- * #### Debug Log File
- Write all communication to and from the engine into a text file.
-
-## A note on classical evaluation versus NNUE evaluation
-
-Both approaches assign a value to a position that is used in alpha-beta (PVS) search
-to find the best move. The classical evaluation computes this value as a function
-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 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).
-
-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.
-
-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
-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
-```
-https://tests.stockfishchess.org/api/nn/[filename]
-```
-replacing `[filename]` as needed.
-
-## What to expect from the Syzygy tablebases?
-
-If the engine is searching a position that is not in the tablebases (e.g.
-a position with 8 pieces), it will access the tablebases during the search.
-If the engine reports a very large score (typically 153.xx), this means
-it has found a winning line into a tablebase position.
-
-If the engine is given a position to search that is in the tablebases, it
-will use the tablebases at the beginning of the search to preselect all
-good moves, i.e. all moves that preserve the win or preserve the draw while
-taking into account the 50-move rule.
-It will then perform a search only on those moves. **The engine will not move
-immediately**, unless there is only a single good move. **The engine likely
-will not report a mate score, even if the position is known to be won.**
-
-It is therefore clear that this behaviour is not identical to what one might
-be used to with Nalimov tablebases. There are technical reasons for this
-difference, the main technical reason being that Nalimov tablebases use the
-DTM metric (distance-to-mate), while the Syzygy tablebases use a variation of the
-DTZ metric (distance-to-zero, zero meaning any move that resets the 50-move
-counter). This special metric is one of the reasons that the Syzygy tablebases are
-more compact than Nalimov tablebases, while still storing all information
-needed for optimal play and in addition being able to take into account
-the 50-move rule.
-
-## Large Pages
-
-Stockfish supports large pages on Linux and Windows. Large pages make
-the hash access more efficient, improving the engine speed, especially
-on large hash sizes. Typical increases are 5..10% in terms of nodes per
-second, but speed increases up to 30% have been measured. The support is
-automatic. Stockfish attempts to use large pages when available and
-will fall back to regular memory allocation when this is not the case.
-
-### Support on Linux
-
-Large page support on Linux is obtained by the Linux kernel
-transparent huge pages functionality. Typically, transparent huge pages
-are already enabled, and no configuration is needed.
-
-### Support on Windows
-
-The use of large pages requires "Lock Pages in Memory" privilege. See
-[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)
-on how to enable this privilege, then run [RAMMap](https://docs.microsoft.com/en-us/sysinternals/downloads/rammap)
-to double-check that large pages are used. We suggest that you reboot
-your computer after you have enabled large pages, because long Windows
-sessions suffer from memory fragmentation, which may prevent Stockfish
-from getting large pages: a fresh session is better in this regard.
-
-## Compiling Stockfish yourself from the sources
-
-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.