995 resultados para Virtex-II-Pro


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High end network security applications demand high speed operation and large rule set support. Packet classification is the core functionality that demands high throughput in such applications. This paper proposes a packet classification architecture to meet such high throughput. We have implemented a Firewall with this architecture in reconflgurable hardware. We propose an extension to Distributed Crossproducting of Field Labels (DCFL) technique to achieve scalable and high performance architecture. The implemented Firewall takes advantage of inherent structure and redundancy of rule set by using our DCFL Extended (DCFLE) algorithm. The use of DCFLE algorithm results in both speed and area improvement when it is implemented in hardware. Although we restrict ourselves to standard 5-tuple matching, the architecture supports additional fields. High throughput classification invariably uses Ternary Content Addressable Memory (TCAM) for prefix matching, though TCAM fares poorly in terms of area and power efficiency. Use of TCAM for port range matching is expensive, as the range to prefix conversion results in large number of prefixes leading to storage inefficiency. Extended TCAM (ETCAM) is fast and the most storage efficient solution for range matching. We present for the first time a reconfigurable hardware implementation of ETCAM. We have implemented our Firewall as an embedded system on Virtex-II Pro FPGA based platform, running Linux with the packet classification in hardware. The Firewall was tested in real time with 1 Gbps Ethernet link and 128 sample rules. The packet classification hardware uses a quarter of logic resources and slightly over one third of memory resources of XC2VP30 FPGA. It achieves a maximum classification throughput of 50 million packet/s corresponding to 16 Gbps link rate for the worst case packet size. The Firewall rule update involves only memory re-initialization in software without any hardware change.

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High end network security applications demand high speed operation and large rule set support. Packet classification is the core functionality that demands high throughput in such applications. This paper proposes a packet classification architecture to meet such high throughput. We have Implemented a Firewall with this architecture in reconfigurable hardware. We propose an extension to Distributed Crossproducting of Field Labels (DCFL) technique to achieve scalable and high performance architecture. The implemented Firewall takes advantage of inherent structure and redundancy of rule set by using, our DCFL Extended (DCFLE) algorithm. The use of DCFLE algorithm results In both speed and area Improvement when It is Implemented in hardware. Although we restrict ourselves to standard 5-tuple matching, the architecture supports additional fields.High throughput classification Invariably uses Ternary Content Addressable Memory (TCAM) for prefix matching, though TCAM fares poorly In terms of area and power efficiency. Use of TCAM for port range matching is expensive, as the range to prefix conversion results in large number of prefixes leading to storage inefficiency. Extended TCAM (ETCAM) is fast and the most storage efficient solution for range matching. We present for the first time a reconfigurable hardware Implementation of ETCAM. We have implemented our Firewall as an embedded system on Virtex-II Pro FPGA based platform, running Linux with the packet classification in hardware. The Firewall was tested in real time with 1 Gbps Ethernet link and 128 sample rules. The packet classification hardware uses a quarter of logic resources and slightly over one third of memory resources of XC2VP30 FPGA. It achieves a maximum classification throughput of 50 million packet/s corresponding to 16 Gbps link rate for file worst case packet size. The Firewall rule update Involves only memory re-initialiization in software without any hardware change.

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With ever increasing network speed, scalable and reliable detection of network port scans has become a major challenge. In this paper, we present a scalable and flexible architecture and a novel algorithm, to detect and block port scans in real time. The proposed architecture detects fast scanners as well as stealth scanners having large inter-probe periods. FPGA implementation of the proposed system gives an average throughput of 2 Gbps with a system clock frequency of 100 MHz on Xilinx Virtex-II Pro FPGA. Experimental results on real network trace show the effectiveness of the proposed system in detecting and blocking network scans with very low false positives and false negatives.

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Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

