With the current demand for mixed-signal SoCs, an increasing number of designers are looking for ADC architectures that can be easily implemented over digital substrates. Since ADC performance is strongly dependent upon physical and electrical features, it gets more difficult for them to benefit from more recent technologies, where these features are more variable. This way, analog signal acquisition is not allowed to follow an evolutionary trend compatible with Moore’s Law. In fact, such trend shall get worst, since newer technologies are expected to have more variable characteristics. Also, for a matter of economy of scale, many times a mixed-signal SoC presents a good amount of idle processing power. In such systems it is advantageous to employ more costly digital signal processing provided that it allows a reduction in the analog area demanded or the use of less expensive analog blocks, able to cope with process variations and uncertainty. Besides the technological concerns, other factors that impact the cost of the design also advise to transfer problems from the analog to the digital domain whenever possible: design automation and self-test requirements, for instance. Recent surveys indicate that the total cost in designer hours for the analog blocks of a mixed-signal system can be up to three times the cost of the digital ones. This manuscript explores the concept of bottom-up analog acquisition design, using statistical sampling as a way to reduce the analog area demanded in the design of ADCs within mixed-signal systems. More particularly, it investigates the possibility of using digital modeling and digital compensation of non-idealities to ease the design of ADCs. The work is developed around three axes: the definition of target applications, the development of digital compensation algorithms and the exploration of architectural possibilities. New methods and architectures are defined and validated. The main notions behind the proposal are analyzed and it is shown that the approach is feasible, opening new paths of future research. Keywords:

Este trabalho propõe uma nova abordagem para o desenvolvimento de sistemas embarcados, através da combinação da abstração e propriedades de verificação de modelos da linguagem declarativa Alloy com a ampla aceitação de Java na indústria. A abordagem surge no contexto de que a automação de software no domínio embarcado tornou-se extremamente necessária, uma vez que atualmente a maior parte do tempo de desenvolvimento é gasta no projeto de software de produtos tão restritos em termos de recursos. As ferramentas de automação de software embarcado devem atender a demanda por produtividade e manutenibilidade, mas respeitar restrições naturais deste tipo de sistema, tais como espaço de memória, potência e desempenho. As ferramentas de automação de projeto lidam com produtividade e manutenibilidade ao permitir especificações de alto nível, tarefa difícil de atender no domínio embarcado devido ao comportamento misto de muitas aplicações embarcadas. Abordagens que promovem meios para verificação formal também são atrativas, embora geralmente sejam difíceis de usar, e por este motivo não são de grande auxílio na tarefa de reduzir o tempo de chegada ao mercado do produto. Através do uso de Alloy, baseada em lógica de primeira-ordem, é possível obter especificações em altonível e verificação formal de modelos com uma única linguagem. Este trabalho apresenta a poderosa abstração proporcionada pela linguagem Alloy em aplicações embarcadas, assim como regras para obter automaticamente código Java a partir de modelos Alloy. A geração de código Java a partir de modelos Alloy, combinada a uma ferramenta de estimativa, provê exploração de espaço de projeto, atendendo assim as fortes restrições do projeto de software embarcado, o que normalmente não é contemplado pela engenharia de software tradicional. / This work proposes a new approach for embedded software development, by combining the abstraction and model verification properties of the Alloy declarative language with the broad acceptance in industry of Java. The approach comes into play since software automation in the embedded domain has become a major need, as currently most of the development time is spent designing software for such hardconstrained resources products. Design automation tools for embedded systems must meet the demand for productivity and maintainability, but constraints such as memory, power and performance must still be considered. Design automation tools deal with productivity and maintainability by allowing high-level specifications, which is hard to accomplish on the embedded domain due to the mixed behavior nature of many embedded applications. Approaches that provide means for formal verification are also attractive, but their usage is usually not straightforward, and for this reason they are not that helpful in dealing with time-tomarket constraints. By using Alloy, based in first-order logic, it is possible to obtain high-level specifications and formal model verification with a single language. This work shows the powerful abstraction provided by the Alloy language for embedded applications, as well as rules for obtaining automatically Java code from Alloy models. The Java source code generation from Alloy models, combined with an estimation tool, provides design space exploration to match tight embedded software design constraints, what is usually not taken into account by standard software engineering techniques.

