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Merge branch 'master' into clusterMergeMaster14

Browse Source 
closes https://github.com/official-stockfish/Stockfish/pull/3980
This commit is contained in:
Joost VandeVondele
2022-04-15 09:27:16 +02:00
parent 80eae02603 19a90b45bc
commit e592dcb8e3
59 changed files with 1344 additions and 1232 deletions
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README.md
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@@ -10,24 +10,28 @@ Cute Chess, eboard, Arena, Sigma Chess, Shredder, Chess Partner or Fritz) in ord
to be used comfortably. Read the documentation for your GUI of choice for information
about how to use Stockfish with it.
The Stockfish engine features two evaluation functions for chess, the classical
evaluation based on handcrafted terms, and the NNUE evaluation based on efficiently
updatable neural networks. The classical evaluation runs efficiently on almost all
CPU architectures, while the NNUE evaluation benefits from the vector
intrinsics available on most CPUs (sse2, avx2, neon, or similar).
The Stockfish engine features two evaluation functions for chess. The efficiently
updatable neural network (NNUE) based evaluation is the default and by far the strongest.
The classical evaluation based on handcrafted terms remains available. The strongest
network is integrated in the binary and downloaded automatically during the build process.
The NNUE evaluation benefits from the vector intrinsics available on most CPUs (sse2,
avx2, neon, or similar).
## Files
This distribution of Stockfish consists of the following files:
* [Readme.md](https://github.com/official-stockfish/Stockfish/blob/master/README.md), the file you are currently reading.
* [Readme.md](https://github.com/official-stockfish/Stockfish/blob/master/README.md),
the file you are currently reading.
* [Copying.txt](https://github.com/official-stockfish/Stockfish/blob/master/Copying.txt), a text file containing the GNU General Public License version 3.
* [Copying.txt](https://github.com/official-stockfish/Stockfish/blob/master/Copying.txt),
a text file containing the GNU General Public License version 3.
* [AUTHORS](https://github.com/official-stockfish/Stockfish/blob/master/AUTHORS), a text file with the list of authors for the project
* [AUTHORS](https://github.com/official-stockfish/Stockfish/blob/master/AUTHORS),
a text file with the list of authors for the project
* [src](https://github.com/official-stockfish/Stockfish/tree/master/src), a subdirectory containing the full source code, including a Makefile
* [src](https://github.com/official-stockfish/Stockfish/tree/master/src),
a subdirectory containing the full source code, including a Makefile
that can be used to compile Stockfish on Unix-like systems.
* a file with the .nnue extension, storing the neural network for the NNUE
@@ -37,7 +41,7 @@ This distribution of Stockfish consists of the following files:
The Universal Chess Interface (UCI) is a standard protocol used to communicate with
a chess engine, and is the recommended way to do so for typical graphical user interfaces
(GUI) or chess tools. Stockfish implements the majority of it options as described
(GUI) or chess tools. Stockfish implements the majority of its options as described
in [the UCI protocol](https://www.shredderchess.com/download/div/uci.zip).
Developers can see the default values for UCI options available in Stockfish by typing
@@ -68,9 +72,9 @@ change them via a chess GUI. This is a list of available UCI options in Stockfis
* #### EvalFile
The name of the file of the NNUE evaluation parameters. Depending on the GUI the
filename might have to include the full path to the folder/directory that contains the file.
Other locations, such as the directory that contains the binary and the working directory,
are also searched.
filename might have to include the full path to the folder/directory that contains
the file. Other locations, such as the directory that contains the binary and the
working directory, are also searched.
* #### UCI_AnalyseMode
An option handled by your GUI.
@@ -103,7 +107,7 @@ change them via a chess GUI. This is a list of available UCI options in Stockfis
Example: `C:\tablebases\wdl345;C:\tablebases\wdl6;D:\tablebases\dtz345;D:\tablebases\dtz6`
It is recommended to store .rtbw files on an SSD. There is no loss in storing
the .rtbz files on a regular HD. It is recommended to verify all md5 checksums
the .rtbz files on a regular HDD. It is recommended to verify all md5 checksums
of the downloaded tablebase files (`md5sum -c checksum.md5`) as corruption will
lead to engine crashes.
@@ -138,8 +142,9 @@ change them via a chess GUI. This is a list of available UCI options in Stockfis
For developers the following non-standard commands might be of interest, mainly useful for debugging:
* #### bench *ttSize threads limit fenFile limitType evalType*
Performs a standard benchmark using various options. The signature of a version (standard node
count) is obtained using all defaults. `bench` is currently `bench 16 1 13 default depth mixed`.
Performs a standard benchmark using various options. The signature of a version
(standard node count) is obtained using all defaults. `bench` is currently
`bench 16 1 13 default depth mixed`.
* #### compiler
Give information about the compiler and environment used for building a binary.
@@ -175,22 +180,27 @@ on the evaluations 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. On CPUs supporting modern vector instructions
(avx2 and similar), the NNUE evaluation results in much stronger playing strength, even
if the nodes per second computed by the engine is somewhat lower (roughly 80% of nps
is typical).
[The nodchip repository](https://github.com/nodchip/Stockfish) provided the first
version of the needed tools to train and develop the NNUE networks. Today, more
advanced training tools are available in
[the nnue-pytorch repository](https://github.com/glinscott/nnue-pytorch/),
while data generation tools are available in
[a dedicated branch](https://github.com/official-stockfish/Stockfish/tree/tools).
On CPUs supporting modern vector instructions (avx2 and similar), the NNUE evaluation
results in much stronger playing strength, even if the nodes per second computed by
the engine is somewhat lower (roughly 80% of nps is typical).
Notes:
1) the NNUE evaluation depends on the Stockfish binary and the network parameter
file (see the EvalFile UCI option). Not every parameter file is compatible with a given
Stockfish binary, but the default value of the EvalFile UCI option is the name of a network
that is guaranteed to be compatible with that binary.
1) the NNUE evaluation depends on the Stockfish binary and the network parameter file
(see the EvalFile UCI option). Not every parameter file is compatible with a given
Stockfish binary, but the default value of the EvalFile UCI option is the name of a
network that is guaranteed to be compatible with that binary.
2) to use the NNUE evaluation, the additional data file with neural network parameters
needs to be available. Normally, this file is already embedded in the binary or it
can be downloaded. The filename for the default (recommended) net can be found as the default
needs to be available. Normally, this file is already embedded in the binary or it can
be downloaded. The filename for the default (recommended) net can be found as the default
value of the `EvalFile` UCI option, with the format `nn-[SHA256 first 12 digits].nnue`
(for instance, `nn-c157e0a5755b.nnue`). This file can be downloaded from
```
@@ -345,10 +355,10 @@ 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 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 the GPL.
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 the GPL v3.
For full details, read the copy of the GPL v3 found in the file named
[*Copying.txt*](https://github.com/official-stockfish/Stockfish/blob/master/Copying.txt).