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. 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.

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enSparse 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.
Has abstract
enSparse 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.
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Sparse matrix–vector multiplication
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enSparse matrix–vector multiplication
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Category:Sparse matrices
Compute kernel
General-purpose computing on graphics processing units
Matrix–vector multiplication
Sparse matrix
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Q16935558
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Category:Sparse matrices
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Sparse matrix–vector multiplication?oldid=1082898804&ns=0
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