Dans le domaine du calcul générique, les circuits FPGA sont très attrayants pour leur performance et leur faible consommation. Cependant, leur présence reste marginale, notamment à cause des limitations des logiciels de développement actuels. En effet, ces limitations obligent les utilisateurs à bien maîtriser de nombreux concepts techniques. Ils obligent à diriger manuellement les processus de synthèse, de façon à obtenir une solution à la fois rapide et conforme aux contraintes des cibles matérielles visées.Une nouvelle méthodologie de génération basée sur la synthèse d'architecture est proposée afin de repousser ces limites. L'exploration des solutions consiste en l'application de transformations itératives à un circuit initial, ce qui accroît progressivement sa rapidité et sa consommation en ressources. La rapidité de ce processus, ainsi que sa convergence sous contraintes de ressources, sont ainsi garanties. L'exploration est également guidée vers les solutions les plus pertinentes grâce à la détection, dans les applications à synthétiser, des sections les plus critiques pour le contexte d'utilisation réel. Cette information peut être affinée à travers un scénario d'exécution transmis par l'utilisateur.Un logiciel démonstrateur pour cette méthodologie, AUGH, est construit. Des expérimentations sont menées sur plusieurs applications reconnues dans le domaine de la synthèse d'architecture. De tailles très différentes, ces applications confirment la pertinence de la méthodologie proposée pour la génération rapide et autonome d'accélérateurs matériels complexes, sous des contraintes de ressources strictes. La méthodologie proposée est très proche du processus de compilation pour les microprocesseurs, ce qui permet son utilisation même par des utilisateurs non spécialistes de la conception de circuits numériques. Ces travaux constituent donc une avancée significative pour une plus large adoption des FPGA comme accélérateurs matériels génériques, afin de rendre les machines de calcul simultanément plus rapides et plus économes en énergie. / In the field of high-performance computing, FPGA circuits are very attractive for their performance and low consumption. However, their presence is still marginal, mainly because of the limitations of current development tools. These limitations force the user to have expert knowledge about numerous technical concepts. They also have to manually control the synthesis processes in order to obtain solutions both fast and that fulfill the hardware constraints of the targeted platforms.A novel generation methodology based on high-level synthesis is proposed in order to push these limits back. The design space exploration consists in the iterative application of transformations to an initial circuit, which progressively increases its rapidity and its resource consumption. The rapidity of this process, along with its convergence under resource constraints, are thus guaranteed. The exploration is also guided towards the most pertinent solutions thanks to the detection of the most critical sections of the applications to synthesize, for the targeted execution context. This information can be refined with an execution scenarion specified by the user.A demonstration tool for this methodology, AUGH, has been built. Experiments have been conducted with several applications known in the field of high-level synthesis. Of very differen sizes, these applications confirm the pertinence of the proposed methodology for fast and automatic generation of complex hardware accelerators, under strict resource constraints. The proposed methodology is very close to the compilation process for microprocessors, which enable it to be used even by users non experts about digital circuit design. These works constitute a significant progress for a broader adoption of FPGA as general-purpose hardware accelerators, in order to make computing machines both faster and more energy-saving.

Heutzutage sind wir von Geräten umgeben, die sowohl Hardware wie auch Software- Komponenten beinhalten. Diese Geräte unterstützen ein breites Spektrum an verschiedenen Domänen, so zum Beispiel Telekommunikation, Luftfahrt, Automobil und andere. Derartige Systeme sind überall aufzufinden und werden als Eingebettete Systeme bezeichnet, da sie zur Informationsverarbeitung in andere Produkte eingebettet werden, wobei die Informationsverarbeitung des eingebetteten Systems jedoch nicht die bezeichnende Funktion des Produkts ist. Die ständig zunehmende Komplexität moderner eingebettete Systeme erfordert die Verwendung von mehreren Komponenten um die Funktionen von einem einzelnen System zu implementieren. Eine solche Steigerung der Funktionalität führt jedoch ebenfalls zu einem Wachstum in der Entwurfs-Komplexität, die korrekt und effizient beherrscht werden muss. Neben hohen Anforderungen bezüglich Leistungsaufnahme, Performanz und Kosten hat auch Time-to-Market-Anforderungen großen Einfluss auf den Entwurf von Eingebetteten Systemen. Design Space Exploration (DSE) beschreibt die systematische Erzeugung und Auswertung von Entwurfs-Alternativen, um die Systemleistung zu