anematodeandJoost VandeVondele
fff35786bf
Passed avx2/bmi2 STC: https://tests.stockfishchess.org/tests/view/69ff99eb9392f0c317213eda LLR: 2.93 (-2.94,2.94) <0.00,2.00> Total: 20992 W: 5469 L: 5192 D: 10331 Ptnml(0-2): 38, 2197, 5751, 2470, 40 Passed avxvnni STC: https://tests.stockfishchess.org/tests/view/6a00022b9392f0c317213f7c LLR: 2.93 (-2.94,2.94) <0.00,2.00> Total: 47328 W: 12328 L: 12009 D: 22991 Ptnml(0-2): 112, 5148, 12847, 5423, 134 Passed NEON STC: https://tests.stockfishchess.org/tests/view/69ff99d69392f0c317213ed8 LLR: 2.96 (-2.94,2.94) <0.00,2.00> Total: 29600 W: 7664 L: 7376 D: 14560 Ptnml(0-2): 48, 3074, 8277, 3344, 57 Passed avx512icl non-regression: https://tests.stockfishchess.org/tests/view/6a002b699392f0c317213f91 LLR: 2.94 (-2.94,2.94) <-1.75,0.25> Total: 90112 W: 23130 L: 22975 D: 44007 Ptnml(0-2): 192, 9939, 24633, 10106, 186 Measurements from vondele (Neoverse V2, armv8-dotprod): ==== master ==== ==== Bench: 2344696 ==== 1 Nodes/second : 280724660 2 Nodes/second : 280647282 3 Nodes/second : 282055192 Average (over 3): 281142378 ==== 50a44640a3 ==== ==== Bench: 2344696 ==== 1 Nodes/second : 284271937 2 Nodes/second : 285638071 3 Nodes/second : 284349426 Average (over 3): 284753144 The patch's benefit is non-uniform and is ~0 for avx512icl unfortunately -- although I think we should be able to find something there.... ## Background/explanation The idea here is to move the non-zero block computation back to the previous layer, and overlap the work better. Then, to avoid trying to emulate compress instructions on targets not supporting them (i.e., everything except for AVX512), we use a `pop_lsb` loop on a bitset enumerating the non-zero blocks, rather than first writing them out as indices. An early AVX2 implementation worked on fishtest (https://tests.stockfishchess.org/tests/view/69c3410534b6988b1e472db4) and linrock demonstrated that it also worked for NEON (https://tests.stockfishchess.org/tests/view/69ce0dc73ddc0eccd617188f). Thanks to him for encouraging me to push this idea over the finish line. To abstract over the particular NNZ representation (bitset or index list), we use `NNZInfo` and `NNZCursor`. The cursor is used to write to one or the other perspective of the NNZ list. I'd appreciate ideas on making the code cleaner/more readable as imo it's still a bit ugly. ## Fixing GCC 15 regression Separately, vondele noticed a regression in ARM performance from GCC 15 caused by suboptimal codegen. See https://discord.com/channels/435943710472011776/813919248455827515/1502837886381461605 for more info, but the easiest fix that I could come up with was inserting a couple `asm` optimization barriers. Single threaded data: ``` average: stockfish.master.13.3 1041619 average: stockfish.master.15.2 999214 average: stockfish.patched.15.2 1031369 ``` There's definitely regressions elsewhere as well, which we shld chase down, but at least this should unblock the arm64 universal binary work. closes https://github.com/official-stockfish/Stockfish/pull/6814 No functional change
Stockfish
A free and strong UCI chess engine.
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Overview
Stockfish is a free and strong UCI chess engine derived from Glaurung 2.1 that analyzes chess positions and computes the optimal moves.
Stockfish does not include a graphical user interface (GUI) that is required to display a chessboard and to make it easy to input moves. These GUIs are developed independently from Stockfish and are available online. Read the documentation for your GUI of choice for information about how to use Stockfish with it.
See also the Stockfish documentation for further usage help.
Files
This distribution of Stockfish consists of the following files:
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README.md, the file you are currently reading.
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Copying.txt, a text file containing the GNU General Public License version 3.
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AUTHORS, a text file with the list of authors for the project.
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src, a subdirectory containing the full source code, including a Makefile that can be used to compile Stockfish on Unix-like systems.
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a file with the .nnue extension, storing the neural network for the NNUE evaluation. Binary distributions will have this file embedded.
Contributing
See Contributing Guide.
Donating hardware
Improving Stockfish requires a massive amount of testing. You can donate your hardware resources by installing the Fishtest Worker and viewing the current tests on Fishtest.
Improving the code
In the chessprogramming wiki, many techniques used in Stockfish are explained with a lot of background information. The section on Stockfish describes many features and techniques used by Stockfish. However, it is generic rather than focused on Stockfish's precise implementation.
The engine testing is done on Fishtest. If you want to help improve Stockfish, please read this guideline first, where the basics of Stockfish development are explained.
Discussions about Stockfish take place these days mainly in the Stockfish Discord server. This is also the best place to ask questions about the codebase and how to improve it.
Compiling Stockfish
Stockfish has support for 32 or 64-bit CPUs, certain hardware instructions, big-endian machines such as Power PC, and other platforms.
On Unix-like systems, it should be easy to compile Stockfish directly from the
source code with the included Makefile in the folder src. In general, it is
recommended to run make help to see a list of make targets with corresponding
descriptions. An example suitable for most Intel and AMD chips:
cd src
make -j profile-build
Detailed compilation instructions for all platforms can be found in our documentation. Our wiki also has information about the UCI commands supported by Stockfish.
Terms of use
Stockfish is free and distributed under the GNU General Public License version 3 (GPL v3). Essentially, this means you are free to do almost exactly what you want with the program, including distributing it among your friends, making it available for download from your website, selling it (either by itself or as part of some bigger software package), or using it as the starting point for a software project of your own.
The only real limitation is that whenever you distribute Stockfish in some way, you MUST always include the license and the full source code (or a pointer to where the source code can be found) to generate the exact binary you are distributing. If you make any changes to the source code, these changes must also be made available under GPL v3.
Acknowledgements
Stockfish uses neural networks trained on data provided by the Leela Chess Zero project, which is made available under the Open Database License (ODbL).