22 resultados para Fpga

em Universidade Federal do Rio Grande do Norte(UFRN)


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This study shows the implementation and the embedding of an Artificial Neural Network (ANN) in hardware, or in a programmable device, as a field programmable gate array (FPGA). This work allowed the exploration of different implementations, described in VHDL, of multilayer perceptrons ANN. Due to the parallelism inherent to ANNs, there are disadvantages in software implementations due to the sequential nature of the Von Neumann architectures. As an alternative to this problem, there is a hardware implementation that allows to exploit all the parallelism implicit in this model. Currently, there is an increase in use of FPGAs as a platform to implement neural networks in hardware, exploiting the high processing power, low cost, ease of programming and ability to reconfigure the circuit, allowing the network to adapt to different applications. Given this context, the aim is to develop arrays of neural networks in hardware, a flexible architecture, in which it is possible to add or remove neurons, and mainly, modify the network topology, in order to enable a modular network of fixed-point arithmetic in a FPGA. Five synthesis of VHDL descriptions were produced: two for the neuron with one or two entrances, and three different architectures of ANN. The descriptions of the used architectures became very modular, easily allowing the increase or decrease of the number of neurons. As a result, some complete neural networks were implemented in FPGA, in fixed-point arithmetic, with a high-capacity parallel processing

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This work proposes hardware architecture, VHDL described, developed to embedded Artificial Neural Network (ANN), Multilayer Perceptron (MLP). The present work idealizes that, in this architecture, ANN applications could easily embed several different topologies of MLP network industrial field. The MLP topology in which the architecture can be configured is defined by a simple and specifically data input (instructions) that determines the layers and Perceptron quantity of the network. In order to set several MLP topologies, many components (datapath) and a controller were developed to execute these instructions. Thus, an user defines a group of previously known instructions which determine ANN characteristics. The system will guarantee the MLP execution through the neural processors (Perceptrons), the components of datapath and the controller that were developed. In other way, the biases and the weights must be static, the ANN that will be embedded must had been trained previously, in off-line way. The knowledge of system internal characteristics and the VHDL language by the user are not needed. The reconfigurable FPGA device was used to implement, simulate and test all the system, allowing application in several real daily problems

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This work treats of an implementation OFDMA baseband processor in hardware for LTE Downlink. The LTE or Long Term Evolution consist the last stage of development of the technology called 3G (Mobile System Third Generation) which offers an increasing in data rate and more efficiency and flexibility in transmission with application of advanced antennas and multiple carriers techniques. This technology applies in your physical layer the OFDMA technical (Orthogonal Frequency Division Multiple Access) for generation of signals and mapping of physical resources in downlink and has as base theoretical to OFDM multiple carriers technique (Orthogonal Frequency Division Multiplexing). With recent completion of LTE specifications, different hardware solutions have been developed, mainly, to the level symbol processing where the implementation of OFDMA processor in base band is commonly considered, because it is also considered a basic architecture of others important applications. For implementation of processor, the reconfigurable hardware offered by devices as FPGA are considered which shares not only to meet the high requirements of flexibility and adaptability of LTE as well as offers possibility of an implementation quick and efficient. The implementation of processor in reconfigurable hardware meets the specifications of LTE physical layer as well as have the flexibility necessary for to meet others standards and application which use OFDMA processor as basic architecture for your systems. The results obtained through of simulation and verification functional system approval the functionality and flexibility of processor implemented

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The use of Field Programmable Gate Array (FPGA) for development of digital control strategies for power electronics applications has aroused a growing interest of many researchers. This interest is due to the great advantages offered by FPGA, which include: lower design effort, high performance and highly flexible prototyping. This work proposes the development and implementation of an unified one-cycle controller for boost CFP rectifier based on FPGA. This controller can be applied to a total of twelve converters, six inverters and six rectifiers defined by four single phase VSI topologies and three voltage modulation types. The topologies considered in this work are: full-bridge, interleaved full-bridge, half-bridge and interleaved half-bridge. While modulations are classified in bipolar voltage modulation (BVM), unipolar voltage modulation (UVM) and clamped voltage modulation (CVM). The proposed project is developed and prototyped using tools Matlab/Simulink® together with the DSP Builder library provided by Altera®. The proposed controller was validated with simulation and experimental results

