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Implement accumulator refresh table

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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
This commit is contained in:
gab8192
2024-04-20 21:26:00 +02:00
committed by Disservin
parent fcba524793
commit 49ef4c935a
12 changed files with 349 additions and 80 deletions
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19
src/evaluate.cpp
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@@ -25,12 +25,14 @@
#include <iomanip>
#include <iostream>
#include <sstream>
#include <memory>
#include "nnue/network.h"
#include "nnue/nnue_misc.h"
#include "position.h"
#include "types.h"
#include "uci.h"
#include "nnue/nnue_accumulator.h"
namespace Stockfish {
@@ -45,7 +47,10 @@ int Eval::simple_eval(const Position& pos, Color c) {
// 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.
Value Eval::evaluate(const Eval::NNUE::Networks& networks, 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());
@@ -55,8 +60,8 @@ Value Eval::evaluate(const Eval::NNUE::Networks& networks, const Position& pos,
int nnueComplexity;
int v;
Value nnue = smallNet ? networks.small.evaluate(pos, true, &nnueComplexity, psqtOnly)
: networks.big.evaluate(pos, true, &nnueComplexity, false);
Value nnue = smallNet ? networks.small.evaluate(pos, nullptr, true, &nnueComplexity, psqtOnly)
: networks.big.evaluate(pos, &caches.big, true, &nnueComplexity, false);
const auto adjustEval = [&](int optDiv, int nnueDiv, int npmDiv, int pawnCountConstant,
int pawnCountMul, int npmConstant, int evalDiv,
@@ -94,20 +99,22 @@ Value Eval::evaluate(const Eval::NNUE::Networks& networks, const Position& pos,
// Trace scores are from white's point of view
std::string Eval::trace(Position& pos, const Eval::NNUE::Networks& networks) {
auto caches = std::make_unique<Eval::NNUE::AccumulatorCaches>();
if (pos.checkers())
return "Final evaluation: none (in check)";
std::stringstream ss;
ss << std::showpoint << std::noshowpos << std::fixed << std::setprecision(2);
ss << '\n' << NNUE::trace(pos, networks) << '\n';
ss << '\n' << NNUE::trace(pos, networks, *caches) << '\n';
ss << std::showpoint << std::showpos << std::fixed << std::setprecision(2) << std::setw(15);
Value v = networks.big.evaluate(pos, false);
Value v = networks.big.evaluate(pos, &caches->big, false);
v = pos.side_to_move() == WHITE ? v : -v;
ss << "NNUE evaluation " << 0.01 * UCIEngine::to_cp(v, pos) << " (white side)\n";
v = evaluate(networks, pos, VALUE_ZERO);
v = evaluate(networks, pos, *caches, VALUE_ZERO);
v = pos.side_to_move() == WHITE ? v : -v;
ss << "Final evaluation " << 0.01 * UCIEngine::to_cp(v, pos) << " (white side)";
ss << " [with scaled NNUE, ...]";