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Load balancing by redundant decomposition and mapping

  • J. F. de Ronde
  • A. Schoneveld
  • P. M. A. Sloot
  • N. Floras
  • J. Reeve
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1067)

Abstract

In this paper a methodology is presented that has been developed in the CAMAS3 project for the purpose of decomposition and mapping of parallel processes to processor topologies. The methodology has been implemented in terms of a toolset, thus allowing automatic decomposition and mapping of parallel processes. The parallel processes and processors are modelled according to a generally applicable formalism, based on the so-called virtual particle model. As a case study the presented methodology is applied to parallel finite element simulations.

Keywords

(redundant) domain decomposition mapping, virtual particles parallel process modelling 

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References

  1. 1.
    J. F. de Ronde and P.M.A. Sloot. Camas-tr-2.1.3.4 map final report. Technical report, University of Amsterdam, October 1995.Google Scholar
  2. 2.
    J.F. de Ronde, B. van Halderen, A. de Mes, M. Beemster, and P.M.A. Sloot. Automatic performance estimation of spmd programs on mpp. In L. Dekker, W. Smit, and J. C. Zuidervaart, editors, Massively Parallel Processing Applications and Development, pages 381–388. EUROSIM, June 1994.Google Scholar
  3. 3.
    N. Floras. Camas-tr-2.2.2.8 ddt user's guide. Technical report, University of Southampton, April 1995.Google Scholar
  4. 4.
    J. De Keyser and D. Roose. Load balancing data parallel programs on distributed memory computers. Parallel Computing, 19:1199–1219, 1993.Google Scholar
  5. 5.
    N. Mansour and G. Fox. Allocating data to multicomputer nodes by physical optimization algorithms for loosely synchronous computations. CONCURRENCY: PRACTICE AND EXPERIENCE, 4(7):557–574, OCTOBER 1992.Google Scholar
  6. 6.
    J. Merlin. Camas-tr-2.2.1.2ida's user's guide. Technical report, University of Southampton, September 1993.Google Scholar
  7. 7.
    N.Floros, J.Reeve, J. Clinckemaille, S.Vlachoutsis, and G. Lonsdale. Comparative efficiencies of domain decompositions. Parallel Computing, 1995. Accepted for publication.Google Scholar
  8. 8.
    M. G. Norman. Models of machines and computation for mapping in multicomputers. ACM Computing Surveys, 25:263–302, 1993.Google Scholar
  9. 9.
    Benno J. Overeinder, Peter M. A. Sloot, and Robbert N. Heederik. A dynamic load balancing system for parallel cluster computing. Future Generation Computer Systems, 1996. Accepted for publication.Google Scholar
  10. 10.
    P.M.A. Sloot, J.A. Kaandorp, and A. Schoneveld. Dynamic complex systems (dcs) a new approach to parallel computing in computational physics. Technical Report TR CS 95, University of Amsterdam, November 1995.Google Scholar
  11. 11.
    P.M.A. Sloot and J. Reeve. Executive report on the camas workbench. Technical Report CAMAS-TR-2.3.7, University of Amsterdam and University of Southampton, October 1995.Google Scholar
  12. 12.
    B. van Halderen and P.M.A. Sloot. Camas-tr-2.1.1.7 sad/parasol final report. Technical report, University Of Amsterdam, October 1995.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • J. F. de Ronde
    • 1
  • A. Schoneveld
    • 1
  • P. M. A. Sloot
    • 1
  • N. Floras
    • 2
  • J. Reeve
    • 2
  1. 1.Department of Mathematics and Computer ScienceUniversity of AmsterdamSJ Amsterdam
  2. 2.Department of Computer ScienceUniversity of SouthamptonUK

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