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O padrão H.264 foi desenvolvido pelo JVT, que foi formado a partir de uma união entre os especialistas do VCEG da ITU-T e do MPEG da ISO/IEC. O padrão H.264 atingiu seu objetivo de alcançar as mais elevadas taxas de processamento dentre todos os padrões existentes, mas à custa de um grande aumento na complexidade computacional. Este aumento de complexidade impede, pelo menos na tecnologia atual, a utilização de codecs H.264 implementados em software, quando se deseja a decodi cação de vídeos de alta de nição em tempo real. Essa dissertação propõe uma solução arquitetural de hardware, denominada MoCHA, para compensação de movimento do decodi cador de vídeo de alta de nição, segundo o padrão H.264/AVC. A MoCHA está dividida em três blocos principais, a predição dos vetores de movimento, o acesso à memória e o processamento de amostras. A utilização de uma cache para explorar a redundância dos dados nos acessos à mem ória, em conjunto com melhorias propostas, alcançou economia de acessos à memória superior a 60%, para os casos testados. Quando uma penalidade de um ciclo por troca de linha de memória é imposta, a economia de ciclos de acesso supera os 75%. No processamento de amostras, a arquitetura realiza o processamento dos dois blocos, que dão origem ao bloco bi-preditivo, de forma serial. Dessa forma, são economizados recursos de hardware, uma vez que a duplicação da estrutura de processamento não é requerida. A arquitetura foi validada a partir de simulações, utilizando entradas extraídas de seqüências codi cadas. Os dados extraídos, salvos em arquivos, serviam de entrada para a simulação. Os resultados da simulação foram salvos em arquivos e comparados com os resultados extraídos. O processador de amostras do compensador de movimento foi prototipado na placa XUP Virtex-II Pro. A placa possui um FPGA VP30 da família Virtex-II PRO da Xilinx. O processador PowerPC 405, presente no dispositivo, foi usado para implementar um test bench para validar a operação do processador de amostras mapeado para o FPGA. O compensador de movimento para o decodi cador de vídeo H.264 foi descrito em VHDL, num total de 30 arquivos e cerca de 13.500 linhas de código. A descrição foi sintetizada pelo sintetizador Syplify Pro da Symplicity para o dispositivo XC2VP30-7 da Xilinx, consumindo 8.465 slices, 5.671 registradores, 10.835 LUTs, 21 blocos de memó- ria interna e 12 multiplicadores. A latência mínima para processar um macrobloco é de 233 ciclos, enquanto a máxima é de 590, sem considerar misses na cache. A freqüência máxima de operação foi de 100,5 MHz. A arquitetura projetada é capaz de processar, no pior caso, 36,7 quadros HDTV de 1080 por 1920, inteiramente bi-preditivos, por segundo. Para quadros do tipo P, que não utilizam a bi-predição, a capacidade de processamento sobe para 64,3 quadros por segundo. A arquitetura apresentada para o processamento de quadros bi-preditivos e a hierarquia de memória são, até o momento, inéditas na literatura. Os trabalhos relativos a decodi cadores completos não apresentam a solução para esse processamento. Os resultados apresentados tornam a MoCHA uma solução arquitetural capaz de fazer parte de um decodi cador para vídeos de alta definição.

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O objectivo deste trabalho é a implementação em hardware de uma Rede Neuronal com um microprocessador embebido, podendo ser um recurso valioso em várias áreas científicas. A importância das implementações em hardware deve-se à flexibilidade, maior desempenho e baixo consumo de energia. Para esta implementação foi utilizado o dispositivo FPGA Virtex II Pro XC2VP30 com um MicroBlaze soft core, da Xilinx. O MicroBlaze tem vantagens como a simplicidade no design, sua reutilização e fácil integração com outras tecnologias. A primeira fase do trabalho consistiu num estudo sobre o FPGA, um sistema reconfigurável que possui características importantes como a capacidade de executar em paralelo tarefas complexas. Em seguida, desenvolveu-se o código de implementação de uma Rede Neuronal Artificial baseado numa linguagem de programação de alto nível. Na implementação da Rede Neuronal aplicou-se, na camada escondida, a função de activação tangente hiperbólica, que serve para fornecer a não linearidade à Rede Neuronal. A implementação é feita usando um tipo de Rede Neuronal que permite apenas ligações no sentido de saída, chamado Redes Neuronais sem realimentação (do Inglês Feedforward Neural Networks - FNN). Como as Redes Neuronais Artificiais são sistemas de processamento de informações, e as suas características são comuns às Redes Neuronais Biológicas, aplicaram-se testes na implementação em hardware e analisou-se a sua importância, a sua eficiência e o seu desempenho. E finalmente, diante dos resultados, fez-se uma análise de abordagem e metodologia adoptada e sua viabilidade.

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It has been well documented that traffic accidents that can be avoided occur when the motorists miss or ignore traffic signs. With the attention of drivers getting diverted due to distractions like cell phone conversations, missing traffic signs has become more prevalent. Also, poor weather and other unfriendly driving conditions sometimes makes the motorists not to be alert all the time and see every traffic sign on the road. Besides, most cars do not have any form of traffic assistance. Because of heavy traffic and proliferation of traffic signs on the roads, there is a need for a system that assists the driver not to miss a traffic sign to reduce the probability of an accident. Since visual information is critical for driving, processed video signals from cameras have been chosen to assist drivers. These inexpensive cameras can be easily mounted on the automobile. The objective of the present investigation and the traffic system development is to recognize the traffic signs electronically and alert drivers. For the case study and the system development, five important and critical traffic signs have been selected. They are: STOP, NO ENTER, NO RIGHT TURN, NO LEFT TURN, and YIELD. The system was evaluated processing still pictures taken from the public roads, and the recognition results were presented in an analysis table to indicate the correct identifications and the false ones. The system reached the acceptable recognition rate of 80% for all five traffic signs. The processing rate was about three seconds. The capabilities of MATLAB, VLSI design platforms and coding have been used to generate a visual warning to complement the visual driver support system with a Field Programmable Gate Array (FPGA) on a XUP Virtex-II Pro Development System.

