✳flâneur — a map of the web's best reading

Learning CUDA by optimizing matrix-vector multiplication (SGEMV) for cuBLAS-like performance - A worklog | Maharshi's blog

maharshi.bearblog.dev · 3,748 words · saved by 1 readers

Learning CUDA by optimizing matrix-vector multiplication (SGEMV) for cuBLAS-like performance

Learning CUDA by optimizing matrix-vector multiplication (SGEMV) for cuBLAS-like performance - A worklog – Maharshi's blog Learning CUDA by optimizing matrix-vector multiplication (SGEMV) for cuBLAS-like performance - A worklog 18 Jan, 2025 Matrix-vector multiplication is a foundational operation in linear algebra, where a matrix transforms an input vector into an output vector. This operation basically powers numerous fields including computer science and deep learning. Optimizing matrix-vector multiplication, especially in the context of GPU programming and CUDA can help us learn many new th

Explore this link on the map →

related reading