Parallel Processing of Adaptive Meshes with Load Balancing

  • Authors:

  • Sajal K. Das;Daniel J. Harvey;Rupak Biswas

  • Affiliations:

  • Univ. of Texas, Arlington;Univ. of Texas, Arlington;NASA Ames Research Center, Moffett Field, CA

  • Venue:
  • IEEE Transactions on Parallel and Distributed Systems
  • Year:
  • 2001

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Abstract

Many scientific applications involve grids that lack a uniform underlying structure. These applications are often also dynamic in nature in that the grid structure significantly changes between successive phases of execution. In parallel computing environments, mesh adaptation of unstructured grids through selective refinement/coarsening has proven to be an effective approach. However, achieving load balance while minimizing interprocessor communication and redistribution costs is a difficult problem. Traditional dynamic load balancers are mostly inadequate because they lack a global view of system loads across processors. In this paper, we propose a novel and general-purpose load balancer that utilizes symmetric broadcast networks (SBN) as the underlying communication topology and compare its performance with a successful global load balancing environment, called PLUM, specifically created to handle adaptive unstructured applications. Our experimental results on an IBM SP2 demonstrate that the SBN-based load balancer achieves lower redistribution costs than that under PLUM by overlapping processing and data migration.