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Enabling simulation at the fifth rung of DFT: Large scale RPA calculations with excellent time to solution


Del Ben, Mauro; Schütt, Ole; Wentz, Tim; Messmer, Peter; Hutter, Jürg; VandeVondele, Joost (2015). Enabling simulation at the fifth rung of DFT: Large scale RPA calculations with excellent time to solution. Computer Physics Communications, 187:120-129.

Abstract

The Random Phase Approximation (RPA), which represents the fifth rung of accuracy in Density Functional Theory (DFT), is made practical for large systems. Energies of condensed phase systems containing thousands of explicitly correlated electrons and 1500 atoms can now be computed in minutes and less than 1 h, respectively. GPU acceleration is employed for dense and sparse linear algebra, while communication is minimized by a judicious data layout. The performance of the algorithms, implemented in the widely used CP2K simulation package, has been investigated on hybrid Cray XC30 and XK7 architectures, up to 16,384 nodes. Our results emphasize the importance of good network performance, in addition to the availability of GPUs and generous on node memory. A new level of predictivity has thus become available for routine application in Monte Carlo and molecular dynamics simulations.

Abstract

The Random Phase Approximation (RPA), which represents the fifth rung of accuracy in Density Functional Theory (DFT), is made practical for large systems. Energies of condensed phase systems containing thousands of explicitly correlated electrons and 1500 atoms can now be computed in minutes and less than 1 h, respectively. GPU acceleration is employed for dense and sparse linear algebra, while communication is minimized by a judicious data layout. The performance of the algorithms, implemented in the widely used CP2K simulation package, has been investigated on hybrid Cray XC30 and XK7 architectures, up to 16,384 nodes. Our results emphasize the importance of good network performance, in addition to the availability of GPUs and generous on node memory. A new level of predictivity has thus become available for routine application in Monte Carlo and molecular dynamics simulations.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Department of Chemistry
Dewey Decimal Classification:540 Chemistry
Language:English
Date:2015
Deposited On:21 Dec 2015 15:25
Last Modified:18 Aug 2018 23:06
Publisher:Elsevier
ISSN:0010-4655
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.cpc.2014.10.021
Project Information:
  • : FunderFP7
  • : Grant ID277910
  • : Project TitleDIAMOND - Discovery and Insight with Advanced Models Of Nanoscale Dimensions

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