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Awesome GitHub RepositoriesLayer-Level Performance Benchmarking
Tools for measuring the execution latency and resource overhead of individual model layers.
Distinct from Deep Learning Optimization: Focuses on measuring individual building blocks rather than overall model optimization
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Awesome Layer-Level Performance Benchmarking GitHub Repositories
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- facebookresearch/xformers
facebookresearch/xformers
10,506Ver en GitHubxformers is a collection of specialized toolsets for fused GPU operators, sparse attention mechanisms, modular transformer components, and performance benchmarking. It provides a library of optimized and interoperable building blocks used to construct and experiment with transformer architectures. The project features a fused CUDA operator library that combines common layers into single GPU operations to increase throughput. It includes a sparse attention framework and memory-efficient attention kernels that utilize tiling strategies and structured sparsity patterns to reduce computational ov
Provides tools for comparing the speed and memory overhead of individual model layers to guide optimization.
Python
