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Strategies for vectorizing the sparse matrix vector product on the CRAY XMP, CRAY 2, and CYBER 205Large, randomly sparse matrix vector products are important in a number of applications in computational chemistry, such as matrix diagonalization and the solution of simultaneous equations. Vectorization of this process is considered for the CRAY XMP, CRAY 2, and CYBER 205, using a matrix of dimension of 20,000 with from 1 percent to 6 percent nonzeros. Efficient scatter/gather capabilities add coding flexibility and yield significant improvements in performance. For the CYBER 205, it is shown that minor changes in the IO can reduce the CPU time by a factor of 50. Similar changes in the CRAY codes make a far smaller improvement.
Document ID
19880023714
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Bauschlicher, Charles W., Jr.
(NASA Ames Research Center Moffett Field, CA, United States)
Partridge, Harry
(NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
August 13, 2013
Publication Date
January 1, 1987
Publication Information
Publication: Journal of Computational Chemistry
Volume: 8
Issue: 5, 19
ISSN: 0192-8651
Subject Category
Computer Programming And Software
Accession Number
88A10941
Distribution Limits
Public
Copyright
Other

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