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search.cpp
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search.cpp
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/*
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 "search.h"
#include <algorithm>
#include <array>
#include <list>
#include <atomic>
#include <cassert>
#include <cmath>
#include <cstdint>
#include <cstdlib>
#include <initializer_list>
#include <string>
#include <utility>
#include <chrono>
#include <iostream>
#include <ratio>
#include "evaluate.h"
#include "misc.h"
#include "movegen.h"
#include "movepick.h"
#include "nnue/network.h"
#include "nnue/nnue_accumulator.h"
#include "nnue/nnue_common.h"
#include "nnue/nnue_misc.h"
#include "position.h"
#include "syzygy/tbprobe.h"
#include "thread.h"
#include "timeman.h"
#include "tt.h"
#include "types.h"
#include "uci.h"
#include "ucioption.h"
namespace Stockfish {
namespace TB = Tablebases;
void syzygy_extend_pv(const OptionsMap& options,
const Search::LimitsType& limits,
Stockfish::Position& pos,
Stockfish::Search::RootMove& rootMove,
Value& v);
using Eval::evaluate;
using namespace Search;
namespace {
// Futility margin
Value futility_margin(Depth d, bool noTtCutNode, bool improving, bool oppWorsening) {
Value futilityMult = 122 - 37 * noTtCutNode;
Value improvingDeduction = improving * futilityMult * 2;
Value worseningDeduction = oppWorsening * futilityMult / 3;
return futilityMult * d - improvingDeduction - worseningDeduction;
}
constexpr int futility_move_count(bool improving, Depth depth) {
return improving ? (3 + depth * depth) : (3 + depth * depth) / 2;
}
// 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) / 5073;
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::min(190 * d - 108, 1596); }
// History and stats update malus, based on depth
int stat_malus(Depth d) { return (d < 4 ? 736 * d - 268 : 2044); }
// 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); }
// 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 {
Skill(int skill_level, int uci_elo) {
if (uci_elo)
{
double e = double(uci_elo - 1320) / (3190 - 1320);
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();
};
Value value_to_tt(Value v, int ply);
Value value_from_tt(Value v, int ply, int r50c);
void update_pv(Move* pv, Move move, const Move* childPv);
void update_continuation_histories(Stack* ss, Piece pc, Square to, int bonus);
void update_killer(Stack* ss, Move move);
void update_quiet_histories(
const Position& pos, Stack* ss, Search::Worker& workerThread, Move move, int bonus);
void update_quiet_stats(
const Position& pos, Stack* ss, Search::Worker& workerThread, Move move, int bonus);
void update_all_stats(const Position& pos,
Stack* ss,
Search::Worker& workerThread,
Move bestMove,
Square prevSq,
Move* quietsSearched,
int quietCount,
Move* capturesSearched,
int captureCount,
Depth depth);
} // namespace
Search::Worker::Worker(SharedState& sharedState,
std::unique_ptr<ISearchManager> sm,
size_t threadId,
NumaReplicatedAccessToken token) :
// Unpack the SharedState struct into member variables
threadIdx(threadId),
numaAccessToken(token),
manager(std::move(sm)),
options(sharedState.options),
threads(sharedState.threads),
tt(sharedState.tt),
networks(sharedState.networks),
refreshTable(networks[token]) {
clear();
}
void Search::Worker::start_searching() {
// Non-main threads go directly to iterative_deepening()
if (!is_mainthread())
{
iterative_deepening();
return;
}
main_manager()->tm.init(limits, rootPos.side_to_move(), rootPos.game_ply(), options,
main_manager()->originalTimeAdjust);
tt.new_search();
if (rootMoves.empty())
{
rootMoves.emplace_back(Move::none());
main_manager()->updates.onUpdateNoMoves(
{0, {rootPos.checkers() ? -VALUE_MATE : VALUE_DRAW, rootPos}});
}
else
{
threads.start_searching(); // start non-main threads
iterative_deepening(); // main thread start searching
}
// When we reach the maximum depth, we can arrive here without a raise of
// threads.stop. However, if we are pondering or in an infinite search,
// the UCI protocol states that we shouldn't print the best move before the
// GUI sends a "stop" or "ponderhit" command. We therefore simply wait here
// until the GUI sends one of those commands.
while (!threads.stop && (main_manager()->ponder || limits.infinite))
{} // Busy wait for a stop or a ponder reset
// Stop the threads if not already stopped (also raise the stop if
// "ponderhit" just reset threads.ponder).
