Applying High Performance Computing Techniques in Astrophysics (original) (raw)

Abstract

When trying to improve the execution time of scientific applications using parallelism, two alternatives appear as the most extended: to use explicit message-passing or using a shared address memory space. MPI and OpenMP are nowadays the industrial standards for each alternative. We broach the parallelization of an astrophysics code used to measure various properties of the accretion disk in a black hole. Different parallel approaches have been implemented: pure MPI and OpenMP versions using cyclic and block distributions, a hybrid MPI+OpenMP parallelization and a MPI Master-Slave strategy. A broad computational experience on a ccNUMA SGI Origin 3000 architecture is presented. From the scientific point of view, the most profitable conclusion is the confirmation of the robustness of the technique that the original code implements.

This work has been partially supported by the EC (FEDER) and the Spanish MCyT (Plan Nacional de I+D+I, TIC2002-04498-C05-05 and TIC2002-04400-C03-03).

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Author information

Authors and Affiliations

  1. Dept. de Estadística, Investigación Operativa y Computación, Univ. de La Laguna, 38271, La Laguna, Spain
    Francisco Almeida & Francisco de Sande
  2. Instituto de Astrofísica de Canarias (IAC), c/Vía Láctea s/n, 38271, La Laguna, Spain
    Evencio Mediavilla & Alex Oscoz

Authors

  1. Francisco Almeida
  2. Evencio Mediavilla
  3. Alex Oscoz
  4. Francisco de Sande

Editor information

Editors and Affiliations

  1. Computer Science Department, University of Tennessee, 37996-3450, Knoxville, TN, USA
    Jack Dongarra
  2. Department of Informatics and Mathematical Modelling, Technical University of Denmark, DK-2800, Lyngby, Denmark
    Kaj Madsen
  3. Informatics & Mathematical Modeling, Technical University of Denmark, DK-2800, Lyngby, Denmark
    Jerzy Waśniewski

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© 2006 Springer-Verlag Berlin Heidelberg

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Almeida, F., Mediavilla, E., Oscoz, A., de Sande, F. (2006). Applying High Performance Computing Techniques in Astrophysics. In: Dongarra, J., Madsen, K., Waśniewski, J. (eds) Applied Parallel Computing. State of the Art in Scientific Computing. PARA 2004. Lecture Notes in Computer Science, vol 3732. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558958\_63

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