optimieren und den gestellten Anforderungen an das System zu genügen. Bei der Entwicklung von Eingebetteten Systemen, speziell beim Platform-Based Design (PBD) führt die zunehmende Anzahl von Design-Entscheidungen auf mehreren Abstraktionsebenen zu einer Explosion der möglichen Kombinationen von Alternativen, was auch für aktuelle DSE Methoden eine Herausforderung darstellt. Jedoch vermag üblicherweise nur eine begrenzte Anzahl von Entwurfs-Alternativen die zusätzlich formulierten nicht-funktionalen Anforderungen zu erfüllen. Darüber hinaus beeinflusst jede Entwurfs- Entscheidung weitere Entscheidungen und damit die resultierenden Systemeigenschaften. Somit existieren Abhängigkeiten zwischen Entwurfs-Entscheidungen und deren Reihenfolge auf dem Weg zur Implementierung des Systems. Zudem gilt es zwischen einer spezifischen Heuristik für eine bestimmte DSE, welche zu verbesserten Optimierungsresultaten führt, sowie globalen Verfahren, welche ihrerseits zur Flexibilität hinsichtlich der Anwendbarkeit bei verschiedenen DSE Szenarien beitragen, abzuwägen. Um die genannten Herausforderungen zu lösen wird eine Modellgetriebene Entwicklung (englisch Model-Driven Engineering, kurz MDE) Methodik für DSE vorgeschlagen. Für diese Methodik wird ein DSE-Domain-Metamodell eingeführt um relevante DSEKonzepte wie Entwurfsraum, Entwurfs-Alternativen, Auswertungs- und Bewertungsverfahren, Einschränkungen und andere abzubilden. Darüber hinaus modelliert das Metamodell verschiedenen DSE-Frage- stellungen, was zur Verbesserung der Flexibilität der vorgeschlagenen Methodik beiträgt. Zur Umsetzung von DSE-Regeln, welche zur Steuerung, Einschränkung und Generierung der Ent- wurfs-Alternativen genutzt werden, finden Modell-zu-Modell-Transformationen Anwendung. Durch die Fokussierung auf die Zuordnung zwischen den Schichten in einem PBDAnsatz wird eine neuartige Entwurfsraumabstraktion eingeführt, um multiple Entwurfsentscheidungen als singuläres DSE Problem zu repräsentieren. Diese auf dem Categorial Graph Product aufbauende Abstraktion entkoppelt den Explorations-Algorithmus vom Entwurfsraum und ist für Umsetzung in automatisierte Werkzeugketten gut geeignet. Basierend auf dieser Abstraktion profitiert die DSE-Methode durch die eingeführte MDEMethodik als solche und ermöglicht nunmehr neue Optimierungsmöglichkeiten sowie die Verbesserung der Integration von DSE in Entwicklungsprozesse und die Spezifikation von DSE-Szenarien. / Atualmente dispositivos contendo hardware e software são encontrados em todos os lugares. Estes dispositivos prestam suporte a uma varieadade de domínios, como telecomunicações, automotivo e outros. Eles são chamados “sistemas embarcados”, pois são sistemas de processamento montados dentro de produtos, cujo sistema de processamento não faz parte da funcionalidade principal do produto. O acréscimo de funções nestes sistemas implica no aumento da complexidade de seu projeto, o qual deve ser adequadamente gerenciado, pois além de requisitos rigorosos em relação à dissipação de potência, desempenho e custos, a pressão sobre o prazo para introdução de um produto no mercado também dificulta seu projeto. Exploração do espaço de projeto (DSE) é a atividade sistemática de gerar e avaliar alternativas de projetos, com o objetivo de otimizar suas propriedades. No desenvolvimento de sistemas embarcados, especialmente em Projeto Baseado em Plataformas (PBD), metodologias de DSE atuais são desafiadas pelo crescimento do número de decisões de projeto, o qual implica na explosão da combinação de alternativas. Porém, somente algumas destas resultam em projetos que atedem os requisitos nãofuncionais. Além disso, as decisões influenciam umas às outras, de forma que a ordem em que estas são tomadas alteram a implementação final do sistema. Outro desafio é o balanço entre flexibilidade da metodologia e seu desempenho, pois métodos globais de otimização são flexíveis, mas apresentam baixo desempenho. Já heurísticas especialmente desenvolvidas para o cenário de DSE em questão apresentam melhor desempenho, porém dificilmente são aplicáveis a diferentes cenários. Com o intuito de superar os desafios é proposta uma metodologia de projeto dirigido por modelos (MDE) adquada para DSE. Um metamodelo do domínio de DSE é definido para representar conceitos como espaço de projeto, métodos de avaliação e restrições. O metamodelo também representa diferentes problemas de DSE aprimorando a flexibilidade da metodologia. Regras de transformações de modelos implementam as regras de DSE, as quais são utilizadas para restringir e guiar a geração de projetos alternativos. Restringindo-se ao mapeamento entre camadas no PBD é proposta uma abstração para representar o espaço de projeto. Ela representa múltiplas decisões de projeto envolvidas no mapeamento como um único problema de DSE. Esta representação é adequada para a implementação em ferramentas automática de DSE e pode beneficiar o processo de DSE com uma abordagem de MDE, aprimorando a especificação de cenários de DSE e sua integração no processo de desenvolvimento. / Nowadays we are surrounded by devices containing hardware and software components. These