threads.stop = true;
// Wait until all threads have finished
threads.wait_for_search_finished();
// When playing in 'nodes as time' mode, subtract the searched nodes from
// the available ones before exiting.
if (limits.npmsec)
main_manager()->tm.advance_nodes_time(threads.nodes_searched()
- limits.inc[rootPos.side_to_move()]);
Worker* bestThread = this;
Skill skill =
Skill(options["Skill Level"], options["UCI_LimitStrength"] ? int(options["UCI_Elo"]) : 0);
if (int(options["MultiPV"]) == 1 && !limits.depth && !limits.mate && !skill.enabled()
&& rootMoves[0].pv[0] != Move::none())
bestThread = threads.get_best_thread()->worker.get();
main_manager()->bestPreviousScore = bestThread->rootMoves[0].score;
main_manager()->bestPreviousAverageScore = bestThread->rootMoves[0].averageScore;
// Send again PV info if we have a new best thread
if (bestThread != this)
main_manager()->pv(*bestThread, threads, tt, bestThread->completedDepth);
std::string ponder;
if (bestThread->rootMoves[0].pv.size() > 1
|| bestThread->rootMoves[0].extract_ponder_from_tt(tt, rootPos))
ponder = UCIEngine::move(bestThread->rootMoves[0].pv[1], rootPos.is_chess960());
auto bestmove = UCIEngine::move(bestThread->rootMoves[0].pv[0], rootPos.is_chess960());
main_manager()->updates.onBestmove(bestmove, ponder);
}
// Main iterative deepening loop. It calls search()
// repeatedly with increasing depth until the allocated thinking time has been
// consumed, the user stops the search, or the maximum search depth is reached.
void Search::Worker::iterative_deepening() {
SearchManager* mainThread = (is_mainthread() ? main_manager() : nullptr);
Move pv[MAX_PLY + 1];
Depth lastBestMoveDepth = 0;
Value lastBestScore = -VALUE_INFINITE;
auto lastBestPV = std::vector{Move::none()};
Value alpha, beta;
Value bestValue = -VALUE_INFINITE;
Color us = rootPos.side_to_move();
double timeReduction = 1, totBestMoveChanges = 0;
int delta, iterIdx = 0;
// Allocate stack with extra size to allow access from (ss - 7) to (ss + 2):
// (ss - 7) is needed for update_continuation_histories(ss - 1) which accesses (ss - 6),
// (ss + 2) is needed for initialization of cutOffCnt and killers.
Stack stack[MAX_PLY + 10] = {};
Stack* ss = stack + 7;
for (int i = 7; i > 0; --i)
{
(ss - i)->continuationHistory =
&this->continuationHistory[0][0][NO_PIECE][0]; // Use as a sentinel
(ss - i)->staticEval = VALUE_NONE;
}
for (int i = 0; i <= MAX_PLY + 2; ++i)
(ss + i)->ply = i;
ss->pv = pv;
if (mainThread)
{
if (mainThread->bestPreviousScore == VALUE_INFINITE)
mainThread->iterValue.fill(VALUE_ZERO);
else
mainThread->iterValue.fill(mainThread->bestPreviousScore);
}
size_t multiPV = size_t(options["MultiPV"]);
Skill skill(options["Skill Level"], options["UCI_LimitStrength"] ? int(options["UCI_Elo"]) : 0);
// When playing with strength handicap enable MultiPV search that we will
// use behind-the-scenes to retrieve a set of possible moves.
if (skill.enabled())
multiPV = std::max(multiPV, size_t(4));
multiPV = std::min(multiPV, rootMoves.size());
int searchAgainCounter = 0;
// Iterative deepening loop until requested to stop or the target depth is reached
while (++rootDepth < MAX_PLY && !threads.stop
&& !(limits.depth && mainThread && rootDepth > limits.depth))
{
// Age out PV variability metric
if (mainThread)
totBestMoveChanges /= 2;
// Save the last iteration's scores before the first PV line is searched and
// all the move scores except the (new) PV are set to -VALUE_INFINITE.
