A passive filter is connected at the output of a voltage source inverter in standalone and grid connected applications to reduce harmonics. This paper presents a parameter design procedure of a passive LC filter conta...
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ISBN:
(纸本)9781538673409;9781538673393
A passive filter is connected at the output of a voltage source inverter in standalone and grid connected applications to reduce harmonics. This paper presents a parameter design procedure of a passive LC filter containing a damping resistor for a five level inverter. The work aims to improve the output waveforms of the inverter and reduce the total harmonic distortion content on its output waveforms. The design is carried out with an objective to provide better attenuation of switching frequency harmonics and effective suppression of resonant peaks. All equations derived are simple and accurate which provides insight into design of passive LC filter with resistance damping without cumbersome algorithms. This work uses a modified methodology to arrive at the value of damping resistance for harmonic reduction with minimum losses. The modified method considers quality factor, resonant peaking, harmonic attenuation rate and power loss in the damping branch to select the resistance value. Simulation and experimental results are included to analyse the harmonic distortion on the output waveforms. Experiments have been conducted on a five level cascaded H-Bridge inverter set up. The modulation scheme is implemented on a FPGA platform using SPARTAN 3E-XCS250E controller. A very good agreement is seen between the experimental and simulation results of the developed filter design. The results prove the effectiveness of the resistive damped passive filter for multilevel inverters.
TCP/IP is widely used both in the Internet as well as in data centers. The protocol makes very few assumptions about the underlying network and provides useful guarantees such as reliable transmission, in-order delive...
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ISBN:
(纸本)9782839918442
TCP/IP is widely used both in the Internet as well as in data centers. The protocol makes very few assumptions about the underlying network and provides useful guarantees such as reliable transmission, in-order delivery, or control flow. The price for this functionality is complexity, latency, and computational overhead, which is especially pronounced in software implementations. While for Internet communication this is acceptable, the overhead is too high in data centers. In this paper, we explore how to optimize a TCP/IP stack running on an FPGA for data center applications with an emphasis on data processing (e.g., key value stores). Using a key-value store and a low-latency consensus protocol implemented on an FPGA as an example of the requirements that arise in data centers, we provide an extensive analysis of the overheads of TCP/IP and the solutions that can be adopted to minimize such an overhead. The proposed optimized TCP/IP stack minimizes tail latencies (a key metric in distributed data processing) and is efficiently implemented so as to be able to share the FPGA with application logic.
Currently, much research looks at treating the behavior properties beginning with the architectural design phase in SCA (Software Component Architectures) based applications. In this paper, we propose to map SCA onto ...
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ISBN:
(纸本)9781538617595
Currently, much research looks at treating the behavior properties beginning with the architectural design phase in SCA (Software Component Architectures) based applications. In this paper, we propose to map SCA onto the Wright ADL in order to verify the behavioral consistency of SCA software architectures. To achieve this goal, we suggest translating this source software architecture into a Wright configuration. Using Wr2fdr tool, this Wright configuration can be automatically translated to a CSP specification acceptable by the FDR2 model-checker.
Hierarchical fuzzy systems (HFSs) have been shown to have the potential to improve interpretability of fuzzy logic systems (FLSs). In recent years, a variety of indices have been proposed to measure the interpretabili...
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ISBN:
(纸本)9781509060344
Hierarchical fuzzy systems (HFSs) have been shown to have the potential to improve interpretability of fuzzy logic systems (FLSs). In recent years, a variety of indices have been proposed to measure the interpretability of FLSs such as the Nauck index and Fuzzy index. However, interpretability indices associated with HFSs have not so far been discussed. The structure of HFSs, with multiple layers, subsystems, and varied topologies, is the main challenge in constructing interpretability indices for HFSs. Thus, the comparison of interpretability between FLSs and HFSs-even at the index level-is still subject to open discussion. This paper begins to address these challenges by introducing extensions to the FLS Nauck and Fuzzy interpretability indices for HFSs. Using the proposed indices, we explore the concept of interpretability in relation to the different structures in FLSs and HFSs. Initial experiments on benchmark datasets show that based on the proposed indices, HFSs with equivalent function to FLSs produce higher indices, i.e. are more interpretable than their corresponding FLSs.
Recurrent neural networks (RNNs) provide state-of-the-art accuracy for performing analytics on datasets with sequence (e.g., language model). This paper studied a state-of-the-art RNN variant, Gated Recurrent Unit (GR...
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ISBN:
(纸本)9782839918442
Recurrent neural networks (RNNs) provide state-of-the-art accuracy for performing analytics on datasets with sequence (e.g., language model). This paper studied a state-of-the-art RNN variant, Gated Recurrent Unit (GRU). We first proposed memoization optimization to avoid 3 out of the 6 dense matrix vector multiplications (SGEMVs) that are the majority of the computation in GRU. Then, we study the opportunities to accelerate the remaining SGEMVs using FPGAs, in comparison to 14-nm ASIC, GPU, and multi-core CPU. Results show that FPGA provides superior performance/Watt over CPU and GPU because FPGA's on-chip BRAMs, hard DSPs, and reconfigurable fabric allow for efficiently extracting fine-grained parallelisms from small/medium size matrices used by GRU. Moreover, newer FPGAs with more DSPs, on-chip BRAMs, and higher frequency have the potential to narrow the FPGA-ASIC efficiency gap.
