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Full Record Details
DOI
10.5286/raltr.2016004
Persistent URL
http://purl.org/net/epubs/work/24733312
Record Status
Checked
Record Id
24733312
Title
Nested dissection revisited
Contributors
C Ashcraft (Livermore Software Technology Corporation)
,
I Duff (STFC Rutherford Appleton Lab.)
,
J Hogg (STFC Rutherford Appleton Lab.)
,
JA Scott (STFC Rutherford Appleton Lab.)
,
S Thorne (STFC Rutherford Appleton Lab.)
Abstract
Nested dissection algorithms are widely used to order large sparse matrices with a symmetric sparsity pattern prior to using a sparse direct linear solver. In this report, we revisit nested dissection algorithms. In particular, level based methods and multilevel methods are examined, along with techniques for refining and improving the ordering. Our experience has led to the development of a new open source nested dissection-based ordering package SPRAL_ND. We report on the design of SPRAL_ND, the options that it offers and illustrate its performance using problems arising from a range of practical applications. Comparisons are made with the widely used MeTiS package. We find that while multilevel methods generally produce the best orderings in terms of the subsequent fill in the matrix factor and the ops needed to compute it, using a non-multilevel ordering that is significantly less expensive to compute can result in a reduction in the total solution time when used with a state-of-the-art parallel sparse direct solver.
Organisation
STFC
,
SCI-COMP
,
SCI-COMP-CM
Keywords
Funding Information
Related Research Object(s):
Licence Information:
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
Language
English (EN)
Type
Details
URI(s)
Local file(s)
Year
Report
RAL Technical Reports
RAL-TR-2016-004. 2016.
RAL-TR-2016-004.pdf
2016
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