A scalable 2-D parallel sparse solver
Conference
·
OSTI ID:125546
- Iowa State Univ., Ames, IA (United States)
Scalability beyond a small number of processors, typically 32 or less, is known to be a problem for existing parallel general sparse (PGS) direct solvers. This paper presents a parallel general sparse PGS direct solver for general sparse linear systems on distributed memory machines. The algorithm is based on the well-known sequential sparse algorithm Y12M. To achieve efficient parallelization, a 2-D scattered decomposition of the sparse matrix is used. The proposed algorithm is more scalable than existing parallel sparse direct solvers. Its scalability is evaluated on a 256 processor nCUBE2s machine using Boeing/Harwell benchmark matrices.
- OSTI ID:
- 125546
- Report Number(s):
- CONF-950212-; TRN: 95:005768-0091
- Resource Relation:
- Conference: 7. Society for Industrial and Applied Mathematics (SIAM) conference on parallel processing for scientific computing, San Francisco, CA (United States), 15-17 Feb 1995; Other Information: PBD: 1995; Related Information: Is Part Of Proceedings of the seventh SIAM conference on parallel processing for scientific computing; Bailey, D.H.; Bjorstad, P.E.; Gilbert, J.R. [eds.] [and others]; PB: 894 p.
- Country of Publication:
- United States
- Language:
- English
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