for (RootMove& rm : rootMoves)
rm.previousScore = rm.score;
size_t pvFirst = 0;
pvLast = 0;
if (!threads.increaseDepth)
searchAgainCounter++;
// MultiPV loop. We perform a full root search for each PV line
for (pvIdx = 0; pvIdx < multiPV; ++pvIdx)
{
if (pvIdx == pvLast)
{
pvFirst = pvLast;
for (pvLast++; pvLast < rootMoves.size(); pvLast++)
if (rootMoves[pvLast].tbRank != rootMoves[pvFirst].tbRank)
break;
}
// Reset UCI info selDepth for each depth and each PV line
selDepth = 0;
// Reset aspiration window starting size
Value avg = rootMoves[pvIdx].averageScore;
delta = 9 + avg * avg / 10424;
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] = 125 * avg / (std::abs(avg) + 89);
optimism[~us] = -optimism[us];
// Start with a small aspiration window and, in the case of a fail
// high/low, re-search with a bigger window until we don't fail
// high/low anymore.
int failedHighCnt = 0;
while (true)
{
// Adjust the effective depth searched, but ensure at least one
// effective increment for every four searchAgain steps (see issue #2717).
Depth adjustedDepth =
std::max(1, rootDepth - failedHighCnt - 3 * (searchAgainCounter + 1) / 4);
rootDelta = beta - alpha;
bestValue = search<Root>(rootPos, ss, alpha, beta, adjustedDepth, false);
// Bring the best move to the front. It is critical that sorting
// is done with a stable algorithm because all the values but the
// first and eventually the new best one is set to -VALUE_INFINITE
// and we want to keep the same order for all the moves except the
// new PV that goes to the front. Note that in the case of MultiPV
// search the already searched PV lines are preserved.
std::stable_sort(rootMoves.begin() + pvIdx, rootMoves.begin() + pvLast);
// If search has been stopped, we break immediately. Sorting is
// safe because RootMoves is still valid, although it refers to
// the previous iteration.
if (threads.stop)
break;
// When failing high/low give some update before a re-search. To avoid
// excessive output that could hang GUIs like Fritz 19, only start
// at nodes > 10M (rather than depth N, which can be reached quickly)
if (mainThread && multiPV == 1 && (bestValue <= alpha || bestValue >= beta)
&& nodes > 10000000)
main_manager()->pv(*this, threads, tt, rootDepth);
// In case of failing low/high increase aspiration window and re-search,
// otherwise exit the loop.
if (bestValue <= alpha)
{
beta = (alpha + beta) / 2;
alpha = std::max(bestValue - delta, -VALUE_INFINITE);
failedHighCnt = 0;
if (mainThread)
mainThread->stopOnPonderhit = false;
}
else if (bestValue >= beta)
{
beta = std::min(bestValue + delta, VALUE_INFINITE);
++failedHighCnt;
}
else
break;
delta += delta / 3;
assert(alpha >= -VALUE_INFINITE && beta <= VALUE_INFINITE);
}
// Sort the PV lines searched so far and update the GUI
std::stable_sort(rootMoves.begin() + pvFirst, rootMoves.begin() + pvIdx + 1);
if (mainThread
&& (threads.stop || pvIdx + 1 == multiPV || nodes > 10000000)
// A thread that aborted search can have mated-in/TB-loss PV and
// score that cannot be trusted, i.e. it can be delayed or refuted
// if we would have had time to fully search other root-moves. Thus
// we suppress this output and below pick a proven score/PV for this
// thread (from the previous iteration).
&& !(threads.abortedSearch && rootMoves[0].uciScore <= VALUE_TB_LOSS_IN_MAX_PLY))
main_manager()->pv(*this, threads, tt, rootDepth);
if (threads.stop)
break;
}
if (!threads.stop)
completedDepth = rootDepth;
// We make sure not to pick an unproven mated-in score,
// in case this thread prematurely stopped search (aborted-search).
if (threads.abortedSearch && rootMoves[0].score != -VALUE_INFINITE
&& rootMoves[0].score <= VALUE_TB_LOSS_IN_MAX_PLY)
{
// Bring the last best move to the front for best thread selection.
