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romz-pl / matrix-matrix-multiply

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Learn matrix-matrix multiplication optimization in C++ through progressively optimized DGEMM implementations, from naïve algorithms to AVX-512 and blocked kernels.

education benchmark performance algorithms cpp hpc optimization linear-algebra simd matrix-multiplication high-performance-computing intrinsics avx2 computer-architecture avx512 dgemm loop-unrolling cache-optimization numerical-computing cache-blocking
  • Updated Jan 15, 2025
  • C++

yanghuafang / compute-acceleration

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How much of GEMM performance is memory access order? Five CPU variants of the same matrix product, a shared-memory tiled CUDA kernel and a CUDA sum reduction, all measured on one shape. Loop reordering alone is worth 37.9x. C++17, CMake, no dependencies.

benchmark cmake hpc cuda nvidia matrix-multiplication cpp17 gpu-computing gemm memory-hierarchy performance-optimization loop-optimization sanitizers parallel-reduction cache-blocking
  • Updated Sep 1, 2026
  • C++

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