Use of cluster OpenMP with the Gaussian quantum chemistry code: A preliminary performance analysis

Rui Yang, Jie Cai, Alistair P. Rendell, V. Ganesh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

The Intel Cluster OpenMP (CLOMP) compiler and associated runtime environment offer the potential to run OpenMP applications over a few nodes of a cluster. This paper reports on our efforts to use CLOMP with the Gaussian quantum chemistry code. Sample results on a four node quad core Intel cluster show reasonable speedups. In some cases it is found preferable to use multiple nodes compared to using multiple cores within a single node. The performances of the different benchmarks are analyzed in terms of page faults and by using a critical path analysis technique.

Original languageEnglish
Title of host publicationEvolving OpenMP in an Age of Extreme Parallelism - 5th International Workshop on OpenMP, IWOMP 2009, Proceedings
Pages53-62
Number of pages10
Volume5568
DOIs
Publication statusPublished - 1 Dec 2009
Externally publishedYes
Event5th International Workshop on OpenMP, IWOMP 2009 - Dresden, Germany
Duration: 3 Jun 20095 Jun 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5568 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Workshop on OpenMP, IWOMP 2009
CountryGermany
CityDresden
Period3/06/095/06/09

Keywords

  • Cluster OpenMP
  • Performance
  • Quantum chemistry code

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    Yang, R., Cai, J., Rendell, A. P., & Ganesh, V. (2009). Use of cluster OpenMP with the Gaussian quantum chemistry code: A preliminary performance analysis. In Evolving OpenMP in an Age of Extreme Parallelism - 5th International Workshop on OpenMP, IWOMP 2009, Proceedings (Vol. 5568, pp. 53-62). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5568 LNCS). https://doi.org/10.1007/978-3-642-02303-3_5