

https://github.com/QueensGambit/CrazyAra/releases
"CrazyAra & ClassicAra 0.9.0
@QueensGambit QueensGambit released this Apr 5, 2021
Notes
This release replaces MCTS with MCGS as the new default and is the first release with standard chess support.
The provided model for chess has been trained supervised on the free KingBase Lite 2019 data set without reinforcement learning so far.
The displayed nps is now considereably lower, because now only the actual nodes in the tree are displayed.
Terminal visits and transposition visits do not count as nodes anymore.
By using MCGS, the required memory allocation has been reduced for a given movetime.
New Variant
Standard chess: A neural network and binary is provided for standard chess.
The executable is called ClassicAra.
Environment Backend
The CrazyAra project now supports a general back-end which allows a better integration to new environments.
An environment is used for move-generation and terminal condition checks.
The following environments have been integrated so far:
Multi-Variant Stockfish
OpenSpiel
Pommerman
Bugfixes
fixed crash in release 0.8.4 when too many transpositions occurred.
fixed bug that single moves were not done instantly if no tree was reused (#56).
fixed bug decreasing nodes after 16 million nodes (#39).
workaround for bug in XBoard / Winboard. UCI-Variant is now repeated if there is only a single variant available (#23).
UCI specific
MultiPV is now supported and can be used for analysis e.g. using LiGround.
UCI options can now be changed, also after the isready command.
Current limitation: Changing the loaded neural network dynamicly after a neural network has already been loaded is not (yet) possible.
UCI Options are now ordered in alphabetical order.
Updated, removed, or renamed certain UCI options (#71).
root command (debug)
For the Root Command: Moves are now displayed in SAN notation instead of UCI notation for better readibility.
UCI moves are now ordered by the current best move and not using the fixed policy ordering.
Miscellaneous
The loaded neural network input and output shapes are now always displayed when loading.
An input shape and output shape check is made for the loaded neural network architecture.
INT8 CPU Back-end
INT8 weights are now available for the MXNet MKL CPU back-end, resulting in a 1.5 - 3x speed-up.
Known issues
The first start-up time of the engine may take 1-15 minutes to generate the trt-engine files.
The process of generating trt-files is done twice, i.e. for batch.size 1 and batch-size 16.
It is recommended to first start the engine from the command line and issue the isready command. More information can be found here. All later loading times should be < 10s.
The available batch sizes are limited to the provided onnx models. Current available batch-sizes are:
1
8
16
64
Regression Test (Crazyhouse)
OS: Ubuntu 18.04
GPU: RTX 2070 OC
Model: Model-OS-96
Opening suite: crazyhouse_mix_cp_130.epd
TC: 10s + 0.1s
Score of CrazyAra 0.9.0 - Release vs CrazyAra 0.8.0 - Release: 208 - 159 - 58 [0.558]
Elo difference: 40.2 +/- 30.9, LOS: 99.5 %, DrawRatio: 13.6 %
425 of 1000 games finished.
TC: 3min + 2s
Score of CrazyAra 0.9.0 - Release vs CrazyAra 0.8.0 - Release: 29 - 19 - 14 [0.581]
Elo difference: 56.5 +/- 78.1, LOS: 92.6 %, DrawRatio: 22.6 %
62 of 1000 games finished.
Inference libraries
The following inference libraries are used in each package:
CrazyAra_ClassicAra_0.9.0_Linux_TensorRT.zip
CUDA 11.2
cuDNN 8.1.1.33
TensorRT-7.2.3.4
CrazyAra_ClassicAra_0.9.0_Linux_MKL.zip
MXNet 1.8.0
Intel oneAPI MKL 2021.2.0
CrazyAra_ClassicAra_0.9.0_Win_TensorRT.zip
CUDA 11.2
cuDNN 8.1.1.33
TensorRT-7.2.3.4
CrazyAra_ClassicAra_0.9.0_Win_MKL.zip
--> TODO
CrazyAra_ClassicAra_0.9.0_Mac_CPU.zip
MXNet 1.8.0
Intel oneAPI MKL 2021.2.0
The release files include the required dll / so-files for convenience. If you already have them installed on your system, can delete them.
v0.9.0
https://github.com/QueensGambit/CrazyAr ... sorRT.zip
v0.8.4
https://github.com/QueensGambit/CrazyAr ... ra_084.exe