Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/25268
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dc.contributor.authorBrownlee, Alexanderen_UK
dc.contributor.authorBurles, Nathanen_UK
dc.contributor.authorSwan, Jerryen_UK
dc.date.accessioned2017-05-30T22:40:20Z-
dc.date.available2017-05-30T22:40:20Z-
dc.date.issued2017-06en_UK
dc.identifier.urihttp://hdl.handle.net/1893/25268-
dc.description.abstractReducing computational energy consumption is of growing importance, particularly at the extremes (i.e. mobile devices and datacentres). Despite the ubiquity of the JavaTM Virtual Machine (JVM), very little work has been done to apply Search Based Software Engineering (SBSE) to minimize the energy consumption of programs that run on it. We describe OPACITOR , a tool for measuring the energy consumption of JVM programs using a bytecode level model of energy cost. This has several advantages over time-based energy approximations or hardware measurements. It is: deterministic.  unaffected by the rest of the computational environment.  able to detect small changes in execution profile, making it highly amenable to metaheuristic search which requires locality of representation. We show how generic SBSE approaches coupled with OPACITOR achieve substantial energy savings for three widely-used software components. Multi-Layer Perceptron implementations minimis- ing both energy and error were found, and energy reductions of up to 70% and 39.85% were obtained over the original code for Quicksort and Object-Oriented container classes respectively. These highlight three important considerations for automatically reducing computational energy: tuning software to particular distributions of data; trading off energy use against functional properties; and handling internal dependencies which can exist within software that render simple sweeps over program variants sub-optimal. Against these, global search greatly simplifies the developer’s job, freeing development time for other tasks.en_UK
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.relationBrownlee A, Burles N & Swan J (2017) Search-based energy optimization of some ubiquitous algorithms. IEEE Transactions on Emerging Topics in Computational Intelligence, 1 (3), pp. 188-201. https://doi.org/10.1109/TETCI.2017.2699193en_UK
dc.relation.urihttp://hdl.handle.net/11667/88en_UK
dc.rightsThis work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/en_UK
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_UK
dc.subjectSearch based software engineeringen_UK
dc.subjectJavaen_UK
dc.subjectenergyen_UK
dc.titleSearch-based energy optimization of some ubiquitous algorithmsen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.1109/TETCI.2017.2699193en_UK
dc.citation.jtitleIEEE Transactions on Emerging Topics in Computational Intelligenceen_UK
dc.citation.issn2471-285Xen_UK
dc.citation.volume1en_UK
dc.citation.issue3en_UK
dc.citation.spage188en_UK
dc.citation.epage201en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.funderEngineering and Physical Sciences Research Councilen_UK
dc.author.emailsbr@cs.stir.ac.uken_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.contributor.affiliationIBM UKen_UK
dc.contributor.affiliationUniversity of Yorken_UK
dc.identifier.wtid531372en_UK
dc.contributor.orcid0000-0003-2892-5059en_UK
dc.date.accepted2017-04-14en_UK
dc.date.filedepositdate2017-04-16en_UK
dc.relation.funderprojectDAASE: Dynamic Adaptive Automated Software Engineeringen_UK
dc.relation.funderrefEP/J017515/1en_UK
Appears in Collections:Computing Science and Mathematics Journal Articles

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