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231224s2015 xx |||||o 00| ||eng c |
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|a 10.1002/jcc.23961
|2 doi
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|a pubmed24n0832.xml
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|a eng
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|a Grajciar, Lukáš
|e verfasserin
|4 aut
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| 245 |
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|a Low-memory iterative density fitting
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|c 2015
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
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|a Date Completed 31.08.2015
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|a Date Revised 27.06.2015
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a © 2015 Wiley Periodicals, Inc.
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|a A new low-memory modification of the density fitting approximation based on a combination of a continuous fast multipole method (CFMM) and a preconditioned conjugate gradient solver is presented. Iterative conjugate gradient solver uses preconditioners formed from blocks of the Coulomb metric matrix that decrease the number of iterations needed for convergence by up to one order of magnitude. The matrix-vector products needed within the iterative algorithm are calculated using CFMM, which evaluates them with the linear scaling memory requirements only. Compared with the standard density fitting implementation, up to 15-fold reduction of the memory requirements is achieved for the most efficient preconditioner at a cost of only 25% increase in computational time. The potential of the method is demonstrated by performing density functional theory calculations for zeolite fragment with 2592 atoms and 121,248 auxiliary basis functions on a single 12-core CPU workstation
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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|a continuous fast multipole method
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| 650 |
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|a density fitting, memory efficient algorithm
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| 650 |
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|a density functional theory
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| 650 |
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|a preconditioned conjugate gradient method
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|i Enthalten in
|t Journal of computational chemistry
|d 1984
|g 36(2015), 20 vom: 30. Juli, Seite 1521-35
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnns
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|g volume:36
|g year:2015
|g number:20
|g day:30
|g month:07
|g pages:1521-35
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|u http://dx.doi.org/10.1002/jcc.23961
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