Real-time simulators have been used as an aid to power system design for many years. Over time, scaled-down physical models and analog computer-based simulators have given way to real-time simulators based on digital ...
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Real-time simulators have been used as an aid to power system design for many years. Over time, scaled-down physical models and analog computer-based simulators have given way to real-time simulators based on digital technology. Another trend has been the need for shorter and shorter frame times for these digital real-time simulators. Modern power electronic systems use high-frequency Pulse-Width Modulated (PWM) controllers. Indications are that frame times of 2 mu S are needed for PWM switching frequencies of 10 KHz. As frequencies increase further it is possible that frame times of less than 1 mu S may be required. In order to achieve these very short frame times, the implementation of this type of simulator requires careful selection of the methods and technologies used. The first involves thorough analysis of the integration method chosen, to ensure that it provides the performance, stability and accuracy required. Additionally, the choice of computing platform is crucial to provide the computational support to meet these very aggressive timing requirements.
The DRAM-Based Reconfigurable Acceleration Fabric (DRAF) uses commodity DRAM technology to implement a bit-level, reconfigurable fabric that improves area density by 10 times and power consumption by more than 3 times...
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The DRAM-Based Reconfigurable Acceleration Fabric (DRAF) uses commodity DRAM technology to implement a bit-level, reconfigurable fabric that improves area density by 10 times and power consumption by more than 3 times over conventional field-programmable gate arrays. Latency overlapping and multicontext support allow DRAF to meet the performance and density requirements of demanding applications in datacenter and mobile environments.
Research has shown that deep neural networks contain significant redundancy, and thus that high classification accuracy can be achieved even when weights and activations are quantized down to binary values. Network bi...
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Research has shown that deep neural networks contain significant redundancy, and thus that high classification accuracy can be achieved even when weights and activations are quantized down to binary values. Network binarization on FPGAs greatly increases area efficiency by replacing resource-hungry multipliers with lightweight XNOR gates. However, an FPGA's fundamental building block, the K-LUT, is capable of implementing far more than an XNOR: it can perform any K-input Boolean operation. Inspired by this observation, we propose LUTNet, an end-to-end hardware-software framework for the construction of area-efficient FPGA-based neural network accelerators using the native LUTs as inference operators. We describe the realization of both unrolled and tiled LUTNet architectures, with the latter facilitating smaller, less power-hungry deployment over the former while sacrificing area and energy efficiency along with throughput. For both varieties, we demonstrate that the exploitation of LUT flexibility allows for far heavier pruning than possible in prior works, resulting in significant area savings while achieving comparable accuracy. Against the state-of-the-art binarized neural network implementation, we achieve up to twice the area efficiency for several standard network models when inferencing popular datasets. We also demonstrate that even greater energy efficiency improvements are obtainable.
Preventive maintenance and monitoring of induction motors is mandatory for industries. Broken rotor bars are among the most common failures in induction motors. Several techniques to detect broken bars have been repor...
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Preventive maintenance and monitoring of induction motors is mandatory for industries. Broken rotor bars are among the most common failures in induction motors. Several techniques to detect broken bars have been reported;however, they focus on motors connected directly to the power supply and do not consider the case for motors connected through variable-speed drives, where detectability becomes ineffective. The novelty of this work consists of a new methodology based on multiple discrete wavelet transforms implemented in a field-programmable gate array, which is able to detect broken rotor bars in direct-line and variable-speed drives fed at various motor operating speeds. Several tests were performed, and results show the system effectiveness.
In this paper, we present an algorithm for circuit partitioning with complex resource constraints in large FPGAs. Traditional partitioning methods estimate the capacity of an FPGA device by counting the number of logi...
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In this paper, we present an algorithm for circuit partitioning with complex resource constraints in large FPGAs. Traditional partitioning methods estimate the capacity of an FPGA device by counting the number of logic blocks, however this is not accurate with the increasing diverse resource types in the new FPGA architectures. We first propose a network flow based method to optimally check whether a circuit or a subcircuit is feasible for a set of available heterogeneous resources. Then the feasibility checking procedure is integrated in the FM-based algorithm for circuit partitioning. Incremental flow technique is employed for efficient implementation. Experimental results on the MCNC benchmark circuits show that our partitioning algorithm not only yields good results, but also is efficient. Our algorithm for partitioning with complex resource constraints is applicable for both multiple FPGA designs (e.g., logic emulation systems) and partitioning-based placement algorithms for a single large hierarchical FPGA (e.g., Actel's ES6500 FPGA family).
