Multi-GPU support on the marrow algorithmic skeleton framework

Detalhes bibliográficos
Autor(a) principal: Alexandre, Fernando Jorge Marques
Data de Publicação: 2013
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/10746
Resumo: Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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spelling Multi-GPU support on the marrow algorithmic skeleton frameworkAlgorithmic skeletonsMultiple GPUsAuto-tuningDissertação para obtenção do Grau de Mestre em Engenharia InformáticaWith the proliferation of general purpose GPUs, workload parallelization and datatransfer optimization became an increasing concern. The natural evolution from using a single GPU, is multiplying the amount of available processors, presenting new challenges, as tuning the workload decompositions and load balancing, when dealing with heterogeneous systems. Higher-level programming is a very important asset in a multi-GPU environment, due to the complexity inherent to the currently used GPGPU APIs (OpenCL and CUDA), because of their low-level and code overhead. This can be obtained by introducing an abstraction layer, which has the advantage of enabling implicit optimizations and orchestrations such as transparent load balancing mechanism and reduced explicit code overhead. Algorithmic Skeletons, previously used in cluster environments, have recently been adapted to the GPGPU context. Skeletons abstract most sources of code overhead, by defining computation patterns of commonly used algorithms. The Marrow algorithmic skeleton library is one of these, taking advantage of the abstractions to automate the orchestration needed for an efficient GPU execution. This thesis proposes the extension of Marrow to leverage the use of algorithmic skeletons in the modular and efficient programming of multiple heterogeneous GPUs, within a single machine. We were able to achieve a good balance between simplicity of the programming model and performance, obtaining good scalability when using multiple GPUs, with an efficient load distribution, although at the price of some overhead when using a single-GPU.projects PTDC/EIA-EIA/102579/2008 and PTDC/EIA-EIA/111518/2009Faculdade de Ciências e TecnologiaPaulino, HervéRUNAlexandre, Fernando Jorge Marques2013-11-20T11:47:09Z20132013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/10746enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T03:44:39Zoai:run.unl.pt:10362/10746Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:19:41.896519Repositório 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 Multi-GPU support on the marrow algorithmic skeleton framework
title Multi-GPU support on the marrow algorithmic skeleton framework
spellingShingle Multi-GPU support on the marrow algorithmic skeleton framework
Alexandre, Fernando Jorge Marques
Algorithmic skeletons
Multiple GPUs
Auto-tuning
title_short Multi-GPU support on the marrow algorithmic skeleton framework
title_full Multi-GPU support on the marrow algorithmic skeleton framework
title_fullStr Multi-GPU support on the marrow algorithmic skeleton framework
title_full_unstemmed Multi-GPU support on the marrow algorithmic skeleton framework
title_sort Multi-GPU support on the marrow algorithmic skeleton framework
author Alexandre, Fernando Jorge Marques
author_facet Alexandre, Fernando Jorge Marques
author_role author
dc.contributor.none.fl_str_mv Paulino, Hervé
RUN
dc.contributor.author.fl_str_mv Alexandre, Fernando Jorge Marques
dc.subject.por.fl_str_mv Algorithmic skeletons
Multiple GPUs
Auto-tuning
topic Algorithmic skeletons
Multiple GPUs
Auto-tuning
description Dissertação para obtenção do Grau de Mestre em Engenharia Informática
publishDate 2013
dc.date.none.fl_str_mv 2013-11-20T11:47:09Z
2013
2013-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/10746
url http://hdl.handle.net/10362/10746
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Faculdade de Ciências e Tecnologia
publisher.none.fl_str_mv Faculdade de Ciências e Tecnologia
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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