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Merge commit 'c14b69790a62aad89fcc471cde482923dfe57f1e' into cluster

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This is the last commit before there are more conflicts.
This commit is contained in:
Steinar H. Gunderson
2025-12-24 15:17:55 +01:00
parent fb9a3d3323 c14b69790a
commit ea9a328340
12 changed files with 148 additions and 125 deletions
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src/bitboard.cpp
+7 -1
View File
@@ -124,8 +124,14 @@ Bitboard sliding_attack(PieceType pt, Square sq, Bitboard occupied) {
for (Direction d : (pt == ROOK ? RookDirections : BishopDirections))
{
Square s = sq;
while (safe_destination(s, d) && !(occupied & s))
while (safe_destination(s, d))
{
attacks |= (s += d);
if (occupied & s)
{
break;
}
}
}
return attacks;
src/evaluate.cpp
+22 -18
View File
@@ -44,6 +44,10 @@ int Eval::simple_eval(const Position& pos, Color 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) > 1018 + 5 * pos.count<PAWN>();
}
// 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.
@@ -55,33 +59,33 @@ Value Eval::evaluate(const Eval::NNUE::Networks& networks,
assert(!pos.checkers());
int simpleEval = simple_eval(pos, pos.side_to_move());
bool smallNet = std::abs(simpleEval) > SmallNetThreshold;
bool smallNet = use_smallnet(pos);
int nnueComplexity;
int v;
Value nnue = smallNet ? networks.small.evaluate(pos, &caches.small, true, &nnueComplexity)
: networks.big.evaluate(pos, &caches.big, true, &nnueComplexity);
const auto adjustEval = [&](int nnueDiv, int pawnCountConstant, int pawnCountMul,
int npmConstant, int evalDiv, int shufflingConstant) {
// Blend optimism and eval with nnue complexity and material imbalance
optimism += optimism * (nnueComplexity + std::abs(simpleEval - nnue)) / 584;
nnue -= nnue * (nnueComplexity * 5 / 3) / nnueDiv;
if (smallNet && nnue * simpleEval < 0)
{
nnue = networks.big.evaluate(pos, &caches.big, true, &nnueComplexity);
smallNet = false;
}
int npm = pos.non_pawn_material() / 64;
v = (nnue * (npm + pawnCountConstant + pawnCountMul * pos.count<PAWN>())
+ optimism * (npmConstant + npm))
/ evalDiv;
// Blend optimism and eval with nnue complexity and material imbalance
optimism += optimism * (nnueComplexity + std::abs(simpleEval - nnue)) / 620;
nnue -= nnue * (nnueComplexity * 5 / 3) / 32082;
// Damp down the evaluation linearly when shuffling
int shuffling = pos.rule50_count();
v = v * (shufflingConstant - shuffling) / 207;
};
v = (nnue
* (32961 + 381 * pos.count<PAWN>() + 349 * pos.count<KNIGHT>()
+ 392 * pos.count<BISHOP>() + 649 * pos.count<ROOK>() + 1211 * pos.count<QUEEN>())
+ optimism
* (4835 + 136 * pos.count<PAWN>() + 375 * pos.count<KNIGHT>()
+ 403 * pos.count<BISHOP>() + 628 * pos.count<ROOK>() + 1124 * pos.count<QUEEN>()))
/ 36860;
if (!smallNet)
adjustEval(32395, 942, 11, 139, 1058, 178);
else
adjustEval(32793, 944, 9, 140, 1067, 206);
// Damp down the evaluation linearly when shuffling
v = v * (204 - pos.rule50_count()) / 208;
// 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);
src/evaluate.h
+2 -3
View File
@@ -29,13 +29,11 @@ class Position;
namespace Eval {
constexpr inline int SmallNetThreshold = 1274;
// The default net name MUST follow the format nn-[SHA256 first 12 digits].nnue
// for the build process (profile-build and fishtest) to work. Do not change the
// name of the macro or the location where this macro is defined, as it is used
// in the Makefile/Fishtest.