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The Reconfigurable Computing is an intermediate solution at the resolution of complex problems, making possible to combine the speed of the hardware with the flexibility of the software. An reconfigurable architecture possess some goals, among these the increase of performance. The use of reconfigurable architectures to increase the performance of systems is a well known technology, specially because of the possibility of implementing certain slow algorithms in the current processors directly in hardware. Amongst the various segments that use reconfigurable architectures the reconfigurable processors deserve a special mention. These processors combine the functions of a microprocessor with a reconfigurable logic and can be adapted after the development process. Reconfigurable Instruction Set Processors (RISP) are a subgroup of the reconfigurable processors, that have as goal the reconfiguration of the instruction set of the processor, involving issues such formats, operands and operations of the instructions. This work possess as main objective the development of a RISP processor, combining the techniques of configuration of the set of executed instructions of the processor during the development, and reconfiguration of itself in execution time. The project and implementation in VHDL of this RISP processor has as intention to prove the applicability and the efficiency of two concepts: to use more than one set of fixed instructions, with only one set active in a given time, and the possibility to create and combine new instructions, in a way that the processor pass to recognize and use them in real time as if these existed in the fixed set of instruction. The creation and combination of instructions is made through a reconfiguration unit, incorporated to the processor. This unit allows the user to send custom instructions to the processor, so that later he can use them as if they were fixed instructions of the processor. In this work can also be found simulations of applications involving fixed and custom instructions and results of the comparisons between these applications in relation to the consumption of power and the time of execution, which confirm the attainment of the goals for which the processor was developed

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Reverberation is caused by the reflection of the sound in adjacent surfaces close to the sound source during its propagation to the listener. The impulsive response of an environment represents its reverberation characteristics. Being dependent on the environment, reverberation takes to the listener characteristics of the space where the sound is originated and its absence does not commonly sounds like “natural”. When recording sounds, it is not always possible to have the desirable characteristics of reverberation of an environment, therefore methods for artificial reverberation have been developed, always seeking a more efficient implementations and more faithful to the real environments. This work presents an implementation in FPGAs (Field Programmable Gate Arrays ) of a classic digital reverberation audio structure, based on a proposal of Manfred Schroeder, using sets of all-pass and comb filters. The developed system exploits the use of reconfigurable hardware as a platform development and implementation of digital audio effects, focusing on the modularity and reuse characteristics

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This work proposes the use of the behavioral model of the hysteresis loop of the ferroelectrics capacitor as a new alternative to the usually costly techniques in the computation of nonlinear functions in artificial neurons implemented on reconfigurable hardware platform, in this case, a FPGA device. Initially the proposal has been validated by the implementation of the boolean logic through the digital models of two artificial neurons: the Perceptron and a variation of the model Integrate and Fire Spiking Neuron, both using the model also digital of the hysteresis loop of the ferroelectric capacitor as it’s basic nonlinear unit for the calculations of the neurons outputs. Finally, it has been used the analog model of the ferroelectric capacitor with the goal of verifying it’s effectiveness and possibly the reduction of the number of necessary logic elements in the case of implementing the artificial neurons on integrated circuit. The implementations has been carried out by Simulink models and the synthesizing has been done through the DSP Builder software from Altera Corporation.

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The number of applications based on embedded systems grows significantly every year, even with the fact that embedded systems have restrictions, and simple processing units, the performance of these has improved every day. However the complexity of applications also increase, a better performance will always be necessary. So even such advances, there are cases, which an embedded system with a single unit of processing is not sufficient to achieve the information processing in real time. To improve the performance of these systems, an implementation with parallel processing can be used in more complex applications that require high performance. The idea is to move beyond applications that already use embedded systems, exploring the use of a set of units processing working together to implement an intelligent algorithm. The number of existing works in the areas of parallel processing, systems intelligent and embedded systems is wide. However works that link these three areas to solve any problem are reduced. In this context, this work aimed to use tools available for FPGA architectures, to develop a platform with multiple processors to use in pattern classification with artificial neural networks

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The semiconductor technologies evolutions leads devices to be developed with higher processing capability. Thus, those components have been used widely in more fields. Many industrial environment such as: oils, mines, automotives and hospitals are frequently using those devices on theirs process. Those industries activities are direct related to environment and health safe. So, it is quite important that those systems have extra safe features yield more reliability, safe and availability. The reference model eOSI that will be presented by this work is aimed to allow the development of systems under a new view perspective which can improve and make simpler the choice of strategies for fault tolerant. As a way to validate the model na architecture FPGA-based was developed.

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RFID (Radio Frequency Identification) identifies object by using the radio frequency which is a non-contact automatic identification technique. This technology has shown its powerful practical value and potential in the field of manufacturing, retailing, logistics and hospital automation. Unfortunately, the key problem that impacts the application of RFID system is the security of the information. Recently, researchers have demonstrated solutions to security threats in RFID technology. Among these solutions are several key management protocols. This master dissertations presents a performance evaluation of Neural Cryptography and Diffie-Hellman protocols in RFID systems. For this, we measure the processing time inherent in these protocols. The tests was developed on FPGA (Field-Programmable Gate Array) platform with Nios IIr embedded processor. The research methodology is based on the aggregation of knowledge to development of new RFID systems through a comparative analysis between these two protocols. The main contributions of this work are: performance evaluation of protocols (Diffie-Hellman encryption and Neural) on embedded platform and a survey on RFID security threats. According to the results the Diffie-Hellman key agreement protocol is more suitable for RFID systems

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Blind Source Separation (BSS) refers to the problem of estimate original signals from observed linear mixtures with no knowledge about the sources or the mixing process. Independent Component Analysis (ICA) is a technique mainly applied to BSS problem and from the algorithms that implement this technique, FastICA is a high performance iterative algorithm of low computacional cost that uses nongaussianity measures based on high order statistics to estimate the original sources. The great number of applications where ICA has been found useful reects the need of the implementation of this technique in hardware and the natural paralelism of FastICA favors the implementation of this algorithm on digital hardware. This work proposes the implementation of FastICA on a reconfigurable hardware platform for the viability of it's use in blind source separation problems, more specifically in a hardware prototype embedded in a Field Programmable Gate Array (FPGA) board for the monitoring of beds in hospital environments. The implementations will be carried out by Simulink models and it's synthesizing will be done through the DSP Builder software from Altera Corporation.

