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Author and maintainer: https://github.com/katursis
Post #15630
733
#cuda
DeepGEMM is a high-performance library that speeds up matrix calculations for large language models using NVIDIA GPUs. It combines key computation tools—including FP8 and FP4 matrix operations, expert systems (MoE), and attention scoring—into one efficient CUDA codebase. All kernels compile automatically at runtime without requiring manual CUDA setup during installation. The benefit to you is faster AI model training and inference: DeepGEMM's performance matches or exceeds specialized libraries across different matrix sizes, achieving up to 1550 TFLOPS on high-end GPUs, while remaining simple and accessible for learning GPU optimization techniques.
https://github.com/deepseek-ai/DeepGEMM
GitHub GitHub - deepseek-ai/DeepGEMM: DeepGEMM: clean and efficient BLAS kernel library on GPU DeepGEMM: clean and efficient BLAS kernel library on GPU - deepseek-ai/DeepGEMM DeepGEMM is a high-performance library that speeds up matrix calculations for large language models using NVIDIA GPUs. It combines key computation tools—including FP8 and FP4 matrix operations, expert systems (MoE), and attention scoring—into one efficient CUDA codebase. All kernels compile automatically at runtime without requiring manual CUDA setup during installation. The benefit to you is faster AI model training and inference: DeepGEMM's performance matches or exceeds specialized libraries across different matrix sizes, achieving up to 1550 TFLOPS on high-end GPUs, while remaining simple and accessible for learning GPU optimization techniques.
https://github.com/deepseek-ai/DeepGEMM
