This release contains a variety of minor bugfixes and minor feature additions. It also incorporates a large number of internal changes to prepare for and support a distributed training run (yay), although distributed training support has deliberately not been enabled yet for the precompiled executables this release.
General Improvements and Features
Supports CUDA 11.1 now, which makes it possible to use KataGo CUDA instead of only OpenCL with NVIDIA RTX 30** GPUs. Beware though that on other GPUs CUDA 11.1 might not actually be faster than 10.2 - in one test on a V100 cloud machine, CUDA 11.1 seemed to be slower than CUDA 10.2. And possible changes to OpenCL speed and to CUDA speed on RTX 30** are also unknown and seem to vary - some users have reported exciting results, some have reported fairly disappointing ones.
Added new gtp config option "ignoreGTPAndForceKomi" that will force a particular komi regardless if the GTP controller tries to specify a different one. And KataGo is also now slightly smarter about guessing default komi based on other rules in the case where absolutely nothing tells KataGo what it should be.
KataGo no longer requires boost libraries in order to be compiled.
OpenCL backend optimized to now require less GPU memory.
Benchmark command should now be more efficient about choosing search ranges for threads.
Analysis Engine
There are several improvements to the json analysis engine.
Can now report the predicted ownership map for each individual move.
Can now report results from an ongoing query, making it possible to do the same things you would with kata-analyze or lz-analyze.
Can now cancel or terminate queries before they finish.
Can now specify differing per-turn priorities in a single query.
Supports priorities outside the range +/- 2^31, making it easier to do priorities based on timestamps or externally-determined large id numbers, or very, very long-running processes.
Bugfixes
Fixes a coding error that would make it sometimes impossible for KataGo to select the optimal move near the end of a game with button Go rules. (Button Go is a ruleset that KataGo supports that has the rules-simplicity and elegance of area scoring, but with the sharper and fairer scoring granularity of territory scoring).
Fix minor parsing bug on some uses of -override-config
Fixed some bugs on how the benchmark command behaved with threads for the Eigen backend.
Other Changes
Shuffle script for selfplay training, which long ago dropped support for shuffling training and validation data separately, now also uses a filepath that just shuffles all data together.
A large number of internal refactors and changes have been made to support acting as a client for distributed training. The cmake option BUILD_DISTRIBUTED=1 will make KataGo compile with support for distributed training, although the official distributed run has not quite started yet.作者: gaozihe 时间: 2020-11-9 21:06
如果您是新用户，不要忘记查看此部分，了解入门和基本使用情况！
最新和最强的神经网络仍然是那些从以前的版本： https://github.com/lightvector/KataGo/releases/tag/v1.4.5
如果你不知道选择哪个版本 （OpenCL， CUDA， Eigen， Eigen AVX2）， 阅读此： https://github.com/lightvector/KataGo#opencl-vs-cuda-vs-eigen