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A challenge that remains in the robotics field is how to make a robot to react in real time to visual stimulus. Traditional computer vision algorithms used to overcome this problem are still very expensive taking too long when using common computer processors. Very simple algorithms like image filtering or even mathematical morphology operations may take too long. Researchers have implemented image processing algorithms in high parallelism hardware devices in order to cut down the time spent in the algorithms processing, with good results. By using hardware implemented image processing techniques and a platform oriented system that uses the Nios II Processor we propose an approach that uses the hardware processing and event based programming to simplify the vision based systems while at the same time accelerating some parts of the used algorithms

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The increase of applications complexity has demanded hardware even more flexible and able to achieve higher performance. Traditional hardware solutions have not been successful in providing these applications constraints. General purpose processors have inherent flexibility, since they perform several tasks, however, they can not reach high performance when compared to application-specific devices. Moreover, since application-specific devices perform only few tasks, they achieve high performance, although they have less flexibility. Reconfigurable architectures emerged as an alternative to traditional approaches and have become an area of rising interest over the last decades. The purpose of this new paradigm is to modify the device s behavior according to the application. Thus, it is possible to balance flexibility and performance and also to attend the applications constraints. This work presents the design and implementation of a coarse grained hybrid reconfigurable architecture to stream-based applications. The architecture, named RoSA, consists of a reconfigurable logic attached to a processor. Its goal is to exploit the instruction level parallelism from intensive data-flow applications to accelerate the application s execution on the reconfigurable logic. The instruction level parallelism extraction is done at compile time, thus, this work also presents an optimization phase to the RoSA architecture to be included in the GCC compiler. To design the architecture, this work also presents a methodology based on hardware reuse of datapaths, named RoSE. RoSE aims to visualize the reconfigurable units through reusability levels, which provides area saving and datapath simplification. The architecture presented was implemented in hardware description language (VHDL). It was validated through simulations and prototyping. To characterize performance analysis some benchmarks were used and they demonstrated a speedup of 11x on the execution of some applications

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A remoção de inconsistências em um projeto é menos custosa quando realizadas nas etapas iniciais da sua concepção. A utilização de Métodos Formais melhora a compreensão dos sistemas além de possuir diversas técnicas, como a especificação e verificação formal, para identificar essas inconsistências nas etapas iniciais de um projeto. Porém, a transformação de uma especificação formal para uma linguagem de programação é uma tarefa não trivial. Quando feita manualmente, é uma tarefa passível da inserção de erros. O uso de ferramentas que auxiliem esta etapa pode proporcionar grandes benefícios ao produto final a ser desenvolvido. Este trabalho propõe a extensão de uma ferramenta cujo foco é a tradução automática de especificações em CSPm para Handel-C. CSP é uma linguagem de descrição formal adequada para trabalhar com sistemas concorrentes. Handel-C é uma linguagem de programação cujo resultado pode ser compilado diretamente para FPGA's. A extensão consiste no aumento no número de operadores CSPm aceitos pela ferramenta, permitindo ao usuário definir processos locais, renomear canais e utilizar guarda booleana em escolhas externas. Além disto, propomos também a implementação de um protocolo de comunicação que elimina algumas restrições da composição paralela de processos na tradução para Handel-C, permitindo que a comunicação entre múltiplos processos possa ser mapeada de maneira consistente e que a mesma somente ocorra quando for autorizada.

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Removing inconsistencies in a project is a less expensive activity when done in the early steps of design. The use of formal methods improves the understanding of systems. They have various techniques such as formal specification and verification to identify these problems in the initial stages of a project. However, the transformation from a formal specification into a programming language is a non-trivial task and error prone, specially when done manually. The aid of tools at this stage can bring great benefits to the final product to be developed. This paper proposes the extension of a tool whose focus is the automatic translation of specifications written in CSPM into Handel-C. CSP is a formal description language suitable for concurrent systems, and CSPM is the notation used in tools support. Handel-C is a programming language whose result can be compiled directly into FPGA s. Our extension increases the number of CSPM operators accepted by the tool, allowing the user to define local processes, to rename channels in a process and to use Boolean guards on external choices. In addition, we also propose the implementation of a communication protocol that eliminates some restrictions on parallel composition of processes in the translation into Handel-C, allowing communication in a same channel between multiple processes to be mapped in a consistent manner and that improper communication in a channel does not ocurr in the generated code, ie, communications that are not allowed in the system specification