#define EvalFileDefaultNameBig "nn-ae6a388e4a1a.nnue"
#define EvalFileDefaultNameBig "nn-c721dfca8cd3.nnue"
#define EvalFileDefaultNameSmall "nn-baff1ede1f90.nnue"
namespace NNUE {
@@ -46,6 +44,7 @@ struct AccumulatorCaches;
std::string trace(Position& pos, const Eval::NNUE::Networks& networks);
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,
src/nnue/layers/clipped_relu.h
+22 -26
View File
@@ -65,41 +65,37 @@ class ClippedReLU {
if constexpr (InputDimensions % SimdWidth == 0)
{
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 auto in = reinterpret_cast<const __m256i*>(input);
const auto out = reinterpret_cast<__m256i*>(output);
for (IndexType i = 0; i < NumChunks; ++i)
{
const __m256i words0 =
_mm256_srai_epi16(_mm256_packs_epi32(_mm256_load_si256(&in[i * 4 + 0]),
_mm256_load_si256(&in[i * 4 + 1])),
_mm256_srli_epi16(_mm256_packus_epi32(_mm256_load_si256(&in[i * 4 + 0]),
_mm256_load_si256(&in[i * 4 + 1])),
WeightScaleBits);
const __m256i words1 =
_mm256_srai_epi16(_mm256_packs_epi32(_mm256_load_si256(&in[i * 4 + 2]),
_mm256_load_si256(&in[i * 4 + 3])),
_mm256_srli_epi16(_mm256_packus_epi32(_mm256_load_si256(&in[i * 4 + 2]),
_mm256_load_si256(&in[i * 4 + 3])),
WeightScaleBits);
_mm256_store_si256(
&out[i], _mm256_permutevar8x32_epi32(
_mm256_max_epi8(_mm256_packs_epi16(words0, words1), Zero), Offsets));
_mm256_store_si256(&out[i], _mm256_permutevar8x32_epi32(
_mm256_packs_epi16(words0, words1), Offsets));
}
}
else
{
constexpr IndexType NumChunks = InputDimensions / (SimdWidth / 2);
const __m128i Zero = _mm_setzero_si128();
const auto in = reinterpret_cast<const __m128i*>(input);
const auto out = reinterpret_cast<__m128i*>(output);
for (IndexType i = 0; i < NumChunks; ++i)
{
const __m128i words0 = _mm_srai_epi16(
_mm_packs_epi32(_mm_load_si128(&in[i * 4 + 0]), _mm_load_si128(&in[i * 4 + 1])),
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_srai_epi16(
_mm_packs_epi32(_mm_load_si128(&in[i * 4 + 2]), _mm_load_si128(&in[i * 4 + 3])),
const __m128i words1 = _mm_srli_epi16(
_mm_packus_epi32(_mm_load_si128(&in[i * 4 + 2]), _mm_load_si128(&in[i * 4 + 3])),
WeightScaleBits);
const __m128i packedbytes = _mm_packs_epi16(words0, words1);
_mm_store_si128(&out[i], _mm_max_epi8(packedbytes, Zero));
_mm_store_si128(&out[i], _mm_packs_epi16(words0, words1));
}
}
constexpr IndexType Start = InputDimensions % SimdWidth == 0
@@ -109,9 +105,7 @@ class ClippedReLU {
#elif defined(USE_SSE2)
constexpr IndexType NumChunks = InputDimensions / SimdWidth;
#ifdef USE_SSE41
const __m128i Zero = _mm_setzero_si128();
#else
#ifndef USE_SSE41
const __m128i k0x80s = _mm_set1_epi8(-128);
#endif
@@ -119,6 +113,15 @@ class ClippedReLU {
const auto out = reinterpret_cast<__m128i*>(output);
for (IndexType i = 0; i < NumChunks; ++i)
{
#if defined(USE_SSE41)
const __m128i words0 = _mm_srli_epi16(
_mm_packus_epi32(_mm_load_si128(&in[i * 4 + 0]), _mm_load_si128(&in[i * 4 + 1])),
WeightScaleBits);
const __m128i words1 = _mm_srli_epi16(
_mm_packus_epi32(_mm_load_si128(&in[i * 4 + 2]), _mm_load_si128(&in[i * 4 + 3])),
WeightScaleBits);
_mm_store_si128(&out[i], _mm_packs_epi16(words0, words1));
#else
const __m128i words0 = _mm_srai_epi16(
_mm_packs_epi32(_mm_load_si128(&in[i * 4 + 0]), _mm_load_si128(&in[i * 4 + 1])),
WeightScaleBits);
@@ -126,15 +129,8 @@ class ClippedReLU {
_mm_packs_epi32(_mm_load_si128(&in[i * 4 + 2]), _mm_load_si128(&in[i * 4 + 3])),
WeightScaleBits);
const __m128i packedbytes = _mm_packs_epi16(words0, words1);
_mm_store_si128(&out[i],
#ifdef USE_SSE41
_mm_max_epi8(packedbytes, Zero)
