New chess engine: Molybdenum 3.0
v.3.0:
This release features a bunch of Elo gains related to search for a total of
~85 STC self play Elo:
Elo | 84.75 +- 4.99 (95%)
Conf | 8.0+0.08s Threads=1 Hash=8MB
Games | N: 10000 W: 3857 L: 1465 D: 4678
Penta | [59, 532, 1886, 2004, 519]
http://aytchell.eu.pythonanywhere.com/test/226/
~70 LTC self play Elo:
Elo | 73.48 +- 9.62 (95%)
Conf | 40.0+0.40s Threads=1 Hash=64MB
Games | N: 2500 W: 880 L: 359 D: 1261
Penta | [8, 132, 527, 497, 86]
http://aytchell.eu.pythonanywhere.com/test/225/
Elo gains:
Transposition table improvements:
TT cutoffs in qsearch: #53
TT move ordering in qsearch: #54
Improved replacement scheme: #55
Smaller entries: #56
Fractional reductions:
In history pruning: #61
In move count pruning: #62
In futility pruning: #63
All the other stuff:
Introduce singular extensions: #51
Use singular search to improve move ordering: #52
Symmetrize history limits: #57
RFP more after bad moves: #59
Tune time management: #60
Tune search; #64
Adjust bestScore if inaccurate: #65
The provided binaries use avx2, bmi2... (v3) / sse3, popcnt.. (v2) optimization respectively, note that even ryzens before zen 3 should be able to use the bmi2 binaries without slowdown, as they contain no pext / pdep instructions
~85 STC self play Elo:
Elo | 84.75 +- 4.99 (95%)
Conf | 8.0+0.08s Threads=1 Hash=8MB
Games | N: 10000 W: 3857 L: 1465 D: 4678
Penta | [59, 532, 1886, 2004, 519]
http://aytchell.eu.pythonanywhere.com/test/226/
~70 LTC self play Elo:
Elo | 73.48 +- 9.62 (95%)
Conf | 40.0+0.40s Threads=1 Hash=64MB
Games | N: 2500 W: 880 L: 359 D: 1261
Penta | [8, 132, 527, 497, 86]
http://aytchell.eu.pythonanywhere.com/test/225/
Elo gains:
Transposition table improvements:
TT cutoffs in qsearch: #53
TT move ordering in qsearch: #54
Improved replacement scheme: #55
Smaller entries: #56
Fractional reductions:
In history pruning: #61
In move count pruning: #62
In futility pruning: #63
All the other stuff:
Introduce singular extensions: #51
Use singular search to improve move ordering: #52
Symmetrize history limits: #57
RFP more after bad moves: #59
Tune time management: #60
Tune search; #64
Adjust bestScore if inaccurate: #65
The provided binaries use avx2, bmi2... (v3) / sse3, popcnt.. (v2) optimization respectively, note that even ryzens before zen 3 should be able to use the bmi2 binaries without slowdown, as they contain no pext / pdep instructions
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