Robust Approximate Inverse Preconditioning for the Conjugate Gradient Method

0403890 - UIVT-O 20000056 RIV US eng J - Článek v odborném periodiku
Benzi, M. - Cullum, J. K. - Tůma, Miroslav
Robust Approximate Inverse Preconditioning for the Conjugate Gradient Method.
SIAM Journal on Scientific Computing. Roč. 22, č. 4 (2000), s. 1318-1332. ISSN 1064-8275. E-ISSN 1095-7197
Grant CEP: GA AV ČR IAA2030706; GA AV ČR IAA2030801
Výzkumný záměr: AV0Z1030915
Kód oboru RIV: BA - Obecná matematika
Impakt faktor: 1.421, rok: 2000

A variant of the AINV factorized sparse approximate inverse algorithm which is applicable to any symmetric positive definite matrix. The new preconditioner is breakdown-free and, when used in conjunction with the conjugate gradient method, results in a reliable solver for highly ill-conditioned linear systems. We also investigate an alternative approach to a stable approximate inverse algorithm, based on the idea of diagonally compensated reduction of matrix entries. The results of numerical tests.
Trvalý link: http://hdl.handle.net/11104/0124177