This minor release contains an updated neural network
Estimated strength increase: ~ 10 Elo
Changes
v7.2.0 introduced a bigger neural network (hidden layer size increased from 2x512 to 2x768 hidden nodes).
Unfortunately it was trained with some experimental changes and the resulting network was only slightly better than the smaller network.
For this new v7.3.0 release, a new network was trained.
Notes
Due to the lack of an ARM-based (Apple Silicon) computer, the new "apple-silicon" builds are untested.
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 |