High Performance Complete and Incomplete Factorizations for Very Large Sparse Systems by using Scotch and PaStiX softwares

Pascal Hénon 1 Francois Pellegrini 1, 2 Pierre Ramet 1, 2 Jean Roman 1, 2 Yousef Saad 3, 4
1 SCALAPPLIX - Algorithms and high performance computing for grand challenge applications
Université Bordeaux Segalen - Bordeaux 2, Université Sciences et Technologies - Bordeaux 1, Inria Bordeaux - Sud-Ouest, École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB), CNRS - Centre National de la Recherche Scientifique : UMR5800
2 LaBRI - Laboratoire Bordelais de Recherche en Informatique
3 U of M - University of Minnesota - Twin Cities
4 Department of Computer Science and Engineering [Minneapolis]
Abstract : PaStiX is a scientific library that provides a high performance direct supernodal solver for very large sparse linear systems. It relies on a block factorization based on an hybrid ordering (Nested Dissection + Halo Approximate Minimum Degree) obtained using the Scotch library. Efficient static scheduling and memory management are used to solve irregular problems with more of 25 millions unknowns on clusters of SMP nodes. In order to solve larger 3D problems, we apply these blockwise algorithms to compute robust and efficient parallel ILU preconditioners.
keyword : Sparse
Type de document :
Communication dans un congrès
Eleventh SIAM Conference on Parallel Processing for Scientific Computing, 2004, San Francisco, United States. 2004
Liste complète des métadonnées
https://hal.inria.fr/inria-00346622
Contributeur : Pierre Ramet <>
Soumis le : jeudi 11 décembre 2008 - 20:38:35
Dernière modification le : jeudi 11 janvier 2018 - 06:22:12

Identifiants

  • HAL Id : inria-00346622, version 1

Collections

INRIA | LABRI | UNIV-BORDEAUX

Citation

Pascal Hénon, Francois Pellegrini, Pierre Ramet, Jean Roman, Yousef Saad. High Performance Complete and Incomplete Factorizations for Very Large Sparse Systems by using Scotch and PaStiX softwares. Eleventh SIAM Conference on Parallel Processing for Scientific Computing, 2004, San Francisco, United States. 2004. 〈inria-00346622〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

110

Contact


archive-ouverte@inria.fr