Strategies for vectorizing the sparse matrix vector product on the CRAY XMP, CRAY 2, and CYBER 205
✍ Scribed by Charles W. Bauschlicher Jr.; Harry Partridge
- Publisher
- John Wiley and Sons
- Year
- 1987
- Tongue
- English
- Weight
- 823 KB
- Volume
- 8
- Category
- Article
- ISSN
- 0192-8651
No coin nor oath required. For personal study only.
✦ Synopsis
Large 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% to 6% nonzeros. Efficient SCATTEWGATHER capabilities add coding flexibility and yield significant improvements in performance. For the CYBER 205, it is shown that minor changes in the I 0 can reduce the CPU time by a factor of 50. Similar changes in the CRAY codes make a far smaller improvement.