Preordering saddle‐point systems for sparse L D L T factorization without pivoting

This paper focuses on efficiently solving large sparse symmetric indefinite systems of linear equations in saddle‐point form using a fill‐reducing ordering technique with a direct solver. Row and column permutations partition the saddle‐point matrix into a block structure constituting a priori pivot...

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Veröffentlicht in:Numerical linear algebra with applications 2018-10, Vol.25 (5)
Hauptverfasser: Lungten, Sangye, Schilders, Wil H.A., Scott, Jennifer A.
Format: Artikel
Sprache:eng
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Zusammenfassung:This paper focuses on efficiently solving large sparse symmetric indefinite systems of linear equations in saddle‐point form using a fill‐reducing ordering technique with a direct solver. Row and column permutations partition the saddle‐point matrix into a block structure constituting a priori pivots of order 1 and 2. The partitioned matrix is compressed by treating each nonzero block as a single entry, and a fill‐reducing ordering is applied to the corresponding compressed graph. It is shown that, provided the saddle‐point matrix satisfies certain criteria, a block L D L T factorization can be computed using the resulting pivot sequence without modification. Numerical results for a range of problems from practical applications using a modern sparse direct solver are presented to illustrate the effectiveness of the approach.
ISSN:1070-5325
1099-1506
DOI:10.1002/nla.2173