#else
_mm_subs_epi8(_mm_adds_epi8(packedbytes, k0x80s), k0x80s)
_mm_store_si128(&out[i], _mm_subs_epi8(_mm_adds_epi8(packedbytes, k0x80s), k0x80s));
#endif
);
}
constexpr IndexType Start = NumChunks * SimdWidth;
src/nnue/nnue_feature_transformer.h
+12 -3
View File
@@ -662,7 +662,10 @@ class FeatureTransformer {
for (IndexType j = 0; j < HalfDimensions / TileHeight; ++j)
{
auto accTile =
reinterpret_cast<vec_t*>(&accumulator.accumulation[Perspective][j * TileHeight]);
auto entryTile = reinterpret_cast<vec_t*>(&entry.accumulation[j * TileHeight]);
for (IndexType k = 0; k < NumRegs; ++k)
acc[k] = entryTile[k];
@@ -677,7 +680,7 @@ class FeatureTransformer {
auto columnA = reinterpret_cast<const vec_t*>(&weights[offsetA]);
for (unsigned k = 0; k < NumRegs; ++k)
acc[k] = vec_add_16(vec_sub_16(acc[k], columnR[k]), columnA[k]);
acc[k] = vec_add_16(acc[k], vec_sub_16(columnA[k], columnR[k]));
}
for (; i < int(removed.size()); ++i)
{
@@ -700,12 +703,17 @@ class FeatureTransformer {
for (IndexType k = 0; k < NumRegs; k++)
vec_store(&entryTile[k], acc[k]);
for (IndexType k = 0; k < NumRegs; k++)
vec_store(&accTile[k], acc[k]);
}
for (IndexType j = 0; j < PSQTBuckets / PsqtTileHeight; ++j)
{
auto accTilePsqt = reinterpret_cast<psqt_vec_t*>(
&accumulator.psqtAccumulation[Perspective][j * PsqtTileHeight]);
auto entryTilePsqt =
reinterpret_cast<psqt_vec_t*>(&entry.psqtAccumulation[j * PsqtTileHeight]);
for (std::size_t k = 0; k < NumPsqtRegs; ++k)
psqt[k] = entryTilePsqt[k];
@@ -730,6 +738,8 @@ class FeatureTransformer {
for (std::size_t k = 0; k < NumPsqtRegs; ++k)
vec_store_psqt(&entryTilePsqt[k], psqt[k]);
for (std::size_t k = 0; k < NumPsqtRegs; ++k)
vec_store_psqt(&accTilePsqt[k], psqt[k]);
}
#else
@@ -753,8 +763,6 @@ class FeatureTransformer {
entry.psqtAccumulation[k] += psqtWeights[index * PSQTBuckets + k];
}
#endif
// The accumulator of the refresh entry has been updated.
// Now copy its content to the actual accumulator we were refreshing
@@ -763,6 +771,7 @@ class FeatureTransformer {
std::memcpy(accumulator.psqtAccumulation[Perspective], entry.psqtAccumulation,
sizeof(int32_t) * PSQTBuckets);
#endif
for (Color c : {WHITE, BLACK})
entry.byColorBB[c] = pos.pieces(c);
src/nnue/nnue_misc.cpp
+1 -3
View File
@@ -45,9 +45,7 @@ constexpr std::string_view PieceToChar(" PNBRQK pnbrqk");
void hint_common_parent_position(const Position& pos,
const Networks& networks,
AccumulatorCaches& caches) {
int simpleEvalAbs = std::abs(simple_eval(pos, pos.side_to_move()));
if (simpleEvalAbs > Eval::SmallNetThreshold)
if (Eval::use_smallnet(pos))
networks.small.hint_common_access(pos, &caches.small);
else
networks.big.hint_common_access(pos, &caches.big);
src/search.cpp
+70 -65
View File
@@ -43,6 +43,7 @@
#include "thread.h"
#include "timeman.h"
#include "tt.h"
#include "types.h"
#include "uci.h"
#include "ucioption.h"
@@ -60,9 +61,9 @@ static constexpr double EvalLevel[10] = {0.981, 0.956, 0.895, 0.949, 0.913,
// Futility margin
Value futility_margin(Depth d, bool noTtCutNode, bool improving, bool oppWorsening) {
Value futilityMult = 126 - 46 * noTtCutNode;
Value improvingDeduction = 58 * improving * futilityMult / 32;
Value worseningDeduction = (323 + 52 * improving) * oppWorsening * futilityMult / 1024;
Value futilityMult = 127 - 48 * noTtCutNode;
Value improvingDeduction = 65 * improving * futilityMult / 32;
Value worseningDeduction = 334 * oppWorsening * futilityMult / 1024;
return futilityMult * d - improvingDeduction - worseningDeduction;
}
@@ -74,15 +75,15 @@ constexpr int futility_move_count(bool improving, Depth depth) {
