Evaluating a scientific SPMD application on a computational grid with different load balancing techniques

  • Authors:
  • André Oliveira;Gabriel Argolo;Pablo Iglesias;Simone Martins;Alexandre Plastino

  • Affiliations:
  • Department of Computer Science, Universidade Federal Fluminense, Niterói, RJ, Brazil;Department of Computer Science, Universidade Federal Fluminense, Niterói, RJ, Brazil;Department of Computer Science, Universidade Federal Fluminense, Niterói, RJ, Brazil;Department of Computer Science, Universidade Federal Fluminense, Niterói, RJ, Brazil;Department of Computer Science, Universidade Federal Fluminense, Niterói, RJ, Brazil

  • Venue:
  • ISSADS'05 Proceedings of the 5th international conference on Advanced Distributed Systems
  • Year:
  • 2005

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Abstract

The performance of SPMD programs is strongly affected by dynamic load imbalancing factors. The use of a suitable load balancing algorithm is essential for overcoming the effects of these imbalancing factors. In this work, we evaluate the performance of a scientific SPMD parallel application when executed on a computational grid, with different kinds of load balancing strategies. The developed SPMD application computes the macroscopic thermal dispersion in porous media. A set of experiments was conducted on a computational grid composed by two geographically separated clusters. The main contribution of this work is the performance evaluation and comparison of a large variety of load balancing techniques under dynamic environment conditions. The experimental results showed the importance of choosing appropriate load balancing strategies when developing SPMD applications on a grid environment.