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
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
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.
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
+[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).
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
+some way, you MUST always include the license, 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.
+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).
projects / stockfish / blobdiff