Processor and method providing an improved matrix storage

Abstract

An adaptive quantization system and method for efficient storage and processing of matrix data is disclosed. The system comprises a processor with circuitry configured to divide a matrix into blocks, assign quantization formats to each block based on content, generate a super-block comprising quantized blocks and associated format information, and store the super-block in memory. The method employs an index to indicate quantization formats, typically using 3 bits per block, and can utilize shared exponents for certain formats. A metadata buffer stores compression information, allowing gradual adoption of compression. The invention optimizes matrix data storage at a fine-grained level, maintains efficient random access, adapts to varying precision requirements within a matrix, and integrates with existing memory hierarchies. This approach significantly improves compression efficiency and processing speed for large-scale matrix operations in fields such as artificial intelligence, machine learning, and high-performance computing.

Dependencies are inferred from the claim text.