devices support a wide spectrum of different domains, such as telecommunication, avionics, automobile, and others. They are found anywhere, and so they are called Embedded Systems, as they are information processing systems embedded into enclosing products, where the processing system is not the main functionality of the product. The ever growing complexity in modern embedded systems requires the utilization of more components to implement the functions of a single system. Such an increasing functionality leads to a growth in the design complexity, which must be managed properly, because besides stringent requirements regarding power, performance and cost, also time-to-market hinders the design of embedded systems. Design Space Exploration (DSE) is the systematic generation and evaluation of design alternatives, in order to optimize system properties and fulfill requirements. In embedded system development, specifically in Platform-Based Design (PBD), current DSE methodologies are challenged by the increasing number of design decisions at multiple abstraction levels, which leads to an explosion of combination of alternatives. However, only a reduced number of these alternatives leads to feasible designs, which fulfill non-functional requirements. Moreover, each design decision influences subsequent decisions and system properties, hence there are inter-dependencies between design decisions, so that the order decisions are made matters to the final system implementation. Furthermore, there is a trade-off between heuristics for specific DSE, which improves the optimization results, and global optimizers, which improve the flexibility to be applied in different DSE scenarios. In order to overcome the identified challenges an MDE methodology for DSE is proposed. For this methodology a DSE Domain metamodel is proposed to represent relevant DSE concepts such as design space, design alternatives, evaluation method, constraints and others. Moreover, this metamodel represents different DSE problems, improving the flexibility of the proposed framework. Model transformations are used to implement DSE rules, which are used to constrain, guide, and generate design candidates. Focusing on the mapping between layers in a PBD approach, a novel design space abstraction is provided to represent multiple design decisions involved in the mapping as a single DSE problem. This abstraction is based on Categorical Graph Product, decoupling the exploration algorithm from the design space and being well suited to be implemented in automatic exploration tools. Upon this abstraction, the DSE method can benefit from the MDE methodology, opening new optimization opportunities, and improving the DSE integration into the development process and specification of DSE scenarios.

Sistemas para análise de imagens partem da premissa de que o conjunto de dados sob investigação está corretamente representado por características. Entretanto, definir quais características representam apropriadamente um conjunto de dados é uma tarefa desafiadora e exaustiva. Grande parte das técnicas de descrição existentes na literatura, especialmente quando os dados têm alta dimensionalidade, são baseadas puramente em medidas estatísticas ou abordagens baseadas em inteligência artificial, e normalmente são caixas-pretas para os usuários. A abordagem proposta nesta dissertação busca abrir esta caixa-preta por meio de representações visuais criadas pela técnica Multidimensional Classical Scaling, permitindo que usuários capturem interativamente a essência sobre a representatividade das características computadas de diferentes descritores. A abordagem é avaliada sobre seis conjuntos de imagens que contém texturas, imagens médicas e cenas naturais. Os experimentos mostram que, conforme a combinação de um conjunto de características melhora a qualidade da representação visual, a acurácia de classificação também melhora. A qualidade das representações é medida pelo índice da silhueta, superando problemas relacionados com a subjetividade de conclusões baseadas puramente em análise visual. Além disso, a capacidade de exploração visual do conjunto sob análise permite que usuários investiguem um dos maiores desafios em classificação de dados: a presença de variação intra-classe. Os resultados sugerem fortemente que esta abordagem pode ser empregada com sucesso como um guia para auxiliar especialistas a explorar, refinar e definir as características que representam apropriadamente um conjunto de imagens / Image analysis systems rely on the fact that the dataset under investigation is correctly represented by features. However, defining a set of features that properly represents a dataset is still a challenging and, in most cases, an exhausting task. Most of the available techniques, especially when a large number of features is considered, are based on purely quantitative statistical measures or approaches based on artificial intelligence, and normally are black-boxes to the user. The approach proposed here seeks to open this black-box by means of visual representations via Multidimensional Classical Scaling