25,161
edits
Changes
no edit summary
=Strong Points=
* Reuses and gets benefits from the very optimized [[Search|search]] function of Stockfish as well as almost all Stockfish's code
* Runs with CPU only, and doesn't require expensive [https://en.wikipedia.org/wiki/Video_card video cards], as well the need for installing drivers and specific libraries. Thus it is much easier to install (compared to engines using [[Neural Networks#Deep|deep]] [[Neural Networks#Convolutional|convolutional neural networks]], such as [[Leela Chess Zero]]) and suitable for almost all modern computers. Using a [[GPU]] is even not practical for that small net - host-device- latency aka. kernel-launch-overhead <ref>[http://www.talkchess.com/forum3/viewtopic.php?f=7&t=74771 AB search with NN on GPU...] by [[Srdja Matovic]], [[CCC]], August 13, 2020 » [[GPU]]</ref> <ref>[https://forums.developer.nvidia.com/t/kernel-launch-latency/62455 kernel launch latency - CUDA / CUDA Programming and bandwidth fromPerformance - NVIDIA Developer Forums] by LukeCuda, June 18, 2018</ref> to a then underemployed GPU are not sufficient for the intended [[Nodes per Second|NPS]] range <ref>[http://www.talkchess.com/forum3/viewtopic.php?f=2&t=74702 stockfish with graphics card] by h1a8, [[CCC]], August 06, 2020</ref>
* Requires much smaller training sets. Some high score networks can be built with the effort of one or a few people within a few days. It doesn't require the massive computing from a supercomputer and/or from community