In this paper we present a methodology for optimizing complex datapath oriented digital circuits. An optimizer was developed based on the earlier development of an automatic circuit synthesizer that synthesizes hardwa...
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In this paper we present a methodology for optimizing complex datapath oriented digital circuits. An optimizer was developed based on the earlier development of an automatic circuit synthesizer that synthesizes hardware description language specifications based on available functional modules. A genetic algorithm is tailored to the problem of digital circuit optimization through the development of specific structures and procedures. In particular, a concise encoding of the circuit is developed that the genetic algorithm can manipulate. Specific crossover and mutation mechanisms are also developed to complement the functionality of the synthesizer. The searches are effected by altering module data type, hardware resource sharing, and module implementation version. A fitness function is derived that makes use of a number of optimization parameters to objectively evaluate each particular circuit. The features of each circuit are calculated and estimated during the analysis phase. (c) 2006 Elsevier B. V. All rights reserved.
Clock and data recovery (CDR) is an essential part in high-speed telecommunication systems. The CDR is used to extract the clock and re-time the received data, which allows a synchronous operation to recover the trans...
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Clock and data recovery (CDR) is an essential part in high-speed telecommunication systems. The CDR is used to extract the clock and re-time the received data, which allows a synchronous operation to recover the transmitted signal. In optical access networks, electrical CDR or optical CDR implementations can be used. However, there are no clear guidelines or recommendations on which CDR implementation should be adopted for better performance. These missing clear recommendations are because the electrical CDR requires electronics design expertise whereas the optical CDR requires optical design expertise. Consequently, in this paper, an all-digital CDR, designed and implemented on the field-programmable gate array platform, and an optical CDR, developed by using fiber Bragg grating technology on the OptiSystem platform, are presented. Furthermore, the integration of these 2 CDR implementations with the optical access network is implemented, and their performance is evaluated for various transmission rates and communication distances. Finally, a comparative study in terms of the bit error rate between the all-digital CDR and the optical CDR is presented.
A LED dimming circuit, together with the KY converter, is presented, which is controlled based on a field-programmable gate array. Via the proposed feedback control strategy, the voltage across the linear current regu...
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A LED dimming circuit, together with the KY converter, is presented, which is controlled based on a field-programmable gate array. Via the proposed feedback control strategy, the voltage across the linear current regulator is reduced so as to upgrade the efficiency of the overall system, with the proposed maximum error selection based on a suitable voltage turning on the diode. Aside from this, each LED string takes direct dimming, and is powered by the KY converter, which has an output inductor and hence upgrades the life of the output capacitor. Experimental results show that the efficiency based on the proposed control method is higher than that based on the traditional control one, particularly at light load.
Today, most microprocessor and microcontroller designs are based on a Reduced Instruction Set Computer core with several operations performed by a digital signal processor system. Here, the design of a RISC and DSP sy...
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Today, most microprocessor and microcontroller designs are based on a Reduced Instruction Set Computer core with several operations performed by a digital signal processor system. Here, the design of a RISC and DSP system is presented that uses very high-density logic (VHDL) and a field-programmable gate array (FPGA). This RISC is a 20-bit processor.
The present work proposes a modified 8-bit AES architecture that performs AES core operations in a single round wherein data is iterated ten times instead of having ten different rounds leading to substantial decrease...
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The present work proposes a modified 8-bit AES architecture that performs AES core operations in a single round wherein data is iterated ten times instead of having ten different rounds leading to substantial decrease in area and power consumption. To enhance the security of AES encryption, boolean masking has been employed for all AES operations, rounds and intermediate data. Modified architecture for AddRoundKey and ByteSubstitution operation has been proposed that employs high order masking. Also, an enhanced key expansion algorithm is proposed that makes AES less vulnerable to saturation attacks and differential power analysis (DPA) attacks. Implementation of the proposed architecture has been done using Vivado Design Suite on Virtex-7 FPGA. Result analysis depicts that, during the performance explore strategy, 179.73 MHz maximum frequency with a throughput of 143.78 Mbps has been achieved whereas, the proposed architecture utilises 757 slices, 962 LUTs and 0.313 watt power using area explore strategy.
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