A Two-Stage Method for Routing in Field-Programmable Gate Arrays with Time-Division Multiplexing

Emerging applications widely use field-programmable gate array(FPGA)prototypes as a tool to verify modern very-large-scale integration(VLSI)circuits,imposing many problems,including routing failure caused by the limited number of connections among blocks of FPGAs therein.Such a shortage of connections can be alleviated through time-division multiplexing(TDM),by which multiple signals sharing an identical routing channel can be transmitted.In this context,the routing quality dominantly decides the performance of such systems,proposing the requirement of minimizing the signal delay between FPGA pairs.This paper proposes algorithms for the routing problem in a multi-FPGA system with TDM support,aiming to minimize the maximum TDM ratio.The algorithm consists of two major stages:(1)A method is proposed to set the weight of an edge according to how many times it is shared by the routing requirements and consequently to compute a set of approximate minimum Steiner trees.(2)A ratio assignment method based on the edge-demand framework is devised for assigning ratios to the edges respecting the TDM ratio constraints.Experiments were conducted against the public benchmarks to evaluate our proposed approach as compared with all published works,and the results manifest that our method achieves a better TDM ratio in comparison.

Resonance Characteristics of Piezoelectric Resonator Based on Digital Driving Circuit of Field-Programmable Gate Array

Piezoelectric resonators are widely used in frequency reference devices, mass sensors, resonant sensors(such as gyros and accelerometers), etc. Piezoelectric resonators usually work in a special resonant mode. Obtaining working resonant mode with high quality is key to improve the performance of piezoelectric resonators. In this paper, the resonance characteristics of a rectangular lead zirconium titanate(PZT) piezoelectric resonator are studied. On the basis of the field-programmable gate array(FPGA) embedded system, direct digital synthesizer(DDS) and automatic gain controller(AGC) are used to generate the driving signals with precisely adjustable frequency and amplitude. The driving signals are used to excite the piezoelectric resonator to the working vibration mode. The influence of the connection of driving electrodes and voltage amplitude on the vibration of the resonator is studied. The quality factor and vibration linearity of the resonator are studied with various driving methods mentioned in this paper. The resonator reaches resonant mode at 330 kHz by different driving methods.The relationship between resonant amplitude and driving signal amplitude is linear. The quality factor reaches over 150 by different driving methods. The results provide a theoretical reference for the efficient excitation of the piezoelectric resonator.

SIES:A Novel Implementation of Spiking Convolutional Neural Network Inference Engine on Field-Programmable Gate Array

Neuromorphic computing is considered to be the future of machine learning,and it provides a new way of cognitive computing.Inspired by the excellent performance of spiking neural networks(SNNs)on the fields of low-power consumption and parallel computing,many groups tried to simulate the SNN with the hardware platform.However,the efficiency of training SNNs with neuromorphic algorithms is not ideal enough.Facing this,Michael et al.proposed a method which can solve the problem with the help of DNN(deep neural network).With this method,we can easily convert a well-trained DNN into an SCNN(spiking convolutional neural network).So far,there is a little of work focusing on the hardware accelerating of SCNN.The motivation of this paper is to design an SNN processor to accelerate SNN inference for SNNs obtained by this DNN-to-SNN method.We propose SIES(Spiking Neural Network Inference Engine for SCNN Accelerating).It uses a systolic array to accomplish the task of membrane potential increments computation.It integrates an optional hardware module of max-pooling to reduce additional data moving between the host and the SIES.We also design a hardware data setup mechanism for the convolutional layer on the SIES with which we can minimize the time of input spikes preparing.We implement the SIES on FPGA XCVU440.The number of neurons it supports is up to 4000 while the synapses are 256000.The SIES can run with the working frequency of 200 MHz,and its peak performance is 1.5625 TOPS.

Speech Separation Algorithm Using Gated Recurrent Network Based on Microphone Array

Speech separation is an active research topic that plays an important role in numerous applications,such as speaker recognition,hearing pros-thesis,and autonomous robots.Many algorithms have been put forward to improve separation performance.However,speech separation in reverberant noisy environment is still a challenging task.To address this,a novel speech separation algorithm using gate recurrent unit(GRU)network based on microphone array has been proposed in this paper.The main aim of the proposed algorithm is to improve the separation performance and reduce the computational cost.The proposed algorithm extracts the sub-band steered response power-phase transform(SRP-PHAT)weighted by gammatone filter as the speech separation feature due to its discriminative and robust spatial position in formation.Since the GRU net work has the advantage of processing time series data with faster training speed and fewer training parameters,the GRU model is adopted to process the separation featuresof several sequential frames in the same sub-band to estimate the ideal Ratio Masking(IRM).The proposed algorithm decomposes the mixture signals into time-frequency(TF)units using gammatone filter bank in the frequency domain,and the target speech is reconstructed in the frequency domain by masking the mixture signal according to the estimated IRM.The operations of decomposing the mixture signal and reconstructing the target signal are completed in the frequency domain which can reduce the total computational cost.Experimental results demonstrate that the proposed algorithm realizes omnidirectional speech sep-aration in noisy and reverberant environments,provides good performance in terms of speech quality and intelligibility,and has the generalization capacity to reverberate.

