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Advanced Matrix Multiplication Optimization on NVIDIA GPUs

salykova.github.io · published 12 January 2025

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https://github.com/gpu-mode

github.com

https://discord.gg/gpumode

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https://github.com/salykova/sgemm.cu

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https://salykova.github.io/matmul

salykova.github.io

How to Optimize a CUDA Matmul Kernel for cuBLAS-like Performance: a Worklog Read at the source ↗

siboehm.com

https://leimao.github.io/article/CUDA-Matrix-Multiplication-Optimization/

leimao.github.io

https://github.com/Yinghan-Li/YHs_Sample/tree/master/cuda/gemm

github.com

https://github.com/tpoisonooo/how-to-optimize-gemm/tree/master

github.com

https://github.com/NervanaSystems/maxas

github.com

https://github.com/tinygrad/tinygrad

github.com

https://developer.nvidia.com/blog/easy-introduction-cuda-c-and-c/

developer.nvidia.com

https://developer.nvidia.com/blog/how-access-global-memory-efficiently-cuda-c-kernels/

developer.nvidia.com

https://developer.nvidia.com/blog/using-shared-memory-cuda-cc/

developer.nvidia.com

CUDA Pro Tip: Increase Performance with Vectorized Memory Access Read at the source ↗

developer.nvidia.com

https://docs.nvidia.com/deploy/nvml-api/group__nvmlClocksThrottleReasons.html

docs.nvidia.com

https://github.com/NVIDIA/nvbench/blob/main/nvbench/detail/l2flush.cuh

github.com

https://docs.nvidia.com/cuda/parallel-thread-execution/

docs.nvidia.com

https://docs.nvidia.com/cuda/cuda-compiler-driver-nvcc/

docs.nvidia.com

https://docs.nvidia.com/cuda/inline-ptx-assembly/index.html

docs.nvidia.com

https://docs.nvidia.com/cuda/parallel-thread-execution/index.html

docs.nvidia.com

https://www.semanticscholar.org/paper/Strassen%E2%80%99s-Algorithm-Reloaded-on-GPUs-Huang-Yu/d3214da488806bf4c870080fca18a7f3ecba1e99

semanticscholar.org

https://docs.nvidia.com/cuda/cuda-c-programming-guide/

docs.nvidia.com

https://github.com/salykova/sgemm.cu/blob/main/src/kernels/128x128x8.cuh

github.com

https://github.com/salykova/sgemm.cu/blob/main/src/kernels/128x128x8_texld.cuh

github.com

https://github.com/salykova/sgemm.cu/blob/main/src/kernels/128x256x8.cuh

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