Utility::move_to_front(rootMoves, [&lastBestPV = std::as_const(lastBestPV)](
const auto& rm) { return rm == lastBestPV[0]; });
rootMoves[0].pv = lastBestPV;
rootMoves[0].score = rootMoves[0].uciScore = lastBestScore;
}
else if (rootMoves[0].pv[0] != lastBestPV[0])
{
lastBestPV = rootMoves[0].pv;
lastBestScore = rootMoves[0].score;
lastBestMoveDepth = rootDepth;
}
if (!mainThread)
continue;
// Have we found a "mate in x"?
if (limits.mate && rootMoves[0].score == rootMoves[0].uciScore
&& ((rootMoves[0].score >= VALUE_MATE_IN_MAX_PLY
&& VALUE_MATE - rootMoves[0].score <= 2 * limits.mate)
|| (rootMoves[0].score != -VALUE_INFINITE
&& rootMoves[0].score <= VALUE_MATED_IN_MAX_PLY
&& VALUE_MATE + rootMoves[0].score <= 2 * limits.mate)))
threads.stop = true;
// If the skill level is enabled and time is up, pick a sub-optimal best move
if (skill.enabled() && skill.time_to_pick(rootDepth))
skill.pick_best(rootMoves, multiPV);
// Use part of the gained time from a previous stable move for the current move
for (auto&& th : threads)
{
totBestMoveChanges += th->worker->bestMoveChanges;
th->worker->bestMoveChanges = 0;
}
// Do we have time for the next iteration? Can we stop searching now?
if (limits.use_time_management() && !threads.stop && !mainThread->stopOnPonderhit)
{
int nodesEffort = rootMoves[0].effort * 100 / std::max(size_t(1), size_t(nodes));
double fallingEval = (1067 + 223 * (mainThread->bestPreviousAverageScore - bestValue)
+ 97 * (mainThread->iterValue[iterIdx] - bestValue))
/ 10000.0;
fallingEval = std::clamp(fallingEval, 0.580, 1.667);
// If the bestMove is stable over several iterations, reduce time accordingly
timeReduction = lastBestMoveDepth + 8 < completedDepth ? 1.495 : 0.687;
double reduction = (1.48 + mainThread->previousTimeReduction) / (2.17 * timeReduction);
double bestMoveInstability = 1 + 1.88 * totBestMoveChanges / threads.size();
double recapture = limits.capSq == rootMoves[0].pv[0].to_sq() ? 0.955 : 1.005;
double totalTime =
mainThread->tm.optimum() * fallingEval * reduction * bestMoveInstability * recapture;
// Cap used time in case of a single legal move for a better viewer experience
if (rootMoves.size() == 1)
totalTime = std::min(500.0, totalTime);
auto elapsedTime = elapsed();
if (completedDepth >= 10 && nodesEffort >= 97 && elapsedTime > totalTime * 0.739
&& !mainThread->ponder)
threads.stop = true;
// Stop the search if we have exceeded the totalTime
if (elapsedTime > totalTime)
{
// If we are allowed to ponder do not stop the search now but
// keep pondering until the GUI sends "ponderhit" or "stop".
if (mainThread->ponder)
mainThread->stopOnPonderhit = true;
else
threads.stop = true;
}
else
threads.increaseDepth = mainThread->ponder || elapsedTime <= totalTime * 0.506;
}
mainThread->iterValue[iterIdx] = bestValue;
iterIdx = (iterIdx + 1) & 3;
}
if (!mainThread)
return;
mainThread->previousTimeReduction = timeReduction;
// If the skill level is enabled, swap the best PV line with the sub-optimal one
if (skill.enabled())
std::swap(rootMoves[0],
*std::find(rootMoves.begin(), rootMoves.end(),
skill.best ? skill.best : skill.pick_best(rootMoves, multiPV)));
}
// Reset histories, usually before a new game
void Search::Worker::clear() {
mainHistory.fill(0);
captureHistory.fill(-700);
pawnHistory.fill(-1188);
correctionHistory.fill(0);
for (bool inCheck : {false, true})
for (StatsType c : {NoCaptures, Captures})
for (auto& to : continuationHistory[inCheck][c])
for (auto& h : to)
h->fill(-58);
for (size_t i = 1; i < reductions.size(); ++i)
reductions[i] = int((18.62 + std::log(size_t(options["Threads"])) / 2) * std::log(i));
refreshTable.clear(networks[numaAccessToken]);
}
