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Master's Dissertation
DOI
https://doi.org/10.11606/D.45.2008.tde-09072008-175128
Document
Author
Full name
Ricardo Luiz de Andrade Abrantes
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2008
Supervisor
Committee
Birgin, Ernesto Julian Goldberg (President)
Biloti, Ricardo Caetano Azevedo
Gubitoso, Marco Dimas
Title in Portuguese
Aplicações de computação paralela em otimização contínua
Keywords in Portuguese
algoritmos paralelos
aplicacões de otimização
métodos de otimizaçãoo contínua
Abstract in Portuguese
No presente trabalho, estudamos alguns conceitos relacionados ao desenvolvimento de programas paralelos, algumas formas de aplicar computação paralela em métodos de otimização contínua e dois métodos que envolvem o uso de otimização. O primeiro método que apresentamos, chamado PUMA (Pointwise Unconstrained Minimization Approach), recupera constantes óticas e espessuras de filmes finos a partir de valores de transmitância. O problema de recuperação é modelado como um problema inverso e resolvido com auxílio de um método de otimização. Através da paralelização do PUMA viabilizamos a recuperação empírica de constantes e espessuras de sistemas compostos por até dois filmes sobrepostos. Relatamos aqui os resultados obtidos e discutimos o desempenho da versão paralela e a qualidade dos resultados obtidos. O segundo método estudado tem o objetivo de obter configurações iniciais de moléculas para simulações de dinâmica molecular e é chamado PACKMOL. O problema de obter uma configuração inicial de moléculas é modelado como um problema de empacotamento e resolvido com o auxílio de um método de otimização. Construímos uma versão paralela do PACKMOL e mostramos os ganhos de desempenho obtidos com a paralelização.
Title in English
Applications of parallel computing in continuous optimization
Keywords in English
continuous optimization methods
optimization applications
parallel algorithms
Abstract in English
In this work we studied some concepts of parallel programming, some ways of using parallel computing in continuous optimization methods and two optimization methods. The first method we present is called PUMA (Pointwise Unconstrained Minimization Approach), and it retrieves optical constants and thicknesses of thin films from transmitance data. The problem of retrieve thickness and optical constants is modeled as an inverse problem and solved with aid of an optimization method. Through the paralelization of PUMA we managed to retrieve optical constants and thicknesses of thin films in structures with one and two superposed films. We describe some results and discuss the performance of the parallel PUMA and the quality of the retrievals. The second studied method is used to build an initial configuration of molecules for molecular dynamics simulations and it is called PACKMOL. The problem of create an initial configuration of molecules is modeled as a packing problem and solved with aid of an optimization method. We developed a parallel version of PACKMOL and we show the obtained performance gains.
 
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dissertacao.pdf (1.82 Mbytes)
Publishing Date
2008-09-01
 
WARNING: The material described below relates to works resulting from this thesis or dissertation. The contents of these works are the author's responsibility.
  • ANDRADE, Ricardo, et al. Estimation of the thickness and the optical parameters of several stacked thin films using optimization [doi:10.1364/AO.47.005208]. Applied Optics [online], 2008, vol. 47, n. 28, p. 5208.
  • MARTíNEZ, L., et al. PACKMOL : A package for building initial configurations for molecular dynamics simulations [doi:10.1002/jcc.21224]. Journal of Computational Chemistry [online], 2009, vol. 30, n. 13, p. 2157-2164.
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