Memristors, as memristive devices, have received a great deal of interest since being fabricated by HP labs. The forgetting effect that has significant influences on memristors＇ performance has to be taken into accou...Memristors, as memristive devices, have received a great deal of interest since being fabricated by HP labs. The forgetting effect that has significant influences on memristors＇ performance has to be taken into account when they are employed. It is significant to build a good model that can express the forgetting effect well for application researches due to its promising prospects in brain-inspired computing. Some models are proposed to represent the forgetting effect but do not work well. In this paper, we present a novel window function, which has good performance in a drift model. We analyze the deficiencies of the previous drift diffusion models for the forgetting effect and propose an improved model. Moreover,the improved model is exploited as a synapse model in spiking neural networks to recognize digit images. Simulation results show that the improved model overcomes the defects of the previous models and can be used as a synapse model in brain-inspired computing due to its synaptic characteristics. The results also indicate that the improved model can express the forgetting effect better when it is employed in spiking neural networks, which means that more appropriate evaluations can be obtained in applications.展开更多
By definition, bionics is the application of biological mechanisms found in nature to artificial systems in order to achieve specific functional goals. Successful examples range from Velcro, the touch fastener inspire...By definition, bionics is the application of biological mechanisms found in nature to artificial systems in order to achieve specific functional goals. Successful examples range from Velcro, the touch fastener inspired by the hooks of burrs, to self-cleaning material, inspired by the surface of the lotus leaf. Recently, a new trend in bionics i Brain-Inspired Computing （BIC） - has captured increasing attention. Instead of learning from burrs and leaves, BIC aims to understand the brain and then utilize its operating principles to achieve powerful and efficient information processing.展开更多
Recent advances in Artificial Intelligence(AI)have indicated that inspirations from the brain can effectively improve the level of intelligence for AI computational models,even if just local and partial inspirations.N...Recent advances in Artificial Intelligence(AI)have indicated that inspirations from the brain can effectively improve the level of intelligence for AI computational models,even if just local and partial inspirations.Nevertheless,realizing and exceeding intelligence at a human level still needs a deeper investigation and inspirations from the brain.The goal of brain-inspired intelligence is to achieve human intelligence inspired from brain neural mechanism and cognitive behavior mechanism.To this end,in this paper we introduce the relationship between AI and neuroscience,the current status of brain-inspired intelligence,the future work in intelligent control systems,and its profound influence in other fields.展开更多
A team of researchers from the University of Science and Technology of China(USTC)of the Chinese Academy of Sciences(CAS)and its partners have made significant advancements in random quantum circuit sampling with Zuch...A team of researchers from the University of Science and Technology of China(USTC)of the Chinese Academy of Sciences(CAS)and its partners have made significant advancements in random quantum circuit sampling with Zuchongzhi-3,a superconducting quantum computing prototype featuring 105 qubits and 182 couplers.展开更多
目前,多核实时系统中同步任务的节能调度研究主要针对的是同构多核处理器平台,而异构多核处理器架构能够更有效地发挥系统性能。将现有的研究直接应用于异构多核系统,在保证可调度性的情况下会导致能耗变高。对此,通过使用动态电压与频...目前,多核实时系统中同步任务的节能调度研究主要针对的是同构多核处理器平台,而异构多核处理器架构能够更有效地发挥系统性能。将现有的研究直接应用于异构多核系统,在保证可调度性的情况下会导致能耗变高。对此,通过使用动态电压与频率调节(Dynamic Voltage Frequency Scaling,DVFS)技术,研究异构多核实时系统中基于任务同步的节能调度问题,提出同步感知的最大能耗节省优先算法(Synchronization Aware-Largest Energy Saved First,SA-LESF)。该算法针对所有任务的速度配置进行迭代优化,直至所有任务均达到其最大限度节能的速度配置。此外,进一步提出基于动态松弛时间回收的同步感知最大能耗节省优先算法(Synchronization Aware-Largest Energy Saved First with Dynamic Reclamation,SA-LESF-DR)。该算法在保证实时任务可调度的同时,实施相应的回收策略,进一步降低系统能耗。实验结果表明,SA-LESF与SA-LESF-DR算法在能耗表现上具有优势,在相同任务集下,相比其他算法可节省高达30%的能耗。展开更多
