Global and localized parallel preconditioning techniques for large scale solid Earth simulations
Future Generation Computer Systems - Selected papers from CCGRID 2002
Parallel Multilevel Sparse Approximate Inverse Preconditioners in Large Sparse Matrix Computations
Proceedings of the 2003 ACM/IEEE conference on Supercomputing
A class of multistep sparse matrix strategies for concept decomposition matrix approximation
Proceedings of the 2009 ACM symposium on Applied Computing
Stabilized approximate inverse preconditioners for indefinite matrices
Proceedings of the 46th Annual Southeast Regional Conference on XX
A two-phase preconditioning strategy of sparse approximate inverse for indefinite matrices
Computers & Mathematics with Applications
Banded target matrices and recursive FSAI for parallel preconditioning
Numerical Algorithms
A generalization of the optimal diagonal approximate inverse preconditioner
Computers & Mathematics with Applications
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We develop a class of parallel multistep successive preconditioning strategies to enhance efficiency and robustness of standard sparse approximate inverse preconditioning techniques. The key idea is to compute a series of simple sparse matrices to approximate the inverse of the original matrix. Studies are conducted to show the advantages of such an approach in terms of both improving preconditioning accuracy and reducing computational cost, compared to the standard sparse approximate inverse preconditioners. Numerical experiments using one prototype implementation to solve a few sparse matrices on a distributed memory parallel computer are reported.