projection technique, enabling users to get insight about the meaning and representativeness of the features computed from different feature extraction algorithms and sets of parameters. This approach is evaluated over six image datasets that contains textures, medical images and outdoor scenes. The results show that, as the combination of sets of features and changes in parameters improves the quality of the visual representation, the accuracy of the classification for the computed features also improves. In order to reduce this subjectiveness, a measure called silhouette index, which was originally proposed to evaluate results of clustering algorithms, is employed. Moreover, the visual exploration of datasets under analysis enable users to investigate one of the greatest challenges in data classification: the presence of intra-class variation. The results strongly suggest that our approach can be successfully employed as a guidance to defining and understanding a set of features that properly represents an image dataset

With the current demand for mixed-signal SoCs, an increasing number of designers are looking for ADC architectures that can be easily implemented over digital substrates. Since ADC performance is strongly dependent upon physical and electrical features, it gets more difficult for them to benefit from more recent technologies, where these features are more variable. This way, analog signal acquisition is not allowed to follow an evolutionary trend compatible with Moore’s Law. In fact, such trend shall get worst, since newer technologies are expected to have more variable characteristics. Also, for a matter of economy of scale, many times a mixed-signal SoC presents a good amount of idle processing power. In such systems it is advantageous to employ more costly digital signal processing provided that it allows a reduction in the analog area demanded or the use of less expensive analog blocks, able to cope with process variations and uncertainty. Besides the technological concerns, other factors that impact the cost of the design also advise to transfer problems from the analog to the digital domain whenever possible: design automation and self-test requirements, for instance. Recent surveys indicate that the total cost in designer hours for the analog blocks of a mixed-signal system can be up to three times the cost of the digital ones. This manuscript explores the concept of bottom-up analog acquisition design, using statistical sampling as a way to reduce the analog area demanded in the design of ADCs within mixed-signal systems. More particularly, it investigates the possibility of using digital modeling and digital compensation of non-idealities to ease the design of ADCs. The work is developed around three axes: the definition of target applications, the development of digital compensation algorithms and the exploration of architectural possibilities. New methods and architectures are defined and validated. The main notions behind the proposal are analyzed and it is shown that the approach is feasible, opening new paths of future research. Keywords:

Heutzutage sind wir von Geräten umgeben, die sowohl Hardware wie auch Software- Komponenten beinhalten. Diese Geräte unterstützen ein breites Spektrum an verschiedenen Domänen, so zum Beispiel Telekommunikation, Luftfahrt, Automobil und andere. Derartige Systeme sind überall aufzufinden und werden als Eingebettete Systeme bezeichnet, da sie zur Informationsverarbeitung in andere Produkte eingebettet werden, wobei die Informationsverarbeitung des eingebetteten Systems jedoch nicht die bezeichnende Funktion des Produkts ist. Die ständig zunehmende Komplexität moderner eingebettete Systeme erfordert die Verwendung von mehreren Komponenten um die Funktionen von einem einzelnen System zu implementieren. Eine solche Steigerung der Funktionalität führt jedoch ebenfalls zu einem Wachstum in der Entwurfs-Komplexität, die korrekt und effizient beherrscht werden muss. Neben hohen Anforderungen bezüglich Leistungsaufnahme, Performanz und Kosten hat auch Time-to-Market-Anforderungen großen Einfluss auf den Entwurf von Eingebetteten Systemen. Design Space Exploration (DSE) beschreibt die systematische Erzeugung und Auswertung von Entwurfs-Alternativen, um die Systemleistung zu optimieren und den gestellten Anforderungen an das System zu genügen. Bei der Entwicklung von Eingebetteten Systemen, speziell beim Platform-Based Design (PBD) führt die zunehmende Anzahl von Design-Entscheidungen auf mehreren Abstraktionsebenen zu einer Explosion der möglichen Kombinationen von Alternativen, was auch für aktuelle DSE Methoden eine Herausforderung darstellt. Jedoch vermag üblicherweise nur eine begrenzte Anzahl von Entwurfs-Alternativen die zusätzlich formulierten nicht-funktionalen Anforderungen zu erfüllen. Darüber hinaus beeinflusst jede Entwurfs- Entscheidung weitere Entscheidungen und damit die resultierenden Systemeigenschaften. Somit existieren Abhängigkeiten zwischen Entwurfs-Entscheidungen und deren Reihenfolge auf dem Weg zur Implementierung des Systems. Zudem gilt es zwischen einer spezifischen Heuristik