Implementation of iterative methods for large sparse nonsymmetric linear systems on a parallel vector machine
Journal Article
·
· International Journal of Supercomputer Applications; (United States)
- Dept. of Computer Science, Univ. of Minnesota, Minneapolis, MN (US)
This paper reports on the restructure of three outstanding iterative methods for large space nonsymmetric linear systems. These methods are CGS (conjugate gradient squared), CRS (conjugate residual squared), and Orthomin(k). The restructured methods are more suitable for vector and parallel processing. The authors implemented these methods on a parallel vector system. The linear systems for the numerical tests are obtained from discretizing four two- dimensional elliptic partial differential equations by finite difference and finite element methods. A vectorizable and parallelizable version of incomplete LU preconditioning is used. The authors restructured the subroutines to enhance the data locality in vector machines with storage hierarchy. Speedup was measured for multitasking by four processors.
- Sponsoring Organization:
- NSF; National Science Foundation, Washington, DC (United States)
- OSTI ID:
- 5001594
- Journal Information:
- International Journal of Supercomputer Applications; (United States), Journal Name: International Journal of Supercomputer Applications; (United States) Vol. 4:4; ISSN 0890-2720; ISSN IJSAE
- Country of Publication:
- United States
- Language:
- English
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