Add large page support for NNUE weights and simplify TT mem management

[stockfish] / README.md

diff --git a/README.md b/README.md
index 2cc88bf4279582e28221de619cdd05cc6966ccad..255ebce2afc02ec6b3190e6c2bd9ae578b4b559d 100644 (file)
--- a/README.md
+++ b/README.md
@@ -12,9 +12,9 @@ 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
-updateable neural networks. The classical evaluation runs efficiently on most 64bit
-CPU architectures, while the NNUE evaluation benefits strongly from the vector
-intrinsics available on modern CPUs (avx2 or similar).
+updateable 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).
 
 
 ## Files
@@ -29,10 +29,11 @@ This distribution of Stockfish consists of the following files:
     that can be used to compile Stockfish on Unix-like systems.
 
   * a file with the .nnue extension, storing the neural network for the NNUE 
-    evaluation.
+    evaluation. Binary distributions will have this file embedded.
 
 Note: to use the NNUE evaluation, the additional data file with neural network parameters
-needs to be downloaded. The filename for the default 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
 ```
@@ -61,11 +62,14 @@ Currently, Stockfish has the following UCI options:
 
   * #### Use NNUE
     Toggle between the NNUE and classical evaluation functions. If set to "true",
-    the network parameters must be available to load from file (see also EvalFile).
+    the network parameters must be available to load from file (see also EvalFile),
+    if they are not embedded in the binary.
 
   * #### EvalFile
     The name of the file of the NNUE evaluation parameters. Depending on the GUI the
-    filename should include the full path to the folder/directory that contains the file.
+    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.
@@ -148,7 +152,7 @@ to find the best move. The classical evaluation computes this value as a functio
 of various chess concepts, handcrafted by experts, tested and tuned using fishtest.
 The NNUE evaluation computes this value with a neural network based on basic
 inputs (e.g. piece positions only). The network is optimized and trained
-on the evalutions of millions of positions at moderate search depth.
+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