Tags: Xen0byte/Stockfish
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Stockfish 14 Official release version of Stockfish 14 Bench: 4770936 --- Today, we have the pleasure to announce Stockfish 14. As usual, downloads will be freely available at https://stockfishchess.org The engine is now significantly stronger than just a few months ago, and wins four times more game pairs than it loses against the previous release version [0]. Stockfish 14 is now at least 400 Elo ahead of Stockfish 7, a top engine in 2016 [1]. During the last five years, Stockfish has thus gained about 80 Elo per year. Stockfish 14 evaluates positions more accurately than Stockfish 13 as a result of two major steps forward in defining and training the efficiently updatable neural network (NNUE) that provides the evaluation for positions. First, the collaboration with the Leela Chess Zero team - announced previously [2] - has come to fruition. The LCZero team has provided a collection of billions of positions evaluated by Leela that we have combined with billions of positions evaluated by Stockfish to train the NNUE net that powers Stockfish 14. The fact that we could use and combine these datasets freely was essential for the progress made and demonstrates the power of open source and open data [3]. Second, the architecture of the NNUE network was significantly updated: the new network is not only larger, but more importantly, it deals better with large material imbalances and can specialize for multiple phases of the game [4]. A new project, kick-started by Gary Linscott and Tomasz Sobczyk, led to a GPU accelerated net trainer written in pytorch.[5] This tool allows for training high-quality nets in a couple of hours. Finally, this release features some search refinements, minor bug fixes and additional improvements. For example, Stockfish is now about 90 Elo stronger for chess960 (Fischer random chess) at short time control. The Stockfish project builds on a thriving community of enthusiasts (thanks everybody!) that contribute their expertise, time, and resources to build a free and open-source chess engine that is robust, widely available, and very strong. We invite our chess fans to join the fishtest testing framework and programmers to contribute to the project on github [6]. Stay safe and enjoy chess! The Stockfish team [0] https://tests.stockfishchess.org/tests/view/60dae5363beab81350aca077 [1] https://nextchessmove.com/dev-builds [2] https://stockfishchess.org/blog/2021/stockfish-13/ [3] https://lczero.org/blog/2021/06/the-importance-of-open-data/ [4] official-stockfish@e8d64af1 [5] https://github.com/glinscott/nnue-pytorch/ [6] https://stockfishchess.org/get-involved/
Stockfish 13 Official release version of Stockfish 13 Bench: 3766422 ----- It is our pleasure to release Stockfish 13 to chess fans worldwide. As usual, downloads are freely available at https://stockfishchess.org The Stockfish project builds on a thriving community of enthusiasts who contribute their expertise, time, and resources to build a free and open-source chess engine that is robust, widely available, and very strong. We would like to thank them all! The good news first: from now on, our users can expect more frequent high-quality releases of Stockfish! Sadly, this decision has been triggered by the start of sales of the Fat Fritz 2 engine by ChessBase, which is a copy of a very recent development version of Stockfish with minor modifications. We refer to our statement on Fat Fritz 2[1] and a community blog[2] for further information. This version of Stockfish is significantly stronger than any of its predecessors. Stockfish 13 outperforms Stockfish 12 by at least 35 Elo[3]. When playing against a one-year-old Stockfish, it wins 60 times more game pairs than it loses[4]. This release features an NNUE network retrained on billions of positions, much faster network evaluation code, and significantly improved search heuristics, as well as additional evaluation tweaks. In the course of its development, this version has won the superfinals of the TCEC Season 19 and TCEC Season 20. Going forward, the Leela Chess Zero and Stockfish teams will join forces to demonstrate our commitment to open source chess engines and training tools, and open data. We are convinced that our free and open-source chess engines serve the chess community very well. Stay safe and enjoy chess! The Stockfish team [1] https://blog.stockfishchess.org/post/643239805544792064/statement-on-fat-fritz-2 [2] https://lichess.org/blog/YCvy7xMAACIA8007/fat-fritz-2-is-a-rip-off [3] https://tests.stockfishchess.org/tests/view/602bcccf7f517a561bc49b11 [4] https://tests.stockfishchess.org/tests/view/600fbb9c735dd7f0f0352d59
