mirror of
https://github.com/official-stockfish/Stockfish.git
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Merge branch 'master' into clusterMergeMaster12
fixes minor merge conflicts looks good: Score of cluster vs master: 15 - 1 - 134 [0.547] 150 Elo difference: 32.5 +/- 17.5, LOS: 100.0 %, DrawRatio: 89.3 % for 4 threads against 4x4 threads at 10+0.1s
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@@ -12,7 +12,7 @@ about how to use Stockfish with it.
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The Stockfish engine features two evaluation functions for chess, the classical
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evaluation based on handcrafted terms, and the NNUE evaluation based on efficiently
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updateable neural networks. The classical evaluation runs efficiently on almost all
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updatable neural networks. The classical evaluation runs efficiently on almost all
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CPU architectures, while the NNUE evaluation benefits from the vector
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intrinsics available on most CPUs (sse2, avx2, neon, or similar).
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@@ -24,6 +24,8 @@ 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
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that can be used to compile Stockfish on Unix-like systems.
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@@ -31,17 +33,6 @@ This distribution of Stockfish consists of the following files:
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* a file with the .nnue extension, storing the neural network for the NNUE
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evaluation. Binary distributions will have this file embedded.
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Note: to use the NNUE evaluation, the additional data file with neural network parameters
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needs to be available. Normally, this file is already embedded in the binary or it can be downloaded.
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The filename for the default (recommended) net can be found as the default
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value of the `EvalFile` UCI option, with the format `nn-[SHA256 first 12 digits].nnue`
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(for instance, `nn-c157e0a5755b.nnue`). This file can be downloaded from
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```
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https://tests.stockfishchess.org/api/nn/[filename]
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```
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replacing `[filename]` as needed.
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## UCI options
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Currently, Stockfish has the following UCI options:
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@@ -53,6 +44,9 @@ Currently, Stockfish has the following UCI options:
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* #### Hash
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The size of the hash table in MB. It is recommended to set Hash after setting Threads.
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* #### Clear Hash
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Clear the hash table.
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* #### Ponder
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Let Stockfish ponder its next move while the opponent is thinking.
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@@ -108,8 +102,8 @@ Currently, Stockfish has the following UCI options:
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* #### SyzygyProbeDepth
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Minimum remaining search depth for which a position is probed. Set this option
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to a higher value to probe less agressively if you experience too much slowdown
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(in terms of nps) due to TB probing.
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to a higher value to probe less aggressively if you experience too much slowdown
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(in terms of nps) due to tablebase probing.
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* #### Syzygy50MoveRule
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Disable to let fifty-move rule draws detected by Syzygy tablebase probes count
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@@ -139,42 +133,50 @@ Currently, Stockfish has the following UCI options:
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Tells the engine to use nodes searched instead of wall time to account for
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elapsed time. Useful for engine testing.
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* #### Clear Hash
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Clear the hash table.
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* #### Debug Log File
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Write all communication to and from the engine into a text file.
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## A note on classical and NNUE evaluation
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## A note on classical evaluation versus NNUE evaluation
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Both approaches assign a value to a position that is used in alpha-beta (PVS) search
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to find the best move. The classical evaluation computes this value as a function
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of various chess concepts, handcrafted by experts, tested and tuned using fishtest.
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The NNUE evaluation computes this value with a neural network based on basic
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inputs (e.g. piece positions only). The network is optimized and trained
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on the evalutions of millions of positions at moderate search depth.
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on the evaluations of millions of positions at moderate search depth.
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The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward.
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It can be evaluated efficiently on CPUs, and exploits the fact that only parts
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of the neural network need to be updated after a typical chess move.
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[The nodchip repository](https://github.com/nodchip/Stockfish) provides additional
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tools to train and develop the NNUE networks.
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tools to train and develop the NNUE networks. On CPUs supporting modern vector instructions
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(avx2 and similar), the NNUE evaluation results in much stronger playing strength, even
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if the nodes per second computed by the engine is somewhat lower (roughly 80% of nps
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is typical).
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On CPUs supporting modern vector instructions (avx2 and similar), the NNUE evaluation
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results in stronger playing strength, even if the nodes per second computed by the engine
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is somewhat lower (roughly 60% of nps is typical).
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Notes:
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Note that the NNUE evaluation depends on the Stockfish binary and the network parameter
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file (see EvalFile). Not every parameter file is compatible with a given Stockfish binary.
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The default value of the EvalFile UCI option is the name of a network that is guaranteed
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to be compatible with that binary.
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1) the NNUE evaluation depends on the Stockfish binary and the network parameter
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file (see the EvalFile UCI option). Not every parameter file is compatible with a given
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Stockfish binary, but the default value of the EvalFile UCI option is the name of a network
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that is guaranteed to be compatible with that binary.
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## What to expect from Syzygybases?
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2) to use the NNUE evaluation, the additional data file with neural network parameters
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needs to be available. Normally, this file is already embedded in the binary or it
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can be downloaded. The filename for the default (recommended) net can be found as the default
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value of the `EvalFile` UCI option, with the format `nn-[SHA256 first 12 digits].nnue`
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(for instance, `nn-c157e0a5755b.nnue`). This file can be downloaded from
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```
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https://tests.stockfishchess.org/api/nn/[filename]
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```
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replacing `[filename]` as needed.
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## What to expect from the Syzygy tablebases?
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If the engine is searching a position that is not in the tablebases (e.g.
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a position with 8 pieces), it will access the tablebases during the search.
