Syracuse University Libraries (Syracuse University) · 1997 · 15 citations · 12 references
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ComputingComputer ScienceHigh-performance ComputingParallel AlgorithmsParallel ComputingScientific ComputingLoad BalancingParallel Algorithm DesignParallel ArchitecturesParallel ComputationParallel Computer ArchitectureParallel Computing SystemsLoad Balancing AlgorithmsLoad Balancing For Numerical AlgorithmsLoad Balancing StrategiesLoad SharingParallel Computing ArchitecturesParallel Particle SimulationParallel Performance OptimizationParallel Scheduling
Parallel computations comprised of multiple, tightly interwoven phases of computation may require a different approach to dynamic load balancing than single-phase computations. This paper presents a load sharing method based on the view of load as a vector, rather than as a scalar. This approach allows multiphase computations to achieve higher efficiency on large-scale multicomputers than possible with traditional techniques. Results are presented for two large-scale particle simulations running on 128 nodes of an Intel Paragon and on 256 processors of a Cray T3D, respectively. INTRODUCTION Load balancing techniques already in the literature have concentrated entirely on single-phase computations (Boillat 1990; Cybenko 1989; Evans and Butt 1993; Heirich and Taylor 1995; Horton 1993; Kohring 1995; Lin and Keller 1987; Muniz and Zaluska 1995; Song 1994; Walshaw and Berzins 1995; Watts et al. 1996; Willebeek-LeMair and Reeves 1993; Williams 1991; Xu and Lau 1997). That is, they work only ...
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