A novel dynamic load balancing scheme for parallel systems

  • Authors:

  • Zhiling Lan;Valerie E. Taylor;Greg Bryan

  • Affiliations:

  • Department of Computer Science, Illinois Institute of Technology, Chicago, IL;Electrical and Computer Engineering Department, Northwestern University, Evanston, IL;Nuclear and Astrophysics Laboratory, Oxford University, Oxford OX13RH, UK

  • Venue:
  • Journal of Parallel and Distributed Computing
  • Year:
  • 2002

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Abstract

Adaptive mesh refinement (AMR) is a type of multiscale algorithm that achieves high resolution in localized regions of dynamic, multidimensional numerical simulations. One of the key issues related to AMR is dynamic load balancing (DLB), which allows large-scale adaptive applications to run efficiently on parallel systems. In this paper, we present an efficient DLB scheme for structured AMR (SAMR) applications. This scheme interleaves a grid-splitting technique with direct grid movements (e.g., direct movement from an overloaded processor to an underloaded processor), for which the objective is to efficiently redistribute workload among all the processors so as to reduce the parallel execution time. The potential benefits of our DLB scheme are examined by incorporating our techniques into a SAMR cosmology application, the ENZO code. Experiments show that by using our scheme, the parallel execution time can be reduced by up to 57 % and the quality of load balancing can be improved by a factor of six, as compared to the original DLB scheme used in ENZO.