Storing Chess Positions in 26 Bytes

A technical guide has outlined a method for storing a complete chess position using only 26 bytes. This represents a significant optimization compared to standard data structures, which often consume significantly more memory. The technique relies on bit-level manipulation to pack all necessary game state information into a compact format.

The breakdown of the 26 bytes is precise. Six bytes are dedicated to the board state, representing the 64 squares. One byte handles the active player, while another manages castling rights. A single byte is also used for the en passant target square. The remaining bytes store the halfmove clock and fullmove number. This efficiency is vital for chess engines that perform millions of calculations per second, where memory access speeds and cache utilization are critical performance factors.

The core of the method lies in the specific allocation of memory for each component of a chess position. To store the location of pieces on the board, the method uses 6 bytes. Since there are 64 squares, and 6 bits are required to represent the 12 unique piece types (plus empty), the total bit requirement is 384 bits. However, the article suggests a more optimized approach using 6 bytes (48 bits) per square, or rather, a bitboard approach where pieces are tracked by type. The specific implementation details suggest using 6 bytes to represent the board state efficiently.

Additional critical game state data is stored in the remaining bytes:

• 1 Byte: Stores the active player (White or Black).
• 1 Byte: Encodes castling rights (Kingside/Queenside for both players).
• 1 Byte: Represents the en passant target square, if available.
• 2 Bytes: Allocated for the halfmove clock and fullmove number.

This structure ensures that every aspect of the game state is captured without wasting space.

The efficiency of this storage method is achieved through bit-level magic. Instead of using standard integer types that often occupy 32 or 64 bits regardless of the value stored, this approach packs data tightly. For example, castling rights only require 4 bits (one for each side), but storing them in a standard byte allows for future expansion or simpler alignment. The 'magic' refers to the bitwise operations used to read and write these values.

By using bitwise AND, OR, and XOR operations, a chess engine can quickly check or update specific flags within the byte. This avoids the overhead of accessing larger memory structures. For the board representation, bitboards are often used, where each bit corresponds to a square. While a full bitboard for all pieces requires 64 bits (8 bytes) per piece type, the article suggests a hybrid approach to fit the entire position into the 26-byte constraint.

Memory optimization is critical for chess engines. During a search, an engine generates millions of positions. If each position takes up excessive memory, the engine's cache performance degrades, leading to slower move calculation. Storing positions in just 26 bytes allows the engine to keep more nodes in the CPU cache, significantly speeding up the search depth.

Furthermore, this compact format benefits transposition tables. These tables store previously evaluated positions to avoid redundant calculations. With smaller entry sizes, the engine can store more entries in the same amount of RAM, increasing the hit rate and overall playing strength. This technique is a standard practice in high-level engine development.

While the concept is mathematically sound, implementing this storage requires careful handling of endianness and data alignment. Developers must ensure that bitwise operations are portable across different architectures. The use of bit-level magic often involves precomputed tables or specific compiler intrinsics to ensure maximum speed.

The method described provides a blueprint for developers looking to reduce the memory footprint of their chess applications. By adhering to this 26-byte standard, developers can ensure their engines remain competitive in terms of speed and efficiency.