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Cloud Optimization for Hot Rolling
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing.
2014 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Cloud computation is an emerging technology where a user can make use of remote computational resources of a service provider instead of using local clusters. Amazon is currently in the process of developing and launching their cloud service Amazon Elastic Compute Cloud (EC2). This report presents data on the performance of parallel global optimization methods in Matlab, as applied to a partial hot rolling mill simulation by investigating theoretical models and benchmarking actual simulation models. The computations are done using both a local cluster and on Amazon EC2 showing that for the off-line optimization of a hot rolling mill simulation it is computationally as feasible to use Amazon EC2 as it is to use a local cluster. Some upper bounds on expected speedup for various optimization methods are shown, which indicates severe limitations in the parallel efficiency of Matlab's GlobalSearch and identifies issues with the parallelization of MultiStart and patternsearch.

Place, publisher, year, edition, pages
2014.
Series
UPTEC F, ISSN 1401-5757 ; 14034
Keyword [en]
optimization, cloud computing, hot rolling
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:uu:diva-233450OAI: oai:DiVA.org:uu-233450DiVA: diva2:752597
External cooperation
ABB AB
Educational program
Master Programme in Engineering Physics
Supervisors
Examiners
Available from: 2014-10-08 Created: 2014-10-05 Last updated: 2014-10-08Bibliographically approved

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CloudOptimizationForHotRolling.pdf(1990 kB)246 downloads
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CiteExportLink to record
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Citation style
  • apa
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  • de-DE
  • en-GB
  • en-US
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  • nn-NB
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Output format
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