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Statements

Subject Item
dbr:Computational_complexity_of_matrix_multiplication
dbo:wikiPageWikiLink
dbr:Sparse_matrix–vector_multiplication
Subject Item
dbr:Conjugate_gradient_method
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dbr:Sparse_matrix–vector_multiplication
Subject Item
dbr:Matrix_multiplication_algorithm
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dbr:Sparse_matrix–vector_multiplication
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dbr:Sparse_matrix–vector_multiplication
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dbr:Sparse_matrix–vector_multiplication
Subject Item
dbr:Sparse_matrix–vector_multiplication
rdfs:label
Sparse matrix–vector multiplication
rdfs:comment
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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dbc:Sparse_matrices
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1082898804
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dbr:General-purpose_computing_on_graphics_processing_units dbr:Compute_kernel dbc:Sparse_matrices dbr:Matrix–vector_multiplication dbr:Sparse_matrix
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dbo:abstract
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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wikipedia-en:Sparse_matrix–vector_multiplication?oldid=1082898804&ns=0
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990
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wikipedia-en:Sparse_matrix–vector_multiplication
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wikipedia-en:Sparse_matrix–vector_multiplication
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dbr:Sparse_matrix–vector_multiplication