Enlarged GMRES for reducing communication

Hussam Al Daas 1, * Laura Grigori 1, * Pascal Hénon 2 Philippe Ricoux 3
* Auteur correspondant
1 ALPINES - Algorithms and parallel tools for integrated numerical simulations
LJLL - Laboratoire Jacques-Louis Lions, Institut National des Sciences Mathématiques et de leurs Interactions, Inria de Paris
Abstract : We propose a variant of the GMRES method for solving linear systems of equations with one or multiple right-hand sides. Our method is based on the idea of the enlarged Krylov subspace to reduce communication. It can be interpreted as a block GMRES method. Hence, we are interested in detecting inexact breakdowns. We introduce a strategy to perform the test of detection. Furthermore, we propose an eigenvalues deflation technique aiming to have two benefits. The first advantage is to avoid the plateau of convergence after the end of a cycle in the restarted version. The second is to have a very fast convergence when solving the same system with different right-hand sides, each given at a different time (useful in the context of CPR preconditioner). With the same memory cost, we obtain a saving of up to 50 % in the number of iterations to reach convergence with respect to the original method.
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[Research Report] RR-9049, Inria Paris. 2017
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Hussam Al Daas, Laura Grigori, Pascal Hénon, Philippe Ricoux. Enlarged GMRES for reducing communication. [Research Report] RR-9049, Inria Paris. 2017. 〈hal-01497943〉

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