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Factorized sparse approximate inverse preconditionings. IV: Simple approaches to rising efficiency
Author(s) -
Kolotilina L. Yu.,
Nikishin A. A.,
Yeremin A. Yu.
Publication year - 1999
Publication title -
numerical linear algebra with applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.02
H-Index - 53
eISSN - 1099-1506
pISSN - 1070-5325
DOI - 10.1002/(sici)1099-1506(199910/11)6:7<515::aid-nla176>3.0.co;2-0
Subject(s) - preconditioner , mathematics , simple (philosophy) , inverse , positive definite matrix , matrix (chemical analysis) , sparse matrix , a priori and a posteriori , inverse problem , numerical analysis , algorithm , iterative method , mathematical analysis , computational chemistry , geometry , eigenvalues and eigenvectors , philosophy , physics , materials science , epistemology , quantum mechanics , chemistry , composite material , gaussian
This paper continues the theoretical and numerical study of the so‐called factorized sparse approximate inverse (FSAI) preconditionings of symmetric positive‐definite matrices and considers two new approaches to improving them. The first one is based on the a posteriori sparsification of an already constructed FSAI preconditioner, whereas the second one amounts to applying another FSAI preconditioning to an already preconditioned matrix. Numerical results for sample FE problems from structural mechanics are presented. Copyright © 1999 John Wiley & Sons, Ltd.