// Add correctionHistory value to raw staticEval and guarantee evaluation does not hit the tablebase range
Value to_corrected_static_eval(Value v, const Worker& w, const Position& pos) {
auto cv = w.correctionHistory[pos.side_to_move()][pawn_structure_index<Correction>(pos)];
v += cv * std::abs(cv) / 7350;
v += cv * std::abs(cv) / 6047;
return std::clamp(v, VALUE_TB_LOSS_IN_MAX_PLY + 1, VALUE_TB_WIN_IN_MAX_PLY - 1);
}
// History and stats update bonus, based on depth
int stat_bonus(Depth d) { return std::clamp(208 * d - 297, 16, 1406); }
int stat_bonus(Depth d) { return std::clamp(187 * d - 288, 17, 1548); }
// History and stats update malus, based on depth
int stat_malus(Depth d) { return (d < 4 ? 520 * d - 312 : 1479); }
int stat_malus(Depth d) { return (d < 4 ? 630 * d - 281 : 1741); }
// Add a small random component to draw evaluations to avoid 3-fold blindness
Value value_draw(size_t nodes) { return VALUE_DRAW - 1 + Value(nodes & 0x2); }
@@ -158,7 +159,8 @@ void Search::Worker::start_searching() {
return;
}
main_manager()->tm.init(limits, rootPos.side_to_move(), rootPos.game_ply(), options);
main_manager()->tm.init(limits, rootPos.side_to_move(), rootPos.game_ply(), options,
main_manager()->originalPly);
tt.new_search();
if (rootMoves.empty())
@@ -352,12 +354,12 @@ void Search::Worker::iterative_deepening() {
// Reset aspiration window starting size
Value avg = rootMoves[pvIdx].averageScore;
delta = 10 + avg * avg / 9530;
delta = 10 + avg * avg / 9828;
alpha = std::max(avg - delta, -VALUE_INFINITE);
beta = std::min(avg + delta, VALUE_INFINITE);
// Adjust optimism based on root move's averageScore (~4 Elo)
optimism[us] = 119 * avg / (std::abs(avg) + 88);
optimism[us] = 116 * avg / (std::abs(avg) + 84);
optimism[~us] = -optimism[us];
// Start with a small aspiration window and, in the case of a fail
@@ -543,7 +545,7 @@ void Search::Worker::clear() {
counterMoves.fill(Move::none());
mainHistory.fill(0);
captureHistory.fill(0);
pawnHistory.fill(0);
pawnHistory.fill(-1300);
correctionHistory.fill(0);
for (bool inCheck : {false, true})
@@ -553,7 +555,7 @@ void Search::Worker::clear() {
h->fill(-60);
for (size_t i = 1; i < reductions.size(); ++i)
reductions[i] = int((18.93 + std::log(size_t(options["Threads"])) / 2) * std::log(i));
reductions[i] = int((21.69 + std::log(size_t(options["Threads"])) / 2) * std::log(i));
refreshTable.clear(networks);
}
@@ -786,7 +788,7 @@ Value Search::Worker::search(
// Use static evaluation difference to improve quiet move ordering (~9 Elo)
if (((ss - 1)->currentMove).is_ok() && !(ss - 1)->inCheck && !priorCapture)
{
int bonus = std::clamp(-13 * int((ss - 1)->staticEval + ss->staticEval), -1796, 1526);
int bonus = std::clamp(-11 * int((ss - 1)->staticEval + ss->staticEval), -1729, 1517);
bonus = bonus > 0 ? 2 * bonus : bonus / 2;
thisThread->mainHistory[~us][((ss - 1)->currentMove).from_to()] << bonus;
if (type_of(pos.piece_on(prevSq)) != PAWN && ((ss - 1)->currentMove).type_of() != PROMOTION)
@@ -808,8 +810,7 @@ Value Search::Worker::search(
// Step 7. Razoring (~1 Elo)
// If eval is really low check with qsearch if it can exceed alpha, if it can't,
// return a fail low.
// Adjust razor margin according to cutoffCnt. (~1 Elo)
if (eval < alpha - 433 - (302 - 141 * ((ss + 1)->cutoffCnt > 3)) * depth * depth)
if (eval < alpha - 474 - 324 * depth * depth)
{
value = qsearch<NonPV>(pos, ss, alpha - 1, alpha);
if (value < alpha)
@@ -820,21 +821,21 @@ Value Search::Worker::search(
// The depth condition is important for mate finding.
