Load Balancing for Spatial-Grid-Based Parallel Numeric Simulations on Clusters of SMPs - A Case Study from an Industrial CFD Simulation

Huaien Gao (), Andreas Schmidt (), Amitava Gupta (), Peter Luksch () and Gerhard Kahl ()
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Huaien Gao: Institut für Informatik, LRR-TUM
Andreas Schmidt: Institut für Informatik, LRR-TUM
Amitava Gupta: Institut für Informatik, LRR-TUM
Peter Luksch: Institut für Informatik, LRR-TUM
Gerhard Kahl: MTU Aero Engines

A chapter in High Performance Computing in Science and Engineering, Munich 2002, 2003, pp 467-481 from Springer

Abstract: Abstract Load distribution is an essential factor to parallel efficiency of numerical simulations that are based on spatial grids, especially on clusters of symmetric multiprocessors (SMPs). This paper presents a method of mapping spatial grid nodes to processors that combines two load balancing methodologies, graph partitioning and graph matching, to achieve maximum parallel efficiency on SMP clusters. The method has been successfully applied to load distribution in a parallel Computational Fluid Dynamics (CFD) simulation code named TRACE. Test runs on the SR8000 prove the effectiveness of the method.

Keywords: Distributed Computing; Load Balancing; Graph Matching; Graph Partitioning; Homogeneous Cluster of SMPs (search for similar items in EconPapers)
Date: 2003
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-55526-8_37

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DOI: 10.1007/978-3-642-55526-8_37

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