A high performance algorithm using pre-processing for the sparse matrix-vector multiplication

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...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Agarwal, R.C., Gustavson, F.G., Zubair, M.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Application software Costs Counting circuits Data mining Data structures Feature extraction Iterative algorithms Sorting Sparse matrices Testing
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