1. The effect of orderings on sparse approximate inverse preconditioners for non-symmetric problems
- Author
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E. Flórez, L. González, María Dolores del Olmo García, and Gustavo Montero
- Subjects
Mathematical optimization ,Discretization ,Preconditioner ,MathematicsofComputing_NUMERICALANALYSIS ,General Engineering ,Inverse ,Sparse approximation ,Krylov subspace ,Computer Science::Numerical Analysis ,Finite element method ,Mathematics::Numerical Analysis ,Matrix (mathematics) ,Rate of convergence ,Applied mathematics ,Software ,Mathematics - Abstract
We experimentally study how reordering techniques affect the rate of convergence of preconditioned Krylov subspace methods for nonsymmetric sparse linear systems, where the preconditioner is a sparse approximate inverse. In addition, we show how the reordering reduces the number of entries in the approximate inverse and thus, the amount of storage and computation required for a given accuracy. These properties are illustrated with several numerical experiments taken from the discretization of PDEs by a finite element method and from a standard matrix collection.
- Published
- 2002
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