PaStiX: A Parallel Direct Solver for Sparse SPD Matrices based on Efficient Static Scheduling and Memory Managment
HÉNON, Pascal
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
RAMET, Pierre
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
ROMAN, Jean
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
HÉNON, Pascal
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
RAMET, Pierre
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
ROMAN, Jean
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
< Réduire
Algorithms and high performance computing for grand challenge applications [SCALAPPLIX]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
Langue
en
Communication dans un congrès
Ce document a été publié dans
Tenth SIAM Conference on Parallel Processing for Scientific Computing, 2001, Portsmouth. 2001
Résumé en anglais
Solving large sparse symmetric positive definite systems of linear equations is a crucial and time-consuming step, arising in many scientific and engineering applications. In this work, we consider the block partitioning ...Lire la suite >
Solving large sparse symmetric positive definite systems of linear equations is a crucial and time-consuming step, arising in many scientific and engineering applications. In this work, we consider the block partitioning and scheduling problem for sparse parallel factorization without pivoting. We focus on the scalability of the parallel solver, and on the compromise between memory overhead and efficiency. We validate this study with parallel experiments on a large collection of irregular industrial problems.< Réduire
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