一款基于新型Field Programmable Gate Array芯片的投影仪梯形校正系统研究与实现

投影设备配备的梯形校正普遍存在校正范围小,画面的一些线条和字符边缘会出现毛刺和不平滑现象,矫正效果不理想.如果采用通用的图像处理芯片和复杂的算法,可以解决上述问题,但又会导致成本急剧上升.为了解决上述矛盾,提出一种基于FPGA(Field Programmable Gate Array)芯片的新型梯形校正实现方案,解决了校正范围与锯齿失真的矛盾问题,并为进一步成为芯片级产品铺平了道路.图像处理采用kaiser窗函数和sinc函数相结合的方法进行插值,这样的滤波器改善了旁瓣抑制,具有较好的通带性能.介绍了梯形失真的产生和校正原理,提出了利用FPGA芯片XC3S400作为核心图像处理单元的梯形校正系统的硬件和软件实现,说明了该芯片结构、功能及特性,最后提供了校正的效果图.

A New Design Method for Variable Digital Filter Based on Field Programmable Gate Array(FPGA)

In order to obtain variable characteristics,the digital filter's type,number of taps and coefficients should be changed constantly such that the desired frequency-domain characteristics can be obtained.This paper proposes a method for self-programmable variable digital filter(VDF) design based on field programmable gate array(FPGA).We implement a digital filter system by using custom embedded micro-processor,programmable finite impulse response(P-FIR) macro module,coefficient-loader,clock manager and analog/digital(A/D) or digital/analog(D/A) controller and other modules.The self-programmable VDF can provide the best solution for realization of digital filter algorithms,which are the low-pass,high-pass,band-pass and band-stop filter algorithms with variable frequency domain characteristics.The design examples with minimum 1 to maximum 32 taps FIR filter,based on Modelsim post-routed simulation and onboard running on XUPV5-LX110T,are provided to demonstrate the effectiveness of the proposed method.

A novel fuzzy logic direct torque controller for a permanent magnet synchronous motor with a field programmable gate array

A high-performance digital servo system built on the platform of a field programmable gate array (FPGA),a fully digitized hardware design scheme of a direct torque control (DTC) and a low speed permanent magnet synchronous motor (PMSM) is proposed. The DTC strategy of PMSM is described with Verilog hardware description language and is employed on-chip FPGA in accordance with the electronic design automation design methodology. Due to large torque ripples in low speed PMSM,the hysteresis controller in a conventional PMSM DTC was replaced by a fuzzy controller. This FPGA scheme integrates the direct torque controller strategy,the time speed measurement algorithm,the fuzzy regulating technique and the space vector pulse width modulation principle. Experimental results indicate the fuzzy controller can provide a controllable speed at 20 r min-1 and torque at 330 N m with satisfactory dynamic and static performance. Furthermore,the results show that this new control strategy decreases the torque ripple drastically and enhances control performance.

Synthesis of Nonlinear Control of Switching Topologies of Buck-Boost Converter Using Fuzzy Logic on Field Programmable Gate Array (FPGA)

An intelligent fuzzy logic inference pipeline for the control of a dc-dc buck-boost converter was designed and built using a semi-custom VLSI chip. The fuzzy linguistics describing the switching topologies of the converter was mapped into a look-up table that was synthesized into a set of Boolean equations. A VLSI chip–a field programmable gate array (FPGA) was used to implement the Boolean equations. Features include the size of RAM chip independent of number of rules in the knowledge base, on-chip fuzzification and defuzzification, faster response with speeds over giga fuzzy logic inferences per sec (FLIPS), and an inexpensive VLSI chip. The key application areas are: 1) on-chip integrated controllers;and 2) on-chip co-integration for entire system of sensors, circuits, controllers, and detectors for building complete instrument systems.

Implimentations of SIMD machine using programmable gate array

Field Programmable Gate Array(FPGA) and Single Instruction Multiple Data(SIMD) processing array share many architecture features. In both architectures, an array is employed to provide high speed computation. In this paper we show that the implementation of a Single Instruction Multiple Data (SIMD) machine the ABC 90 using the Field Programmable Gate Array (FPGA) is not completely suitable because of its characteristics. The comparison between the programmable gate arrays show that, they have many architectures features in common. Within this framework, we examine the differences and similarities between these array structures and touch upon techniques and lessons which can be done between these architectures in order to choose the appropriate Programmable gate array to implement a general purpose parallel computer. In this paper we introduce the principal of the Dynamically Programmable Date Array(DPGA) which combines the best feature of the FPGA and the SIMD arrays into a single array architecture. By the same way we show that the DPGA is more appropriate then the FPGA for wiring, hardwiring the general purpose parallel computers: SIMD and its implementation.

