指數基金係提供投資者追隨市場指數成長的投資工具，且投資者僅需考量市場風險即可，其建構方式有完全複製法、分層法、抽樣法、及最佳化法。本論文使用目標規劃模型建構指數基金，此法可歸類為最佳化法。由於模型中每種股票的投資數量設為整數變數，加上控制股票種類數量的0-1變數，因此所建構的目標規劃模型為混合型整數線性規劃問題。此問題在大尺度模型時往往無法求得其最佳解，我們研究此模型的結構提出一組縮小解集合空間的合理不等式，應用切面法加入必需的不等式後再根據本模型的對偶性質發展出有效率的啟發式演算法，最後將此模型及演算法應用在模擬台灣發行量加權股價指數。 / Index fund is an investment tool which tracks a stock-market index and thus is associated with market risk only. Its attraction to investors is low investment risk and low administrative expenses. Four different approaches to index fund construction can be classified as full replication, stratification, sampling, and optimizing respectively. In this thesis, we construct an index fund via the goal programming model with the optimizing approach. The model can be formulated as a mixed integer linear programming. The exact optimal solution can not be obtained when the model becomes large. We then develop a valid inequality and use this valid inequality to develop a cutting plane method. We also propose an efficient heuristic by adopting the dual property. Finally, an empirical study applying to the Taiwan Stock Exchange Capitalization Weighted Stock Index is given to show the efficiency of the algorithm.

Field-Programmable Gate Arrays (FPGAs) systems now comprise many processing elements that are processors running software and hardware engines used to accelerate specific functions. To make the programming of such a system simpler, it is easiest to think of a shared-memory environment, much like in current multi-core processor systems. This thesis introduces a novel, shared-memory, cache-coherent infrastructure for heterogeneous systems implemented on FPGAs that can then form the basis of a shared-memory programming model for heterogeneous systems. With simulation results, it is shown that the cache-coherent infrastructure outperforms the infrastructure of Woods [1] with a speedup of 1.10. The thesis explores the various configurations of the cache interconnection network and the benefit of the cache-to-cache cache line data transfer with its impact on main memory access. Finally, the thesis shows the cache-coherent infrastructure has very little overhead when using its cache coherence implementation.

Field-Programmable Gate Arrays (FPGAs) systems now comprise many processing elements that are processors running software and hardware engines used to accelerate specific functions. To make the programming of such a system simpler, it is easiest to think of a shared-memory environment, much like in current multi-core processor systems. This thesis introduces a novel, shared-memory, cache-coherent infrastructure for heterogeneous systems implemented on FPGAs that can then form the basis of a shared-memory programming model for heterogeneous systems. With simulation results, it is shown that the cache-coherent infrastructure outperforms the infrastructure of Woods [1] with a speedup of 1.10. The thesis explores the various configurations of the cache interconnection network and the benefit of the cache-to-cache cache line data transfer with its impact on main memory access. Finally, the thesis shows the cache-coherent infrastructure has very little overhead when using its cache coherence implementation.

We tackle the problem of automated code generation for a High Level Architecture (HLA)- compliant federate application, given a model of the federation architecture including the federate&rsquo / s behavior model. The behavior model is based on Live Sequence Charts (LSCs), adopted as the behavioral specification formalism in the Federation Architecture Metamodel (FAMM). The FAMM is constructed conforming to metaGME, the meta-metamodel offered by Generic Modeling Environment (GME). FAMM serves as a formal language for describing federation architectures. We present a code generator that generates Java/AspectJ code directly from a federation architecture model. An objective is to help verify a federation architecture by testing it early in the development lifecycle. Another objective is to help developers construct complete federate applications. Our approach to achieve these objectives is aspect-oriented in that the code generated from the LSC in conjunction with the Federation Object Model (FOM) serves as the base code on which the computation logic is weaved as an aspect.

