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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. The input vector x and the output vector y are dense. In the case of a repeated y = Ax operation involving the same input matrix A but possibly changing numerical values of its elements, A can be preprocessed to reduce both the parallel and sequential run time of the SpMV kernel.

See also

• Matrix–vector multiplication
• General-purpose computing on graphics processing units#Kernels

References

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

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