Fault Prediction and Diagnosis of Warship Equipment Field Programmable Gate Array Software

In order to solve the current high failure rate of warship equipment field programmable gate array( FPGA) software,fault detection is not timely enough and FPGA detection equipment is expensive and so on. After in-depth research,this paper proposes a warship equipment FPGA software based on Xilinx integrated development environment( ISE) and ModelSim software.Functional simulation and timing simulation to verify the correctness of the logic design of the FPGA,this method is very convenient to view the signal waveform inside the FPGA program to help FPGA test engineers to achieve FPGA fault prediction and diagnosis. This test method has important engineering significance for the upgrading of warship equipment.

Implementation of Synchronization Technology in Orthogonal Frequency Division Multiplex System Based on Field Programming Gate Array

In this paper,analyzed is the symbol synchronization algorithm in orthogonal frequency division multiplex(OFDM)system,and accomplished are the hardware circuit design of coarse and elaborate synchronization algorithms.Based on the analysis of coarse and elaborate synchronization algorithms,multiplexed are,the module accumulator,division and output judgement,which can evidently save the hardware resource cost.The analysis of circuit sequence and wave form simulation of the design scheme shows that the proposed method efficiently reduce system resources and power consumption.

Lax-Oleinik-Type Formulas and Efficient Algorithms for Certain High-Dimensional Optimal Control Problems

Two of the main challenges in optimal control are solving problems with state-dependent running costs and developing efficient numerical solvers that are computationally tractable in high dimensions.In this paper,we provide analytical solutions to certain optimal control problems whose running cost depends on the state variable and with constraints on the control.We also provide Lax-Oleinik-type representation formulas for the corresponding Hamilton-Jacobi partial differential equations with state-dependent Hamiltonians.Additionally,we present an efficient,grid-free numerical solver based on our representation formulas,which is shown to scale linearly with the state dimension,and thus,to overcome the curse of dimensionality.Using existing optimization methods and the min-plus technique,we extend our numerical solvers to address more general classes of convex and nonconvex initial costs.We demonstrate the capabilities of our numerical solvers using implementations on a central processing unit(CPU)and a field-programmable gate array(FPGA).In several cases,our FPGA implementation obtains over a 10 times speedup compared to the CPU,which demonstrates the promising performance boosts FPGAs can achieve.Our numerical results show that our solvers have the potential to serve as a building block for solving broader classes of high-dimensional optimal control problems in real-time.

Design of a High Precision Array Pulse Sensor in TCM

We designed a high-precision array pulse sensor for TCM （traditional Chinese medicine） that can directly transform pulse-pressure signal into electric current signal and is compatible with CMOS technology. We adopted a sacrificelayer craft for the transistor gate. During testing, we found that the precision of the capacitor for the array sensor is 0. 5fF/hPa when the pressure was changing within the range of 1.5kPa to 9.5kPa. More importantly, the output-current and the pressure of the sensor have a good linearity and exponential characteristics. According to the data from the experiment,we conclude that the characteristic of the response-current is related to the area of the MOS gate.

Machine learning algorithm partially reconfigured on FPGA for an image edge detection system

Unmanned aerial vehicles(UAVs)have been widely used in military,medical,wireless communications,aerial surveillance,etc.One key topic involving UAVs is pose estimation in autonomous navigation.A standard procedure for this process is to combine inertial navigation system sensor information with the global navigation satellite system(GNSS)signal.However,some factors can interfere with the GNSS signal,such as ionospheric scintillation,jamming,or spoofing.One alternative method to avoid using the GNSS signal is to apply an image processing approach by matching UAV images with georeferenced images.But a high effort is required for image edge extraction.Here a support vector regression(SVR)model is proposed to reduce this computational load and processing time.The dynamic partial reconfiguration(DPR)of part of the SVR datapath is implemented to accelerate the process,reduce the area,and analyze its granularity by increasing the grain size of the reconfigurable region.Results show that the implementation in hardware is 68 times faster than that in software.This architecture with DPR also facilitates the low power consumption of 4 mW,leading to a reduction of 57%than that without DPR.This is also the lowest power consumption in current machine learning hardware implementations.Besides,the circuitry area is 41 times smaller.SVR with Gaussian kernel shows a success rate of 99.18%and minimum square error of 0.0146 for testing with the planning trajectory.This system is useful for adaptive applications where the user/designer can modify/reconfigure the hardware layout during its application,thus contributing to lower power consumption,smaller hardware area,and shorter execution time.

