Performance study of filtered back-projection algorithms implemented on GPUs

Detalhes bibliográficos
Autor(a) principal: Faria, Bruno
Data de Publicação: 2012
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://proa.ua.pt/index.php/revdeti/article/view/16662
Resumo: In recent years the use of graphical processing units (GPUs) in the diverse fields of science has increase dramatically. This increase is not only due to the GPU tremendous computational power, but also because they are relatively cheap when compared to clusters. In this work we explore the use of the GPU to reduce the computational time of the filtered back projection algorithm on computed tomography. To address the computational gain of the GPU implementation, two CPU implementations have been developed: single-core and multi-core. Both CPU implementations are benchmarked against the GPU implementation. In either case the GPU implementation proved to be a faster alternative. When compared to the CPU implementations the GPU was 273 times faster than the single-core CPU implementation and 34 times than the multi-core implementation.  
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spelling Performance study of filtered back-projection algorithms implemented on GPUsIn recent years the use of graphical processing units (GPUs) in the diverse fields of science has increase dramatically. This increase is not only due to the GPU tremendous computational power, but also because they are relatively cheap when compared to clusters. In this work we explore the use of the GPU to reduce the computational time of the filtered back projection algorithm on computed tomography. To address the computational gain of the GPU implementation, two CPU implementations have been developed: single-core and multi-core. Both CPU implementations are benchmarked against the GPU implementation. In either case the GPU implementation proved to be a faster alternative. When compared to the CPU implementations the GPU was 273 times faster than the single-core CPU implementation and 34 times than the multi-core implementation.  UA Editora2012-01-01T00:00:00Zjournal articleinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://proa.ua.pt/index.php/revdeti/article/view/16662oai:proa.ua.pt:article/16662Eletrónica e Telecomunicações; Vol 5 No 4 (2012); 416-419Eletrónica e Telecomunicações; vol. 5 n.º 4 (2012); 416-4192182-97721645-0493reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAPenghttps://proa.ua.pt/index.php/revdeti/article/view/16662https://proa.ua.pt/index.php/revdeti/article/view/16662/11784https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessFaria, Bruno2022-09-26T11:00:03Zoai:proa.ua.pt:article/16662Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:07:55.312800Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Performance study of filtered back-projection algorithms implemented on GPUs
title Performance study of filtered back-projection algorithms implemented on GPUs
spellingShingle Performance study of filtered back-projection algorithms implemented on GPUs
Faria, Bruno
title_short Performance study of filtered back-projection algorithms implemented on GPUs
title_full Performance study of filtered back-projection algorithms implemented on GPUs
title_fullStr Performance study of filtered back-projection algorithms implemented on GPUs
title_full_unstemmed Performance study of filtered back-projection algorithms implemented on GPUs
title_sort Performance study of filtered back-projection algorithms implemented on GPUs
author Faria, Bruno
author_facet Faria, Bruno
author_role author
dc.contributor.author.fl_str_mv Faria, Bruno
description In recent years the use of graphical processing units (GPUs) in the diverse fields of science has increase dramatically. This increase is not only due to the GPU tremendous computational power, but also because they are relatively cheap when compared to clusters. In this work we explore the use of the GPU to reduce the computational time of the filtered back projection algorithm on computed tomography. To address the computational gain of the GPU implementation, two CPU implementations have been developed: single-core and multi-core. Both CPU implementations are benchmarked against the GPU implementation. In either case the GPU implementation proved to be a faster alternative. When compared to the CPU implementations the GPU was 273 times faster than the single-core CPU implementation and 34 times than the multi-core implementation.  
publishDate 2012
dc.date.none.fl_str_mv 2012-01-01T00:00:00Z
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dc.identifier.uri.fl_str_mv https://proa.ua.pt/index.php/revdeti/article/view/16662
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url https://proa.ua.pt/index.php/revdeti/article/view/16662
identifier_str_mv oai:proa.ua.pt:article/16662
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://proa.ua.pt/index.php/revdeti/article/view/16662
https://proa.ua.pt/index.php/revdeti/article/view/16662/11784
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dc.publisher.none.fl_str_mv UA Editora
publisher.none.fl_str_mv UA Editora
dc.source.none.fl_str_mv Eletrónica e Telecomunicações; Vol 5 No 4 (2012); 416-419
Eletrónica e Telecomunicações; vol. 5 n.º 4 (2012); 416-419
2182-9772
1645-0493
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