Answer set programming (ASP) is a declarative approach to solving search problems. Logic programming constitutes the foundation of ASP. ASP is not a proof-theoretical approach where you get solutions by answer substitutions. Instead, the problem is represented by a logic program in such a way that models of the program according to the answer set semantics correspond to solutions of the problem. Answer set solvers (Smodels, Cmodels, Clasp, and Dlv) are used for finding answer sets of a given program. Although users can write programs with variables for convenience, current answer set solvers work on ground logic programs where there are no variables. The grounding step of ASP generates a propositional instance of a logic program with variables. It may generate a huge propositional instance and make the search process of answer set solvers more difficult. Model generation theorem provers (Paradox, Darwin, and FM-Darwin) have the capability of producing a model when the first-order input theory is satisfiable. This work proposes the use of model generation theorem provers as computational engines for ASP. The main motivation is to eliminate the grounding step of ASP completely or to perform it more intelligently using the model generation system. Additionally, regardless of grounding, model generation systems may display better performance than the current solvers. The proposed method can be seen as lifting SAT-based ASP, where SAT solvers are used to compute answer sets, to the first-order level for tight programs. A completion procedure which transforms a logic program to formulas of first-order logic is utilized. Besides completion, other transformations which are necessary for forming a firstorder theory suitable for model generation theorem provers are investigated. A system called Completor is implemented for handling all the necessary transformations. The empirical results demonstrate that the use of Completor and the theorem provers together can be an eective way of computing answer sets. Especially, the run time results of Paradox in the experiments has showed that using Completor and Paradox together is favorable compared to answer set solvers. This advantage has been more clearly observed for programs with large propositional instances, since grounding can be a bottleneck for such programs.

Continuous live stream analysis applications are increasingly common. Video-based surveillance, emergency response, disaster recovery, and critical infrastructure monitoring are all examples of such applications. These applications are distributed and typically require significant computing resources (like a cluster of workstations) for analysis. In addition to live data, many such applications also require access to historical data that was streamed in the past and is now archived. While distributed programming support for traditional high-performance computing applications is fairly mature, existing solutions for live stream analysis applications are still in their early stages and, in our view, inadequate. We explore the system-level value of recognizing temporal properties -- a critical aspect of the application domain. We present "temporal streams", a programming model supporting a higher-level, domain-targeted programming abstraction for such applications. It provides a simple but expressive stream abstraction encompassing transport, manipulation and storage of streaming data. The semantics of the programming model are tailored to the application domain by explicitly recognizing the temporal aspects of continuous streams, providing a common interface for both time-based retrieval of current streaming data and data persistence. The unifying trait of time enables access to both current streaming data and archived historical data using the same interface; the communication and storage abstraction are the same -- a unified stream data abstraction, uniformly modeling stream data interactions. "Temporal streams" defines how distributed threads of computation interact implicitly via streams, but does not impose a particular model of computation constraining the interactions between distributed actors, targeting loosely coupled distributed systems with no centralized control. In particular, it targets stream analysis scenarios requiring significant signal processing on heavyweight streams such as audio and video. These unstructured streams are data rich but are not directly interpretable until meaningful features are extracted; consequently, feature detection and subsequent analysis are the major computational requirements. We also use the programming model as a vehicle for exploring systems software design issues, realizing "temporal streams" as a distributed runtime in the tradition of loosely coupled distributed systems with strong communication boundaries. We thoroughly examine the concrete software architecture and elements of implementation. We also describe two generations of system implementations, including the broad development philosophy, specific design principles and salient low-level details. The runtime is designed to be relatively lightweight and suitable as a substrate for higher-level, more domain-specific middleware or application functionality. Even with a relatively simple programming model, a carefully designed system architecture can provide a surprisingly rich and flexibly substrate for upper software layers. We also evaluate our system implementation in two ways; first, we present a series of quantitative experimental results designed to assess the performance of key primitives in our architecture in isolation. We also use motivating applications to evaluate "temporal streams" in the context of realistic application scenarios. We develop three motivating applications and provide quantitative and qualitative analyses of these applications in the context of "temporal streams." We show that, although it provides needed higher-level functionality to enable live stream analysis applications, our runtime does not add significant overhead to the stream computation at the core of each application. Finally, we also review the relationship of "temporal streams" (both the programming model and architecture) to other approaches, including database-oriented Stream Data Management Systems (SDMS), various stream processing engines, stream programming languages and parallel batch processing systems, as well as traditional distributed programming systems and communication frameworks.

