VDBSCAN plus : Performance Optimization Based on GPU Parallelism

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.creatorValencio, Carlos Roberto [UNESP]-
Autor(es): dc.creatorDaniel, Guilherme Priolli [UNESP]-
Autor(es): dc.creatorMedeiros, Camila Alves de [UNESP]-
Autor(es): dc.creatorCansian, Adriano Mauro [UNESP]-
Autor(es): dc.creatorBaida, Luiz Carlos [UNESP]-
Autor(es): dc.creatorFerrari, Fernando [UNESP]-
Autor(es): dc.creatorHorng, S. J.-
Data de aceite: dc.date.accessioned2022-02-22T00:12:41Z-
Data de disponibilização: dc.date.available2022-02-22T00:12:41Z-
Data de envio: dc.date.issued2020-12-09-
Data de envio: dc.date.issued2020-12-09-
Data de envio: dc.date.issued2013-01-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/PDCAT.2013.11-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/197449-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/197449-
Descrição: dc.descriptionSpatial 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.-
Descrição: dc.descriptionSao Paulo State Univ, Dept Ciencias Comp & Estat, Sao Paulo, Brazil-
Descrição: dc.descriptionSao Paulo State Univ, Dept Ciencias Comp & Estat, Sao Paulo, Brazil-
Formato: dc.format23-28-
Idioma: dc.languageen-
Publicador: dc.publisherIeee-
Relação: dc.relation2013 International Conference On Parallel And Distributed Computing, Applications And Technologies (pdcat)-
???dc.source???: dc.sourceWeb of Science-
Palavras-chave: dc.subjectspatial data mining-
Palavras-chave: dc.subjectspatial clustering-
Palavras-chave: dc.subjectGPU (Graphics Processing Unit)-
Palavras-chave: dc.subjectVDBSCAN (Varied Density Based Spatial Clustering of Applications with Noise)-
Título: dc.titleVDBSCAN plus : Performance Optimization Based on GPU Parallelism-
Aparece nas coleções:Repositório Institucional - Unesp

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