Training optimum-path forest on graphics processing units

Detalhes bibliográficos
Autor(a) principal: Iwashita, Adriana S. [UNESP]
Data de Publicação: 2014
Outros Autores: Romero, Marcos V.T. [UNESP], Baldassin, Alexandro [UNESP], Costa, Kelton A.P. [UNESP], Papa, João P. [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.5220/0004737805810588
http://hdl.handle.net/11449/227857
Resumo: In this paper, we presented a Graphics Processing Unit (GPU)-based training algorithm for Optimum-Path Forest (OPF) classifier. The proposed approach employs the idea of a vector-matrix multiplication to speed up both traditional OPF training algorithm and a recently proposed Central Processing Unit (CPU)-based OPF training algorithm. Experiments in several public datasets have showed the efficiency of the proposed approach, which demonstrated to be up to 14 times faster for some datasets. To the best of our knowledge, this is the first GPU-based implementation for OPF training algorithm. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.
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spelling Training optimum-path forest on graphics processing unitsGraphics Processing UnitOptimum-Path ForestIn this paper, we presented a Graphics Processing Unit (GPU)-based training algorithm for Optimum-Path Forest (OPF) classifier. The proposed approach employs the idea of a vector-matrix multiplication to speed up both traditional OPF training algorithm and a recently proposed Central Processing Unit (CPU)-based OPF training algorithm. Experiments in several public datasets have showed the efficiency of the proposed approach, which demonstrated to be up to 14 times faster for some datasets. To the best of our knowledge, this is the first GPU-based implementation for OPF training algorithm. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.Department of Computing São Paulo State University, Bauru, São PauloDepartment of Statistics Applied Mathematics and Computation São Paulo State University, Rio-Claro, São PauloDepartment of Computing São Paulo State University, Bauru, São PauloDepartment of Statistics Applied Mathematics and Computation São Paulo State University, Rio-Claro, São PauloUniversidade Estadual Paulista (UNESP)Iwashita, Adriana S. [UNESP]Romero, Marcos V.T. [UNESP]Baldassin, Alexandro [UNESP]Costa, Kelton A.P. [UNESP]Papa, João P. [UNESP]2022-04-29T07:20:28Z2022-04-29T07:20:28Z2014-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject581-588http://dx.doi.org/10.5220/0004737805810588VISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications, v. 2, p. 581-588.http://hdl.handle.net/11449/22785710.5220/00047378058105882-s2.0-84906914165Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengVISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applicationsinfo:eu-repo/semantics/openAccess2024-04-23T16:11:34Zoai:repositorio.unesp.br:11449/227857Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-04-23T16:11:34Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Training optimum-path forest on graphics processing units
title Training optimum-path forest on graphics processing units
spellingShingle Training optimum-path forest on graphics processing units
Iwashita, Adriana S. [UNESP]
Graphics Processing Unit
Optimum-Path Forest
title_short Training optimum-path forest on graphics processing units
title_full Training optimum-path forest on graphics processing units
title_fullStr Training optimum-path forest on graphics processing units
title_full_unstemmed Training optimum-path forest on graphics processing units
title_sort Training optimum-path forest on graphics processing units
author Iwashita, Adriana S. [UNESP]
author_facet Iwashita, Adriana S. [UNESP]
Romero, Marcos V.T. [UNESP]
Baldassin, Alexandro [UNESP]
Costa, Kelton A.P. [UNESP]
Papa, João P. [UNESP]
author_role author
author2 Romero, Marcos V.T. [UNESP]
Baldassin, Alexandro [UNESP]
Costa, Kelton A.P. [UNESP]
Papa, João P. [UNESP]
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Iwashita, Adriana S. [UNESP]
Romero, Marcos V.T. [UNESP]
Baldassin, Alexandro [UNESP]
Costa, Kelton A.P. [UNESP]
Papa, João P. [UNESP]
dc.subject.por.fl_str_mv Graphics Processing Unit
Optimum-Path Forest
topic Graphics Processing Unit
Optimum-Path Forest
description In this paper, we presented a Graphics Processing Unit (GPU)-based training algorithm for Optimum-Path Forest (OPF) classifier. The proposed approach employs the idea of a vector-matrix multiplication to speed up both traditional OPF training algorithm and a recently proposed Central Processing Unit (CPU)-based OPF training algorithm. Experiments in several public datasets have showed the efficiency of the proposed approach, which demonstrated to be up to 14 times faster for some datasets. To the best of our knowledge, this is the first GPU-based implementation for OPF training algorithm. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.
publishDate 2014
dc.date.none.fl_str_mv 2014-01-01
2022-04-29T07:20:28Z
2022-04-29T07:20:28Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.5220/0004737805810588
VISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications, v. 2, p. 581-588.
http://hdl.handle.net/11449/227857
10.5220/0004737805810588
2-s2.0-84906914165
url http://dx.doi.org/10.5220/0004737805810588
http://hdl.handle.net/11449/227857
identifier_str_mv VISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications, v. 2, p. 581-588.
10.5220/0004737805810588
2-s2.0-84906914165
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv VISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 581-588
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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