Devido à complexidade das aplicações, a demanda crescente por sistemas que usam milhões de transistores e hardware complexo; tem sido desenvolvidas ferramentas que convertem C em Linguagem de Descrição de Hardware, tais como VHDL e Verilog. Neste contexto, esta tese apresenta o projeto ChipCflow, o qual usa arquitetura a fluxo de dados, para implementar lógica de alto desempenho em Field Programmable Gate Array (FPGA). Maquinas a fluxo de dados são computadores programáveis, cujo hardware é otimizado para computação paralela de granularidade fina dirigida por dados. Em outras palavras, a execução de programas é determinado pela disponibilidade dos dados, assim, o paralelismo é intrínseco neste sistema. Por outro lado, com o avanço da tecnologia da microeletrônica, o FPGA tem sido utilizado principalmente devido a sua flexibilidade, facilidade para implementar sistemas complexos e paralelismo intrínseco. Um dos desafios é criar ferramentas para programadores que usam linguagem de alto nível (HLL), como a linguagem C, e produzir hardware diretamente. Essas ferramentas devem usar a máxima experiência dos programadores, o paralelismo das arquiteturas a fluxo de dados dinâmica, a flexibilidade e o paralelismo do FPGA, para produzir um hardware eficiente, otimizado para alto desempenho e baixo consumo de energia. O projeto ChipCflow é uma ferramenta que converte os programas de aplicação escritos em linguagem C para a linguagem VHDL, baseado na arquitetura a fluxo de dados dinâmica. O principal objetivo dessa tese é definir e implementar os operadores do ChipCflow, usando a arquitetura a fluxo de dados dinâmica em FPGA. Esses operadores usam tagged tokens para identificar dados, com base em instâncias de operadores. A implementação dos operadores e das instâncias usam um modelo de implementação assíncrono em FPGA para obter maior velocidade e menor consumo / Due to the complexity of applications, the growing demand for both systems using millions of transistors and consecutive complex hardware, tools that convert C into a Hardware Description Language (HDL), as VHDL and Verilog, have been developed. In this context this thesis presents the ChipCflow project, which uses dataflow architecture to implement high-performance logics in Field Programmable Gate Array (FPGA). Dataflow machines are programmable computers whose hardware is optimized for fine-grain data-flow parallel computation. In other words the execution of programs is determined by data availability, thus parallelism is intrinsic in these systems. On the other hand, with the advance of technology of microelectronics, the FPGA has been used mainly because of its flexibility, facilities to implement complex systems and intrinsic parallelism. One of the challenges is to create tools for programmers who use HLL (High Level Language), such as C language, producing hardware directly. These tools should use the utmost experience of the programmers, the parallelism of dynamic dataflow architecture and the flexibility and parallelism of FPGA to produce efficient hardware optimized for high performance and lower power consumption. The ChipCflow project is a tool that converts application programs written in C language into VHDL, based on the dynamic dataflow architecture. The main goal in this thesis is to define and implement the operators of ChipCflow using dynamic dataflow architecture in FPGA. These operators use tagged tokens to identify data based on instances of operators and their implementation and instances use an asynchronous implementation model in FPGA to achieve faster speed and lower consumption

In this paper we present a dataflow processor architecture based on [1], which is driven by controlflow generated tokens. We will show the special properties of this architecture with regard to scalability, extensibility, and parallelism. In this context we outline the application scope and compare our approach with related work. Advantages and disadvantages will be discussed and we suggest solutions to solve the disadvantages. Finally an example of the implementation of this architecture will be given and we have a look at further developments. We believe the features of this basic approach predestines the architecture especially for embedded systems and system on chips.

Research into modular approaches for constructing power electronics control systems has provided a number of benefits, as well as new opportunities. Control systems composed of an interconnected collection of standardized parts makes distributed processing a realistic possibility. Unfortunately, current strategies to supporting software on such systems have a number of critical drawbacks. Many existing approaches rely on centralized control strategies, fail to support fault tolerance in the face of failures among processing nodes or communications links, and fail to robustly support live addition or removal of nodes from a running network. In this context, failure of a single element means failure of the entire system. This thesis describes research to extend the Dataflow Architecture Real-time Kernel (DARK) to support distributed, fault-tolerant execution of control algorithms for power electronics control systems. An appropriate scheme for fault-tolerant scheduling of processes on distributed processing nodes is described, added to DARK, and evaluated. Literature indicates that fault-tolerant multiprocessor scheduling for hard real-time tasks with task precedence constraints is an NP-hard problem. The new system is based on an off-line fault-tolerant scheduling strategy that generates a static schedule of tasks for each processing unit to follow. This algorithm handles both the task precedence constraints and the constraints imposed by the underlying network protocol(DRPESNET). Modifications to the underlying daisy-chained, packet-switched, time-triggered ring network protocol to support communications fault tolerance and plug-and-play addition or removal of live nodes from an existing control system are also described. / Master of Science