962 resultados para hardware deskribapen lengoaiak
Resumo:
An application specific programmable processor (ASIP) suitable for the real-time implementation of matrix computations such as Singular Value and QR Decomposition is presented. The processor incorporates facilities for the issue of parallel instructions and a dual-bus architecture that are designed to achieve high performance. Internally, it uses a CORDIC module to perform arithmetic operations, with pipelining of the internal recursive loop exploited to multiplex the two independent micro-rotations onto a single piece of hardware. The net result is a flexible processing element whose functionality can be changed under program control, which combines high performance with efficient silicon implementation. This is illustrated through the results of a detailed silicon design study and the applications of the techniques to a combined SVD/QRD system.
Resumo:
This paper proposes a novel hybrid forward algorithm (HFA) for the construction of radial basis function (RBF) neural networks with tunable nodes. The main objective is to efficiently and effectively produce a parsimonious RBF neural network that generalizes well. In this study, it is achieved through simultaneous network structure determination and parameter optimization on the continuous parameter space. This is a mixed integer hard problem and the proposed HFA tackles this problem using an integrated analytic framework, leading to significantly improved network performance and reduced memory usage for the network construction. The computational complexity analysis confirms the efficiency of the proposed algorithm, and the simulation results demonstrate its effectiveness
Resumo:
Maximakinin is an N-terminally extended bradykinin (DLPKINRKGPRPPGFSPFR) from the venom of a Chinese toad (Bombina maxima) that displays highly selective activity at mammalian arterial smooth muscle receptors. In this study, we report that incubation of maximakinin with either kallikrein or human saliva generates catabolites with enhanced bioactivity that retain the tissue selective effects of the parent molecule. In addition, we have observed that kallikrein rapidly cleaves the C-terminal arginyl residue of both maximakinin and bradykinin – a cleavage hitherto considered to be performed by a carboxypeptidase that facilitates selective bradykinin receptor targeting. Maximakinin has thus evolved as a `smart' defensive weapon in the toad with inherent resistance to the signal-terminating protease hardware in the potential predator. Thus, natural selection of amphibian skin peptides for antipredator defence, through interspecies delivery by an exogenous secretory mode, produces subtle structural stabilization modifications that can potentially provide new insights for the design of orally active and selectively targeted peptide therapeutics.
Resumo:
Paper describes an effcicient approach for provisioning of network resources based on SLAs and a range of negotiating agents. The work arose from direct collboration with Fujitsu research and invlolved a worldwide press reslease of their agent brokering system which was based on this; also, a plenary address: A.Marshall (QUB) & A.Campbell (Columbia, USA) at 4th IFIP/IEEE International conference on Management of Multimedia Networks and Services' 2001 (MMNS'01). ISSN: 0926-6801
Resumo:
A generic architecture for implementing the advanced encryption standard (AES) encryption algorithm in silicon is proposed. This allows the instantiation of a wide range of chip specifications, with these taking the form of semiconductor intellectual property (IP) cores. Cores implemented from this architecture can perform both encryption and decryption and support four modes of operation: (i) electronic codebook mode; (ii) output feedback mode; (iii) cipher block chaining mode; and (iv) ciphertext feedback mode. Chip designs can also be generated to cover all three AES key lengths, namely 128 bits, 192 bits and 256 bits. On-the-fly generation of the round keys required during decryption is also possible. The general, flexible and multi-functional nature of the approach described contrasts with previous designs which, to date, have been focused on specific implementations. The presented ideas are demonstrated by implementation in FPGA technology. However, the architecture and IP cores derived from this are easily migratable to other silicon technologies including ASIC and PLD and are capable of covering a wide range of modem communication systems cryptographic requirements. Moreover, the designs produced have a gate count and throughput comparable with or better than the previous one-off solutions.
Resumo:
A novel tag computation circuit for a credit based Self-Clocked Fair Queuing (SCFQ) Scheduler is presented. The scheduler combines Weighted Fair Queuing (WFQ) with a credit based bandwidth reallocation scheme. The proposed architecture is able to reallocate bandwidth on the fly if particular links suffer from channel quality degradation .The hardware architecture is parallel and pipelined enabling an aggregated throughput rate of 180 million tag computations per second. The throughput performance is ideal for Broadband Wireless Access applications, allowing room for relatively complex computations in QoS aware adaptive scheduling. The high-level system break-down is described and synthesis results for Altera Stratix II FPGA technology are presented.
Resumo:
Grey Level Co-occurrence Matrix (GLCM), one of the best known tool for texture analysis, estimates image properties related to second-order statistics. These image properties commonly known as Haralick texture features can be used for image classification, image segmentation, and remote sensing applications. However, their computations are highly intensive especially for very large images such as medical ones. Therefore, methods to accelerate their computations are highly desired. This paper proposes the use of programmable hardware to accelerate the calculation of GLCM and Haralick texture features. Further, as an example of the speedup offered by programmable logic, a multispectral computer vision system for automatic diagnosis of prostatic cancer has been implemented. The performance is then compared against a microprocessor based solution.
Resumo:
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.
Resumo:
WebCom-G is a fledgling Grid Operating System, designed to provide independent service access through interoperability with existing middlewares. It offers an expressive programming model that automatically handles task synchronisation – load balancing, fault tolerance, and task allocation are handled at the WebCom-G system level – without burdening the application writer. These characteristics, together with the ability of its computing model to mix evaluation strategies to match the characteristics of the geographically dispersed facilities and the overall problem- solving environment, make WebCom-G a promising grid middleware candidate.
Resumo:
High-speed field-programmable gate array (FPGA) implementations of an adaptive least mean square (LMS) filter with application in an electronic support measures (ESM) digital receiver, are presented. They employ "fine-grained" pipelining, i.e., pipelining within the processor and result in an increased output latency when used in the LMS recursive system. Therefore, the major challenge is to maintain a low latency output whilst increasing the pipeline stage in the filter for higher speeds. Using the delayed LMS (DLMS) algorithm, fine-grained pipelined FPGA implementations using both the direct form (DF) and the transposed form (TF) are considered and compared. It is shown that the direct form LMS filter utilizes the FPGA resources more efficiently thereby allowing a 120 MHz sampling rate.