Research Library

Premium Preordering saddle‐point systems for sparse L D L T factorization without pivoting
Author(s)
Lungten Sangye,
Schilders Wil H.A.,
Scott Jennifer A.
Publication year2018
Publication title
numerical linear algebra with applications
Resource typeJournals
PublisherWiley
Summary 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.
Subject(s)a priori and a posteriori , algorithm , block (permutation group theory) , block structure , combinatorics , composite material , discrete mathematics , epistemology , estimator , factorization , gaussian , geometry , linear system , materials science , mathematical analysis , mathematical optimization , mathematics , matrix (chemical analysis) , philosophy , physics , quantum mechanics , saddle , saddle point , solver , sparse matrix , statistics
Language(s)English
SCImago Journal Rank1.02
H-Index53
eISSN1099-1506
pISSN1070-5325
DOI10.1002/nla.2173

Seeing content that should not be on Zendy? Contact us.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here