Effective parallel preconditioning with sparse approximate inverses
Conference
·
OSTI ID:125553
- Stanford Univ., CA (United States)
- Universitaet Wuezburg (Germany)
A parallel preconditioner is presented for the solution of general sparse linear systems of equations. A sparse approximate inverse is computed explicitly, and then applied as a preconditioner to an iterative method. The computation of the preconditioner is inherently parallel, and its application only requires a matrix-vector product. The sparsity pattern of the approximate inverse is not imposed a priori but captured automatically. This keeps the amount of work and the number of nonzero entries in the preconditioner to a minimum. An extensive set of test problems from scientific and industrial applications provides convincing evidence of the effectiveness of this new approach.
- OSTI ID:
- 125553
- Report Number(s):
- CONF-950212--
- Country of Publication:
- United States
- Language:
- English
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