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 ...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.展开更多
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 conv...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.展开更多
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...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.展开更多
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 ...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.展开更多
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-dep...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.展开更多
This paper proposes a parallel cyclic shift structure of address decoder to realize a high-throughput encoding and decoding method for irregular-quasi-cyclic low-density parity-check(IR-QC-LDPC)codes,with a dual-diago...This paper proposes a parallel cyclic shift structure of address decoder to realize a high-throughput encoding and decoding method for irregular-quasi-cyclic low-density parity-check(IR-QC-LDPC)codes,with a dual-diagonal parity structure.A normalized min-sum algorithm(NMSA)is employed for decoding.The whole verification of the encoding and decoding algorithm is simulated with Matlab,and the code rates of 5/6 and 2/3 are selected respectively for the initial bit error ratio as 6%and 1.04%.Based on the results of simulation,multi-code rates are compatible with different basis matrices.Then the simulated algorithms of encoder and decoder are migrated and implemented on the field programmable gate array(FPGA).The 183.36 Mbps throughput of encoder and the average 27.85 Mbps decoding throughput with the initial bit error ratio 6%are realized based on FPGA.展开更多
SRAM(Static Random Access Memory)型FPGA凭借其动态结构调整的灵活性等特点,被广泛应用于工业领域。针对动态可重构功能单元的布局问题,分析了模拟退火解决方案的局限性,提出了基于电路分层划分和时延驱动的在线布局算法。算法首先按...SRAM(Static Random Access Memory)型FPGA凭借其动态结构调整的灵活性等特点,被广泛应用于工业领域。针对动态可重构功能单元的布局问题,分析了模拟退火解决方案的局限性,提出了基于电路分层划分和时延驱动的在线布局算法。算法首先按最小分割原则将电路划分为一定数目的层,然后按自顶向下的原则在芯片的每一层中布局划分出的层,同时保证电路关键路径的延时最小。实验结果表明,所述算法在时延、线长和运行时间方面均优于VPR算法。展开更多
Field Programmable Gate Array(FPGA) is an efficient reconfigurable integrated circuit platform and has become a core signal processing microchip device of digital systems over the last decade. With the rapid developme...Field Programmable Gate Array(FPGA) is an efficient reconfigurable integrated circuit platform and has become a core signal processing microchip device of digital systems over the last decade. With the rapid development of semiconductor technology, the performance and system integration of FPGA devices have been significantly progressed, and at the same time new challenges arise. The design of FPGA architecture is required to evolve to meet these challenges, while also taking advantage of ever increased microchip density. This survey reviews the recent development of advanced FPGA architectures, including improvement of the programming technologies, logic blocks, interconnects, and embedded resources. Moreover, some important emerging design issues of FPGA architectures, such as novel memory based FPGAs and 3D FPGAs, are also presented to provide an outlook for future FPGA development.展开更多
基金Science &Technology Plan Foundation of Hunan Province,China(No.2010F3102)Science Research Foundation of Hunan Province,China(No.08C392)
文摘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.
文摘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.
基金financially supported by the National Council for Scientific and Technological Development(CNPq,Brazil),Swedish-Brazilian Research and Innovation Centre(CISB),and Saab AB under Grant No.CNPq:200053/2022-1the National Council for Scientific and Technological Development(CNPq,Brazil)under Grants No.CNPq:312924/2017-8 and No.CNPq:314660/2020-8.
文摘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.
基金supported by the Natural Science Foundation of Sichuan Province of China under Grant No.2022NSFSC0500the National Natural Science Foundation of China under Grant No.62072076.
文摘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.
文摘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.
基金supported by the National Natural Science Foundation of China(11705191)the Anhui Provincial Natural Science Foundation(1808085QF180)the Natural Science Foundation of Shanghai(18ZR1443600)
文摘This paper proposes a parallel cyclic shift structure of address decoder to realize a high-throughput encoding and decoding method for irregular-quasi-cyclic low-density parity-check(IR-QC-LDPC)codes,with a dual-diagonal parity structure.A normalized min-sum algorithm(NMSA)is employed for decoding.The whole verification of the encoding and decoding algorithm is simulated with Matlab,and the code rates of 5/6 and 2/3 are selected respectively for the initial bit error ratio as 6%and 1.04%.Based on the results of simulation,multi-code rates are compatible with different basis matrices.Then the simulated algorithms of encoder and decoder are migrated and implemented on the field programmable gate array(FPGA).The 183.36 Mbps throughput of encoder and the average 27.85 Mbps decoding throughput with the initial bit error ratio 6%are realized based on FPGA.
文摘SRAM(Static Random Access Memory)型FPGA凭借其动态结构调整的灵活性等特点,被广泛应用于工业领域。针对动态可重构功能单元的布局问题,分析了模拟退火解决方案的局限性,提出了基于电路分层划分和时延驱动的在线布局算法。算法首先按最小分割原则将电路划分为一定数目的层,然后按自顶向下的原则在芯片的每一层中布局划分出的层,同时保证电路关键路径的延时最小。实验结果表明,所述算法在时延、线长和运行时间方面均优于VPR算法。
基金Supported by National Natural Science Foundation of China(No.61271149)National High Technology Research and Development Program of China(No.2012AA-012301)National Science and Technology Major Project of China(No.2013ZX03006004)
文摘Field Programmable Gate Array(FPGA) is an efficient reconfigurable integrated circuit platform and has become a core signal processing microchip device of digital systems over the last decade. With the rapid development of semiconductor technology, the performance and system integration of FPGA devices have been significantly progressed, and at the same time new challenges arise. The design of FPGA architecture is required to evolve to meet these challenges, while also taking advantage of ever increased microchip density. This survey reviews the recent development of advanced FPGA architectures, including improvement of the programming technologies, logic blocks, interconnects, and embedded resources. Moreover, some important emerging design issues of FPGA architectures, such as novel memory based FPGAs and 3D FPGAs, are also presented to provide an outlook for future FPGA development.