Nos últimos anos, computação em grade tem emergido como uma forma de utilização de recursos geograficamente distribuídos em múltiplas organizações. Devido ao fato de grids serem altamente distribuídos e compostos por recursos heterogêneos, a computação em grade tem dado importância a requisitos específicos, como escalabilidade, desempenho e a necessidade de um modelo de programação adequado. Vários modelos de programação já foram propostos para a computação em grade. Entretanto, ate agora, nenhum deles supriu todos os requisitos. Diferentemente, na área de alto desempenho em clusters, o modelo de passagem de mensagens se tornou um verdadeiro padrão com um grande número de bibliotecas e aplicações legadas. Este trabalho propõe um framework híbrido que combina os altos desempenho e aceitação do padrão MPI, melhorado com extensões intuitivas para permitir aos desenvolvedores o projeto e desenvolvimento de aplicações em grade ou a gridi-ficação de aplicações já existentes, com a flexibilidade de um runtime baseado em componentes, modelando uma hierarquia de recursos e suportando a comunicação entre clusters. A solução proposta se baseia na adição de comunicadores MPI e uma API relacionada, a qual oferece um suporte ao desenvolvimento de aplicações que levam em conta a topologia hierárquica de grades computacionais, adequado a desenvolvedores habituados a MPI. características (Simula_c~ao Baseada no Algoritmo de Monte Carlo, Mergesort e um solver Poisson3D) mostraram que a gridificação pode melhorar consideravelmente o desempenho dessas aplicações em ambientes de grade. Ainda que o objetivo deste trabalho não seja competir com distribuições MPI existentes, o desempenho da solução proposta _e comparável ao desempenho de MPI, sendo melhor em alguns casos. A partir dos resultados obtidos com o protótipo apresentado, é possível concluir que o custo adicionado pela utilização de componentes não é desprezível, mas dentro do esperado. Entretanto, espera-se que os benefícios para aplicações de grade devem superar os custos adicionais. Além disso, as extensões a interface MPI oferecem a usuários as abstrações necessárias ao projeto de algoritmos paralelos de forma hierárquica, visando ambientes de grade. / In the past several years, grid computing has emerged as a way to harness computing resources geographically distributed across multiple organizations. Due to its inherently largely distributed and heterogeneous nature, grid computing has enlarged the importance of specific requirements, such as scalability, performance and the need of an adequate programming model. Several programming models have been proposed for grid programming. Nonetheless, so far, none of them met all the requirements. Differently, in the field of high performance cluster computing, the message passing model became a true standard with a large number of libraries and legacy applications. This work proposes a hybrid framework that combines the high performance and high acceptability of the MPI standard boosted with intuitive extensions to enable developers to design grid applications or "gridify" existing ones with the flexibility of a component-based runtime modeling resources hierarchy and offering support to inter-cluster communication. The proposed solution relies on the addition of new MPI communicators and a related API, which may offer a support well-suited to programmers used to MPI in order to reflect a hierarchical topology within the deployed application. Carlo Simulation, a Mergesort and a Poissond3D solver) have shown that the "gridification" of applications improve application performance on grid environments. Even if the goal is not to compete against existing MPI distributions, the performance of the solution is comparable with MPI performance, even better in some cases. From the results obtained in the evaluation of this prototype, we conclude that the overhead introduced by the components is not negligible, but inside of the expected. However, we can expect the benefits to grid applications to bypass the generated overhead. Besides, the extended interface may offer users the adequate abstractions to design parallel algorithms in a hierarchical way addressing grid environments.