This paper presents a smart compensation system based on MCA7707 (a kind of signal processor). The li near errors and high order errors of a sensor (especially piezoresistive sensor) can be corrected by using this s...This paper presents a smart compensation system based on MCA7707 (a kind of signal processor). The li near errors and high order errors of a sensor (especially piezoresistive sensor) can be corrected by using this system. It can optimize the process of piezoresi stive sensor calibration and compensation, then, a total error factor within 0.2 % of the sensor′s repeatability errors is obtained. Data are recorded and coeff icients are determined automatically by this system, thus, the sensor compensati on is simplified greatly. For operating easily, a wizard compensation program is designed to correct every error and to get the optimum compensation.展开更多
As an important branch of information security algorithms,the efficient and flexible implementation of stream ciphers is vital.Existing implementation methods,such as FPGA,GPP and ASIC,provide a good support,but they ...As an important branch of information security algorithms,the efficient and flexible implementation of stream ciphers is vital.Existing implementation methods,such as FPGA,GPP and ASIC,provide a good support,but they could not achieve a better tradeoff between high speed processing and high flexibility.ASIC has fast processing speed,but its flexibility is poor,GPP has high flexibility,but the processing speed is slow,FPGA has high flexibility and processing speed,but the resource utilization is very low.This paper studies a stream cryptographic processor which can efficiently and flexibly implement a variety of stream cipher algorithms.By analyzing the structure model,processing characteristics and storage characteristics of stream ciphers,a reconfigurable stream cryptographic processor with special instructions based on VLIW is presented,which has separate/cluster storage structure and is oriented to stream cipher operations.The proposed instruction structure can effectively support stream cipher processing with multiple data bit widths,parallelism among stream cipher processing with different data bit widths,and parallelism among branch control and stream cipher processing with high instruction level parallelism;the designed separate/clustered special bit registers and general register heaps,key register heaps can satisfy cryptographic requirements.So the proposed processor not only flexibly accomplishes the combination of multiple basic stream cipher operations to finish stream cipher algorithms.It has been implemented with 0.18μm CMOS technology,the test results show that the frequency can reach 200 MHz,and power consumption is 310 mw.Ten kinds of stream ciphers were realized in the processor.The key stream generation throughput of Grain-80,W7,MICKEY,ACHTERBAHN and Shrink algorithm is 100 Mbps,66.67 Mbps,66.67 Mbps,50 Mbps and 800 Mbps,respectively.The test result shows that the processor presented can achieve good tradeoff between high performance and flexibility of stream ciphers.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.61332003)High Performance Computing Laboratory,China(Grant No.201501-02)
文摘Memristors, as memristive devices, have received a great deal of interest since being fabricated by HP labs. The forgetting effect that has significant influences on memristors＇ performance has to be taken into account when they are employed. It is significant to build a good model that can express the forgetting effect well for application researches due to its promising prospects in brain-inspired computing. Some models are proposed to represent the forgetting effect but do not work well. In this paper, we present a novel window function, which has good performance in a drift model. We analyze the deficiencies of the previous drift diffusion models for the forgetting effect and propose an improved model. Moreover,the improved model is exploited as a synapse model in spiking neural networks to recognize digit images. Simulation results show that the improved model overcomes the defects of the previous models and can be used as a synapse model in brain-inspired computing due to its synaptic characteristics. The results also indicate that the improved model can express the forgetting effect better when it is employed in spiking neural networks, which means that more appropriate evaluations can be obtained in applications.
文摘By definition, bionics is the application of biological mechanisms found in nature to artificial systems in order to achieve specific functional goals. Successful examples range from Velcro, the touch fastener inspired by the hooks of burrs, to self-cleaning material, inspired by the surface of the lotus leaf. Recently, a new trend in bionics i Brain-Inspired Computing （BIC） - has captured increasing attention. Instead of learning from burrs and leaves, BIC aims to understand the brain and then utilize its operating principles to achieve powerful and efficient information processing.