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If the engine reports a very large score (typically 153.xx), this means
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that it has found a winning line into a tablebase position.
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If the engine reports a very large score (typically 153.xx), this means
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it has found a winning line into a tablebase position.
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If the engine is given a position to search that is in the tablebases, it
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will use the tablebases at the beginning of the search to preselect all
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@@ -182,14 +184,14 @@ good moves, i.e. all moves that preserve the win or preserve the draw while
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taking into account the 50-move rule.
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It will then perform a search only on those moves. **The engine will not move
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immediately**, unless there is only a single good move. **The engine likely
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will not report a mate score even if the position is known to be won.**
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will not report a mate score, even if the position is known to be won.**
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It is therefore clear that this behaviour is not identical to what one might
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be used to with Nalimov tablebases. There are technical reasons for this
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difference, the main technical reason being that Nalimov tablebases use the
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DTM metric (distance-to-mate), while Syzygybases use a variation of the
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DTM metric (distance-to-mate), while the Syzygy tablebases use a variation of the
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DTZ metric (distance-to-zero, zero meaning any move that resets the 50-move
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counter). This special metric is one of the reasons that Syzygybases are
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counter). This special metric is one of the reasons that the Syzygy tablebases are
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more compact than Nalimov tablebases, while still storing all information
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needed for optimal play and in addition being able to take into account
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the 50-move rule.
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@@ -227,8 +229,8 @@ to ```rank 0``` only (e.g. ```srun --input=0 --output=0```).
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Stockfish supports large pages on Linux and Windows. Large pages make
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the hash access more efficient, improving the engine speed, especially
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on large hash sizes. Typical increases are 5..10% in terms of nps, but
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speed increases up to 30% have been measured. The support is
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on large hash sizes. Typical increases are 5..10% in terms of nodes per
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second, but speed increases up to 30% have been measured. The support is
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automatic. Stockfish attempts to use large pages when available and
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will fall back to regular memory allocation when this is not the case.
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@@ -236,17 +238,17 @@ will fall back to regular memory allocation when this is not the case.
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Large page support on Linux is obtained by the Linux kernel
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transparent huge pages functionality. Typically, transparent huge pages
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are already enabled and no configuration is needed.
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are already enabled, and no configuration is needed.
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### Support on Windows
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The use of large pages requires "Lock Pages in Memory" privilege. See
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[Enable the Lock Pages in Memory Option (Windows)](https://docs.microsoft.com/en-us/sql/database-engine/configure-windows/enable-the-lock-pages-in-memory-option-windows)
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on how to enable this privilege. Logout/login may be needed
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afterwards. Due to memory fragmentation, it may not always be
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possible to allocate large pages even when enabled. A reboot
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might alleviate this problem. To determine whether large pages
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are in use, see the engine log.
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on how to enable this privilege, then run [RAMMap](https://docs.microsoft.com/en-us/sysinternals/downloads/rammap)
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to double-check that large pages are used. We suggest that you reboot
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your computer after you have enabled large pages, because long Windows
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sessions suffer from memory fragmentation, which may prevent Stockfish
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from getting large pages: a fresh session is better in this regard.
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## Compiling Stockfish yourself from the sources
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@@ -261,11 +263,11 @@ targets with corresponding descriptions.
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```
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cd src
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make help
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make build ARCH=x86-64-modern
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make net
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make build ARCH=x86-64-modern
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```
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When not using the Makefile to compile (for instance with Microsoft MSVC) you
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When not using the Makefile to compile (for instance, with Microsoft MSVC) you
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need to manually set/unset some switches in the compiler command line; see
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file *types.h* for a quick reference.
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@@ -301,8 +303,9 @@ generic rather than being focused on Stockfish's precise implementation.
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Nevertheless, a helpful resource.
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* The latest source can always be found on [GitHub](https://github.com/official-stockfish/Stockfish).
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Discussions about Stockfish take place in the [FishCooking](https://groups.google.com/forum/#!forum/fishcooking)
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group and engine testing is done on [Fishtest](https://tests.stockfishchess.org/tests).
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Discussions about Stockfish take place these days mainly in the [FishCooking](https://groups.google.com/forum/#!forum/fishcooking)
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group and on the [Stockfish Discord channel](https://discord.gg/nv8gDtt).
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The engine testing is done on [Fishtest](https://tests.stockfishchess.org/tests).
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If you want to help improve Stockfish, please read this [guideline](https://github.com/glinscott/fishtest/wiki/Creating-my-first-test)
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first, where the basics of Stockfish development are explained.
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@@ -310,16 +313,17 @@ first, where the basics of Stockfish development are explained.
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## Terms of use
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Stockfish is free, and distributed under the **GNU General Public License version 3**
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(GPL v3). Essentially, this means that you are free to do almost exactly
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(GPL v3). Essentially, this means you are free to do almost exactly
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what you want with the program, including distributing it among your
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friends, making it available for download from your web site, selling
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friends, making it available for download from your website, selling
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it (either by itself or as part of some bigger software package), or
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using it as the starting point for a software project of your own.
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The only real limitation is that whenever you distribute Stockfish in
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some way, you must always include the full source code, or a pointer
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to where the source code can be found. If you make any changes to the
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source code, these changes must also be made available under the GPL.
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some way, you MUST always include the full source code, or a pointer
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to where the source code can be found, to generate the exact binary
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you are distributing. If you make any changes to the source code,
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these changes must also be made available under the GPL.
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For full details, read the copy of the GPL v3 found in the file named
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*Copying.txt*.
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Reference in New Issue
Block a user