if (!ss->ttPv && depth < 11
&& eval - futility_margin(depth, cutNode && !ss->ttHit, improving, opponentWorsening)
- (ss - 1)->statScore / 254
- (ss - 1)->statScore / 252
>= beta
&& eval >= beta && eval < VALUE_TB_WIN_IN_MAX_PLY && (!ttMove || ttCapture))
return beta > VALUE_TB_LOSS_IN_MAX_PLY ? (eval + beta) / 2 : eval;
// Step 9. Null move search with verification search (~35 Elo)
if (!PvNode && (ss - 1)->currentMove != Move::null() && (ss - 1)->statScore < 16993
&& eval >= beta && ss->staticEval >= beta - 19 * depth + 326 && !excludedMove
if (!PvNode && (ss - 1)->currentMove != Move::null() && (ss - 1)->statScore < 15246
&& eval >= beta && ss->staticEval >= beta - 21 * depth + 366 && !excludedMove
&& pos.non_pawn_material(us) && ss->ply >= thisThread->nmpMinPly
&& beta > VALUE_TB_LOSS_IN_MAX_PLY)
{
assert(eval - beta >= 0);
// Null move dynamic reduction based on depth and eval
Depth R = std::min(int(eval - beta) / 134, 6) + depth / 3 + 4;
Depth R = std::min(int(eval - beta) / 152, 6) + depth / 3 + 5;
ss->currentMove = Move::null();
ss->continuationHistory = &thisThread->continuationHistory[0][0][NO_PIECE][0];
@@ -849,7 +850,16 @@ Value Search::Worker::search(
if (nullValue >= beta && nullValue < VALUE_TB_WIN_IN_MAX_PLY)
{
if (thisThread->nmpMinPly || depth < 16)
{
if (nullValue >= ss->staticEval)
{
auto bonus = std::min(int(nullValue - ss->staticEval) * depth / 32,
CORRECTION_HISTORY_LIMIT / 16);
thisThread->correctionHistory[us][pawn_structure_index<Correction>(pos)]
<< bonus;
}
return nullValue;
}
assert(!thisThread->nmpMinPly); // Recursive verification is not allowed
@@ -871,9 +881,12 @@ Value Search::Worker::search(
if (PvNode && !ttMove)
depth -= 3;
if (!PvNode && ss->ttHit && (tte->bound() & BOUND_UPPER) && ttValue > alpha + 5 * depth)
depth--;
// Use qsearch if depth <= 0.
if (depth <= 0)
return qsearch<PV>(pos, ss, alpha, beta);
return qsearch<PvNode ? PV : NonPV>(pos, ss, alpha, beta);
// For cutNodes without a ttMove, we decrease depth by 2 if depth is high enough.
if (cutNode && depth >= 8 && (!ttMove || tte->bound() == BOUND_UPPER))
@@ -882,7 +895,7 @@ Value Search::Worker::search(
// Step 11. ProbCut (~10 Elo)
// If we have a good enough capture (or queen promotion) and a reduced search returns a value
// much above beta, we can (almost) safely prune the previous move.
probCutBeta = beta + 159 - 66 * improving;
probCutBeta = beta + 176 - 65 * improving;
if (
!PvNode && depth > 3
&& std::abs(beta) < VALUE_TB_WIN_IN_MAX_PLY
@@ -939,7 +952,7 @@ Value Search::Worker::search(
moves_loop: // When in check, search starts here
// Step 12. A small Probcut idea, when we are in check (~4 Elo)
probCutBeta = beta + 420;
probCutBeta = beta + 440;
if (ss->inCheck && !PvNode && ttCapture && (tte->bound() & BOUND_LOWER)
&& tte->depth() >= depth - 4 && ttValue >= probCutBeta
&& std::abs(ttValue) < VALUE_TB_WIN_IN_MAX_PLY && std::abs(beta) < VALUE_TB_WIN_IN_MAX_PLY)
@@ -1009,8 +1022,7 @@ moves_loop: // When in check, search starts here
if (!rootNode && pos.non_pawn_material(us) && bestValue > VALUE_TB_LOSS_IN_MAX_PLY)
{
// Skip quiet moves if movecount exceeds our FutilityMoveCount threshold (~8 Elo)
if (!moveCountPruning)
moveCountPruning = moveCount >= futility_move_count(improving, depth);
moveCountPruning = moveCount >= futility_move_count(improving, depth);
// Reduced depth of the next LMR search
int lmrDepth = newDepth - r;
@@ -1024,15 +1036,15 @@ moves_loop: // When in check, search starts here
// Futility pruning for captures (~2 Elo)
if (!givesCheck && lmrDepth < 7 && !ss->inCheck)
{
Value futilityValue = ss->staticEval + 295 + 280 * lmrDepth