Stockfish 12 Official release version of Stockfish 12 Bench: 3624569 ----------------------- It is our pleasure to release Stockfish 12 to users world-wide Downloads will be freely available at https://stockfishchess.org/download/ This version 12 of Stockfish plays significantly stronger than any of its predecessors. In a match against Stockfish 11, Stockfish 12 will typically win at least ten times more game pairs than it loses. This jump in strength, visible in regular progression tests during development[1], results from the introduction of an efficiently updatable neural network (NNUE) for the evaluation in Stockfish[2], and associated tuning of the engine as a whole. The concept of the NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. Stockfish remains a CPU-only engine, since the NNUE networks can be very efficiently evaluated on CPUs. The recommended parameters of the NNUE network are embedded in distributed binaries, and Stockfish will use NNUE by default. Both the NNUE and the classical evaluations are available, and can be used to assign values to positions that are later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evaluations of millions of positions. The Stockfish project builds on a thriving community of enthusiasts that contribute their expertise, time, and resources to build a free and open source chess engine that is robust, widely available, and very strong. We invite chess fans to join the fishtest testing framework and programmers to contribute on github[3]. Stay safe and enjoy chess! The Stockfish team [1] https://github.com/glinscott/fishtest/wiki/Regression-Tests [2] official-stockfish@84f3e86 [3] https://stockfishchess.org/get-involved/
Add NNUE evaluation This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish. Both the NNUE and the classical evaluations are available, and can be used to assign a value to a position that is later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evalutions of millions of positions at moderate search depth. The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. It can be evaluated efficiently on CPUs, and exploits the fact that only parts of the neural network need to be updated after a typical chess move. [The nodchip repository](https://github.com/nodchip/Stockfish) provides additional tools to train and develop the NNUE networks. This patch is the result of contributions of various authors, from various communities, including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather, rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler, dorzechowski, and vondele. This new evaluation needed various changes to fishtest and the corresponding infrastructure, for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged. The first networks have been provided by gekkehenker and sergiovieri, with the latter net (nn-97f742aaefcd.nnue) being the current default. The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option, provided the `EvalFile` option points the the network file (depending on the GUI, with full path). The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest: 60000 @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c ELO: 92.77 +-2.1 (95%) LOS: 100.0% Total: 60000 W: 24193 L: 8543 D: 27264 Ptnml(0-2): 609, 3850, 9708, 10948, 4885 40000 @ 20+0.2 th 8 https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58 ELO: 89.47 +-2.0 (95%) LOS: 100.0% Total: 40000 W: 12756 L: 2677 D: 24567 Ptnml(0-2): 74, 1583, 8550, 7776, 2017 At the same time, the impact on the classical evaluation remains minimal, causing no significant regression: sprt @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b LLR: 2.94 (-2.94,2.94) {-6.00,-4.00} Total: 34936 W: 6502 L: 6825 D: 21609 Ptnml(0-2): 571, 4082, 8434, 3861, 520 sprt @ 60+0.6 th 1 https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d LLR: 2.93 (-2.94,2.94) {-6.00,-4.00} Total: 10088 W: 1232 L: 1265 D: 7591 Ptnml(0-2): 49, 914, 3170, 843, 68 The needed networks can be found at https://tests.stockfishchess.org/nns It is recommended to use the default one as indicated by the `EvalFile` UCI option. Guidelines for testing new nets can be found at https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests Integration has been discussed in various issues: official-stockfish#2823 official-stockfish#2728 The integration branch will be closed after the merge: official-stockfish#2825 https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip closes official-stockfish#2912 This will be an exciting time for computer chess, looking forward to seeing the evolution of this approach. Bench: 4746616
Tweak cutnode reduction
Less reduction for second move at non-check CUT node with depth <= 10.
