Efficiently updatable neural network
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An efficiently updatable neural network (NNUE, a Japanese wordplay on
NNUE was invented by Yu Nasu and introduced to computer shogi in 2018.[4][5] On 6 August 2020, NNUE was for the first time ported to a chess engine, Stockfish 12.[6][7] Since 2021, all of the top rated classical chess engines such as Komodo Dragon have an NNUE implementation to remain competitive.
NNUE runs efficiently on central processing units without a requirement for a graphics processing unit (GPU).
The neural network used for the original 2018 computer shogi implementation consists of four weight layers: W1 (16-bit integers) and W2, W3 and W4 (8-bit). It has 4 fully-connected layers, ReLU activation functions, and outputs a single number, being the score of the board.
W1 encoded the king's position and therefore this layer needed only to be re-evaluated once the king moved. It used
See also
- elmo (shogi engine)
- Stockfish chess engine- The chapter about NNUE features a visualization of NNUE.
- List of chess software
References
- ^ Gary Linscott (April 30, 2021). "NNUE". Retrieved December 12, 2020.
- ^ "Stockfish 12". Stockfish Blog. Retrieved 19 October 2020.
- ^ "Stockfish - Chessprogramming wiki". www.chessprogramming.org. Retrieved 2020-08-18.
- ^ a b Yu Nasu (April 28, 2018). "Efficiently Updatable Neural-Network-based Evaluation Function for computer Shogi" (PDF) (in Japanese).
- ^ Yu Nasu (April 28, 2018). "Efficiently Updatable Neural-Network-based Evaluation Function for computer Shogi (Unofficial English Translation)" (PDF).
- ^ "Introducing NNUE Evaluation". 6 August 2020.
- ^ Joost VandeVondele (July 25, 2020). "official-stockfish / Stockfish, NNUE merge".
External links
- NNUE on the Chess Programming Wiki.
- NNUE evaluation functions for computer shogi on github.com