CROUT VERSIONS OF ILU FOR GENERAL SPARSE MATRICES.
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| Title: | CROUT VERSIONS OF ILU FOR GENERAL SPARSE MATRICES. |
|---|---|
| Authors: | Li, Na1 nli@cs.umn.edu, Saad, Yousef2 saad@cs.umn.edu, Chow, Edmond echow@llnl.gov |
| Source: | SIAM Journal on Scientific Computing. 2003, Vol. 25 Issue 2, p716-728. 13p. |
| Subjects: | Factorization of operators, Algorithms, Iterative methods (Mathematics), Sparse matrices, Linear systems |
| Abstract: | This paper presents an efficient implementation of the incomplete LU (ILU) factorization derived from the Crout version of Gaussian elimination. At step k of the elimination, the kth row of U and the kth column of L are computed using previously computed rows of U and columns of L. The data structure and implementation borrow from already known techniques used in developing both sparse direct solution codes and incomplete Cholesky factorizations. This version of ILU can be computed much faster than standard threshold-based ILU factorizations computed rowwise or columnwise. In addition, the data structure allows efficient implementations of more rigorous and effective dropping strategies. [ABSTRACT FROM AUTHOR] |
| Copyright of SIAM Journal on Scientific Computing is the property of Society for Industrial & Applied Mathematics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 12217041 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: CROUT VERSIONS OF ILU FOR GENERAL SPARSE MATRICES. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Li%2C+Na%22">Li, Na</searchLink><relatesTo>1</relatesTo><i> nli@cs.umn.edu</i><br /><searchLink fieldCode="AR" term="%22Saad%2C+Yousef%22">Saad, Yousef</searchLink><relatesTo>2</relatesTo><i> saad@cs.umn.edu</i><br /><searchLink fieldCode="AR" term="%22Chow%2C+Edmond%22">Chow, Edmond</searchLink><i> echow@llnl.gov</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22SIAM+Journal+on+Scientific+Computing%22">SIAM Journal on Scientific Computing</searchLink>. 2003, Vol. 25 Issue 2, p716-728. 13p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Factorization+of+operators%22">Factorization of operators</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Iterative+methods+%28Mathematics%29%22">Iterative methods (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22Sparse+matrices%22">Sparse matrices</searchLink><br /><searchLink fieldCode="DE" term="%22Linear+systems%22">Linear systems</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper presents an efficient implementation of the incomplete LU (ILU) factorization derived from the Crout version of Gaussian elimination. At step k of the elimination, the kth row of U and the kth column of L are computed using previously computed rows of U and columns of L. The data structure and implementation borrow from already known techniques used in developing both sparse direct solution codes and incomplete Cholesky factorizations. This version of ILU can be computed much faster than standard threshold-based ILU factorizations computed rowwise or columnwise. In addition, the data structure allows efficient implementations of more rigorous and effective dropping strategies. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of SIAM Journal on Scientific Computing is the property of Society for Industrial & Applied Mathematics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1137/S1064827502405094 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 13 StartPage: 716 Subjects: – SubjectFull: Factorization of operators Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Iterative methods (Mathematics) Type: general – SubjectFull: Sparse matrices Type: general – SubjectFull: Linear systems Type: general Titles: – TitleFull: CROUT VERSIONS OF ILU FOR GENERAL SPARSE MATRICES. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Li, Na – PersonEntity: Name: NameFull: Saad, Yousef – PersonEntity: Name: NameFull: Chow, Edmond IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: 2003 Type: published Y: 2003 Identifiers: – Type: issn-print Value: 10648275 Numbering: – Type: volume Value: 25 – Type: issue Value: 2 Titles: – TitleFull: SIAM Journal on Scientific Computing Type: main |
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