Block approximate inverse preconditioners for sparse nonsymmetric linear systems

[EN] In this paper block approximate inverse preconditioners to solve sparse nonsymmetric linear systems with iterative Krylov subspace methods are studied. The computation of the preconditioners involves consecutive updates of variable rank of an initial and nonsingular matrix A0 and the applicatio...

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Detalles Bibliográficos
Autores: Cerdán Soriano, Juana Mercedes, Marín Mateos-Aparicio, José|||0000-0002-7825-2836, Mas Marí, José|||0000-0002-2835-974X, Faraj El Guelei, Táher, Malla Martínez, Natalia
Tipo de recurso: artículo
Fecha de publicación:2010
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/99451
Acceso en línea:https://riunet.upv.es/handle/10251/99451
Access Level:acceso abierto
Palabra clave:Approximate inverse preconditioners
Variable rank updates
Block algorithms
Krylov iterative methods
Sherman-Morrison-Woodbury formula
MATEMATICA APLICADA
Descripción
Sumario:[EN] In this paper block approximate inverse preconditioners to solve sparse nonsymmetric linear systems with iterative Krylov subspace methods are studied. The computation of the preconditioners involves consecutive updates of variable rank of an initial and nonsingular matrix A0 and the application of the Sherman-MorrisonWoodbury formula to compute an approximate inverse decomposition of the updated matrices. Therefore, they are generalizations of the preconditioner presented in Bru et al. [SIAM J. Sci. Comput., 25 (2003), pp. 701¿715]. The stability of the preconditioners is studied and it is shown that their computation is breakdown-free for H-matrices. To test the performance the results of numerical experiments obtained for a representative set of matrices are presented.