Skip to Main content Skip to Navigation

Using Postordering and Static Symbolic Factorization for Parallel Sparse LU

Michel Cosnard 1 Laura Grigori 1
1 RESEDAS - Software Tools for Telecommunications and Distributed Systems
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : In this report we present several improvements of widely used parallel LU factorization methods on sparse matrices. First we characterize the L, U factors in terms of their corresponding LU elimination forest. This characterization can be used as a compact storage scheme of the matrix as well as of the task dependence graph. To improve the use of BLAS in the numerical factorization, we perform a postorder traversal of the LU eforest thus obtaining larger supernodes. To expose more task parallelism for a sparse matrix, we build a more accurate task dependence graph that includes only the least necessary dependencies. Experiments compared favorably our methods against methods implemented in the S* environment on the SGI's Origin2000 multiprocessor.
Document type :
Complete list of metadata
Contributor : Rapport de Recherche Inria Connect in order to contact the contributor
Submitted on : Friday, May 19, 2006 - 6:37:20 PM
Last modification on : Friday, February 4, 2022 - 3:31:04 AM
Long-term archiving on: : Saturday, April 3, 2010 - 9:42:53 PM


  • HAL Id : inria-00069935, version 1



Michel Cosnard, Laura Grigori. Using Postordering and Static Symbolic Factorization for Parallel Sparse LU. [Technical Report] RT-0237, INRIA. 1999, pp.13. ⟨inria-00069935⟩



Record views


Files downloads