// Main search function for both PV and non-PV nodes
template<NodeType nodeType>
Value Search::Worker::search(
Position& pos, Stack* ss, Value alpha, Value beta, Depth depth, bool cutNode) {
constexpr bool PvNode = nodeType != NonPV;
constexpr bool rootNode = nodeType == Root;
// Dive into quiescence search when the depth reaches zero
if (depth <= 0)
return qsearch < PvNode ? PV : NonPV > (pos, ss, alpha, beta);
// Limit the depth if extensions made it too large
depth = std::min(depth, MAX_PLY - 1);
// Check if we have an upcoming move that draws by repetition
if (!rootNode && alpha < VALUE_DRAW && pos.upcoming_repetition(ss->ply))
{
alpha = value_draw(this->nodes);
if (alpha >= beta)
return alpha;
}
assert(-VALUE_INFINITE <= alpha && alpha < beta && beta <= VALUE_INFINITE);
assert(PvNode || (alpha == beta - 1));
assert(0 < depth && depth < MAX_PLY);
assert(!(PvNode && cutNode));
Move pv[MAX_PLY + 1], capturesSearched[32], quietsSearched[32];
StateInfo st;
ASSERT_ALIGNED(&st, Eval::NNUE::CacheLineSize);
Key posKey;
Move move, excludedMove, bestMove;
Depth extension, newDepth;
Value bestValue, value, eval, maxValue, probCutBeta;
bool givesCheck, improving, priorCapture, opponentWorsening;
bool capture, moveCountPruning, ttCapture;
Piece movedPiece;
int moveCount, captureCount, quietCount;
// Step 1. Initialize node
Worker* thisThread = this;
ss->inCheck = pos.checkers();
priorCapture = pos.captured_piece();
Color us = pos.side_to_move();
moveCount = captureCount = quietCount = ss->moveCount = 0;
bestValue = -VALUE_INFINITE;
maxValue = VALUE_INFINITE;
// Check for the available remaining time
if (is_mainthread())
main_manager()->check_time(*thisThread);
// Used to send selDepth info to GUI (selDepth counts from 1, ply from 0)
if (PvNode && thisThread->selDepth < ss->ply + 1)
thisThread->selDepth = ss->ply + 1;
if (!rootNode)
{
// Step 2. Check for aborted search and immediate draw
if (threads.stop.load(std::memory_order_relaxed) || pos.is_draw(ss->ply)
|| ss->ply >= MAX_PLY)
return (ss->ply >= MAX_PLY && !ss->inCheck)
? evaluate(networks[numaAccessToken], pos, refreshTable,
thisThread->optimism[us])
: value_draw(thisThread->nodes);
// Step 3. Mate distance pruning. Even if we mate at the next move our score
// would be at best mate_in(ss->ply + 1), but if alpha is already bigger because
// a shorter mate was found upward in the tree then there is no need to search
// because we will never beat the current alpha. Same logic but with reversed
// signs apply also in the opposite condition of being mated instead of giving
// mate. In this case, return a fail-high score.
alpha = std::max(mated_in(ss->ply), alpha);
beta = std::min(mate_in(ss->ply + 1), beta);
if (alpha >= beta)
return alpha;
}
assert(0 <= ss->ply && ss->ply < MAX_PLY);
bestMove = Move::none();
(ss + 1)->killer = Move::none();
(ss + 2)->cutoffCnt = 0;
Square prevSq = ((ss - 1)->currentMove).is_ok() ? ((ss - 1)->currentMove).to_sq() : SQ_NONE;
ss->statScore = 0;
// Step 4. Transposition table lookup
excludedMove = ss->excludedMove;
posKey = pos.key();
auto [ttHit, ttData, ttWriter] = tt.probe(posKey);
// Need further processing of the saved data
ss->ttHit = ttHit;
ttData.move = rootNode ? thisThread->rootMoves[thisThread->pvIdx].pv[0]
: ttHit ? ttData.move
: Move::none();
ttData.value = ttHit ? value_from_tt(ttData.value, ss->ply, pos.rule50_count()) : VALUE_NONE;
ss->ttPv = excludedMove ? ss->ttPv : PvNode || (ttHit && ttData.is_pv);
ttCapture = ttData.move && pos.capture_stage(ttData.move);
// At this point, if excluded, skip straight to step 6, static eval. However,
// to save indentation, we list the condition in all code between here and there.
