| Abstract |
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| In Krylov-based iterative methods, the computation of an orthonormal basis of the Krylov space is a key issue in the algorithms because the many scalar products are often a bottleneck in parallel distributedenvironments. Using GMRES, we present a comparison of four variants of the Gram-Schmidt process on distributed memory machines.Our experiments are carried on an application in astrophysics and on a convection-diffusion example. We show that the iterative classical Gram-Schmidt method overcomes its three competitors in speed and in parallel scalability while keeping robust numerical properties. |
| Contact |
| Valerie Fraysse CERFACS,42 avenue Gaspard Coriolis,31057 Toulouse cedex 1,FRANCE Valerie.Fraysse@cerfacs.fr |