Parallel acceleration of krylov solvers by factorized approximate inverse preconditioners

Authors:
Luca Bergamaschi;Ángeles Martínez
Affiliations:
Dipartimento di Metodi e Modelli Matematici per le Scienze Applicate, Università di Padova, Padova, Italy;Dipartimento di Metodi e Modelli Matematici per le Scienze Applicate, Università di Padova, Padova, Italy
Venue:
VECPAR'04 Proceedings of the 6th international conference on High Performance Computing for Computational Science
Year:
2004

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Abstract

This paper describes and tests a parallel implementation of a factorized approximate inverse preconditioner (FSAI) to accelerate iterative linear system solvers. Such a preconditioner reveals an efficient accelerator of both Conjugate gradient and BiCGstab iterative methods in the parallel solution of large linear systems arising from the discretization of the advection-diffusion equation. The resulting message passing code allows the solution of large problems leading to a very cost-effective algorithm for the solution of large and sparse linear systems.