Reliable performance prediction for multigrid software on distributed memory systems

We propose a model for describing and predicting the parallel performance of a broad class of parallel numerical software on distributed memory architectures. The purpose of this model is to allow reliable predictions to be made for the performance of the software on large numbers of processors of a...

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Bibliographic Details
Published in:	Advances in engineering software (1992) Vol. 42; no. 5; pp. 247 - 258
Main Authors:	Romanazzi, Giuseppe, Jimack, Peter K., Goodyer, Christopher E.
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.05.2011
Subjects:	Distributed memory architectures Multigrid algorithms Parallel distributed algorithms Parallel engineering software Partial differential equations Performance prediction Performance prediction Parallel engineering software Parallel distributed algorithms Multigrid algorithms Distributed memory architectures Partial differential equations
ISSN:	0965-9978
Online Access:	Get full text
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Summary:	We propose a model for describing and predicting the parallel performance of a broad class of parallel numerical software on distributed memory architectures. The purpose of this model is to allow reliable predictions to be made for the performance of the software on large numbers of processors of a given parallel system, by only benchmarking the code on small numbers of processors. Having described the methods used, and emphasized the simplicity of their implementation, the approach is tested on a range of engineering software applications that are built upon the use of multigrid algorithms. Despite their simplicity, the models are demonstrated to provide both accurate and robust predictions across a range of different parallel architectures, partitioning strategies and multigrid codes. In particular, the effectiveness of the predictive methodology is shown for a practical engineering software implementation of an elastohydrodynamic lubrication solver.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	0965-9978
DOI:	10.1016/j.advengsoft.2010.10.005