The emergent technology of system-on-chip (SoC) devices promises lighter, smaller, cheaper, and more capable and reliable space electronic systems that could help to unveil some of the most treasured secrets in our un...
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The emergent technology of system-on-chip (SoC) devices promises lighter, smaller, cheaper, and more capable and reliable space electronic systems that could help to unveil some of the most treasured secrets in our universe. This technology is an improvement over the technology that is currently used in space applications, which lags behind state-of-the-art commercial-off-the-shelf (COTS) equipment by several generations. SoC technology integrates all computational power required by next-generation space exploration science instruments onto a single chip. This presentation will describe a Xilinx Zynqbased data acquisition, cloud-screening and compression computing system that has been developed at the Jet Propulsion Laboratory (JPL) foJJPL's Next Generation Imaging Spectrometers (NGIS). The Xilinx Zynq-based Alpha Data hardware assembly fits into a 120mm by 190m by 40mm assembly and uses 9 watts at peak performance. The computing element is a Xilinx Zynq Z7045Q which includes a Kintex-7 FPGA (equivalent to 3 RAD Virtex5 FPGAs in terms of logic cell resources) and dual-core ARM Cortex-A9 Processors (equivalent to 10 RAD750 Power PCs in term of processing capability).
Convolutional neural networks (CNNs) are revolutionizing a variety of machine learning tasks, but they present significant computational challenges. Recently, FPGA-based accelerators have been proposed to improve the ...
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ISBN:
(纸本)9782839918442
Convolutional neural networks (CNNs) are revolutionizing a variety of machine learning tasks, but they present significant computational challenges. Recently, FPGA-based accelerators have been proposed to improve the speed and efficiency of CNNs. Current approaches construct an accelerator optimized to maximize the overall throughput of iteratively computing the CNN layers. However, this approach leads to dynamic resource underutilization because the same accelerator is used to compute CNN layers of radically varying dimensions. We present a new CNN accelerator design that improves the dynamic resource utilization. Using the same FPGA resources, we build multiple accelerators, each specialized for specific CNN layers. Our design achieves 1.3x higher throughput than the state of the art when evaluating the convolutional layers of the popular AlexNet CNN on a Xilinx Virtex-7 FPGA.
FPGAs are promising platforms to efficiently execute distributed graph algorithms. Unfortunately, they are notoriously hard to program, especially when the problem size and system complexity increases. In this paper, ...
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ISBN:
(纸本)9782839918442
FPGAs are promising platforms to efficiently execute distributed graph algorithms. Unfortunately, they are notoriously hard to program, especially when the problem size and system complexity increases. In this paper, we propose GraVF, a high-level design framework for distributed graph processing on FPGAs. It leverages the vertex-centric paradigm, which is naturally distributed and requires the user to define only very small kernels and their associated message semantics for the target application. The user design may subsequently be elaborated and compiled to the target system automatically by the framework. To demonstrate the flexibility and capabilities of the proposed framework, 4 graph algorithms with distinct requirements have been implemented, namely breadth-first search, PageRank, single source shortest path, and connected component. Results show that the proposed framework is capable of producing FPGA designs with performance comparable to similar custom designs while requiring only minimal input from the user.
This paper presents a robust fuzzy-sliding mode control (FSC) technique for speed control of a drive system based on dual star induction machine (DISM). The machine is fed by two multilevel voltage source inverters (M...
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ISBN:
(纸本)9781538668672;9781538668665
This paper presents a robust fuzzy-sliding mode control (FSC) technique for speed control of a drive system based on dual star induction machine (DISM). The machine is fed by two multilevel voltage source inverters (MLVSI) and its control is achieved using a fuzzy-sliding mode controller combined with the indirect field oriented control (IFOC) technique. The MLVSI technology has recently emerged and applied to DC-AC conversion to obtain sinusoidal waveform and to fulfill different applications constraints such as: high power conversion, power segmentation and power control. The FSC has many advantages, such as: fast response good robustness, high efficiency and suppressed chattering phenomenon. The presented study is validated by a series of simulation results showing the main responses of the drive system in case of different operating conditions. Also, the proposed FSC controller is compared to the classical PI controller and demonstrated superior performances.
Sharing multi-cycle hardware blocks like the DSP48E1 primitive in Xilinx FPGAs can result in significant resource savings, but complicates scheduling. For high-throughput, DSP blocks must be pipelined, which results i...
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ISBN:
(纸本)9782839918442
Sharing multi-cycle hardware blocks like the DSP48E1 primitive in Xilinx FPGAs can result in significant resource savings, but complicates scheduling. For high-throughput, DSP blocks must be pipelined, which results in a high initiation interval (II) for resource shared implementations. In this paper, we propose a resource reduction technique that minimises DSP block usage while also offering improved II over traditional approaches. This is integrated in a high-level tool which takes datapath descriptions in C and generates synthesisable Verilog RTL with different levels of resource sharing. We demonstrate significantly improved throughput compared to traditional resource sharing while achieving resource reduction compared to resource unconstrained and HLS implementations. The approach explores an otherwise infeasible design space between resource unconstrained and traditional resource sharing methods.
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