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dc.contributor.authorGerardo Abel Laguna-Sanchez, 0000-0001-5145-1248-
dc.contributor.otherOlguín Carbajal, M.-
dc.contributor.otherCruz Cortés, N.-
dc.contributor.otherBarrón Fernández, R.-
dc.contributor.otherCadena Martínez, R.-
dc.date.accessioned2018-06-26T04:36:21Z-
dc.date.available2018-06-26T04:36:21Z-
dc.date.issued2016-
dc.identifier.otherhttp://www.jatit.org/volumes/Vol86No2/1Vol86No2.pdf-
dc.identifier.urihttp://hdl.handle.net/20.500.12222/141-
dc.descriptionThe computational power of a Graphics Processing Unit (GPU), relative to a single CPU, presents a promising alternative to write parallel codes in an efficient and economical way. Differential Evolution (DE) algorithm is a global optimization based on bio-inspired heuristic. DE has a good performance, low computational complexity and need few parameters. This article presents parallel implementation of this population-based heuristic, implemented on a NVIDIA GPU device with multi-thread support and using CUDA as the model of parallel programming for these case. Our goal is to give some insights about GPU’s parallel programming by a simple and almost straightforward parallel code, and compare the performance of DE algorithm running on a multithreading GPU. This work shows that with a parallel code and a NVIDIA GPU not only the execution time is reduced but also the convergence behavior to the global optimum may be changed in a significant manner with respect the original sequential code.es_MX
dc.formatapplication/pdfes_MX
dc.languageenges_MX
dc.publisherJATITes_MX
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/es_MX
dc.subjectINGENIERÍA Y TECNOLOGÍAes_MX
dc.titleA differential evolution algorithm parallel implementation in a GPUes_MX
dc.typearticlees_MX
dc.rights.licensehttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.rights.licenseinfo:eu-repo/semantics/restrictedAccesses_MX
dc.subject.keywordsMultithreadinges_MX
dc.subject.keywordsParallel Programminges_MX
dc.subject.keywordsGPUes_MX
dc.subject.keywordsDifferential Evolution and Fine Graines_MX
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_MX
dc.coveragePKes_MX
dc.audienceresearcherses_MX
dc.identificador.materia7es_MX
dc.source.otherJournal of Theoretical and Applied Information Technology (JATIT) (2) vol.86 (2016)es_MX
dc.source.otherISSN: 1992-8645es_MX
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