Rodrigues, J.N., Johnson, S.P., Walshaw, C. ORCID: https://orcid.org/0000-0003-0253-7779 and Cross, M. (2000) An automatable generic strategy for dynamic load balancing in parallel structured mesh CFD codes. In: Parallel Computational Fluid Dynamics 1999: Towards Teraflops, Optimization and Novel Formulations. North-Holland, Amsterdam, The Netherlands, pp. 345-353. ISBN 978044482851 (doi:10.1016/B978-044482851-4.50043-8)

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Abstract

Parallel computing is now widely used in numerical simulation, particularly for application codes based on finite difference and finite element methods. A popular and successful technique employed to parallelize such codes onto large distributed memory systems is to partition the mesh into sub-domains that are then allocated to processors. The code then executes in parallel, using the SPMD methodology, with message passing for inter-processor interactions. In order to improve the parallel efficiency of an imbalanced structured mesh CFD code, a new dynamic load balancing (DLB) strategy has been developed in which the processor partition range limits of just one of the partitioned dimensions uses non-coincidental limits, as opposed to coincidental limits. The ‘local’ partition limit change allows greater flexibility in obtaining a balanced load distribution, as the workload increase, or decrease, on a processor is no longer restricted by the ‘global’ (coincidental) limit change. The automatic implementation of this generic DLB strategy within an existing parallel code is presented in this chapter, along with some preliminary results.

Item Type:	Conference Proceedings
Title of Proceedings:	Parallel Computational Fluid Dynamics 1999: Towards Teraflops, Optimization and Novel Formulations
Additional Information:	[1] This paper was first presented at the International Parallel CFD 1999 Conference (Parallel CFD '99) held from 23-26 May 1999 in Williamsburg, Virginia, USA.
Uncontrolled Keywords:	dynamic load balancing, parallel structured mesh, CFD, computational fluid dynamics
Subjects:	Q Science > QA Mathematics > QA76 Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering
Pre-2014 Departments:	School of Computing & Mathematical Sciences School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis > Computational Science & Engineering Group School of Computing & Mathematical Sciences > Computer & Computational Science Research Group School of Computing & Mathematical Sciences > Department of Computer Science School of Computing & Mathematical Sciences > Department of Mathematical Sciences
Related URLs:	Organisation
Last Modified:	14 Oct 2016 08:59
URI:	http://gala.gre.ac.uk/id/eprint/254

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