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https://github.com/sockspls/badfish
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Start all threads searching on root position and use only the shared TT table as synching scheme. It seems this scheme scales better than YBWC for high number of threads. Verified for nor regression at STC 3 threads LLR: -2.95 (-2.94,2.94) [-3.00,1.00] Total: 40232 W: 6908 L: 7130 D: 26194 Verified for nor regression at LTC 3 threads LLR: 2.95 (-2.94,2.94) [-3.00,1.00] Total: 28186 W: 3908 L: 3798 D: 20480 Verified for nor regression at STC 7 threads LLR: 2.95 (-2.94,2.94) [-3.00,1.00] Total: 3607 W: 674 L: 526 D: 2407 Verified for nor regression at LTC 7 threads LLR: 2.95 (-2.94,2.94) [-3.00,1.00] Total: 4235 W: 671 L: 528 D: 3036 Tested with fixed games at LTC with 20 threads ELO: 44.75 +-7.6 (95%) LOS: 100.0% Total: 2069 W: 407 L: 142 D: 1520 Tested with fixed games at XLTC (120secs) with 20 threads ELO: 28.01 +-6.7 (95%) LOS: 100.0% Total: 2275 W: 349 L: 166 D: 1760 Original patch of mbootsector, with additional work from Ivan Ivec (log formula), Joerg Oster (id loop simplification) and Marco Costalba (assorted formatting and rework). Bench: 8116244
134 lines
5 KiB
C++
134 lines
5 KiB
C++
/*
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Stockfish, a UCI chess playing engine derived from Glaurung 2.1
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Copyright (C) 2004-2008 Tord Romstad (Glaurung author)
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Copyright (C) 2008-2015 Marco Costalba, Joona Kiiski, Tord Romstad
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Stockfish is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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Stockfish is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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#include <algorithm>
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#include <cfloat>
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#include <cmath>
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#include "search.h"
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#include "timeman.h"
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#include "uci.h"
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TimeManagement Time; // Our global time management object
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namespace {
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enum TimeType { OptimumTime, MaxTime };
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const int MoveHorizon = 50; // Plan time management at most this many moves ahead
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const double MaxRatio = 7.0; // When in trouble, we can step over reserved time with this ratio
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const double StealRatio = 0.33; // However we must not steal time from remaining moves over this ratio
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// move_importance() is a skew-logistic function based on naive statistical
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// analysis of "how many games are still undecided after n half-moves". Game
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// is considered "undecided" as long as neither side has >275cp advantage.
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// Data was extracted from CCRL game database with some simple filtering criteria.
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double move_importance(int ply) {
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const double XScale = 9.3;
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const double XShift = 59.8;
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const double Skew = 0.172;
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return pow((1 + exp((ply - XShift) / XScale)), -Skew) + DBL_MIN; // Ensure non-zero
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}
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template<TimeType T>
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int remaining(int myTime, int movesToGo, int ply, int slowMover)
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{
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const double TMaxRatio = (T == OptimumTime ? 1 : MaxRatio);
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const double TStealRatio = (T == OptimumTime ? 0 : StealRatio);
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double moveImportance = (move_importance(ply) * slowMover) / 100;
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double otherMovesImportance = 0;
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for (int i = 1; i < movesToGo; ++i)
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otherMovesImportance += move_importance(ply + 2 * i);
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double ratio1 = (TMaxRatio * moveImportance) / (TMaxRatio * moveImportance + otherMovesImportance);
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double ratio2 = (moveImportance + TStealRatio * otherMovesImportance) / (moveImportance + otherMovesImportance);
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return int(myTime * std::min(ratio1, ratio2)); // Intel C++ asks an explicit cast
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}
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} // namespace
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/// init() is called at the beginning of the search and calculates the allowed
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/// thinking time out of the time control and current game ply. We support four
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/// different kinds of time controls, passed in 'limits':
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///
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/// inc == 0 && movestogo == 0 means: x basetime [sudden death!]
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/// inc == 0 && movestogo != 0 means: x moves in y minutes
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/// inc > 0 && movestogo == 0 means: x basetime + z increment
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/// inc > 0 && movestogo != 0 means: x moves in y minutes + z increment
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void TimeManagement::init(Search::LimitsType& limits, Color us, int ply)
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{
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int minThinkingTime = Options["Minimum Thinking Time"];
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int moveOverhead = Options["Move Overhead"];
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int slowMover = Options["Slow Mover"];
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int npmsec = Options["nodestime"];
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// If we have to play in 'nodes as time' mode, then convert from time
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// to nodes, and use resulting values in time management formulas.
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// WARNING: Given npms (nodes per millisecond) must be much lower then
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// real engine speed to avoid time losses.
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if (npmsec)
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{
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if (!availableNodes) // Only once at game start
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availableNodes = npmsec * limits.time[us]; // Time is in msec
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// Convert from millisecs to nodes
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limits.time[us] = (int)availableNodes;
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limits.inc[us] *= npmsec;
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limits.npmsec = npmsec;
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}
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startTime = limits.startTime;
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unstablePvFactor = 1;
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optimumTime = maximumTime = std::max(limits.time[us], minThinkingTime);
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const int MaxMTG = limits.movestogo ? std::min(limits.movestogo, MoveHorizon) : MoveHorizon;
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// We calculate optimum time usage for different hypothetical "moves to go"-values
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// and choose the minimum of calculated search time values. Usually the greatest
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// hypMTG gives the minimum values.
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for (int hypMTG = 1; hypMTG <= MaxMTG; ++hypMTG)
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{
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// Calculate thinking time for hypothetical "moves to go"-value
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int hypMyTime = limits.time[us]
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+ limits.inc[us] * (hypMTG - 1)
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- moveOverhead * (2 + std::min(hypMTG, 40));
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hypMyTime = std::max(hypMyTime, 0);
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int t1 = minThinkingTime + remaining<OptimumTime>(hypMyTime, hypMTG, ply, slowMover);
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int t2 = minThinkingTime + remaining<MaxTime >(hypMyTime, hypMTG, ply, slowMover);
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optimumTime = std::min(t1, optimumTime);
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maximumTime = std::min(t2, maximumTime);
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}
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if (Options["Ponder"])
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optimumTime += optimumTime / 4;
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optimumTime = std::min(optimumTime, maximumTime);
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}
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