Sparse matrix ordering with Scotch

  • François Pellegrini
  • Jean Roman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1225)


Finding good orderings is a critical issue for the efficient factorization of sparse symmetric matrices, both in terms of space usage and solution time. Several ordering techniques have been proposed, among which nested dissection is gaining increasing popularity, due to its suitability for parallel solving.

This paper presents the sparse matrix ordering capabilities of Scotch, a software package for static mapping, graph partitioning, and sparse matrix ordering. Scotch uses nested dissection ordering, and computes small vertex separators from edge separators by computing minimum covers on the bipartite graphs associated with the edge-cuts.

We give brief descriptions of our implementation of nested dissection and of the separation and ordering methods that it uses, and compare its performance to other ordering programs.


Bipartite Graph Sparse Matrix Graph Partitioning Mesh Stiffness Operation Count 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • François Pellegrini
    • 1
  • Jean Roman
    • 1
  1. 1.LaBRI, URA CNRS 1304Université Bordeaux ITalenceFrance

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