Memory Optimization to Build a Schur Complement in an Hybrid Solver
CASADEI, Astrid
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
RAMET, Pierre
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
CASADEI, Astrid
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
RAMET, Pierre
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
< Réduire
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems [BACCHUS]
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en
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Ce document a été publié dans
2012p. 11
Résumé en anglais
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 ...Lire la suite >
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.< Réduire
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