für eine bestimmte DSE, welche zu verbesserten Optimierungsresultaten führt, sowie globalen Verfahren, welche ihrerseits zur Flexibilität hinsichtlich der Anwendbarkeit bei verschiedenen DSE Szenarien beitragen, abzuwägen. Um die genannten Herausforderungen zu lösen wird eine Modellgetriebene Entwicklung (englisch Model-Driven Engineering, kurz MDE) Methodik für DSE vorgeschlagen. Für diese Methodik wird ein DSE-Domain-Metamodell eingeführt um relevante DSEKonzepte wie Entwurfsraum, Entwurfs-Alternativen, Auswertungs- und Bewertungsverfahren, Einschränkungen und andere abzubilden. Darüber hinaus modelliert das Metamodell verschiedenen DSE-Frage- stellungen, was zur Verbesserung der Flexibilität der vorgeschlagenen Methodik beiträgt. Zur Umsetzung von DSE-Regeln, welche zur Steuerung, Einschränkung und Generierung der Ent- wurfs-Alternativen genutzt werden, finden Modell-zu-Modell-Transformationen Anwendung. Durch die Fokussierung auf die Zuordnung zwischen den Schichten in einem PBDAnsatz wird eine neuartige Entwurfsraumabstraktion eingeführt, um multiple Entwurfsentscheidungen als singuläres DSE Problem zu repräsentieren. Diese auf dem Categorial Graph Product aufbauende Abstraktion entkoppelt den Explorations-Algorithmus vom Entwurfsraum und ist für Umsetzung in automatisierte Werkzeugketten gut geeignet. Basierend auf dieser Abstraktion profitiert die DSE-Methode durch die eingeführte MDEMethodik als solche und ermöglicht nunmehr neue Optimierungsmöglichkeiten sowie die Verbesserung der Integration von DSE in Entwicklungsprozesse und die Spezifikation von DSE-Szenarien. / Atualmente dispositivos contendo hardware e software são encontrados em todos os lugares. Estes dispositivos prestam suporte a uma varieadade de domínios, como telecomunicações, automotivo e outros. Eles são chamados “sistemas embarcados”, pois são sistemas de processamento montados dentro de produtos, cujo sistema de processamento não faz parte da funcionalidade principal do produto. O acréscimo de funções nestes sistemas implica no aumento da complexidade de seu projeto, o qual deve ser adequadamente gerenciado, pois além de requisitos rigorosos em relação à dissipação de potência, desempenho e custos, a pressão sobre o prazo para introdução de um produto no mercado também dificulta seu projeto. Exploração do espaço de projeto (DSE) é a atividade sistemática de gerar e avaliar alternativas de projetos, com o objetivo de otimizar suas propriedades. No desenvolvimento de sistemas embarcados, especialmente em Projeto Baseado em Plataformas (PBD), metodologias de DSE atuais são desafiadas pelo crescimento do número de decisões de projeto, o qual implica na explosão da combinação de alternativas. Porém, somente algumas destas resultam em projetos que atedem os requisitos nãofuncionais. Além disso, as decisões influenciam umas às outras, de forma que a ordem em que estas são tomadas alteram a implementação final do sistema. Outro desafio é o balanço entre flexibilidade da metodologia e seu desempenho, pois métodos globais de otimização são flexíveis, mas apresentam baixo desempenho. Já heurísticas especialmente desenvolvidas para o cenário de DSE em questão apresentam melhor desempenho, porém dificilmente são aplicáveis a diferentes cenários. Com o intuito de superar os desafios é proposta uma metodologia de projeto dirigido por modelos (MDE) adquada para DSE. Um metamodelo do domínio de DSE é definido para representar conceitos como espaço de projeto, métodos de avaliação e restrições. O metamodelo também representa diferentes problemas de DSE aprimorando a flexibilidade da metodologia. Regras de transformações de modelos implementam as regras de DSE, as quais são utilizadas para restringir e guiar a geração de projetos alternativos. Restringindo-se ao mapeamento entre camadas no PBD é proposta uma abstração para representar o espaço de projeto. Ela representa múltiplas decisões de projeto envolvidas no mapeamento como um único problema de DSE. Esta representação é adequada para a implementação em ferramentas automática de DSE e pode beneficiar o processo de DSE com uma abordagem de MDE, aprimorando a especificação de cenários de DSE e sua integração no processo de desenvolvimento. / Nowadays we are surrounded by devices containing hardware and software components. These devices support a wide spectrum of different domains, such as telecommunication, avionics, automobile, and others. They are found anywhere, and so they are called Embedded Systems, as they are information processing systems embedded into enclosing products, where the processing system is not the main functionality of the product. The ever growing complexity in modern embedded systems requires the utilization of more components to implement the functions of a single system. Such an increasing functionality leads to a growth in the design complexity, which must be managed properly, because besides stringent requirements regarding power, performance and cost, also time-to-market hinders the design of embedded systems. Design Space Exploration (DSE) is the systematic generation and evaluation of design alternatives, in