Difference between revisions of "Stockfish NNUE"

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* [http://www.talkchess.com/forum3/viewtopic.php?f=2&t=74666 SF NNUE Problem] by Stephen Ham, [[CCC]], August 03, 2020
 
* [http://www.talkchess.com/forum3/viewtopic.php?f=2&t=74666 SF NNUE Problem] by Stephen Ham, [[CCC]], August 03, 2020
 
* <span id="Continue"></span>[http://www.talkchess.com/forum3/viewtopic.php?f=7&t=74531&start=8 Re: NNUE accessible explanation] by [[Jonathan Rosenthal]], [[CCC]], August 03, 2020 » [[#NNUEaccExp|NNUE accessible explanation]]
 
* <span id="Continue"></span>[http://www.talkchess.com/forum3/viewtopic.php?f=7&t=74531&start=8 Re: NNUE accessible explanation] by [[Jonathan Rosenthal]], [[CCC]], August 03, 2020 » [[#NNUEaccExp|NNUE accessible explanation]]
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* [http://www.talkchess.com/forum3/viewtopic.php?f=2&t=74683 Is this SF NN almost like 20 MB book?] by [[Jouni Uski]], [[CCC]], August 04, 2020
  
 
=External Links=  
 
=External Links=  
 
==Chess Engine==
 
==Chess Engine==
 
* [http://yaneuraou.yaneu.com/2020/06/19/stockfish-nnue-the-complete-guide/ Stockfish NNUE – The Complete Guide], June 19, 2020 (Japanese and English)
 
* [http://yaneuraou.yaneu.com/2020/06/19/stockfish-nnue-the-complete-guide/ Stockfish NNUE – The Complete Guide], June 19, 2020 (Japanese and English)
* [https://github.com/nodchip/Stockfish GitHub - nodchip/Stockfish: UCI chess engine] by [[Nodchip]]
+
* [https://github.com/nodchip/Stockfish GitHub - nodchip/Stockfish: UCI chess engine] by [[Hisayori Noda|Nodchip]]
 
* [https://github.com/joergoster/Stockfish-NNUE GitHub - joergoster/Stockfish-NNUE: UCI Chess engine Stockfish with an Efficiently Updatable Neural-Network-based evaluation function] hosted by [[Jörg Oster]]
 
* [https://github.com/joergoster/Stockfish-NNUE GitHub - joergoster/Stockfish-NNUE: UCI Chess engine Stockfish with an Efficiently Updatable Neural-Network-based evaluation function] hosted by [[Jörg Oster]]
 
* [https://github.com/FireFather/sf-nnue GitHub - FireFather/sf-nnue: Stockfish NNUE (efficiently updateable neural network)] by [[Norman Schmidt]]
 
* [https://github.com/FireFather/sf-nnue GitHub - FireFather/sf-nnue: Stockfish NNUE (efficiently updateable neural network)] by [[Norman Schmidt]]

Revision as of 21:07, 4 August 2020

Home * Engines * Stockfish * NNUE

Stockfish NNUE Logo [1]

Stockfish NNUE,
a Stockfish branch by Hisayori Noda aka Nodchip, which uses Efficiently Updatable Neural Networks - stylized as ƎUИИ or reversed as NNUE - to replace its standard evaluation. NNUE, introduced in 2018 by Yu Nasu [2], were previously successfully applied in Shogi evaluation functions embedded in a Stockfish based search [3], such as YaneuraOu [4], and Kristallweizen-kai [5]. In 2019, Nodchip incorporated NNUE into Stockfish 10 - as a proof of concept, and with the intention to give something back to the Stockfish community [6]. After support and announcements by Henk Drost in May 2020 [7] and subsequent enhancements, Stockfish NNUE was established and recognized. In summer 2020, with more people involved in testing and training, the computer chess community bursts out enthusiastically due to its rapidly raising playing strength with different networks trained using a mixture of supervised and reinforcement learning methods. Despite the approximately halved search speed, Stockfish NNUE seemingly became stronger than its original [8]. In July 2020, the playing code of NNUE is put into the official Stockfish repository as a branch for further development and examination. However, the training code still remains in Nodchip's repository [9] [10].

NNUE Structure

The neural network consists of four layers. The input layer is heavily overparametrized, feeding in the board representation for all king placements per side. The efficiency of NNUE is due to incremental update of the input layer outputs in make and unmake move, where only a tiny fraction of its neurons need to be considered [11]. The remaining three layers with 256x2x32-32x32-32x1 neurons are computational less expensive, best calculated using appropriate SIMD instructions performing fast 16-bit integer arithmetic, like SSE2 or AVX2 on x86-64, or if available, AVX-512.

StockfishNNUELayers.png

NNUE layers in action [12]

Strong Points

  • Reuses and gets benefits from the very optimized search function of Stockfish as well as almost all Stockfish's code
  • Runs with CPU only, doesn't require expensive video cards, and the need for installing video drivers and specific libraries, thus it becomes much easier to install (compare with other NN engines such as Leela Chess Zero) for users and can run with almost all modern computers
  • 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

See also

Forum Posts

2020 ...

January ...

July

Re: NNUE accessible explanation by Jonathan Rosenthal, CCC, July 23, 2020
Re: NNUE accessible explanation by Jonathan Rosenthal, CCC, July 24, 2020
Re: NNUE accessible explanation by Jonathan Rosenthal, CCC, August 03, 2020

August

External Links

Chess Engine

Misc

Hiromi Uehara, Martin Valihora, Tony Grey, David Fiuczynski

References

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