// At non-PV nodes we check for an early TT cutoff
if (!PvNode && !excludedMove && ttData.depth > depth - (ttData.value <= beta)
&& ttData.value != VALUE_NONE // Can happen when !ttHit or when access race in probe()
&& (ttData.bound & (ttData.value >= beta ? BOUND_LOWER : BOUND_UPPER)))
{
// If ttMove is quiet, update move sorting heuristics on TT hit (~2 Elo)
if (ttData.move && ttData.value >= beta)
{
// Bonus for a quiet ttMove that fails high (~2 Elo)
if (!ttCapture)
update_quiet_stats(pos, ss, *this, ttData.move, stat_bonus(depth));
// Extra penalty for early quiet moves of
// the previous ply (~1 Elo on STC, ~2 Elo on LTC)
if (prevSq != SQ_NONE && (ss - 1)->moveCount <= 2 && !priorCapture)
update_continuation_histories(ss - 1, pos.piece_on(prevSq), prevSq,
-stat_malus(depth + 1));
}
// Partial workaround for the graph history interaction problem
// For high rule50 counts don't produce transposition table cutoffs.
if (pos.rule50_count() < 90)
return ttData.value;
}
// Step 5. Tablebases probe
if (!rootNode && !excludedMove && tbConfig.cardinality)
{
int piecesCount = pos.count<ALL_PIECES>();
if (piecesCount <= tbConfig.cardinality
&& (piecesCount < tbConfig.cardinality || depth >= tbConfig.probeDepth)
&& pos.rule50_count() == 0 && !pos.can_castle(ANY_CASTLING))
{
TB::ProbeState err;
TB::WDLScore wdl = Tablebases::probe_wdl(pos, &err);
// Force check of time on the next occasion
if (is_mainthread())
main_manager()->callsCnt = 0;
if (err != TB::ProbeState::FAIL)
{
thisThread->tbHits.fetch_add(1, std::memory_order_relaxed);
int drawScore = tbConfig.useRule50 ? 1 : 0;
Value tbValue = VALUE_TB - ss->ply;
// Use the range VALUE_TB to VALUE_TB_WIN_IN_MAX_PLY to score
value = wdl < -drawScore ? -tbValue
: wdl > drawScore ? tbValue
: VALUE_DRAW + 2 * wdl * drawScore;
Bound b = wdl < -drawScore ? BOUND_UPPER
: wdl > drawScore ? BOUND_LOWER
: BOUND_EXACT;
if (b == BOUND_EXACT || (b == BOUND_LOWER ? value >= beta : value <= alpha))
{
ttWriter.write(posKey, value_to_tt(value, ss->ply), ss->ttPv, b,
std::min(MAX_PLY - 1, depth + 6), Move::none(), VALUE_NONE,
tt.generation());
return value;
}
if (PvNode)
{
if (b == BOUND_LOWER)
bestValue = value, alpha = std::max(alpha, bestValue);
else
maxValue = value;
}
}
}
}
// Step 6. Static evaluation of the position
Value unadjustedStaticEval = VALUE_NONE;
if (ss->inCheck)
{
// Skip early pruning when in check
ss->staticEval = eval = VALUE_NONE;
improving = false;
goto moves_loop;
}
else if (excludedMove)
{
// Providing the hint that this node's accumulator will be used often
// brings significant Elo gain (~13 Elo).
Eval::NNUE::hint_common_parent_position(pos, networks[numaAccessToken], refreshTable);
unadjustedStaticEval = eval = ss->staticEval;
}
else if (ss->ttHit)
{
// Never assume anything about values stored in TT
unadjustedStaticEval = ttData.eval;
if (unadjustedStaticEval == VALUE_NONE)
unadjustedStaticEval =
evaluate(networks[numaAccessToken], pos, refreshTable, thisThread->optimism[us]);
else if (PvNode)
Eval::NNUE::hint_common_parent_position(pos, networks[numaAccessToken], refreshTable);
ss->staticEval = eval = to_corrected_static_eval(unadjustedStaticEval, *thisThread, pos);
// ttValue can be used as a better position evaluation (~7 Elo)
if (ttData.value != VALUE_NONE
&& (ttData.bound & (ttData.value > eval ? BOUND_LOWER : BOUND_UPPER)))
eval = ttData.value;
}
else
{
unadjustedStaticEval =
evaluate(networks[numaAccessToken], pos, refreshTable, thisThread->optimism[us]);
ss->staticEval = eval = to_corrected_static_eval(unadjustedStaticEval, *thisThread, pos);
// Static evaluation is saved as it was before adjustment by correction history
ttWriter.write(posKey, VALUE_NONE, ss->ttPv, BOUND_NONE, DEPTH_UNSEARCHED, Move::none(),
unadjustedStaticEval, tt.generation());
}
// 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(-10 * int((ss - 1)->staticEval + ss->staticEval), -1664, 1471) + 752;
thisThread->mainHistory[~us][((ss - 1)->currentMove).from_to()] << bonus;
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]
<< bonus / 2;
}
// Set up the improving flag, which is true if current static evaluation is
// bigger than the previous static evaluation at our turn (if we were in
// check at our previous move we look at static evaluation at move prior to it
// and if we were in check at move prior to it flag is set to true) and is
// false otherwise. The improving flag is used in various pruning heuristics.
