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Awesome GitHub RepositoriesMemory Layout Optimizations
Techniques for rearranging data structures to improve cache locality and memory access patterns.
Distinguishing note: Focuses on weight permutation for memory alignment.
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Awesome Memory Layout Optimizations GitHub Repositories
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- microsoft/BitNet
microsoft/BitNet
28,521View on GitHubBitNet is a quantized inference engine designed to execute highly compressed language models by performing arithmetic on low-precision, bit-level weight data. It functions as a model optimization toolkit and a high-performance kernel library, enabling the execution of large language models on consumer hardware by reducing memory footprints and increasing processing speeds. The project distinguishes itself through hardware-specific kernel optimizations that leverage native processor instructions to accelerate matrix multiplication. By utilizing packed integer arithmetic and memory-aligned weig
Rearranges model data structures to optimize cache locality and increase throughput.
Python
