In this paper we introduce a new class library to model transformations of parallel algorithms. SYMPAD serves as a basis to develop automated tools and methods to generate efficient implementations of such algorithms. The paper gives an overview over the general structure, as well as features of the library. We further describe the fundamental design process that is controlled by our developed methods.

The new parallelization technology is presented in this work. The technology is suitable for parallelization of linear algebra problems that arise during solution of PDE and PDE systems. The new technology combines the strong points of "data parallel" and "global memory" parallel programming models. Using the pecularities of the problems of a given class, the technology allows to write effective code easily, with the addition of the possibility for semi-automatic parallelization. The work consists of 3 parts: the review of existing technologies, the description of the new one, various applications. / Šiame darbe pateikiama nauja tiesinės algebros algoritmų, atsirandančių sprendžiant dif. lygtis ir jų sistemas, lygiagretinimo technologija. Ši technologija apjungia "lygiagrečiųjų duomenų" ir "globalios atminties" lygiagretinimo modelių privalumus, ir, naudojant apibrėžtos klasės uždavinių yptaumus, leidžia lengvai gauti efektyvų programos kodą, kuris pusiau automatiškai lygiagretinamas. Darbas susideda iš 3 dalių: egzistuojančių priemonių apžvalga, naujos technologijos aprašymas, įvairūs taikymai.

Šiame darbe pateikiama nauja tiesinės algebros algoritmų, atsirandančių sprendžiant dif. lygtis ir jų sistemas, lygiagretinimo technologija. Ši technologija apjungia "lygiagrečiųjų duomenų" ir "globalios atminties" lygiagretinimo modelių privalumus, ir, naudojant apibrėžtos klasės uždavinių yptaumus, leidžia lengvai gauti efektyvų programos kodą, kuris pusiau automatiškai lygiagretinamas. Darbas susideda iš 3 dalių: egzistuojančių priemonių apžvalga, naujos technologijos aprašymas, įvairūs taikymai. / The new parallelization technology is presented in this work. The technology is suitable for parallelization of linear algebra problems that arise during solution of PDE and PDE systems. The new technology combines the strong points of "data parallel" and "global memory" parallel programming models. Using the pecularities of the problems of a given class, the technology allows to write effective code easily, with the addition of the possibility for semi-automatic parallelization. The work consists of 3 parts: the review of existing technologies, the description of the new one, various applications.

Global optimization problems are relevant in various fields of research and industry, such as chemistry, biology, biomedicine, operational research, etc. Normally it is easier to solve optimization problems having some specific properties of objective function such as linearity, convexity, differentiability, etc. However, there are a lot of practical problems that do not satisfy such properties or even cannot be expressed in an adequate mathematical form. Therefore, it is popular to use random search optimization methods in solving such optimization problems. The dissertation deals with investigation of random search global optimization algorithms, their parallelization and application to solve practical problems. The work is focused on modification and parallelization of particle swarm optimization and genetic algorithms. The modification of particle swarm optimization algorithm, based on reduction of the search area is proposed, and several strategies to parallelize the algorithm are investigated. The algorithm is applied to solve Multiple Gravity Assist problem using parallel computing system. A hybrid global multi-objective optimization algorithm is developed by modifying single agent stochastic search strategy, and incorporating it into multi-objective optimization genetic algorithm. Several strategies to parallelize multi-objective optimization genetic algorithm is proposed. Parallel algorithms are experimentally investigated by solving competitive facility location... [to full text] / Optimizavimo uždaviniai sutinkami įvairiose mokslo ir pramonės srityse, tokiose kaip chemija, biologija, biomedicina, operacijų tyrimai ir pan. Paprastai efektyviausiai sprendžiami uždaviniai, turintys tam tikras savybes, tokias kaip tikslo funkcijų tiesiškumas, iškilumas, diferencijuojamumas ir pan. Tačiau ne visi praktikoje pasitaikantys optimizavimo uždaviniai tenkina šias savybes, o kartais iš vis negali būti išreiškiami adekvačia matematine išraiška. Tokiems uždaviniam spręsti yra populiarūs atsitiktinės paieškos optimizavimo metodai. Disertacijoje yra tiriami atsitiktinės paieškos optimizavimo metodai, jų lygiagretinimo galimybės ir taikymas praktikoje pasitaikantiems uždaviniams spręsti. Pagrindinis dėmesys skiriamas dalelių spiečiaus optimizavimo ir genetinių algoritmų modifikavimui ir lygiagretinimui. Disertacijoje yra siūloma dalelių spiečiaus optimizavimo algoritmo modifikacija, grįsta pieškos srities siaurinimu, ir tiriamos kelios algoritmo lygiagretinimo strategijos. Algoritmas yra taikomas erdvėlaivių skrydžių trajektorijų optimizavimo uždaviniui spręsti lygiagrečiųjų skaičiavimų sistemose. Taip pat yra siūlomas hibridinis globaliojo daugiakriterio optimizavimo algoritmas, gautas modifikuojant vieno agento stochastinės paieškos algoritmą ir įkomponuojant į daugiakriterio optimizavimo genetinį algoritmą. Siūlomos kelios daugiakriterio genetinio algoritmo lygiagretinimo strategijos. Jų pagrindu gauti lygiagretieji algoritmai eksperimentiškai tiriami sprendžiant... [toliau žr. visą tekstą]

