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v5.1.0
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@github-actions github-actions released this 13 Feb 07:49
· 137 commits to master since this release
v5.1.0
8c5bd12

This releases comes with a bigger neural network and support for Syzygy Tablebase

Estimated strength increase: ~ 40 Elo

Changes

  • Increased hidden layer size
  • Re-introduced GPU trainer
  • Fixed UCI compatibility issue with Nibbler Chess UI
  • Fixed analysis mode issue when search reaches the maximum depth
  • Integrated Fathom for Syzygy Tablebase support
  • Some minor search-related improvements

Note

Due to a compilation issue the no-popcount compatibility build for Windows has been temporarily removed.

Installation

The chess engine is available for Windows and Linux and requires a 64 Bit CPU.
There are optimized executables available for different CPU micro-architecture generations.

Starting with Velvet v4.1.0 there are also builds for macOS provided.
Currently there are no specific optimizations for the ARM-based/Apple Silicon builds implemented, so
the macOS builds for x86_64 might be faster.

If you have a relatively modern CPU (2013+) with AVX2 support, then the ...-x86_64-avx2 executable is highly recommended for best performance.

Executable Description Min. CPU Generation Required Instruction Sets
x86_64-avx2 Recommended for best performance on a modern CPU Intel Haswell / Zen1 AVX2, BMI1
x86_64-sse4-popcnt Lower performance, recommended for CPUs without AVX2 support Intel Nehalem / AMD Bulldozer SSE4.2, SSE3, POPCNT
x86_64-nopopcnt Lowest performance, but compatible with most x86_64 CPUs --- SSE2, CMOV
apple-silicon Native builds for Apple Silicon processors (ARM aarch64) Apple M1
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