improving = (ss - 2)->staticEval != VALUE_NONE
? ss->staticEval > (ss - 2)->staticEval
: (ss - 4)->staticEval != VALUE_NONE && ss->staticEval > (ss - 4)->staticEval;
opponentWorsening = ss->staticEval + (ss - 1)->staticEval > 2;
// Step 7. Razoring (~1 Elo)
// If eval is really low, check with qsearch if we can exceed alpha. If the
// search suggests we cannot exceed alpha, return a speculative fail low.
if (eval < alpha - 494 - 290 * depth * depth)
{
value = qsearch<NonPV>(pos, ss, alpha - 1, alpha);
if (value < alpha && std::abs(value) < VALUE_TB_WIN_IN_MAX_PLY)
return value;
}
// Step 8. Futility pruning: child node (~40 Elo)
// The depth condition is important for mate finding.
if (!ss->ttPv && depth < 13
&& eval - futility_margin(depth, cutNode && !ss->ttHit, improving, opponentWorsening)
- (ss - 1)->statScore / 260
>= beta
&& eval >= beta && (!ttData.move || ttCapture) && beta > VALUE_TB_LOSS_IN_MAX_PLY
&& eval < VALUE_TB_WIN_IN_MAX_PLY)
return beta + (eval - beta) / 3;
// Step 9. Null move search with verification search (~35 Elo)
if (!PvNode && (ss - 1)->currentMove != Move::null() && (ss - 1)->statScore < 14389
&& eval >= beta && ss->staticEval >= beta - 21 * depth + 390 && !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) / 202, 6) + depth / 3 + 5;
ss->currentMove = Move::null();
ss->continuationHistory = &thisThread->continuationHistory[0][0][NO_PIECE][0];
pos.do_null_move(st, tt);
Value nullValue = -search<NonPV>(pos, ss + 1, -beta, -beta + 1, depth - R, !cutNode);
pos.undo_null_move();
// Do not return unproven mate or TB scores
if (nullValue >= beta && nullValue < VALUE_TB_WIN_IN_MAX_PLY)
{
if (thisThread->nmpMinPly || depth < 16)
return nullValue;
assert(!thisThread->nmpMinPly); // Recursive verification is not allowed
// Do verification search at high depths, with null move pruning disabled
// until ply exceeds nmpMinPly.
thisThread->nmpMinPly = ss->ply + 3 * (depth - R) / 4;
Value v = search<NonPV>(pos, ss, beta - 1, beta, depth - R, false);
thisThread->nmpMinPly = 0;
if (v >= beta)
return nullValue;
}
}
// Step 10. Internal iterative reductions (~9 Elo)
// For PV nodes without a ttMove, we decrease depth.
if (PvNode && !ttData.move)
depth -= 3;
// Use qsearch if depth <= 0
if (depth <= 0)
return qsearch<PV>(pos, ss, alpha, beta);
// For cutNodes, if depth is high enough, decrease depth by 2 if there is no ttMove,
// or by 1 if there is a ttMove with an upper bound.
if (cutNode && depth >= 7 && (!ttData.move || ttData.bound == BOUND_UPPER))
depth -= 1 + !ttData.move;
// 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 + 184 - 53 * improving;
if (!PvNode && depth > 3
&& std::abs(beta) < VALUE_TB_WIN_IN_MAX_PLY
// If value from transposition table is lower than probCutBeta, don't attempt
// probCut there and in further interactions with transposition table cutoff
// depth is set to depth - 3 because probCut search has depth set to depth - 4
// but we also do a move before it. So effective depth is equal to depth - 3.
