Preordering saddle-point systems for sparse LDLT factorization without pivoting
| Autor: | Sangye Lungten, Jennifer A. Scott, Wil H. A. Schilders |
|---|---|
| Přispěvatelé: | Center for Analysis, Scientific Computing & Appl. |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Algebra and Number Theory
Applied Mathematics Block matrix 010103 numerical & computational mathematics 02 engineering and technology Solver System of linear equations 01 natural sciences 020202 computer hardware & architecture Sparse symmetric indefinite matrices Factorization Saddle point 0202 electrical engineering electronic engineering information engineering LDLfactorization Saddle-point systems Applied mathematics Partition (number theory) A priori and a posteriori 0101 mathematics Fill-reducing ordering Saddle Mathematics |
| Zdroj: | Numerical Linear Algebra with Applications, 25(5):e2173. Wiley |
| ISSN: | 1070-5325 |
| Popis: | 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 LDLT 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. |
| Databáze: | OpenAIRE |
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