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Sparse matrix–vector multiplication

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Sparse matrix-vector multiplication (SpMV) of the form is a widely used computational kernel existing in many scientific applications. The input matrix is sparse. The input vector and the output vector are dense. In the case of a repeated operation involving the same input matrix but possibly changing numerical values of its elements, can be preprocessed to reduce both the parallel and sequential run time of the SpMV kernel.[1]

References

  1. ^ "Hypergraph Partitioning Based Models and Methods for Exploiting Cache Locality in Sparse Matrix-Vector Multiplication". Retrieved 13 April 2014.