DETECTING SECONDARY BOTTLENECKS IN PARALLEL QUANTUM CHEMISTRY APPLICATIONS USING MPI

Reema Mahajan, Dieter Kranzlmüller, Jens Volkert, Ulrich H. E. Hansmann and Siegfried Höfinger
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Reema Mahajan: Department of Chemical Engineering, Indian Institute of Technology, Delhi, Hauz Khas, New Delhi-16, India
Dieter Kranzlmüller: Institute of Graphics and Parallel Processing, Johannes Kepler University Linz, Altenberger Straße 69, A-4040, Linz, Austria
Jens Volkert: Institute of Graphics and Parallel Processing, Johannes Kepler University Linz, Altenberger Straße 69, A-4040, Linz, Austria
Ulrich H. E. Hansmann: Department of Physics, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49331-1295, USA;
Siegfried Höfinger: Department of Physics, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49331-1295, USA

International Journal of Modern Physics C (IJMPC), 2008, vol. 19, issue 01, 1-13

Abstract: Profiling tools such asgprofandssrunare used to analyze the run-time performance of a scientific application. The profiling is done in serial and in parallel mode using MPI as the communication interface. The application is a quantum chemistry program using Hartree Fock theory and Pulays DIIS method. An extensive set of test cases is taken into account in order to reach uniform conclusions. A known problem with decreased parallel scalability can thus be narrowed down to a single subroutine responsible for the reduction in Speed Up. The critical module is analyzed and a typical pitfall with triple matrix multiplications is identified. After overhauling the critical subroutine re-examination of the run-time behavior shows significantly improved performance and markedly improved parallel scalability. The lessons learned here might be of interest to other people working in similar fields with similar problems.

Keywords: MPI; quantum chemistry; performance analysis; profiling tools; bottlenecks (search for similar items in EconPapers)
Date: 2008
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DOI: 10.1142/S0129183108011899

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