The efficient solution to non-symmetric linear systems is still an open issue on parallel computers. In this short pa-per we generalize to the non-symmetric case the Block Factorized Sparse Approximate Inverse (BFSAI) preconditioner which has already proved very effective on symmetric positive definite (SPD) problems. The proposed algorithm is experimented with in a number of large size matrices showing both a good robustness and scalability.
Generalizing block FSAI preconditioning to unsymmetric indefinite matrices
FERRONATO, MASSIMILIANO;JANNA, CARLO;PINI, GIORGIO;GAMBOLATI, GIUSEPPE
2012
Abstract
The efficient solution to non-symmetric linear systems is still an open issue on parallel computers. In this short pa-per we generalize to the non-symmetric case the Block Factorized Sparse Approximate Inverse (BFSAI) preconditioner which has already proved very effective on symmetric positive definite (SPD) problems. The proposed algorithm is experimented with in a number of large size matrices showing both a good robustness and scalability.
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