This thesis is concerned with problems of using computers to interpret scenes from television camera pictures. In particular, it tackles the problem of interpreting the picture in terms of lines and curves, rather like an artist's line drawing. This is very time consuming if done by a single, serial processor. However, if many processors were used simultaneously it could be done much more rapidly. In this thesis the task of line and curve extraction is expressed in terms of constraints, in a form that is susceptible to parallel computation. Iterative algorithms to perform this task have been designed and tested. They are proved to be convergent and to achieve the computation specified. Some previous work on the design of properly convergent, parallel algorithms has drawn on the mathematics of optimisation by relaxation. This thesis develops the use of these techniques for applying "continuity constraints" in line and curve description. First, the constraints are imposed "almost everywhere" on the grey-tone picture data, in two dimensions. Some "discontinuities" - places where the constraints are not satisfied - remain, and they form the lines and curves required for picture interpretation Secondly, a similar process is applied along each line or curve to segment it. Discontinuities in the angle of the tangent along the line or curve mark the positions of vertices. In each case the process is executed in parallel throughout the picture. It is shown that the specification of such a process as an optimisation problem is non-convex and this means that an optimal solution cannot necessarily be found in a reasonable time A method is developed for efficiently achieving a good sub-optimal solution. A parallel array processor is a large array of processor cells which can act simultaneously, throughout a picture. A software emulator of such a processor array was coded in C and a POP-2 based high level language, PARAPIC, to drive it was written and used to validate the parallel algorithms developed in the thesis It is argued that the scope, in a vision system, of parallel methods such as those exploited in this work is extensive. The implications for the design of hardware to perform low-level vision are discussed and it is suggested that a machine consisting of fewer, more powerful cells than in a parallel array processor would execute the parallel algorithms more efficiently.

The prediction of correct secondary structures of large RNAs is one of the unsolved challenges of computational molecular biology. Among the major obstacles is the fact that accurate calculations scale as O(n⁴), so the computational requirements become prohibitive as the length increases. We present a new parallel multicore and scalable program called GTfold, which is one to two orders of magnitude faster than the de facto standard programs mfold and RNAfold for folding large RNA viral sequences and achieves comparable accuracy of prediction. We analyze the algorithm's concurrency and describe the parallelism for a shared memory environment such as a symmetric multiprocessor or multicore chip. We are seeing a paradigm shift to multicore chips and parallelism must be explicitly addressed to continue gaining performance with each new generation of systems. We provide a rigorous proof of correctness of an optimized algorithm for internal loop calculations called internal loop speedup algorithm (ILSA), which reduces the time complexity of internal loop computations from O(n⁴) to O(n³) and show that the exact algorithms such as ILSA are executed with our method in affordable amount of time. The proof gives insight into solving these kinds of combinatorial problems. We have documented detailed pseudocode of the algorithm for predicting minimum free energy secondary structures which provides a base to implement future algorithmic improvements and improved thermodynamic model in GTfold. GTfold is written in C/C++ and freely available as open source from our website.

Thesis (M.C.S.) - Carleton University, 2007. / Includes bibliographical references (p. 77-84). Also available in electronic format on the Internet.

Thesis (M.S.)--Mississippi State University. Department of Electrical and Computer Engineering. / Title from title screen. Includes bibliographical references.

