockfish::TranspositionTable::hashfull
@@ -105,7 +100,12 @@ diff $network verify.nnue
# more general testing, following an uci protocol exchange # more general testing, following an uci protocol exchange
cat << EOF > game.exp cat << EOF > game.exp
set timeout 240 set timeout 240
# to correctly catch eof we need the following line
# expect_before timeout { exit 2 } eof { exit 3 }
expect_before timeout { exit 2 }
spawn $exeprefix ./stockfish spawn $exeprefix ./stockfish
expect "Stockfish"
send "uci\n" send "uci\n"
expect "uciok" expect "uciok"
@@ -118,27 +118,106 @@ cat << EOF > game.exp
send "go nodes 1000\n" send "go nodes 1000\n"
expect "bestmove" expect "bestmove"
send "ucinewgame\n"
send "position startpos moves e2e4 e7e6\n" send "position startpos moves e2e4 e7e6\n"
send "go nodes 1000\n" send "go nodes 1000\n"
expect "bestmove" expect "bestmove"
send "ucinewgame\n"
send "position fen 5rk1/1K4p1/8/8/3B4/8/8/8 b - - 0 1\n" send "position fen 5rk1/1K4p1/8/8/3B4/8/8/8 b - - 0 1\n"
send "go depth 10\n" send "go depth 10\n"
expect "bestmove" expect "bestmove"
send "setoption name UCI_ShowWDL value true\n" send "ucinewgame\n"
send "position startpos\n" send "position fen 5rk1/1K4p1/8/8/3B4/8/8/8 b - - 0 1\n"
send "flip\n" send "flip\n"
send "go depth 5\n" send "go depth 10\n"
expect "bestmove" expect "bestmove"
send "setoption name Skill Level value 10\n" send "ucinewgame\n"
send "position startpos\n" send "position startpos\n"
send "go depth 5\n" send "go depth 5\n"
expect -re {info depth \d+ seldepth \d+ multipv \d+ score cp \d+ nodes \d+ nps \d+ hashfull \d+ tbhits \d+ time \d+ pv}
expect "bestmove"
send "ucinewgame\n"
send "setoption name UCI_ShowWDL value true\n"
send "position startpos\n"
send "go depth 9\n"
expect -re {info depth 1 seldepth \d+ multipv \d+ score cp \d+ wdl \d+ \d+ \d+ nodes \d+ nps \d+ hashfull \d+ tbhits \d+ time \d+ pv}
expect -re {info depth 2 seldepth \d+ multipv \d+ score cp \d+ wdl \d+ \d+ \d+ nodes \d+ nps \d+ hashfull \d+ tbhits \d+ time \d+ pv}
expect -re {info depth 3 seldepth \d+ multipv \d+ score cp \d+ wdl \d+ \d+ \d+ nodes \d+ nps \d+ hashfull \d+ tbhits \d+ time \d+ pv}
expect -re {info depth 4 seldepth \d+ multipv \d+ score cp \d+ wdl \d+ \d+ \d+ nodes \d+ nps \d+ hashfull \d+ tbhits \d+ time \d+ pv}
expect -re {info depth 5 seldepth \d+ multipv \d+ score cp \d+ wdl \d+ \d+ \d+ nodes \d+ nps \d+ hashfull \d+ tbhits \d+ time \d+ pv}
expect -re {info depth 6 seldepth \d+ multipv \d+ score cp \d+ wdl \d+ \d+ \d+ nodes \d+ nps \d+ hashfull \d+ tbhits \d+ time \d+ pv}
expect -re {info depth 7 seldepth \d+ multipv \d+ score cp \d+ wdl \d+ \d+ \d+ nodes \d+ nps \d+ hashfull \d+ tbhits \d+ time \d+ pv}
expect -re {info depth 8 seldepth \d+ multipv \d+ score cp \d+ wdl \d+ \d+ \d+ nodes \d+ nps \d+ hashfull \d+ tbhits \d+ time \d+ pv}
expect -re {info depth 9 seldepth \d+ multipv \d+ score cp \d+ wdl \d+ \d+ \d+ nodes \d+ nps \d+ hashfull \d+ tbhits \d+ time \d+ pv}
expect "bestmove" expect "bestmove"
send "setoption name Clear Hash\n" send "setoption name Clear Hash\n"
send "ucinewgame\n"
send "position fen 5K2/8/2qk4/2nPp3/3r4/6B1/B7/3R4 w - e6\n"
send "go depth 18\n"
expect "score mate 1"
expect "pv d5e6"
expect "bestmove d5e6"
send "ucinewgame\n"
send "position fen 2brrb2/8/p7/Q7/1p1kpPp1/1P1pN1K1/3P4/8 b - -\n"
send "go depth 18\n"
expect "score mate -1"
expect "bestmove"
send "ucinewgame\n"
send "position fen 7K/P1p1p1p1/2P1P1Pk/6pP/3p2P1/1P6/3P4/8 w - - 0 1\n"
send "go nodes 500000\n"
expect "bestmove"
send "ucinewgame\n"
send "position fen 8/5R2/2K1P3/4k3/8/b1PPpp1B/5p2/8 w - -\n"
