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@jnlt3 jnlt3 released this 06 Aug 09:25
· 206 commits to main since this release
7.0
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Learn about vigilant mode.

Search

Black Marlin's search now includes the threats idea from Koivisto. There are various other search tweaks, though most notably, the search algorithm has been tuned automatically via the usage of SPSA. The new search parameters result in a much wider, yet much stronger search.

Evaluation

The neural network has doubled in size and has been trained on a much larger dataset than previously done. This data has been generated by the author of Seer and resulted in significant gains.

Self Play Results

ELO | 134.35 +- 3.48 (95%)
CONF | 8.0+0.08s Threads=1 Hash=8MB
GAMES | N: 20000 W: 8935 L: 1565 D: 9500

Testing

Testing has been done on the main OpenBench instance. Aside from increased hardware, this has the added benefit of ideas being verified by various other engine authors. Thanks to Andrew Grant and all the engine authors on the instance.

Thanks

Analog Hors, for developing cozy chess.
MinusKelvin (Frozenight author), for exchanging ideas.
Koivisto authors, for the idea of using threats in search.
Connor (Seer author), for generating data.
Andrew Grant, for developing OpenBench.
noobpwnftw, for providing the OpenBench hardware.

Selecting Binaries

If you are on Apple Silicon, the binary is blackmarlin-darwin-arm.

If you know the capabilities of your CPU:
x86-64: SSE2
x86-64-v2: SSSE3, SSE4.2
x86-64-v3: AVX2
x86-64-v4: AVX512

Otherwise, pick your operating system and start from the binary with the highest x86-64 level and pick a lower one until the binary doesn't crash. Alternatively, check the link here.

Assets 15