order to optimize system properties and fulfill requirements. In embedded system development, specifically in Platform-Based Design (PBD), current DSE methodologies are challenged by the increasing number of design decisions at multiple abstraction levels, which leads to an explosion of combination of alternatives. However, only a reduced number of these alternatives leads to feasible designs, which fulfill non-functional requirements. Moreover, each design decision influences subsequent decisions and system properties, hence there are inter-dependencies between design decisions, so that the order decisions are made matters to the final system implementation. Furthermore, there is a trade-off between heuristics for specific DSE, which improves the optimization results, and global optimizers, which improve the flexibility to be applied in different DSE scenarios. In order to overcome the identified challenges an MDE methodology for DSE is proposed. For this methodology a DSE Domain metamodel is proposed to represent relevant DSE concepts such as design space, design alternatives, evaluation method, constraints and others. Moreover, this metamodel represents different DSE problems, improving the flexibility of the proposed framework. Model transformations are used to implement DSE rules, which are used to constrain, guide, and generate design candidates. Focusing on the mapping between layers in a PBD approach, a novel design space abstraction is provided to represent multiple design decisions involved in the mapping as a single DSE problem. This abstraction is based on Categorical Graph Product, decoupling the exploration algorithm from the design space and being well suited to be implemented in automatic exploration tools. Upon this abstraction, the DSE method can benefit from the MDE methodology, opening new optimization opportunities, and improving the DSE integration into the development process and specification of DSE scenarios.

Com os grandes avanços recentes dos sistemas computacionais, houve a possibilidade de ascensão de dispositivos inovadores, como os modernos telefones celulares e tablets com telas sensíveis ao toque. Para gerenciar adequadamente estas diversas interfaces é necessário utilizar o software dependente do hardware (HdS), que é responsável pelo controle e acesso a estes dispositivos. Além deste complexo arranjo de componentes, para atender a crescente demanda por mais funcionalidades integradas, o paradigma de multiprocessamento vem sendo adotado para aumentar o desempenho das plataformas. Devido à lacuna de produtividade de sistemas, tanto a indústria como a academia têm pesquisado processos mais eficientes para construir e simular sistemas cada vez mais complexos. A premissa dos trabalhos do estado da arte está em trabalhar com modelos com alto nível de abstração e de precisão que permitam ao projetista avaliar rapidamente o sistema, sem ter que depender de lentos e complexos modelos baseados em ISS. Neste trabalho é definido um conjunto de construtores para modelagem de plataformas baseadas em processadores, com suporte para desenvolvimento de HdS e reusabilidade dos componentes, técnicas para estimativa estática de tempo simulado em ambiente nativo de simulação e suporte para plataformas multiprocessadas. Foram realizados experimentos com aplica- ções de entrada e saída intensiva, computação intensiva e multiprocessada, com ganho médio de desempenho da ordem de 1.000 vezes e precisão de estimativas com erro médio inferior a 3%, em comparação com uma plataforma de referência baseada em ISS._________________________________________________________________________________________ ABSTRACT: The amazing advances of computer systems technology enabled the rise of innovative devices, such as modern touch sensitive cell phones and tablets. To properly manage these various interfaces, it is required the use of the Hardwaredependent Software (HdS) that is responsible for these devices control and access. Besides this complex arrangement of components, to meet the growing demand for more integrated features, the multiprocessing paradigm has been adopted to increase the platforms performance. Due to the system design gap, both industry and academia have been researching for more efficient processes to build and simulate systems with this increasingly complexity. The premise of the state of art works is the development of high level of abstraction and precise models to enable the designer to quickly evaluate the system, without having to rely on slow and complex models based on instruction set simulators (ISS). This work defined a set of constructors for processor-based platforms modeling, supporting HdS development and components reusability, techniques for static simulation timing estimation in native environment and support for multiprocessor platforms. Experiments were carried out with input and output intensive, compute intensive and multiprocessed applications leading to an average performance speed up of about 1,000 times and average timing estimation accuracy of less than 3%, when compared with a reference platform based on ISS.

