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Parallel performance prediction for multigrid codes on distributed memory architectures

Romanazzi, G and Jimack, P.K. (2007) Parallel performance prediction for multigrid codes on distributed memory architectures. In: Perrott, R., Chapman, B.M., Subhlok, J., Fernandes de Mello, R. and Yang, Y.T., (eds.) High Performance Computing and Communications. HPCC 2007, Proceedings. Third International Conference, HPCC 2007, September 26-28, 2007, Houston, USA. Lecture Notes in Computer Science (4782). Springer , Berlin / Heidelberg , pp. 647-658. ISBN 978-3-540-75443-5

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We propose a model for describing the parallel performance of multigrid software on distributed memory architectures. The goal of the model is to allow reliable predictions to be made as to the execution time of a given code on a large number of processors, of a given parallel system, by only benchmarking the code on small numbers of processors. This has potential applications for the scheduling of jobs in a Grid computing environment where reliable predictions as to execution times on different systems will be valuable. The model is tested for two different multigrid codes running on two different parallel architectures and the results obtained are discussed.

Item Type: Proceedings Paper
Copyright, Publisher and Additional Information: © Springer-Verlag Berlin Heidelberg 2007. This is an author produced version of a paper published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Parallel Distributed Algorithms; Grid Computing; Cluster Computing; Performance Evaluation and Prediction.
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering (Leeds) > School of Computing (Leeds)
Depositing User: Miss Jamie Grant
Date Deposited: 10 Mar 2009 12:06
Last Modified: 06 Jun 2014 00:52
Published Version: http://dx.doi.org/10.1007/978-3-540-75444-2_61
Status: Published
Publisher: Springer
Refereed: Yes
Identification Number: 10.1007/978-3-540-75444-2_61
Related URLs:
URI: http://eprints.whiterose.ac.uk/id/eprint/7945

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