Parallelization and implementation of methods for image reconstruction

Detalhes bibliográficos
Autor(a) principal: Bento, Fábio André de Oliveira
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/10400.6/3702
Resumo: Algebraic reconstruction algorithms are iterative algorithms that are used in many area including medicine, seismology or meteorology. These algorithms are known to be highly computational intensive. This may be especially troublesome for real-time applications or when processed by conventional low-cost personnel computers. One of these real time applications is the reconstruction of water vapor images from Global Navigation Satellite System (GNSS) observations. The parallelization of algebraic reconstruction algorithms has the potential to diminish signi cantly the required resources permitting to obtain valid solutions in time to be used for nowcasting and forecasting weather models. The main objective of this dissertation was to present and analyse diverse shared memory libraries and techniques in CPU and GPU for algebraic reconstruction algorithms. It was concluded that the parallelization compensates over sequential implementations. Overall the GPU implementations were found to be only slightly faster than the CPU implementations, depending on the size of the problem being studied. A secondary objective was to develop a software to perform the GNSS water vapor reconstruction using the implemented parallel algorithms. This software has been developed with success and diverse tests were made namely with synthetic and real data, the preliminary results shown to be satisfactory. This dissertation was written in the Space & Earth Geodetic Analysis Laboratory (SEGAL) and was carried out in the framework of the Structure of Moist convection in high-resolution GNSS observations and models (SMOG) (PTDC/CTE-ATM/119922/2010) project funded by FCT.
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spelling Parallelization and implementation of methods for image reconstructionApplications in GNSS water vapor tomographyReconstrução algébrica - AlgoritmosParalelização - Central processing unitParalelização - Graphic processing unitReconstrução de imagem - ParalelizaçãoReconstrução de imagem - MétodosReconstrução de imagem - Vapor de águaGNSS water vapor tomography - AplicaçõesAlgebraic reconstruction algorithms are iterative algorithms that are used in many area including medicine, seismology or meteorology. These algorithms are known to be highly computational intensive. This may be especially troublesome for real-time applications or when processed by conventional low-cost personnel computers. One of these real time applications is the reconstruction of water vapor images from Global Navigation Satellite System (GNSS) observations. The parallelization of algebraic reconstruction algorithms has the potential to diminish signi cantly the required resources permitting to obtain valid solutions in time to be used for nowcasting and forecasting weather models. The main objective of this dissertation was to present and analyse diverse shared memory libraries and techniques in CPU and GPU for algebraic reconstruction algorithms. It was concluded that the parallelization compensates over sequential implementations. Overall the GPU implementations were found to be only slightly faster than the CPU implementations, depending on the size of the problem being studied. A secondary objective was to develop a software to perform the GNSS water vapor reconstruction using the implemented parallel algorithms. This software has been developed with success and diverse tests were made namely with synthetic and real data, the preliminary results shown to be satisfactory. This dissertation was written in the Space & Earth Geodetic Analysis Laboratory (SEGAL) and was carried out in the framework of the Structure of Moist convection in high-resolution GNSS observations and models (SMOG) (PTDC/CTE-ATM/119922/2010) project funded by FCT.Algoritmos de reconstrução algébrica são algoritmos iterativos que são usados em muitas áreas incluindo medicina, sismologia ou meteorologia. Estes algoritmos são conhecidos por serem bastante exigentes computacionalmente. Isto pode ser especialmente complicado para aplicações de tempo real ou quando processados por computadores pessoais de baixo custo. Uma destas aplicações de tempo real é a reconstrução de imagens de vapor de água a partir de observações de sistemas globais de navegação por satélite. A paralelização dos algoritmos de reconstrução algébrica permite que se reduza significativamente os requisitos computacionais permitindo obter soluções válidas para previsão meteorológica num curto espaço de tempo. O principal objectivo desta dissertação é apresentar e analisar diversas bibliotecas e técnicas multithreading para a reconstrução algébrica em CPU e GPU. Foi concluído que a paralelização compensa sobre a implementações sequenciais. De um modo geral as