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→Lc0: wording
Leela Chess Zero consists of an executable to play or analyze [[Chess Game|games]], initially dubbed '''LCZero''', soon rewritten by a team around [[Alexander Lyashuk]] for better performance and then called '''Lc0''' <ref>[https://github.com/LeelaChessZero/lc0/wiki/lc0-transition lc0 transition · LeelaChessZero/lc0 Wiki · GitHub]</ref> <ref>[http://www.talkchess.com/forum3/viewtopic.php?f=2&t=68094&start=91 Re: TCEC season 13, 2 NN engines will be participating, Leela and Deus X] by [[Gian-Carlo Pascutto]], [[CCC]], August 03, 2018</ref>. This executable, the actual chess engine, performs the [[Monte-Carlo Tree Search|MCTS]] and reads the self-taught [[Neural Networks#Convolutional|CNN]], which weights are persistent in a separate file.
Lc0 is written in [[Cpp|C++]] (started with [[Cpp#14|C++14]] then upgraded to [[Cpp#17|C++17]]) and may be compiled for various platforms and backends. Since deep CNN approaches are best suited to run massively in parallel on [[GPU|GPUs]] to perform all the [[Float|floating point]] [https://en.wikipedia.org/wiki/Dot_product dot products] for thousands of neurons,
the preferred target platforms are [[Nvidia]] [[GPU|GPUs]] supporting [https://en.wikipedia.org/wiki/CUDA CUDA] and [https://en.wikipedia.org/wiki/cuDNN cuDNN] libraries <ref>[https://developer.nvidia.com/cudnn NVIDIA cuDNN | NVIDIA Developer]</ref>. [[Ankan Banerjee]] wrote the cuDNN, backen (also shared by [[Deus X]] and [[Allie]] <ref>[http://www.talkchess.com/forum3/viewtopic.php?f=2&t=71822&start=48 Re: My failed attempt to change TCEC NN clone rules] by [[Adam Treat]], [[CCC]], September 19, 2019</ref>), and DX12 backend code. There exist meanwhile different Lc0 backends to be used with different hardware, not all neural network architectures/features are supported on all backends. Different backends and different network architectures with different net size give different nodes per secondand Elo. CPUs can be utilized for example via BLAS and DNNL and GPUs via CUDA, cuDNN, OpenCL, DX12, Metal, ONNX, oneDNN backends.
=Description=
