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A parallel block LU decomposition method for distributed finite element matrices

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Title: A parallel block LU decomposition method for distributed finite element matrices
Authors: Maurer, Daniel1 daniel.maurer@kit.edu, Wieners, Christian
Source: Parallel Computing. Dec2011, Vol. 37 Issue 12, p742-758. 17p.
Subjects: Finite element method, Matrices (Mathematics), Decomposition method, Parallel algorithms, Performance, Schur complement
Abstract: Abstract: In this work we present a new parallel direct linear solver for matrices resulting from finite element problems. The algorithm follows the nested dissection approach, where the resulting Schur complements are also distributed in parallel. The sparsity structure of the finite element matrices is used to pre-compute an efficient block structure for the LU factors. We demonstrate the performance and the parallel scaling behavior by several test examples. [Copyright &y& Elsevier]
Copyright of Parallel Computing is the property of Elsevier B.V. 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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DbLabel: Engineering Source
An: 67328428
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: A parallel block LU decomposition method for distributed finite element matrices
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  Data: <searchLink fieldCode="AR" term="%22Maurer%2C+Daniel%22">Maurer, Daniel</searchLink><relatesTo>1</relatesTo><i> daniel.maurer@kit.edu</i><br /><searchLink fieldCode="AR" term="%22Wieners%2C+Christian%22">Wieners, Christian</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22Parallel+Computing%22">Parallel Computing</searchLink>. Dec2011, Vol. 37 Issue 12, p742-758. 17p.
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  Data: <searchLink fieldCode="DE" term="%22Finite+element+method%22">Finite element method</searchLink><br /><searchLink fieldCode="DE" term="%22Matrices+%28Mathematics%29%22">Matrices (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22Decomposition+method%22">Decomposition method</searchLink><br /><searchLink fieldCode="DE" term="%22Parallel+algorithms%22">Parallel algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Performance%22">Performance</searchLink><br /><searchLink fieldCode="DE" term="%22Schur+complement%22">Schur complement</searchLink>
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  Data: Abstract: In this work we present a new parallel direct linear solver for matrices resulting from finite element problems. The algorithm follows the nested dissection approach, where the resulting Schur complements are also distributed in parallel. The sparsity structure of the finite element matrices is used to pre-compute an efficient block structure for the LU factors. We demonstrate the performance and the parallel scaling behavior by several test examples. [Copyright &y& Elsevier]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Parallel Computing is the property of Elsevier B.V. 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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      – Type: doi
        Value: 10.1016/j.parco.2011.05.007
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      – Code: eng
        Text: English
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        PageCount: 17
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      – SubjectFull: Finite element method
        Type: general
      – SubjectFull: Matrices (Mathematics)
        Type: general
      – SubjectFull: Decomposition method
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      – SubjectFull: Parallel algorithms
        Type: general
      – SubjectFull: Performance
        Type: general
      – SubjectFull: Schur complement
        Type: general
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      – TitleFull: A parallel block LU decomposition method for distributed finite element matrices
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            NameFull: Maurer, Daniel
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            – D: 01
              M: 12
              Text: Dec2011
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              Y: 2011
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