Value futilityValue = ss->staticEval + 276 + 256 * lmrDepth
+ PieceValue[capturedPiece] + captHist / 7;
if (futilityValue <= alpha)
continue;
}
// SEE based pruning for captures and checks (~11 Elo)
int seeHist = std::clamp(captHist / 32, -197 * depth, 196 * depth);
if (!pos.see_ge(move, -186 * depth - seeHist))
int seeHist = std::clamp(captHist / 32, -177 * depth, 175 * depth);
if (!pos.see_ge(move, -183 * depth - seeHist))
continue;
}
else
@@ -1040,22 +1052,21 @@ moves_loop: // When in check, search starts here
int history =
(*contHist[0])[movedPiece][move.to_sq()]
+ (*contHist[1])[movedPiece][move.to_sq()]
+ (*contHist[3])[movedPiece][move.to_sq()] / 2
+ thisThread->pawnHistory[pawn_structure_index(pos)][movedPiece][move.to_sq()];
// Continuation history based pruning (~2 Elo)
if (lmrDepth < 6 && history < -4081 * depth)
if (lmrDepth < 6 && history < -4076 * depth)
continue;
history += 2 * thisThread->mainHistory[us][move.from_to()];
lmrDepth += history / 4768;
lmrDepth += history / 4401;
Value futilityValue =
ss->staticEval + (bestValue < ss->staticEval - 52 ? 134 : 54) + 142 * lmrDepth;
ss->staticEval + (bestValue < ss->staticEval - 53 ? 151 : 57) + 140 * lmrDepth;
// Futility pruning: parent node (~13 Elo)
if (!ss->inCheck && lmrDepth < 13 && futilityValue <= alpha)
if (!ss->inCheck && lmrDepth < 10 && futilityValue <= alpha)
{
if (bestValue <= futilityValue && std::abs(bestValue) < VALUE_TB_WIN_IN_MAX_PLY
&& futilityValue < VALUE_TB_WIN_IN_MAX_PLY)
@@ -1066,7 +1077,7 @@ moves_loop: // When in check, search starts here
lmrDepth = std::max(lmrDepth, 0);
// Prune moves with negative SEE (~4 Elo)
if (!pos.see_ge(move, -28 * lmrDepth * lmrDepth))
if (!pos.see_ge(move, -26 * lmrDepth * lmrDepth))
continue;
}
}
@@ -1086,11 +1097,11 @@ moves_loop: // When in check, search starts here
// so changing them requires tests at these types of time controls.
// Recursive singular search is avoided.
if (!rootNode && move == ttMove && !excludedMove
&& depth >= 4 - (thisThread->completedDepth > 32) + ss->ttPv
&& depth >= 4 - (thisThread->completedDepth > 35) + ss->ttPv
&& std::abs(ttValue) < VALUE_TB_WIN_IN_MAX_PLY && (tte->bound() & BOUND_LOWER)
&& tte->depth() >= depth - 3)
{
Value singularBeta = ttValue - (65 + 52 * (ss->ttPv && !PvNode)) * depth / 63;
Value singularBeta = ttValue - (57 + 50 * (ss->ttPv && !PvNode)) * depth / 64;
Depth singularDepth = newDepth / 2;
ss->excludedMove = move;
@@ -1100,16 +1111,16 @@ moves_loop: // When in check, search starts here
if (value < singularBeta)
{
int doubleMargin = 251 * PvNode - 241 * !ttCapture;
int doubleMargin = 298 * PvNode - 209 * !ttCapture;
int tripleMargin =
135 + 234 * PvNode - 248 * !ttCapture + 124 * (ss->ttPv || !ttCapture);
int quadMargin = 447 + 354 * PvNode - 300 * !ttCapture + 206 * ss->ttPv;
117 + 252 * PvNode - 270 * !ttCapture + 111 * (ss->ttPv || !ttCapture);
int quadMargin = 471 + 343 * PvNode - 281 * !ttCapture + 217 * ss->ttPv;
extension = 1 + (value < singularBeta - doubleMargin)
+ (value < singularBeta - tripleMargin)
+ (value < singularBeta - quadMargin);
depth += ((!PvNode) && (depth < 14));
depth += ((!PvNode) && (depth < 15));
}
// Multi-cut pruning
@@ -1138,17 +1149,13 @@ moves_loop: // When in check, search starts here
// If we are on a cutNode but the ttMove is not assumed to fail high over current beta (~1 Elo)
else if (cutNode)
extension = -2;
// If the ttMove is assumed to fail low over the value of the reduced search (~1 Elo)
else if (ttValue <= value)
extension = -1;
}
// Extension for capturing the previous moved piece (~0 Elo on STC, ~1 Elo on LTC)
else if (PvNode && move == ttMove && move.to_sq() == prevSq