Ce manuscrit présente une méthode de conception au niveau système reposant sur la programmation fonctionnelle typée et visant à atténuer certains des problèmes complexifiant le développement des systèmes numériques modernes, tels que leurs tailles importantes ou la grande variété des blocs les constituant. Nous proposons un ensemble de mécanismes permettant de mélanger au sein d'un même design plusieurs formalismes de description distincts («modèles de calcul») se situant potentiellement à des niveaux d'abstraction différents. De plus, nous offrons au concepteur la possibilité d'expliciter directement les paramètres explorables de chaque sous-partie du design, puis d'en déterminer des valeurs acceptables via une étape d'exploration partiellement ou totalement automatisée réalisée à l'échelle du système. Les gains qu'apportent ces stratégies nouvelles sont illustrés sur plusieurs exemples. / This work presents a novel system-level design method based on typed functional programming and aiming at mitigating some of the issues making the development of modern digital systems complex, such as their increasing sizes and the variety of their subcomponents. We propose a range of mechanisms allowing to mix within a single design several description formalisms (``models of computation''), possibly at different abstraction levels. Moreover, the designer is provided with means to directly express the explorable parameters of each part of their design, and to find acceptable values for them through a partially or totally automatic system-wide architectural exploration step. The advantages brought by those new strategies are illustrated on several examples.

Devido ao grande número de otimizações fornecidas pelos compiladores modernos e à ampla possibilidade de ordenação dessas transformações, uma eficiente Exploração do Espaço de Projeto (DSE) se faz necessária para procurar a melhor sequência de otimização de uma determinada função ou fragmento de código. Como esta exploração é uma tarefa complexa e dispendiosa, apresentamos uma nova abordagem de DSE capaz de reduzir esse tempo de exploração e selecionar sequências de otimização que melhoraram o desempenho dos códigos transformados. Nossa abordagem utiliza um conjunto de funções de referência, para as quais uma representação simbólica do código (DNA) e a melhor sequência de otimização são conhecidas. O DSE de novas funções é baseado em uma abordagem de agrupamento aplicado sobre o código DNA que identifica similaridades entre funções. O agrupamento utiliza três técnicas para a mineração de dados: distância de compressão normalizada, algoritmo de reconstrução de árvores filogenéticas (Neighbor Joining) e identificação de grupos por ambiguidade. As otimizações das funções de referência identificadas como similares formam o espaço que é explorado para encontrar a melhor sequência para a nova função. O DSE pode utilizar o conjunto reduzido de otimizações de duas formas: como o espaço de projeto ou como a configuração inicial do algoritmo. Em ambos os casos, a adoção de uma pré-seleção baseada no agrupamento permite o uso de algoritmos de busca simples e rápidos. Os resultados experimentais revelam que a nova abordagem resulta numa redução significativa no tempo total de exploração, ao mesmo tempo que alcança um desempenho próximo ao obtido através de uma busca mais extensa e dispendiosa baseada em algoritmos genéticos. / Due to the large number of optimizations provided in modern compilers and to compiler optimization specific opportunities, a Design Space Exploration (DSE) is necessary to search for the best sequence of compiler optimizations for a given code fragment (e.g., function). As this exploration is a complex and time consuming task, we present new DSE strategies to reduce the exploration time and still select optimization sequences able to improve the performance of each function. The DSE is based on a clustering approach which groups functions with similarities and then explore the reduced search space provided by the optimizations previously suggested for the functions in each group. The identification of similarities between functions uses a data mining method which is applied to a symbolic representation of the source code. The DSE strategies uses the reduced optimizations set identified by clustering in two ways: as the design space or as the initial configuration of the algorithm. In both ways, the adoption of a pre-selection based on clustering allows the use of simple and fast DSE algorithms. Several experiments for evaluating the effectiveness of the proposed approach address the exploration of compiler optimization sequences. Besides, we investigate the impact of each technique or component employed in the selection process. Experimental results reveal that the use of our new clustering-based DSE approach achieved a significant reduction on the total exploration time of the search space at the same time that obtained performance speedups close to a traditional genetic algorithmbased approach.