Sparse matrix–vector multiplication

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

References

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^ Hypergraph Partitioning Based Models and Methods for Exploiting Cache Locality in Sparse Matrix-Vector Multiplication Read More: http://epubs.siam.org/doi/abs/10.1137/100813956

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[2] Hypergraph Partitioning Based Models and Methods for Exploiting Cache Locality in Sparse Matrix-Vector Multiplication Read More: http://epubs.siam.org/doi/abs/10.1137/100813956

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