We discuss issues related to domain decomposition and multilevel preconditioning techniques which are often employed for solving large sparse linear systems in parallel computations. We implement a parallel preconditioner for solving general sparse linear systems based on a two level block ILU factorization strategy. We give some new data structures and strategies to construct a local coefficient matrix and a local Schur complement matrix on each processor. The preconditioner constructed is fast and robust for solving certain large sparse matrices. Numerical experiments show that our domain based two level block ILU preconditioners are more robust and more efficient than some published ILU preconditioners based on Schur complement techniques for parallel sparse matrix solutions.
|Title of host publication||Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002|
|Number of pages||1|
|ISBN (Electronic)||0769515738, 9780769515731|
|State||Published - 2002|
|Event||16th International Parallel and Distributed Processing Symposium, IPDPS 2002 - Ft. Lauderdale, United States|
Duration: Apr 15 2002 → Apr 19 2002
|Name||Proceedings - International Parallel and Distributed Processing Symposium, IPDPS 2002|
|Conference||16th International Parallel and Distributed Processing Symposium, IPDPS 2002|
|Period||4/15/02 → 4/19/02|
Bibliographical notePublisher Copyright:
© 2002 IEEE.
ASJC Scopus subject areas
- Computer Networks and Communications
- Modeling and Simulation