A parallel algorithm based on the S-dimensional minimization of the Rayleigh quotient is proposed to evaluate the s ~ S/2 leftmost eigenpairs of the generalized symmetric positive definite eigenproblem. The minimization is performed via a conjugate gradient-like procedure accelerated by a factorized approximate inverse preconditioner (FSAI). The resulting code attains a high level of parallel efficiency and reveals comparable with the PARPACK package on a set of large matrices.

Parallel solution of sparse eigenproblems by simultaneous Rayleigh quotient optimization with FSAI preconditioning

A. MARTINEZ;
2004-01-01

Abstract

A parallel algorithm based on the S-dimensional minimization of the Rayleigh quotient is proposed to evaluate the s ~ S/2 leftmost eigenpairs of the generalized symmetric positive definite eigenproblem. The minimization is performed via a conjugate gradient-like procedure accelerated by a factorized approximate inverse preconditioner (FSAI). The resulting code attains a high level of parallel efficiency and reveals comparable with the PARPACK package on a set of large matrices.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2950233
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