Learn matrix-matrix multiplication optimization in C++ through progressively optimized DGEMM implementations, from naïve algorithms to AVX-512 and blocked kernels.
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Updated
Jan 15, 2025 - C++
Learn matrix-matrix multiplication optimization in C++ through progressively optimized DGEMM implementations, from naïve algorithms to AVX-512 and blocked kernels.
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.
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