&& thisThread->captureHistory[movedPiece][move.to_sq()]
[type_of(pos.piece_on(move.to_sq()))]
> 4016)
> 3748)
extension = 1;
}
@@ -1199,11 +1206,10 @@ moves_loop: // When in check, search starts here
ss->statScore = 2 * thisThread->mainHistory[us][move.from_to()]
+ (*contHist[0])[movedPiece][move.to_sq()]
+ (*contHist[1])[movedPiece][move.to_sq()]
+ (*contHist[3])[movedPiece][move.to_sq()] - 5078;
+ (*contHist[1])[movedPiece][move.to_sq()] - 5266;
// Decrease/increase reduction for moves with a good/bad history (~8 Elo)
r -= ss->statScore / (17662 - std::min(depth, 16) * 105);
r -= ss->statScore / (14519 - std::min(depth, 15) * 103);
// Step 17. Late moves reduction / extension (LMR, ~117 Elo)
if (depth >= 2 && moveCount > 1 + rootNode)
@@ -1340,7 +1346,7 @@ moves_loop: // When in check, search starts here
else
{
// Reduce other moves if we have found at least one score improvement (~2 Elo)
if (depth > 2 && depth < 13 && beta < 15868 && value > -14630)
if (depth > 2 && depth < 13 && std::abs(value) < VALUE_TB_WIN_IN_MAX_PLY)
depth -= 2;
assert(depth > 0);
@@ -1383,13 +1389,18 @@ moves_loop: // When in check, search starts here
// Bonus for prior countermove that caused the fail low
else if (!priorCapture && prevSq != SQ_NONE)
{
int bonus = (depth > 5) + (PvNode || cutNode) + ((ss - 1)->statScore < -14455)
+ ((ss - 1)->moveCount > 10) + (!ss->inCheck && bestValue <= ss->staticEval - 130)
+ (!(ss - 1)->inCheck && bestValue <= -(ss - 1)->staticEval - 77);
int bonus = (depth > 4) + (depth > 5) + (PvNode || cutNode) + ((ss - 1)->statScore < -13241)
+ ((ss - 1)->moveCount > 10) + (!ss->inCheck && bestValue <= ss->staticEval - 127)
+ (!(ss - 1)->inCheck && bestValue <= -(ss - 1)->staticEval - 74);
update_continuation_histories(ss - 1, pos.piece_on(prevSq), prevSq,
stat_bonus(depth) * bonus);
thisThread->mainHistory[~us][((ss - 1)->currentMove).from_to()]
<< stat_bonus(depth) * bonus / 2;
if (type_of(pos.piece_on(prevSq)) != PAWN && ((ss - 1)->currentMove).type_of() != PROMOTION)
thisThread->pawnHistory[pawn_structure_index(pos)][pos.piece_on(prevSq)][prevSq]
<< stat_bonus(depth) * bonus * 4;
}
if (PvNode)
@@ -1535,6 +1546,8 @@ Value Search::Worker::qsearch(Position& pos, Stack* ss, Value alpha, Value beta,
// Stand pat. Return immediately if static value is at least beta
if (bestValue >= beta)
{
if (std::abs(bestValue) < VALUE_TB_WIN_IN_MAX_PLY && !PvNode)
bestValue = (3 * bestValue + beta) / 4;
if (!ss->ttHit)
Cluster::save(tt, threads, thisThread, tte, posKey, value_to_tt(bestValue, ss->ply),
false, BOUND_LOWER, DEPTH_NONE, Move::none(), unadjustedStaticEval,
@@ -1546,7 +1559,7 @@ Value Search::Worker::qsearch(Position& pos, Stack* ss, Value alpha, Value beta,
if (bestValue > alpha)
alpha = bestValue;
futilityBase = ss->staticEval + 270;
futilityBase = ss->staticEval + 264;
}
const PieceToHistory* contHist[] = {(ss - 1)->continuationHistory,
@@ -1560,8 +1573,6 @@ Value Search::Worker::qsearch(Position& pos, Stack* ss, Value alpha, Value beta,
MovePicker mp(pos, ttMove, depth, &thisThread->mainHistory, &thisThread->captureHistory,
contHist, &thisThread->pawnHistory);
int quietCheckEvasions = 0;
// Step 5. Loop through all pseudo-legal moves until no moves remain
// or a beta cutoff occurs.
while ((move = mp.next_move()) != Move::none())
@@ -1614,23 +1625,17 @@ Value Search::Worker::qsearch(Position& pos, Stack* ss, Value alpha, Value beta,
}
}
// We prune after the second quiet check evasion move, where being 'in check' is
// implicitly checked through the counter, and being a 'quiet move' apart from
// being a tt move is assumed after an increment because captures are pushed ahead.
