Training optimum-path forest on graphics processing units
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , , , |
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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Repositório Institucional da UNESP |
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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:29462024-08-06T00:08:44.838954Repositório 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 |
|
_version_ |
1808129589242757120 |