Load Balancing for the Parallel Adaptive Solution of Partial Differential Equations.

Abstract

An adaptive technique for a partial differential system automatically adjusts a computational mesh or varies the order of a numerical procedure with a goal of obtaining a solution satisfying prescribed accuracy criteria in an optimal fashion. Processor load imbalances will, therefore, be introduced at adaptive enrichment steps during the course of a parallel computation. We develop and describe three procedures for retaining and restoring load balance that have low unit cost and are appropriate for use in an adaptive solution environment. Tiling balances loading by using local optimality criteria within overlapping processor neighborhoods. Elemental data are migrated between processors within the same neighborhoods to restore balance. Tiling can potentially be improved by creating a dynamic partition graph connecting processors and their neighboring regions. After coloring the edges of the graph, elemental data are transferred between processors by pairwise exchange. Octree decomposition of a spatial domain is a successful three-dimensional mesh generation strategy. By performing tree traversals that (I) appraise subtree costs and (II) partition spatial regions accordingly, we show that octree structures may also be used to balance processor loading. Computational results are reported for two- and three-dimensional systems using nCUBE/2 hypercube, MasPar MP-2, and Thinking Machines CM-5 computers.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1994
Accession Number
ADA290450

Entities

People

  • C. Ozturan
  • H. L. Decougny
  • J. E. Flaherty
  • K. D. Devine
  • R. M. Loy

Organizations

  • Rensselaer Polytechnic Institute

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Aircrafts
  • Computational Fluid Dynamics
  • Computational Science
  • Computations
  • Computer Science
  • Computers
  • Differential Equations
  • Equations
  • Flow
  • Helicopters
  • High Performance Computing
  • Parallel Computing
  • Parallel Processing
  • Partial Differential Equations
  • Three Dimensional
  • Two Dimensional

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Graph Algorithms and Convex Optimization.
  • Parallel and Distributed Computing.