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001     153314
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024 7 _ |a arXiv:1404.4161
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024 7 _ |a 2128/6732
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024 7 _ |a altmetric:2285601
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037 _ _ |a FZJ-2014-02955
100 1 _ |a Berljafa, Mario
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245 _ _ |a An Optimized and Scalable Eigensolver for Sequences of Eigenvalue Problems
260 _ _ |c 2014
336 7 _ |a Preprint
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336 7 _ |a Electronic Article
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336 7 _ |a ARTICLE
|2 BibTeX
500 _ _ |a 20 Pages, 6 figures. Invited submission to special issue of Concurrency and Computation: Practice and Experience
520 _ _ |a In many scientific applications the solution of non-linear differential equations are obtained through the set-up and solution of a number of successive eigenproblems. These eigenproblems can be regarded as a sequence whenever the solution of one problem fosters the initialization of the next. In addition, some eigenproblem sequences show a connection between the solutions of adjacent eigenproblems. Whenever is possible to unravel the existence of such a connection, the eigenproblem sequence is said to be a correlated. When facing with a sequence of correlated eigenproblems the current strategy amounts to solving each eigenproblem in isolation. We propose a novel approach which exploits such correlation through the use of an eigensolver based on subspace iteration and accelerated with Chebyshev polynomials (ChFSI). The resulting eigensolver, is optimized by minimizing the number of matvec multiplications and parallelized using the Elemental library framework. Numerical results shows that ChFSI achieves excellent scalability and is competitive with current dense linear algebra parallel eigensolvers.
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588 _ _ |a Dataset connected to arXivarXiv
700 1 _ |a Wortmann, Daniel
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700 1 _ |a Di Napoli, Edoardo
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|e Corresponding Author
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856 4 _ |u https://juser.fz-juelich.de/record/153314/files/FZJ-2014-02955.pdf
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914 1 _ |y 2014
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