Nos últimos anos, computação em grade tem emergido como uma forma de utilização de recursos geograficamente distribuídos em múltiplas organizações. Devido ao fato de grids serem altamente distribuídos e compostos por recursos heterogêneos, a computação em grade tem dado importância a requisitos específicos, como escalabilidade, desempenho e a necessidade de um modelo de programação adequado. Vários modelos de programação já foram propostos para a computação em grade. Entretanto, ate agora, nenhum deles supriu todos os requisitos. Diferentemente, na área de alto desempenho em clusters, o modelo de passagem de mensagens se tornou um verdadeiro padrão com um grande número de bibliotecas e aplicações legadas. Este trabalho propõe um framework híbrido que combina os altos desempenho e aceitação do padrão MPI, melhorado com extensões intuitivas para permitir aos desenvolvedores o projeto e desenvolvimento de aplicações em grade ou a gridi-ficação de aplicações já existentes, com a flexibilidade de um runtime baseado em componentes, modelando uma hierarquia de recursos e suportando a comunicação entre clusters. A solução proposta se baseia na adição de comunicadores MPI e uma API relacionada, a qual oferece um suporte ao desenvolvimento de aplicações que levam em conta a topologia hierárquica de grades computacionais, adequado a desenvolvedores habituados a MPI. características (Simula_c~ao Baseada no Algoritmo de Monte Carlo, Mergesort e um solver Poisson3D) mostraram que a gridificação pode melhorar consideravelmente o desempenho dessas aplicações em ambientes de grade. Ainda que o objetivo deste trabalho não seja competir com distribuições MPI existentes, o desempenho da solução proposta _e comparável ao desempenho de MPI, sendo melhor em alguns casos. A partir dos resultados obtidos com o protótipo apresentado, é possível concluir que o custo adicionado pela utilização de componentes não é desprezível, mas dentro do esperado. Entretanto, espera-se que os benefícios para aplicações de grade devem superar os custos adicionais. Além disso, as extensões a interface MPI oferecem a usuários as abstrações necessárias ao projeto de algoritmos paralelos de forma hierárquica, visando ambientes de grade. / In the past several years, grid computing has emerged as a way to harness computing resources geographically distributed across multiple organizations. Due to its inherently largely distributed and heterogeneous nature, grid computing has enlarged the importance of specific requirements, such as scalability, performance and the need of an adequate programming model. Several programming models have been proposed for grid programming. Nonetheless, so far, none of them met all the requirements. Differently, in the field of high performance cluster computing, the message passing model became a true standard with a large number of libraries and legacy applications. This work proposes a hybrid framework that combines the high performance and high acceptability of the MPI standard boosted with intuitive extensions to enable developers to design grid applications or "gridify" existing ones with the flexibility of a component-based runtime modeling resources hierarchy and offering support to inter-cluster communication. The proposed solution relies on the addition of new MPI communicators and a related API, which may offer a support well-suited to programmers used to MPI in order to reflect a hierarchical topology within the deployed application. Carlo Simulation, a Mergesort and a Poissond3D solver) have shown that the "gridification" of applications improve application performance on grid environments. Even if the goal is not to compete against existing MPI distributions, the performance of the solution is comparable with MPI performance, even better in some cases. From the results obtained in the evaluation of this prototype, we conclude that the overhead introduced by the components is not negligible, but inside of the expected. However, we can expect the benefits to grid applications to bypass the generated overhead. Besides, the extended interface may offer users the adequate abstractions to design parallel algorithms in a hierarchical way addressing grid environments.

