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VDBSCAN plus : Performance Optimization Based on GPU Parallelism

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dc.contributor.authorValencio, Carlos Roberto [UNESP]
dc.contributor.authorDaniel, Guilherme Priolli [UNESP]
dc.contributor.authorMedeiros, Camila Alves de [UNESP]
dc.contributor.authorCansian, Adriano Mauro [UNESP]
dc.contributor.authorBaida, Luiz Carlos [UNESP]
dc.contributor.authorFerrari, Fernando [UNESP]
dc.contributor.authorHorng, S. J.
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2020-12-10T22:31:55Z
dc.date.available2020-12-10T22:31:55Z
dc.date.issued2013-01-01
dc.description.abstractSpatial data mining techniques enable the knowledge extraction from spatial databases. However, the high computational cost and the complexity of algorithms are some of the main problems in this area. This work proposes a new algorithm referred to as VDBSCAN+, which derived from the algorithm VDBSCAN (Varied Density Based Spatial Clustering of Applications with Noise) and focuses on the use of parallelism techniques in GPU (Graphics Processing Unit), obtaining a significant performance improvement, by increasing the runtime by 95% in comparison with VDBSCAN.en
dc.description.affiliationSao Paulo State Univ, Dept Ciencias Comp & Estat, Sao Paulo, Brazil
dc.description.affiliationUnespSao Paulo State Univ, Dept Ciencias Comp & Estat, Sao Paulo, Brazil
dc.format.extent23-28
dc.identifierhttp://dx.doi.org/10.1109/PDCAT.2013.11
dc.identifier.citation2013 International Conference On Parallel And Distributed Computing, Applications And Technologies (pdcat). New York: Ieee, p. 23-28, 2013.
dc.identifier.dimensionspub.1095284507
dc.identifier.doi10.1109/PDCAT.2013.11
dc.identifier.isbn978-1-4799-2419-6
dc.identifier.orcid0000-0003-4494-1454
dc.identifier.urihttp://hdl.handle.net/11449/197449
dc.identifier.wosWOS:000361018500005
dc.language.isoeng
dc.publisherIeee
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartof2013 International Conference On Parallel And Distributed Computing, Applications And Technologies (pdcat)
dc.rights.accessRightsAcesso restritopt
dc.rights.sourceRightsclosed
dc.sourceWeb of Science
dc.sourceDimensions
dc.subjectspatial data mining
dc.subjectspatial clustering
dc.subjectGPU (Graphics Processing Unit)
dc.subjectVDBSCAN (Varied Density Based Spatial Clustering of Applications with Noise)
dc.titleVDBSCAN plus : Performance Optimization Based on GPU Parallelismen
dc.typeTrabalho apresentado em eventopt
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
dcterms.rightsHolderIeee
dspace.entity.typePublication
relation.isOrgUnitOfPublication43c38943-bd6f-4fb6-a9a5-8482a1f632c0
relation.isOrgUnitOfPublication.latestForDiscovery43c38943-bd6f-4fb6-a9a5-8482a1f632c0
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Biociências Letras e Ciências Exatas, São José do Rio Pretopt
unesp.departmentCiências da Computação e Estatística - IBILCEpt

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São José do Rio Preto - IBILCE - Instituto de Biociências, Letras e Ciências Exatas