&& !(ttData.depth >= depth - 3 && ttData.value != VALUE_NONE && ttData.value < probCutBeta))
{
assert(probCutBeta < VALUE_INFINITE && probCutBeta > beta);
MovePicker mp(pos, ttData.move, probCutBeta - ss->staticEval, &thisThread->captureHistory);
Piece captured;
while ((move = mp.next_move()) != Move::none())
{
assert(move.is_ok());
if (move == excludedMove)
continue;
if (!pos.legal(move))
continue;
assert(pos.capture_stage(move));
movedPiece = pos.moved_piece(move);
captured = pos.piece_on(move.to_sq());
// Prefetch the TT entry for the resulting position
prefetch(tt.first_entry(pos.key_after(move)));
ss->currentMove = move;
ss->continuationHistory =
&this->continuationHistory[ss->inCheck][true][pos.moved_piece(move)][move.to_sq()];
thisThread->nodes.fetch_add(1, std::memory_order_relaxed);
pos.do_move(move, st);
// Perform a preliminary qsearch to verify that the move holds
value = -qsearch<NonPV>(pos, ss + 1, -probCutBeta, -probCutBeta + 1);
// If the qsearch held, perform the regular search
if (value >= probCutBeta)
value =
-search<NonPV>(pos, ss + 1, -probCutBeta, -probCutBeta + 1, depth - 4, !cutNode);
pos.undo_move(move);
if (value >= probCutBeta)
{
thisThread->captureHistory[movedPiece][move.to_sq()][type_of(captured)]
<< stat_bonus(depth - 2);
// Save ProbCut data into transposition table
ttWriter.write(posKey, value_to_tt(value, ss->ply), ss->ttPv, BOUND_LOWER,
depth - 3, move, unadjustedStaticEval, tt.generation());
return std::abs(value) < VALUE_TB_WIN_IN_MAX_PLY ? value - (probCutBeta - beta)
: value;
}
}
Eval::NNUE::hint_common_parent_position(pos, networks[numaAccessToken], refreshTable);
}
moves_loop: // When in check, search starts here
// Step 12. A small Probcut idea (~4 Elo)
probCutBeta = beta + 390;
if ((ttData.bound & BOUND_LOWER) && ttData.depth >= depth - 4 && ttData.value >= probCutBeta
&& std::abs(beta) < VALUE_TB_WIN_IN_MAX_PLY)
return probCutBeta;
const PieceToHistory* contHist[] = {(ss - 1)->continuationHistory,
(ss - 2)->continuationHistory,
(ss - 3)->continuationHistory,
(ss - 4)->continuationHistory,
nullptr,
(ss - 6)->continuationHistory};
MovePicker mp(pos, ttData.move, depth, &thisThread->mainHistory, &thisThread->captureHistory,
contHist, &thisThread->pawnHistory, ss->killer);
value = bestValue;
moveCountPruning = false;
// Step 13. Loop through all pseudo-legal moves until no moves remain
// or a beta cutoff occurs.
while ((move = mp.next_move(moveCountPruning)) != Move::none())
{
assert(move.is_ok());
if (move == excludedMove)
continue;
// Check for legality
if (!pos.legal(move))
continue;
// At root obey the "searchmoves" option and skip moves not listed in Root
// Move List. In MultiPV mode we also skip PV moves that have been already
// searched and those of lower "TB rank" if we are in a TB root position.
if (rootNode
&& !std::count(thisThread->rootMoves.begin() + thisThread->pvIdx,
thisThread->rootMoves.begin() + thisThread->pvLast, move))
continue;
ss->moveCount = ++moveCount;
if (rootNode && is_mainthread() && nodes > 10000000)
{
main_manager()->updates.onIter(
{depth, UCIEngine::move(move, pos.is_chess960()), moveCount + thisThread->pvIdx});
}
if (PvNode)
(ss + 1)->pv = nullptr;
extension = 0;
capture = pos.capture_stage(move);
movedPiece = pos.moved_piece(move);
givesCheck = pos.gives_check(move);
// Calculate new depth for this move
newDepth = depth - 1;
int delta = beta - alpha;
Depth r = reduction(improving, depth, moveCount, delta);
// Step 14. Pruning at shallow depth (~120 Elo).
// Depth conditions are important for mate finding.
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)
moveCountPruning = moveCount >= futility_move_count(improving, depth);
// Reduced depth of the next LMR search
int lmrDepth = newDepth - r;
if (capture || givesCheck)
{
Piece capturedPiece = pos.piece_on(move.to_sq());
int captHist =
thisThread->captureHistory[movedPiece][move.to_sq()][type_of(capturedPiece)];