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Reconfigurable hardware can be used to build a multitasking system where tasks are assigned to HW resources at run-time according to the requirements of the running applications. These tasks are frequently represented as direct acyclic graphs and their execution is typically controlled by an embedded processor that schedules the graph execution. In order to improve the efficiency of the system, the scheduler can apply prefetch and reuse techniques that can greatly reduce the reconfiguration latencies. For an embedded processor all these computations represent a heavy computational load that can significantly reduce the system performance. To overcome this problem we have implemented a HW scheduler using reconfigurable resources. In addition we have implemented both prefetch and replacement techniques that obtain as good results as previous complex SW approaches, while demanding just a few clock cycles to carry out the computations. We consider that the HW cost of the system (in our experiments 3% of a Virtex-II PRO xc2vp30 FPGA) is affordable taking into account the great efficiency of the techniques applied to hide the reconfiguration latency and the negligible run-time penalty introduced by the scheduler computations.

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Leukocyte Elastase Inhibitor (LEI, also called serpin B1) is a protein involved in apoptosis among other physiological processes. We have previously shown that upon cleavage by its cognate protease, LEI is transformed into L-DNase II, a protein with a pro-apoptotic activity. The caspase independent apoptotic pathway, in which L-DNase II is the final effector, interacts with other pro-apoptotic molecules like Poly-ADP-Ribose polymerase (PARP) or Apoptosis Inducing Factor (AIF). The screening of LEI/L-DNase II interactions showed a possible interaction with several members of the BCL-2 family of proteins which are known to have a central role in the regulation of caspase dependent cell death. In this study, we investigated the regulation of LEI/L-DNase II pathway by two members of this family of proteins: BAX and BCL-2, which have opposite effects on cell survival. We show that, in both BHK and HeLa cells, LEI/L-DNase II can interact with BCL-2 and BAX in apoptotic and non-apoptotic conditions. These proteins which are usually thought to be anti-apoptotic and pro-apoptotic respectively, both inhibit the L-DNase II pro-apoptotic activity. These results give further insight in the regulation of caspase-independent pathways and highlight the involvement of the intracellular environment of a given protein in the determinism of its function. They also add a link between caspase-dependent and independent pathways of apoptosis.

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This paper presents the evaluation in power consumption of a clocking technique for pipelined designs. The technique shows a dynamic power consumption saving of around 30% over a conventional global clocking mechanism. The results were obtained from a series of experiments of a systolic circuit implemented in Virtex-II devices. The conversion from a global-clocked pipelined design to the proposed technique is straightforward, preserving the original datapath design. The savings can be used immediately either as a power reduction benefit or to increase the frequency of operation of a design for the same power consumption.

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A variation of the least means squares (LMS) algorithm, called the delayed LMS (DLMS) algorithm is an ideally suited to achieve highly pipelined, adaptive digital filter implementations. The paper presents an efficient method of determining the delays in the DLMS filter and then transferring these delays using retiming in order to achieve fully pipelined circuit architectures for FPGA implementation. The method has been used to derive a series of retimed delayed LMS (RDLMS) architectures, which considerable reduce the number of delays and convergence time and give superior performance in terms of throughput rate when compared to previous work. Three circuit architectures and three hardware shared versions are presented which have been implemented using the Virtex-II FPGA technology resulting in a throughout rate of 182 Msample/s.

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Dynamic power consumption is very dependent on interconnect, so clever mapping of digital signal processing algorithms to parallelised realisations with data locality is vital. This is a particular problem for fast algorithm implementations where typically, designers will have sacrificed circuit structure for efficiency in software implementation. This study outlines an approach for reducing the dynamic power consumption of a class of fast algorithms by minimising the index space separation; this allows the generation of field programmable gate array (FPGA) implementations with reduced power consumption. It is shown how a 50% reduction in relative index space separation results in a measured power gain of 36 and 37% over a Cooley-Tukey Fast Fourier Transform (FFT)-based solution for both actual power measurements for a Xilinx Virtex-II FPGA implementation and circuit measurements for a Xilinx Virtex-5 implementation. The authors show the generality of the approach by applying it to a number of other fast algorithms namely the discrete cosine, the discrete Hartley and the Walsh-Hadamard transforms.

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Very high speed and low area hardware architectures of the SHACAL-1 encryption algorithm are presented in this paper. The SHACAL algorithm was a submission to the New European Schemes for Signatures, Integrity and Encryption (NESSIE) project and it is based on the SHA-1 hash algorithm. To date, there have been no performance metrics published on hardware implementations of this algorithm. A fully pipelined SHACAL-1 encryption architecture is described in this paper and when implemented on a Virtex-II X2V4000 FPGA device, it runs at a throughput of 17 Gbps. A fully pipelined decryption architecture achieves a speed of 13 Gbps when implemented on the same device. In addition, iterative architectures of the algorithm are presented. The SHACAL-1 decryption algorithm is derived and also presented in this paper, since it was not provided in the submission to NESSIE. © Springer-Verlag Berlin Heidelberg 2003.