Forked on my github from nodchips SF-NNUE repository, working towards symbiotic training with Leelenstein. You can download StockFiNN 0.1 and follow progress here: https://www.patreon.com/posts/stockfinn-0-1-38717611
It is progressing very fast so testing is in flux, but here are some scaling results worth seeing.
Using the default avx2 compile I posted I get about 1.6-1.7M nps with the default 1 thread bench, it's about 40-50% as fast as sf-dev. (There is also an intel skylake bmi2 compile I made) FYI, under a full AVX2 load CPUs get very hot so need good cooling to not downclock.
All testing done with my same 320 game no draw book on 3950x with 1 thread and full 6 man EGTB on nvme ssd. I used Brainfish compile with large pages because it is the fastest Stockfish on my system.
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15s+0.15s
Score of StockFiNN vs BrainFish_200420: 66 - 155 - 99 [0.361]
Elo difference: -99.2 +/- 32.4, LOS: 0.0 %, DrawRatio: 30.9 %
30s+0.3s
Score of StockFiNN vs BrainFish_200420: 72 - 127 - 121 [0.414]
Elo difference: -60.3 +/- 30.2, LOS: 0.0 %, DrawRatio: 37.8 %
60s+0.6s
Score of StockFiNN vs BrainFish_200420: 74 - 103 - 143 [0.455]
Elo difference: -31.6 +/- 28.4, LOS: 1.5 %, DrawRatio: 44.7 %
120+1.2s
Score of StockFiNN vs BrainFish_200420: 79 - 75 - 166 [0.506]
Elo difference: 4.3 +/- 26.4, LOS: 62.6 %, DrawRatio: 51.9 %
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fixed 100k nodes
Score of StockFiNN vs BrainFish_200420: 144 - 95 - 81 [0.577]
Elo difference: 53.6 +/- 33.2, LOS: 99.9 %, DrawRatio: 25.3 %
fixed 1 million nodes
Score of StockFiNN vs BrainFish_200420: 125 - 66 - 129 [0.592]
Elo difference: 64.8 +/- 29.6, LOS: 100.0 %, DrawRatio: 40.3 %