Sparse matrix vector multiplication techniques on the IBM 3090 VF

Authors:
Alexander Peters
Affiliations:
-
Venue:
Parallel Computing
Year:
1991

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Abstract

This article demonstrates the benefits of applying Fortran programming techniques based on outer loop vectorization and the multiply-and-add compound instruction to the implementation of several sparse matrix vector multiplication algorithms on the IBM 3090 VF. The discussed algorithms use the scalar and vector ITPACK storage schemes and some variants of them. Their performance is analysed by comparing the execution rates and the storage requirements for several test matrices from the Harwell-Boeing collection.