anematodeandDisservin
1a67ccc72e
We did quite a few tests because this is a pretty involved change with unknown scaling behavior, but results are decent. [STC 10+0.1 1th, non-regression](https://tests.stockfishchess.org/tests/live_elo/6941ce3b46f342e1ec210180) ``` LLR: 2.93 (-2.94,2.94) <-1.75,0.25> Total: 83200 W: 21615 L: 21452 D: 40133 Ptnml(0-2): 247, 9064, 22844, 9169, 276 ``` [STC 5+0.05 8th](https://tests.stockfishchess.org/tests/live_elo/693dc38346f342e1ec20f555) ``` LLR: 3.48 (-2.94,2.94) <0.00,2.00> Total: 58536 W: 15067 L: 14688 D: 28781 Ptnml(0-2): 87, 6474, 15781, 6825, 101 ``` [LTC 20+0.2 8th](https://tests.stockfishchess.org/tests/live_elo/693f2afb46f342e1ec20f847) ``` LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 27716 W: 7211 L: 6925 D: 13580 Ptnml(0-2): 8, 2674, 8207, 2962, 7 ``` [LTC 10+0.1 64th](https://tests.stockfishchess.org/tests/live_elo/694003aa46f342e1ec20fac4): ``` LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 16918 W: 4439 L: 4182 D: 8297 Ptnml(0-2): 3, 1493, 5213, 1744, 6 ``` [NUMA test, 5+0.05 256th](https://tests.stockfishchess.org/tests/view/6941ee4e46f342e1ec210203) ``` LLR: 2.95 (-2.94,2.94) <0.00,2.00> Total: 7124 W: 1910 L: 1678 D: 3536 Ptnml(0-2): 0, 560, 2211, 790, 1 ``` [LTC 60+0.6 64th](https://tests.stockfishchess.org/tests/live_elo/6940a85346f342e1ec20fcde): ``` LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 15504 W: 4045 L: 3826 D: 7633 Ptnml(0-2): 0, 1002, 5530, 1219, 1 ``` Bonus (courtesy of Viz): The 1 double kill in this last test was master blundering a cool mate in 3: https://lichess.org/jyNZuRl4 Basically the idea here is to share correction history between threads. That way, T1 can use the correction values produced by T2, which already searched positions with that pawn structure etc., so that T1 can search more efficiently. The table size per thread is about the same, so we shouldn't get a large increase in hash collisions; in fact, I'd expect a lower collision rate overall. Although I came up with and implemented the idea independently, [Caissa](https://github.com/Witek902/Caissa) was the first engine to implement corrhist sharing (and corrhist in the first place) – this idea is not completely novel. The table size is rounded to a power of two. In particular, it's `65536 * nextPowerOfTwo(threadCount)`. That way, the indexing operation becomes an AND of the key bits with a mask, rather than something more expensive (e.g., a `mul_hi64`-style approach or a modulo). The updates are racy, like the TT, but because `entry` is hoisted into a register, there's no risk of writing back a value that's out of the designated range `[-D, D]`. Various attempts at rewriting using atomics led to substantial slowdowns, so we begrudgingly ignored the functions in thread sanitizer, but at some point we'd like to make this better. We allocate one shared correction history per NUMA node, because the penalty associated with crossing nodes is substantial – I get a 40% hit with NPS=4 and 256 threads, which is intolerable. With separate tables per NUMA node I get a 6% penalty for nodes per second, which isn't ideal but apparently compensated for. closes https://github.com/official-stockfish/Stockfish/pull/6478 Bench: 2690604 Co-authored-by: Disservin <disservin.social@gmail.com>
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).