A high performance algorithm using pre-processing for the sparse matrix-vector multiplication
Published in Conference on High Performance Computing (Supercomputing) • Dec 1, 1992
NobleIDNI1P02W35R04S00
Authors:,,
R. C. Agarwal
Fred G. Gustavson
Mohammad Zubair
Abstract
The authors propose a feature-extraction-based algorithm (FEBA) for sparse matrix-vector multiplication. The key idea of FEBA is to exploit any regular structure present in the sparse matrix by extracting it and processing it separately. The order in which these structures are extracted is determine...
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