Solving large problems in linear algebra

Bernard Philippe 1
1 SAGE - Simulations and Algorithms on Grids for Environment
Inria Rennes – Bretagne Atlantique , IRISA-D1 - SYSTÈMES LARGE ÉCHELLE
Abstract : Many numerical simulations end up on a problem of linear algebra involving an operator which is expressed after discretization by a very large sparse matrix. Typically, the problems include linear system solving, computation of eigenvalues and corresponding eigenvectors, and application of a function of the matrix on a given vector. To solve such problems, the methods based on Krylov subspaces have the advantage of not requiring a transformation of the matrix since they only use the matrix as an operator, i.e. through the multiplication of the matrix by a vector. The classical procedure to run these methods is the Arnoldi process which iteratively builds an orthonormal basis of the Krylov subspace. Unfortunately, this procedure has a limited potential for parallelism. To get rid of the bottleneck of the Gram-Schmidt procedure which is the heart of the Arnoldi process, non-orthonormal bases of Krylov subspaces are considered. The difficulty is then to avoid construction of too ill-conditioned bases. In this talk, we propose two types of three-term recurrences to generate such bases. In the last part and as an illustration, we present GPREMS, a parallel GMRES method preconditioned by a Multiplicative block-Schwarz iteration.
Type de document :
Communication dans un congrès
Fourth Annual meeting of the "Lebanese Society for the Mathematical Sciences" LSMS-2013, 2013, Beirut, Lebanon. 2013
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https://hal.inria.fr/hal-00903742
Contributeur : Géraldine Pichot <>
Soumis le : jeudi 21 novembre 2013 - 10:39:27
Dernière modification le : mardi 16 janvier 2018 - 15:54:11

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  • HAL Id : hal-00903742, version 1

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Bernard Philippe. Solving large problems in linear algebra. Fourth Annual meeting of the "Lebanese Society for the Mathematical Sciences" LSMS-2013, 2013, Beirut, Lebanon. 2013. 〈hal-00903742〉

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