Preconditioners for the conjugate gradient algorithm using Gram-Schmidt and least squares methods

Authors:
Julien Straubhaar
Affiliations:
Institut de Mathématiques, Université de Neuchâtel, neuchâ, Switzerland
Venue:
International Journal of Computer Mathematics
Year:
2007

Citing 6
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Parallel preconditioners for the conjugate gradient algorithm using Gram-Schmidt and least squares methods

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Abstract

This paper is devoted to the study of some preconditioners for the conjugate gradient algorithm used to solve large sparse linear and symmetric positive definite systems. The construction of a preconditioner based on the Gram-Schmidt orthogonalization process and the least squares method is presented. Some results on the condition number of the preconditioned system are provided. Finally, numerical comparisons are given for different preconditioners.