if (quietCheckEvasions > 1)
break;
// Continuation history based pruning (~3 Elo)
if (!capture
&& (*contHist[0])[pos.moved_piece(move)][move.to_sq()]
+ (*contHist[1])[pos.moved_piece(move)][move.to_sq()]
+ thisThread->pawnHistory[pawn_structure_index(pos)][pos.moved_piece(move)]
[move.to_sq()]
<= 4000)
<= 4348)
continue;
// Do not search moves with bad enough SEE values (~5 Elo)
if (!pos.see_ge(move, -69))
if (!pos.see_ge(move, -63))
continue;
}
@@ -1643,8 +1648,6 @@ Value Search::Worker::qsearch(Position& pos, Stack* ss, Value alpha, Value beta,
&thisThread
->continuationHistory[ss->inCheck][capture][pos.moved_piece(move)][move.to_sq()];
quietCheckEvasions += !capture && ss->inCheck;
// Step 7. Make and search the move
thisThread->nodes.fetch_add(1, std::memory_order_relaxed);
pos.do_move(move, st, givesCheck);
@@ -1698,7 +1701,7 @@ Value Search::Worker::qsearch(Position& pos, Stack* ss, Value alpha, Value beta,
Depth Search::Worker::reduction(bool i, Depth d, int mn, int delta) {
int reductionScale = reductions[d] * reductions[mn];
return (reductionScale + 1318 - delta * 760 / rootDelta) / 1024 + (!i && reductionScale > 1066);
return (reductionScale + 1147 - delta * 755 / rootDelta) / 1024 + (!i && reductionScale > 1125);
}
// elapsed() returns the time elapsed since the search started. If the
@@ -1839,6 +1842,8 @@ void update_all_stats(const Position& pos,
// by moves at ply -1, -2, -3, -4, and -6 with current move.
void update_continuation_histories(Stack* ss, Piece pc, Square to, int bonus) {
bonus = bonus * 45 / 64;
for (int i : {1, 2, 3, 4, 6})
{
// Only update the first 2 continuation histories if we are in check
@@ -1876,7 +1881,7 @@ void update_quiet_histories(
update_continuation_histories(ss, pos.moved_piece(move), move.to_sq(), bonus);
int pIndex = pawn_structure_index(pos);
workerThread.pawnHistory[pIndex][pos.moved_piece(move)][move.to_sq()] << bonus;
workerThread.pawnHistory[pIndex][pos.moved_piece(move)][move.to_sq()] << bonus / 2;
}
// Updates move sorting heuristics
src/search.h
+1
View File
@@ -220,6 +220,7 @@ class SearchManager: public ISearchManager {
Depth depth) const;
Stockfish::TimeManagement tm;
int originalPly;
int callsCnt;
std::atomic_bool ponder;
src/thread.cpp
+1
View File
@@ -172,6 +172,7 @@ void ThreadPool::clear() {
main_manager()->callsCnt = 0;
main_manager()->bestPreviousScore = VALUE_INFINITE;
main_manager()->bestPreviousAverageScore = VALUE_INFINITE;
main_manager()->originalPly = -1;
main_manager()->previousTimeReduction = 1.0;
main_manager()->tm.clear();
}
src/timeman.cpp
+7 -4
View File
@@ -44,10 +44,8 @@ void TimeManagement::advance_nodes_time(std::int64_t nodes) {
// the bounds of time allowed for the current game ply. We currently support:
// 1) x basetime (+ z increment)
// 2) x moves in y seconds (+ z increment)
void TimeManagement::init(Search::LimitsType& limits,
Color us,
int ply,
const OptionsMap& options) {
void TimeManagement::init(
Search::LimitsType& limits, Color us, int ply, const OptionsMap& options, int& originalPly) {
TimePoint npmsec = TimePoint(options["nodestime"]);
// If we have no time, we don't need to fully initialize TM.
@@ -58,6 +56,9 @@ void TimeManagement::init(Search::LimitsType& limits,
if (limits.time[us] == 0)
return;
if (originalPly == -1)
originalPly = ply;
TimePoint moveOverhead = TimePoint(options["Move Overhead"]);
// optScale is a percentage of available time to use for the current move.
@@ -106,6 +107,8 @@ void TimeManagement::init(Search::LimitsType& limits,
{
// Use extra time with larger increments
double optExtra = scaledInc < 500 ? 1.0 : 1.13;
if (ply - originalPly < 2)
optExtra *= 0.95;
// Calculate time constants based on current time left.
double logTimeInSec = std::log10(scaledTime / 1000.0);
src/timeman.h
+2 -1
View File
@@ -36,7 +36,8 @@ struct LimitsType;
// the maximum available time, the game move number, and other parameters.
class TimeManagement {
public:
void init(Search::LimitsType& limits, Color us, int ply, const OptionsMap& options);
void init(
Search::LimitsType& limits, Color us, int ply, const OptionsMap& options, int& originalPly);
TimePoint optimum() const;
TimePoint maximum() const;
src/tt.cpp
+1 -1
View File
@@ -35,7 +35,7 @@ namespace Stockfish {
void TTEntry::save(
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)
move16 = m;