STC:
LLR: 2.94 (-2.94,2.94) {-0.50,1.50}
Total: 38680 W: 7490 L: 7245 D: 23945
Ptnml(0-2): 643, 4441, 8967, 4606, 683
https://tests.stockfishchess.org/tests/view/5f21e1782f7e63962b99f451
LTC:
LLR: 2.95 (-2.94,2.94) {0.25,1.75}
Total: 71976 W: 9003 L: 8636 D: 54337
Ptnml(0-2): 440, 6414, 21972, 6663, 499
https://tests.stockfishchess.org/tests/view/5f2245762f7e63962b99f4bd
closes official-stockfish#2868
Bench: 4746616
Stockfish 11 Official release version of Stockfish 11. Bench: 5156767 ----------------------- It is our pleasure to release Stockfish 11 to our fans and supporters. Downloads are freely available at http://stockfishchess.org/download/ This version 11 of Stockfish is 50 Elo stronger than the last version, and 150 Elo stronger than the version which famously lost a match to AlphaZero two years ago. This makes Stockfish the strongest chess engine running on your smartphone or normal desktop PC, and we estimate that on a modern four cores CPU, Stockfish 11 could give 1:1000 time odds to the human chess champion having classical time control, and be on par with him. More specific data, including nice cumulative curves for the progression of Stockfish strength over the last seven years, can be found on [our progression page][1], at [Stefan Pohl site][2] or at [NextChessMove][3]. In October 2019 Stockfish has regained its crown in the TCEC competition, beating in the superfinal of season 16 an evolution of the neural-network engine Leela that had won the previous season. This clash of style between an alpha-beta and an neural-network engine produced spectacular chess as always, with Stockfish [emerging victorious this time][0]. Compared to Stockfish 10, we have made hundreds of improvements to the [codebase][4], from the evaluation function (improvements in king attacks, middlegame/endgame transitions, and many more) to the search algorithm (some innovative coordination methods for the searching threads, better pruning of unsound tactical lines, etc), and fixed a couple of bugs en passant. Our testing framework [Fishtest][5] has also seen its share of improvements to continue propelling Stockfish forward. Along with a lot of small enhancements, Fishtest has switched to new SPRT bounds to increase the chance of catching Elo gainers, along with a new testing book and the use of pentanomial statistics to be more resource-efficient. Overall the Stockfish project is an example of open-source at its best, as its buzzing community of programmers sharing ideas and daily reviewing their colleagues' patches proves to be an ideal form to develop innovative ideas for chess programming, while the mathematical accuracy of the testing framework allows us an unparalleled level of quality control for each patch we put in the engine. If you wish, you too can help our ongoing efforts to keep improving it, just [get involved][6] :-) Stockfish is also special in that every chess fan, even if not a programmer, [can easily help][7] the team to improve the engine by connecting their PC to Fishtest and let it play some games in the background to test new patches. Individual contributions vary from 1 to 32 cores, but this year Bojun Guo made it a little bit special by plugging a whole data center during the whole year: it was a vertiginous experience to see Fishtest spikes with 17466 cores connected playing [25600 games/minute][8]. Thanks Guo! The Stockfish team [0]: <http://mytcecexperience.blogspot.com/2019/10/season-16-superfinal-games-91-100.html> [1]: <https://github.com/glinscott/fishtest/wiki/Regression-Tests> [2]: <https://www.sp-cc.de/index.htm> [3]: <https://nextchessmove.com/dev-builds> [4]: <https://github.com/official-stockfish/Stockfish> [5]: <https://tests.stockfishchess.org/tests> [6]: <https://stockfishchess.org/get-involved/> [7]: <https://github.com/glinscott/fishtest/wiki> [8]: <https://groups.google.com/forum/?fromgroups=#!topic/fishcooking/lebEmG5vgng%5B1-25%5D>
Stockfish 10 Official release version of Stockfish 10. This is also the 10th anniversary version of the Stockfish project, which started exactly ten years ago! I wish to extend a huge thank you to all contributors and authors in our amazing community :-) Bench: 3939338
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