implementações GPU obtiveram resultados relativamente melhores que implementações em CPU, isto dependendo do tamanho do problema a ser estudado. Um objectivo secundário era desenvolver uma aplicação que realizasse a reconstrução de imagem de vapor de água através de sistemas globais de navegação por satélite de uma forma paralela. Este software tem sido desenvolvido com sucesso e diversos testes foram realizados com dados sintéticos e dados reais, os resultados preliminares foram satisfatórios. Esta dissertação foi escrita no Space & Earth Geodetic Analysis Laboratory (SEGAL) e foi realizada de acordo com o projecto Structure 01' Moist convection in high-resolution GNSS observations and models (SMOG) (PTDC / CTE-ATM/ 11992212010) financiado pelo FCT.Fundação para a Ciência e a Tecnologia (FCT)Crocker, Paul AndrewFernandes, Rui Manuel da SilvauBibliorumBento, Fábio André de Oliveira2015-07-13T09:55:52Z20132013-102013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.6/3702TID:201290073enginfo: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:RCAAP2023-12-15T09:38:31Zoai:ubibliorum.ubi.pt:10400.6/3702Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:44:08.534465Repositório 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 Parallelization and implementation of methods for image reconstruction
Applications in GNSS water vapor tomography
title Parallelization and implementation of methods for image reconstruction
spellingShingle Parallelization and implementation of methods for image reconstruction
Bento, Fábio André de Oliveira
Reconstrução algébrica - Algoritmos
Paralelização - Central processing unit
Paralelização - Graphic processing unit
Reconstrução de imagem - Paralelização
Reconstrução de imagem - Métodos
Reconstrução de imagem - Vapor de água
GNSS water vapor tomography - Aplicações
title_short Parallelization and implementation of methods for image reconstruction
title_full Parallelization and implementation of methods for image reconstruction
title_fullStr Parallelization and implementation of methods for image reconstruction
title_full_unstemmed Parallelization and implementation of methods for image reconstruction
title_sort Parallelization and implementation of methods for image reconstruction
author Bento, Fábio André de Oliveira
author_facet Bento, Fábio André de Oliveira
author_role author
dc.contributor.none.fl_str_mv Crocker, Paul Andrew
Fernandes, Rui Manuel da Silva
uBibliorum
dc.contributor.author.fl_str_mv Bento, Fábio André de Oliveira
dc.subject.por.fl_str_mv Reconstrução algébrica - Algoritmos
Paralelização - Central processing unit
Paralelização - Graphic processing unit
Reconstrução de imagem - Paralelização
Reconstrução de imagem - Métodos
Reconstrução de imagem - Vapor de água
GNSS water vapor tomography - Aplicações
topic Reconstrução algébrica - Algoritmos
Paralelização - Central processing unit
Paralelização - Graphic processing unit
Reconstrução de imagem - Paralelização
Reconstrução de imagem - Métodos
Reconstrução de imagem - Vapor de água
GNSS water vapor tomography - Aplicações
description Algebraic reconstruction algorithms are iterative algorithms that are used in many area including medicine, seismology or meteorology. These algorithms are known to be highly computational intensive. This may be especially troublesome for real-time applications or when processed by conventional low-cost personnel computers. One of these real time applications is the reconstruction of water vapor images from Global Navigation Satellite System (GNSS) observations. The parallelization of algebraic reconstruction algorithms has the potential to diminish signi cantly the required resources permitting to obtain valid solutions in time to be used for nowcasting and forecasting weather models. The main objective of this dissertation was to present and analyse diverse shared memory libraries and techniques in CPU and GPU for algebraic reconstruction algorithms. It was concluded that the parallelization compensates over sequential implementations. Overall the GPU implementations were found to be only slightly faster than the CPU implementations, depending on the size of the problem being studied. A secondary objective was to develop a software to perform the GNSS water vapor reconstruction using the implemented parallel algorithms. This software has been developed with success and diverse tests were made namely with synthetic and real data, the preliminary results shown to be satisfactory. This dissertation was written in the Space & Earth Geodetic Analysis Laboratory (SEGAL) and was carried out in the framework of the Structure of Moist convection in high-resolution GNSS observations and models (SMOG) (PTDC/CTE-ATM/119922/2010) project funded by FCT.
publishDate 2013
dc.date.none.fl_str_mv 2013
2013-10
2013-01-01T00:00:00Z
2015-07-13T09:55:52Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.6/3702
TID:201290073
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