大尺寸机载显示模块动态背光控制系统设计

机载大尺寸液晶显示器(liquid crystal display,LCD)显示模块具有亮度高和功耗大的特点。为了降低其动态功耗,介绍了一种用于大尺寸机载显示模块的动态背光控制系统。该系统采用发光二极管(light emitting diode,LED)动态背光控制技术,通过对背光的动态调节,提高动态显示效果和达到节能的目的。对系统的硬件电路和软件设计算法进行了详细的介绍,并进行实验验证。结果表明,该系统能够有效地提高机载显示模块的动态显示效果,并显著降低了动态功耗。

GJB 5000B在FPGA工程中的应用分析

为引入软件工程化管理办法对设计开发实践实施管理,结合GJB 5000B体系要求,对现场可编程逻辑门阵列(Field Programmable Gate Array,FPGA)的设计开发流程和GJB 5000B的工程实践要求进行梳理、比对和分析,并提出一套FPGA开发管理在GJB 5000B推进实践中的实施办法。研究成果可为GJB 5000B在FPGA工程中的应用提供一定参考。

Design and development of multi-channel front end electronics based on dual-polarity charge-to-digital converter for SiPM detector applications

With the development of silicon photomultiplier(SiPM)technology,front-end electronics for SiPM signal processing have been highly sought after in various fields.A compact 64-channel front-end electronics(FEE)system achieved by fieldprogrammable gate array-based charge-to-digital converter(FPGA-QDC)technology was built and developed.The FEE consists of an analog board and FPGA board.The analog board incorporates commercial amplifiers,resistors,and capacitors.The FPGA board is composed of a low-cost FPGA.The electronics performance of the FEE was evaluated in terms of noise,linearity,and uniformity.A positron emission tomography(PET)detector with three different readout configurations was designed to validate the readout capability of the FEE for SiPM-based detectors.The PET detector was made of a 15×15 lutetium–yttrium oxyorthosilicate(LYSO)crystal array directly coupled with a SiPM array detector.The experimental results show that FEE can process dual-polarity charge signals from the SiPM detectors.In addition,it shows a good energy resolution for 511-keV gamma photons under the dual-end readout for the LYSO crystal array irradiated by a Na-22 source.Overall,the FEE based on FPGA-QDC shows promise for application in SiPM-based radiation detectors.

An alternative approach of the programmable arrays and applications

There is an increasing interest of using the Programmable arrays for performing different hardware. In this paper we give an alternative approach and the applications of the Programmable Gate Arrays. We show the field and the domain where they are more adequate and wihch kind of Programmable array is more efficient to apply. The DPGA and the FPGA are both Programmable Gate Array. They have more possibilities then the conventional devices such as 64 bits microprocessor, however a microprocessor coupled with a programmable array has more opportunity and their implementation is increasing. It is impossible to enumerate all possible uses of Programmable Gate Array. However we use the parameters Latency and throughput. Finite State Machine(FSM), control of data path, processor coupled with a programmable array to build up an alternative approach of the devices and their applications.

Quantum Information Processing in a Coupled Cavity Array

We consider a one-dimensional array of L identical coupled cavities,and each cavity is doped with atwo-level qubit.Experimentally,it has been developed in several varieties by the newest technology.We find that theone-qubit quantum state can be perfectly transferred through the cavity array,and the entanglement between the firsttwo qubits can also be transferred to the last two qubits.In addition,we successfully realized the entangling gate andswap gate in the coupled cavity array.

FPGA-based acceleration for binary neural networks in edge computing

As a core component in intelligent edge computing,deep neural networks(DNNs)will increasingly play a critically important role in addressing the intelligence-related issues in the industry domain,like smart factories and autonomous driving.Due to the requirement for a large amount of storage space and computing resources,DNNs are unfavorable for resource-constrained edge computing devices,especially for mobile terminals with scarce energy supply.Binarization of DNN has become a promising technology to achieve a high performance with low resource consumption in edge computing.Field-programmable gate array(FPGA)-based acceleration can further improve the computation efficiency to several times higher compared with the central processing unit(CPU)and graphics processing unit(GPU).This paper gives a brief overview of binary neural networks(BNNs)and the corresponding hardware accelerator designs on edge computing environments,and analyzes some significant studies in detail.The performances of some methods are evaluated through the experiment results,and the latest binarization technologies and hardware acceleration methods are tracked.We first give the background of designing BNNs and present the typical types of BNNs.The FPGA implementation technologies of BNNs are then reviewed.Detailed comparison with experimental evaluation on typical BNNs and their FPGA implementation is further conducted.Finally,certain interesting directions are also illustrated as future work.