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Memory Optimization to Build a Schur Complement in an Hybrid Solver
Casadei Astrid 1, 2, Pierre Ramet 1, 2
(2012)

Solving linear system $Ax=b$ in parallel where $A$ is a large sparse matrix is a very recurrent problem in numerical simulations. One of the state-of-the-art most promising algorithm is the hybrid method based on domain decomposition and Schur complement. In this method, a direct solver is used as a subroutine on each subdomain matrix. This approach is subject to serious memory overhead. In this paper, we investigate new techniques to reduce memory consumption during the build of the Schur complement by a direct solver. Our method allows memory peak reduction from 10% to 30% on each processus for typical test cases.
1:  Laboratoire Bordelais de Recherche en Informatique (LaBRI)
CNRS : UMR5800 – Université Sciences et Technologies - Bordeaux I – École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB) – Université Victor Segalen - Bordeaux II
2:  BACCHUS (INRIA Bordeaux - Sud-Ouest)
INRIA – Université de Bordeaux – CNRS : UMR5800
Computer Science/Numerical Analysis

Computer Science/Distributed, Parallel, and Cluster Computing
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