Um autômato celular é um sistema dinâmico discreto que evolui pela iteração de regras. Os valores das variáveis do sistema mudam em função de seus valores correntes. Os autômatos celulares podem ser aplicados na resolução de diversos problemas. A tarefa de encontrar uma regra de transição que solucione um determinado problema pode ser generalizada como um problema de indução de regras para autômatos celulares. Várias abordagens baseadas em técnicas de computação evolucionária vêm sendo empregadas neste problema. No entanto, estas restringem-se a aplicações específicas. A principal contribuição deste trabalho é a proposição de uma metodologia genérica para indução de regras de autômatos celulares. Para alcançar este objetivo a pesquisa foi segmentada em quatro etapas. Na primeira etapa avaliou-se o desempenho de alguns parâmetros de previsão de comportamento calculados em função de regras de transição. Os resultados obtidos nesta etapa indicaram que os parâmetros de previsão de comportamento dinâmico devem ser utilizados de forma criteriosa. Este cuidado reside na possibilidade de se obter soluções válidas, porém, não satisfatórias. Ressalta-se também a necessidade da existência de parâmetros de referência que para a maioria dos problemas reais, não está disponível. Na segunda etapa apresentou-se um novo método para a previsão do comportamento dinâmico. Este método considera a regra de transição e a configuração inicial do autômato celular. Para a previsão utilizou-se como referência os padrões de comportamento dinâmico qualitativos descritos por Wolfram. O método mostrou-se eficiente para regras de comportamento nulo. Como o processo de simulação da dinâmica de um sistema pode ter um custo computacional elevado, desenvolveu-se uma terceira metodologia. Nesta metodologia implementou-se uma arquitetura baseada no conceito de hardware/software co-design com a finalidade de contornar problemas referentes a tempo de processamento. Esta arquitetura realiza a evolução de autômatos celulares utilizando lógica reconfigurável. A arquitetura diminuiu o tempo de processamento por centenas de vezes, mas algumas restrições do modelo, como número limitado de células lógicas e reprogramações do hardware inviabilizaram seu uso. Considerando-se as restrições impostas pela arquitetura implementada, iniciou-se a quarta etapa da pesquisa onde foi desenvolvida uma nova arquitetura paralela fundamentada no paradigma mestre-escravo. Neste paradigma um processo mestre implementa o algoritmo evolucionário e um conjunto de processos escravos dividem a tarefa de validação das regras obtidas. O sistema é executado em um cluster composto por 120 núcleos de processamento que se interligam por meio de uma rede ethernet. A estratégia co-evolucionária baseada em um modelo insular permitiu a busca por soluções que apresentam um melhor valor para função de fitness. O sistema genérico implementado sobre um ambiente paralelo foi capaz de solucionar os problemas abordados. Uma análise de distribuição de tarefas entre vários processadores enfatizou os benefícios do processamento paralelo. Os experimentos também indicaram um conjunto de parâmetros evolucionários de referência que podem ser utilizados para configurar o sistema. As contribuições deste trabalho foram tanto teóricas, com as avaliações realizadas sobre os parâmetros e os diferentes métodos de previsão de comportamento dinâmico, quanto metodológicas, pois desenvolveu-se a proposta de duas arquiteturas de processamento distintas. / A cellular automata is a discrete dynamic system that evolves thought interactions of rules and can be applied to solve several complex problems. The task to find the transition rule to solve a problem can be generalized as a problem of rule induction for cellular automata. Several approaches, based on evolutionary computation techniques, have been proposed to solve this problem. However, there is no generic methodology capable of being applied to a large range of problems. The main contribution of this work is a generic methodology for rule induction for cellular automata. This research was done in four steps to achieve this objective. In the first step we evaluated the performance of some dynamic behavior forecasting parameters calculated as function of a transition rule. The obtained results indicated that those parameters can be used in a careful way. This is due to the possibility of obtaining valid, but insatisfactory solutions. We stress the importance of considering reference parameters, which for the majority of real problems, are not available. In the second research step we proposed a new method to forecast the dynamic behavior. This method considers the transition rule and the initial configuration of the cellular automata. We used the qualitative dynamic behavior patterns described by Wolfram as reference to the forecast. This method was efficient for null behavior rules. Since the process of dynamic simulation can have a high computational cost, we developed a third methodology: an architecture based on the concept of hardware/software co-design to accelerate the processing time. This architecture implements the evolution of cellular automata using reconfigurable logic and was able to decrease hundreds of times the processing time. In the fourth step we developed a new parallel architecture based on the master-slave paradigm. In this paradigm, the master process implements the evolutionary algorithm and a set of slaves processes divide the task of validating the obtained rules. The system runs in a cluster with 120 processing cores connected by a local area network. The co-evolutionary strategy based on an insular model allowed the search for high quality solutions. The generic system implemented over a parallel environment was able to solve the problems proposed. A task distribution analyses among several processors emphasized the benefits of parallel processing. The experiments also indicated a set of reference parameters that can be used to configure the system. The contributions of this work were theoretical and methodological. The former refers to the evaluations done and the different methods for dynamic behavior forecasting parameters. The latter is about the development of two architectures for processing.

Este trabalho de pesquisa tem por objetivo apresentar e investigar a viabilidade de um método numérico que contempla o paralelismo no tempo. Este método numérico está associado a problemas de condição inicial e de contorno para equações diferenciais parciais (evolutivas). Diferentemente do método proposto neste trabalho, a maioria dos métodos numéricos associados a equações diferencias parciais evolutivas e tradicionalmente encontrados, contemplam apenas o paralelismo no espaço. Daí, a motivação em realizar o presente trabalho de pesquisa, buscando não somente um método com paralelismo no tempo mas, sobretudo, um método viável do ponto de vista computacional. Para isso, a implementação do esquema numérico proposto está por conta de um algoritmo paralelo escrito na linguagem C e que utiliza a biblioteca MPI. A análise dos resultados obtidos com os testes de desempenho revelam um método numérico escalável e que exige pouco nível de comunicação entre processadores. / This research aims to present and investigate the feasibility of a numerical method that considers the parallelism in time. This numerical method is associated with problems of initial and boundary conditions for (evolutionary) partial differential equations. Unlike the method proposed in this work, most of the numerical methods associated with evolutionary partial diferential equations and traditionally found include only parallelism in space. Hence, the motivation for carrying out the present research work,seeking not only a method with parallelism in time but,above all, a viable method. The implementation of this proposed computational parallel algorithm was written with the language C and uses the MPI library. The results obtained from performance tests reveal a scalable and numerical method that requires little level of communication amount processors