基金supported by the General Program of National Natural Science Foundation of China(Grant No.61876021)the General Program of Beijing Natural Science Foundation(Grant No.4212037)。
文摘Recent advances in Artificial Intelligence(AI)have indicated that inspirations from the brain can effectively improve the level of intelligence for AI computational models,even if just local and partial inspirations.Nevertheless,realizing and exceeding intelligence at a human level still needs a deeper investigation and inspirations from the brain.The goal of brain-inspired intelligence is to achieve human intelligence inspired from brain neural mechanism and cognitive behavior mechanism.To this end,in this paper we introduce the relationship between AI and neuroscience,the current status of brain-inspired intelligence,the future work in intelligent control systems,and its profound influence in other fields.
文摘A team of researchers from the University of Science and Technology of China(USTC)of the Chinese Academy of Sciences(CAS)and its partners have made significant advancements in random quantum circuit sampling with Zuchongzhi-3,a superconducting quantum computing prototype featuring 105 qubits and 182 couplers.
文摘目前,多核实时系统中同步任务的节能调度研究主要针对的是同构多核处理器平台,而异构多核处理器架构能够更有效地发挥系统性能。将现有的研究直接应用于异构多核系统,在保证可调度性的情况下会导致能耗变高。对此,通过使用动态电压与频率调节(Dynamic Voltage Frequency Scaling,DVFS)技术,研究异构多核实时系统中基于任务同步的节能调度问题,提出同步感知的最大能耗节省优先算法(Synchronization Aware-Largest Energy Saved First,SA-LESF)。该算法针对所有任务的速度配置进行迭代优化,直至所有任务均达到其最大限度节能的速度配置。此外,进一步提出基于动态松弛时间回收的同步感知最大能耗节省优先算法(Synchronization Aware-Largest Energy Saved First with Dynamic Reclamation,SA-LESF-DR)。该算法在保证实时任务可调度的同时,实施相应的回收策略,进一步降低系统能耗。实验结果表明,SA-LESF与SA-LESF-DR算法在能耗表现上具有优势,在相同任务集下,相比其他算法可节省高达30%的能耗。
文摘This paper presents a smart compensation system based on MCA7707 (a kind of signal processor). The li near errors and high order errors of a sensor (especially piezoresistive sensor) can be corrected by using this system. It can optimize the process of piezoresi stive sensor calibration and compensation, then, a total error factor within 0.2 % of the sensor′s repeatability errors is obtained. Data are recorded and coeff icients are determined automatically by this system, thus, the sensor compensati on is simplified greatly. For operating easily, a wizard compensation program is designed to correct every error and to get the optimum compensation.
基金supported by National Natural Science Foundation of China with granted No.61404175
文摘As an important branch of information security algorithms,the efficient and flexible implementation of stream ciphers is vital.Existing implementation methods,such as FPGA,GPP and ASIC,provide a good support,but they could not achieve a better tradeoff between high speed processing and high flexibility.ASIC has fast processing speed,but its flexibility is poor,GPP has high flexibility,but the processing speed is slow,FPGA has high flexibility and processing speed,but the resource utilization is very low.This paper studies a stream cryptographic processor which can efficiently and flexibly implement a variety of stream cipher algorithms.By analyzing the structure model,processing characteristics and storage characteristics of stream ciphers,a reconfigurable stream cryptographic processor with special instructions based on VLIW is presented,which has separate/cluster storage structure and is oriented to stream cipher operations.The proposed instruction structure can effectively support stream cipher processing with multiple data bit widths,parallelism among stream cipher processing with different data bit widths,and parallelism among branch control and stream cipher processing with high instruction level parallelism;the designed separate/clustered special bit registers and general register heaps,key register heaps can satisfy cryptographic requirements.So the proposed processor not only flexibly accomplishes the combination of multiple basic stream cipher operations to finish stream cipher algorithms.It has been implemented with 0.18μm CMOS technology,the test results show that the frequency can reach 200 MHz,and power consumption is 310 mw.Ten kinds of stream ciphers were realized in the processor.The key stream generation throughput of Grain-80,W7,MICKEY,ACHTERBAHN and Shrink algorithm is 100 Mbps,66.67 Mbps,66.67 Mbps,50 Mbps and 800 Mbps,respectively.The test result shows that the processor presented can achieve good tradeoff between high performance and flexibility of stream ciphers.
