Paper Info
Title
Sparse matrix vector multiplication techniques on the IBM 3090 VF
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.
Year
DOI
Venue
1991
10.1016/S0167-8191(05)80007-9
Parallel Computing
Keywords
Field
DocType
harwell-boeing collection,test matrix,execution rate,ibm 3090 vf,timing results,storage requirement,multiply-and-add compound instruction,sparse storage techniques,sparse matrices,fortran programming technique,matrix vector multiplications,sparse matrix vector multiplication,outer loop vectorization,vector itpack storage scheme,sparse matrix
Linear algebra,Sparse matrix-vector multiplication,Matrix (mathematics),Computer science,Parallel computing,Vectorization (mathematics),Fortran,Theoretical computer science,Numerical analysis,Matrix multiplication,Sparse matrix
Journal
Volume
Issue
ISSN
17
12
Parallel Computing
Citations 
PageRank 
References 
3
1.49
8
Authors
1
Name
Order
Citations
PageRank
Alexander Peters162.99