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Performance Assessment of the Canonical Genetic Algorithm: a Study on Parallel Processing Via GPU Architecture

dc.contributor.authorFazendeiro, Paulo
dc.contributor.authorPrata, Paula
dc.date.accessioned2020-01-10T14:31:00Z
dc.date.available2020-01-10T14:31:00Z
dc.date.issued2017
dc.description.abstractGenetic Algorithms (GAs) exhibit a well-balanced operation, combining exploration with exploitation. This balance, which has a strong impact on the quality of the solutions, depends on the right choice of the genetic operators and on the size of the population. The results reported in the present work shows that the GPU architecture is an efficient alternative to implement population-based search methods. In the case of heavy workloads the speedup gains are quite impressive. The reported experiments also show that the two-dimensional granularity offered by the GPU architecture is advantageous for the operators presenting functional and data independence at the population+genotype level.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.4324/9781315366388pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.6/8205
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectData parallelismpt_PT
dc.subjectGPGPUpt_PT
dc.subjectParallel Genetic Algorithmspt_PT
dc.subjectOpenCLpt_PT
dc.titlePerformance Assessment of the Canonical Genetic Algorithm: a Study on Parallel Processing Via GPU Architecturept_PT
dc.typebook part
dspace.entity.typePublication
person.familyNameFazendeiro
person.familyNamePrata
person.givenNamePaulo
person.givenNamePaula
person.identifier.ciencia-id911F-3584-721F
person.identifier.ciencia-id651F-C1C8-44AD
person.identifier.orcid0000-0001-6054-7188
person.identifier.orcid0000-0002-3072-0186
person.identifier.ridB-7713-2008
person.identifier.scopus-author-id19640174600
person.identifier.scopus-author-id6506143567
rcaap.embargofctCopyright cedido à editora no momento da publicaçãopt_PT
rcaap.rightsclosedAccesspt_PT
rcaap.typebookPartpt_PT
relation.isAuthorOfPublication47442970-f246-4908-b873-0b58e684a9e9
relation.isAuthorOfPublication138a0dac-5e5d-466c-901d-4ed34f860403
relation.isAuthorOfPublication.latestForDiscovery47442970-f246-4908-b873-0b58e684a9e9

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