Initialement con¸cu pour d´echarger le CPU des tˆaches de rendu graphique, le GPU estdevenu une architecture massivement parall`ele adapt´ee au traitement de donn´ees volumineuses.Alors qu’il occupe une part de march´e importante dans le Calcul Haute Performance, uned´emarche d’Ad´equation Algorithme Architecture est n´eanmoins requise pour impl´ementerefficacement un algorithme sur GPU.La contribution de cette th`ese est double. Dans un premier temps, nous pr´esentons legain significatif apport´e par l’impl´ementation optimis´ee d’un algorithme de granulom´etrie(l’ordre de grandeur passe de l’heure `a la minute pour un volume de 10243 voxels). Un mod`eleanalytique permettant d’´etablir les variations de performance de l’application de granulom´etriesur GPU a ´egalement ´et´e d´efini et pourrait ˆetre ´etendu `a d’autres algorithmes r´eguliers.Dans un second temps, un outil facilitant le d´eploiement d’applications de Traitementdu Signal et de l’Image sur cluster multi-GPU a ´et´e d´evelopp´e. Pour cela, le champ d’actiondu programmeur est r´eduit au d´ecoupage du programme en tˆaches et `a leur mapping sur les´el´ements de calcul (GPP ou GPU). L’am´elioration notable du d´ebit sortant d’une applicationstreaming de calcul de carte de saillence visuelle a d´emontr´e l’efficacit´e de notre outil pourl’impl´ementation d’une solution sur cluster multi-GPU. Afin de permettre un ´equilibrage decharge dynamique, une m´ethode de migration de tˆaches a ´egalement ´et´e incorpor´ee `a l’outil. / Originally designed to relieve the CPU from graphics rendering tasks, the GPU has becomea massively parallel architecture suitable for processing large amounts of data. While it haswon a significant market share in the High Performance Computing domain, an Algorithm-Architecture Matching approach is still necessary to efficiently implement an algorithm onGPU.The contribution of this thesis is twofold. Firstly, we present the significant gain providedby the implementation of a granulometry optimized algorithm (computation time decreasesfrom several hours to less than minute for a volume of 10243 voxels). An analytical modelestablishing the performance variations of the granulometry application is also presented. Webelieve it can be expanded to other regular algorithms.Secondly, the deployment of Signal and Image processing applications on multi-GPUcluster can be a tedious task for the programmer. In order to help him, we developped alibrary that reduces the scope of the programmer’s contribution in the development. Hisremaining tasks are decomposing the application into a Data Flow Graph and giving mappingannotations in order for the tool to automatically dispatch tasks on the processing elements(GPP or GPU). The throughput of a visual sailency streaming application is then improvedthanks to the efficient implementation brought by our tool on a multi-GPU cluster. In orderto permit dynamic load balancing, a task migration method has also been incorporated into it.

Dans cette thèse nous étudions l’isolation mémoire et les mesures de communications efficaces par passage de message dans le contexte des environnements à mémoire partagée et la programmation orientée-objets. L’état de l’art en la matière se base presque exclusivement sur deux techniques complémentaires dites de propriété des objets (ownership) et d’unicité de références (reference uniqueness) afin d’adresser les problèmes de sécurité dans les programmes concurrents. Il est frappant de constater que la grande majorité des travaux existants emploient des méthodes de vérification statique des programmes, qui requirent soit un effort d’annotations soit l’introduction de fortes contraintes sur la forme et les références vers messages échangés. Notre contribution avec SIAAM est la démonstration d’une solution d’isolation réalisée uniquement à l’exécution et basée sur le modèle de programmation par acteurs. Cette solution purement dynamique ne nécessite ni annotations ni vérification statique des programmes. SIAAM permet la communication sans copie de messages de forme arbitraire. Nous présentons la sémantique formelle de SIAAM ainsi qu’une preuve d’isolation vérifiée avec l’assistant COQ. L’implantation du modèle de programmation pour le langage Java est réalisé dans la machine virtuelle JikesRVM. Enfin nous décrivons un ensemble d’analyses statiques qui réduit automatiquement le cout à l’exécution de notre approche. / In this thesis we study state isolation and efficient message-passing in the context of concurrent object-oriented programming. The ’ownership’ and ’reference uniqueness’ techniques have been extensively employed to address concurrency safety in the past. Strikingly the vast majority of the previous works rely on a set of statically checkable typing rules, either requiring an annotation overhead or introducing strong restrictions on the shape and the aliasing of the exchanged messages.Our contribution with SIAAM is the demonstration of a purely runtime, actor-based, annotation-free, aliasing-proof approach to concurrent state isolation allowing efficient communication of arbitrary objects graphs. We present the formal semantic of SIAAM, along with a machine-checked proof of isolation. An implementation of the model has been realized in a state-of-the-art Java virtual-machine and a set of custom static analyses automatically reduce the runtime overhead.