A Self-scheduling Scheme for Parallel Processing in Heterogeneous Environment: Simulations of the Monte Carlo Type

  • Grzegorz Musiał
  • Lech Dȩbski
  • Dorota Jeziorek-Knioła
  • Krzysztof Goła̧b
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4967)


A parallelization scheme, which drives processing in simulations of the Monte Carlo type, suitable in highly heterogeneous computer system of a general purpose, is proposed. The message passing is applied and the MPI library is exploited. For testing, the 2D Ising model in a magnetic field is taken. The dependence of speedup on the number of parallel processes is studied, showing that the scheme works well in different parallel computer systems. The condition for the best speedup in these simulations is explained. The possibility of parallel use of any available computing power from the surrounding is also indicated.


parallelization of processing heterogeneous environment Monte Carlo simulations 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    TOP500 Supercomputer Sites, http://www.top500.org/
  2. 2.
    MPI Forum Home Page, http://www.mpi-forum.org/
  3. 3.
    Falicov, L.M., Kimball, J.C.: Phys. Rev. Lett.  22, 997 (1969)Google Scholar
  4. 4.
    Lenański, R., Wojtkiewicz, J.: phys. stat. sol (b) 236, 408 (2003)Google Scholar
  5. 5.
    Swendsen, R.H., Wang, J.-S.: Phys. Rev. Lett. 58, 86 (1987); U. Wolff, Phys. Rev. Lett. 62, 361 (1989)Google Scholar
  6. 6.
    Wang, F., Landau, D.P.: Phys. Rev. E64, 056101 (2001)Google Scholar
  7. 7.
    Musiał, G.: Phys. Rev. B69, 024407 (2004)Google Scholar
  8. 8.
    Binder, K., Heerman, D.W.: Monte Carlo Simulation in Statistical Physics. Springer Series in Solid State Physics, vol. 80. Springer, Berlin (1988)MATHGoogle Scholar
  9. 9.
    Binder, K., Landau, D.P.: Phys. Rev.  B30, 1877 (1984)Google Scholar
  10. 10.
    Wojtkiewicz, J., Musiał, G., Dȩbski, L.: phys. stat. sol (c).  3, 199 (2006)Google Scholar
  11. 11.
    Musiał, G., Dȩbski, L.: Lect. Notes in Comp. Scie, vol. 2328, p. 535 (2002)Google Scholar
  12. 12.
    LAM/MPI and Open MPI Home Page, http://www.lam-mpi.org/
  13. 13.
    Lastovetsky, A., Reddy, R.: J. Parallel Distrib. Comput. 66, 197 (2006)MATHGoogle Scholar
  14. 14.
    Lastovetsky, A.: Parallel Computing 28, 1369 (2002)Google Scholar
  15. 15.
    NetSolve/GridSolve Home Page, http://icl.cs.utk.edu/netsolve/
  16. 16.
    Dȩbski, L., Musiał, G., Rogiers, J.: In: Wyrzykowski, R., Dongarra, J., Paprzycki, M., Waśniewski, J. (eds.) PPAM 2004. LNCS, vol. 3019, p. 455. Springer, Heidelberg (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Grzegorz Musiał
    • 1
  • Lech Dȩbski
    • 1
  • Dorota Jeziorek-Knioła
    • 1
  • Krzysztof Goła̧b
    • 2
  1. 1.Institute of PhysicsA. Mickiewicz UniversityPoznańPoland
  2. 2.Fakultät für InformatikTechnische Universität MünchenGarching 

Personalised recommendations