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Parallelization of a multiconfigurational perturbation theory
Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - Ångström, Theoretical Chemistry.
Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - Ångström, Theoretical Chemistry.ORCID iD: 0000-0001-7567-8295
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2013 (English)In: Journal of Computational Chemistry, ISSN 0192-8651, E-ISSN 1096-987X, Vol. 34, no 22, 1937-1948 p.Article in journal (Refereed) Published
Abstract [en]

In this work, we present a parallel approach to complete and restricted active space second-order perturbation theory, (CASPT2/RASPT2). We also make an assessment of the performance characteristics of its particular implementation in the Molcas quantum chemistry programming package. Parallel scaling is limited by memory and I/O bandwidth instead of available cores. Significant time savings for calculations on large and complex systems can be achieved by increasing the number of processes on a single machine, as long as memory bandwidth allows, or by using multiple nodes with a fast, low-latency interconnect. We found that parallel efficiency drops below 50% when using 8-16 cores on the shared-memory architecture, or 16-32 nodes on the distributed-memory architecture, depending on the calculation. This limits the scalability of the implementation to a moderate amount of processes. Nonetheless, calculations that took more than 3 days on a serial machine could be performed in less than 5 h on an InfiniBand cluster, where the individual nodes were not even capable of running the calculation because of memory and I/O requirements. This ensures the continuing study of larger molecular systems by means of CASPT2/RASPT2 through the use of the aggregated computational resources offered by distributed computing systems.

Place, publisher, year, edition, pages
2013. Vol. 34, no 22, 1937-1948 p.
Keyword [en]
parallellization, CASPT2, multiconfigurational perturbation theory, high performance computing
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:uu:diva-204820DOI: 10.1002/jcc.23342ISI: 000321437900009OAI: oai:DiVA.org:uu-204820DiVA: diva2:640370
Available from: 2013-08-13 Created: 2013-08-12 Last updated: 2017-12-06Bibliographically approved

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Delcey, Mickaël G.Lindh, Roland

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