A Performance Study of Sparse Cholesky Factorization on INTEL iPSC/860

Abstract

The problem of Cholesky factorization of a sparse matrix has been very well investigated on sequential machines. A number of efficient codes exist for factorizing large unstructured sparse matrices, for example, codes from Harwell Subroutine Library 4 and Sparspak 7. However, there is a lack of such efficient codes on parallel machines in general, and distributed memory machines in particular. Some of the issues which are critical to the implementation of sparse Cholesky factorization on a distributed memory parallel machine are: ordering, partitioning and mapping, load balancing, and ordering of various tasks within a processor. Addressing these issues optimally for unstructured sparse matrices is a challenging task. In this paper we focus on the effect of various partitioning schemes on the performance of sparse Cholesky factorization on the INTEL iPSC/860. We also propose a new partitioning heuristic for structured as well as unstructured sparse matrices, and compare its performance with the other schemes.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1992
Accession Number
ADA251186

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  • M. Ghose
  • M. Zubair

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