send "go depth 18 searchmoves c6d7\n"
expect "score mate 2 * pv c6d7 * f7f5"
expect "bestmove c6d7"
send "ucinewgame\n"
send "position fen 8/5R2/2K1P3/4k3/8/b1PPpp1B/5p2/8 w - -\n"
send "go mate 2 searchmoves c6d7\n"
expect "score mate 2 * pv c6d7"
expect "bestmove c6d7"
send "ucinewgame\n"
send "position fen 8/5R2/2K1P3/4k3/8/b1PPpp1B/5p2/8 w - -\n"
send "go nodes 500000 searchmoves c6d7\n"
expect "score mate 2 * pv c6d7 * f7f5"
expect "bestmove c6d7"
send "ucinewgame\n"
send "position fen 1NR2B2/5p2/5p2/1p1kpp2/1P2rp2/2P1pB2/2P1P1K1/8 b - - \n"
send "go depth 27\n"
expect "score mate -2"
expect "pv d5e6 c8d8"
expect "bestmove d5e6"
send "ucinewgame\n"
send "position fen 8/5R2/2K1P3/4k3/8/b1PPpp1B/5p2/8 w - - moves c6d7 f2f1q\n"
send "go depth 18\n"
expect "score mate 1 * pv f7f5"
expect "bestmove f7f5"
send "ucinewgame\n"
send "position fen 8/5R2/2K1P3/4k3/8/b1PPpp1B/5p2/8 w - -\n"
send "go depth 18 searchmoves c6d7\n"
expect "score mate 2 * pv c6d7 * f7f5"
expect "bestmove c6d7"
send "ucinewgame\n"
send "position fen 8/5R2/2K1P3/4k3/8/b1PPpp1B/5p2/8 w - - moves c6d7\n"
send "go depth 18 searchmoves e3e2\n"
expect "score mate -1 * pv e3e2 f7f5"
expect "bestmove e3e2"
send "setoption name EvalFile value verify.nnue\n" send "setoption name EvalFile value verify.nnue\n"
send "position startpos\n" send "position startpos\n"
send "go depth 5\n" send "go depth 5\n"
@@ -147,6 +226,13 @@ cat << EOF > game.exp
send "setoption name MultiPV value 4\n" send "setoption name MultiPV value 4\n"
send "position startpos\n" send "position startpos\n"
send "go depth 5\n" send "go depth 5\n"
expect "bestmove"
send "setoption name Skill Level value 10\n"
send "position startpos\n"
send "go depth 5\n"
expect "bestmove"
send "setoption name Skill Level value 20\n"
send "quit\n" send "quit\n"
expect eof expect eof
@@ -164,17 +250,30 @@ fi
cat << EOF > syzygy.exp cat << EOF > syzygy.exp
set timeout 240 set timeout 240
# to correctly catch eof we need the following line
# expect_before timeout { exit 2 } eof { exit 3 }
expect_before timeout { exit 2 }
spawn $exeprefix ./stockfish spawn $exeprefix ./stockfish
expect "Stockfish"
send "uci\n" send "uci\n"
send "setoption name SyzygyPath value ../tests/syzygy/\n" send "setoption name SyzygyPath value ../tests/syzygy/\n"
expect "info string Found 35 tablebases" {} timeout {exit 1} expect "info string Found 35 WDL and 35 DTZ tablebase files (up to 4-man)."
send "bench 128 1 8 default depth\n" send "bench 128 1 8 default depth\n"
expect "Nodes searched :"
send "ucinewgame\n" send "ucinewgame\n"
send "position fen 4k3/PP6/8/8/8/8/8/4K3 w - - 0 1\n" send "position fen 4k3/PP6/8/8/8/8/8/4K3 w - - 0 1\n"
send "go depth 5\n" send "go depth 5\n"
expect -re {score cp 20000|score mate}
expect "bestmove" expect "bestmove"
send "ucinewgame\n"
send "position fen 8/1P6/2B5/8/4K3/8/6k1/8 w - - 0 1\n" send "position fen 8/1P6/2B5/8/4K3/8/6k1/8 w - - 0 1\n"
send "go depth 5\n" send "go depth 5\n"
expect -re {score cp 20000|score mate}
expect "bestmove"
send "ucinewgame\n"
send "position fen 8/1P6/2B5/8/4K3/8/6k1/8 b - - 0 1\n"
send "go depth 5\n"
expect -re {score cp -20000|score mate}
expect "bestmove" expect "bestmove"
send "quit\n" send "quit\n"
expect eof expect eof
@@ -187,6 +286,9 @@ EOF
for exp in game.exp syzygy.exp for exp in game.exp syzygy.exp
do do
echo "======== $exp =============="
cat $exp
echo "============================"
echo "$prefix expect $exp $postfix" echo "$prefix expect $exp $postfix"
eval "$prefix expect $exp $postfix" eval "$prefix expect $exp $postfix"