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Science China(Information Sciences) 2022年第8期65卷 297-298页

作者： Xuepeng ZHAN jiezhi chen Zhigang JI School of Information Science and Engineering Shandong University State Key Laboratory of High-end Server and Storage Technology National Key Laboratory of Science and Technology on Micro/Nano Fabrication Shanghai Jiaotong University

Dear editor,Random telegraph noise(RTN) has attracted rising attention with the diminishing device size. In each device, the number of dopant atoms and defects reduces to quantifiable levels, resulting in higher time-zero and-dependent variability. RTN is observed as the sudden and random discrete drain current fluctuation under constant voltage,

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Flash memory based computing-in-memory system to solve partial differential equations

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Science China(Information Sciences) 2021年第6期64卷 257-258页

作者： Yang FENG Fei WANG Xuepeng ZHAN Yuan LI jiezhi chen School of Information Science and Engineering Shandong University

Dear editor,Many emerging non-volatile memories(NVM), such as resistive random access memory(RRAM) [1], phase-change memory(PCM) [2], and ferroelectric RAM(FeR AM) [3],together with the conventional flash memory [4, 5... 详细信息

关键词： Flash memory based computing-in-memory system to solve partial differential equations

Laser processing induced nonvolatile memory in chaotic graphene oxide films for flexible reservoir computing applications

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Journal of Semiconductors 2024年第12期45卷 130-134页

作者： Bo chen Baojie Zhu Yifan Wu Pengpeng Sang Jixuan Wu Xuepeng Zhan jiezhi chen School of Information Science and Engineering(ISE) Shandong UniversityQingdao 266237China

Graphene oxide,as a 2D material with nanometer thickness,offers ultra-high mobility,chaotic properties,and low *** make graphene oxide memristors beneficial for reservoir computing(RC)*** this study,continuous-wave(CW)laser processing is used to reduce chaotic graphene oxide(CGO)films,resulting in the non-volatile storage capability based on the reduced chaotic graphene oxide(rCGO)*** power significantly impacts the characteristics of the rCGO *** characterization indicates that laser radiation can effectively reduce the oxygen content in CGO *** optimized laser power,the rCGO memristor achieves a large ratio at 18 mW laser *** from the short-term mem-ory characteristics,distinct conductive states are achieved,which are further utilized to construct RC *** a third con-trol probe,the rCGO memristor can express rich reservoir states,demonstrating accuracy in predicting the Hénon map with an NRMSE below *** findings provide the potential for developing flexible RC networks based on graphene oxide memris-tors via laser processing.

关键词： chaotic graphene oxide laser processing reservoir computing

A gate-tunable artificial synapse based on vertically assembled van der Waals ferroelectric heterojunction

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Journal of Materials Science & Technology 2022年第33期128卷 239-244页

作者： Yaning Wang Wanying Li Yimeng Guo Xin Huang Zhaoping Luo Shuhao Wu Hai Wang jiezhi chen Xiuyan Li Xuepeng Zhan Hanwen Wang Shenyang National Laboratory for Materials Science Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China School of Material Science and Engineering University of Science and Technology of ChinaShenyang 110016China Department of Applied Physics Aalto UniversityAaltoFinland School of Information Science and Engineering(ISE) Shandong UniversityQingdao 266237China

Memtransistor,a multi-terminal device that combines both the characteristics of a memristor and a transistor,has been intensively studied in two-dimensional layered materials(2 DLM),which show potential for applications in such as neuromorphic ***,while often based on the migration of ions or atomic defects in the conduction channels,performances of memtransistors suffer from the poor reliability and ***,those known 2 DLM-based memtransistors are mostly constructed in a lateral manner,which hinders the further increasing of the transistor densities per *** now,fabricating non-atomic-diffusion based memtransistors with vertical structure remains ***,we demonstrate a vertically-integrated ferroelectric memristor by hetero-integrating the 2 D ferroelectric materials CuInP_(2)S_(6)(CIPS)into a graphite/CuInP_(2)S_(6)/MoS_(2)vertical *** behaviour and multi-level resistance states were *** synaptic behaviours including excitatory postsynaptic current,paired-pulse-facilitation,and spike-amplitude-dependent plasticity are successfully ***,by applying a gate potential,the memristive behaviour and synaptic features can be effectively gate *** findings pave the way for the realization of novel gate-tunable ferroelectric synaptic devices with the capability to perform complex neural functions.

关键词： van der Waals heterostructures Ferroelectrics Memristor Artificial synapse Neuromorphic computing

Optimized operation scheme of flash-memory-based neural network online training with ultra-high endurance

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Journal of Semiconductors 2024年第1期45卷 33-37页

作者： Yang Feng Zhaohui Sun Yueran Qi Xuepeng Zhan Junyu Zhang Jing Liu Masaharu Kobayashi Jixuan Wu jiezhi chen School of Information Science and Engineering(ISE) Shandong UniversityQingdao 266200China Neumem Co. LtdHefei 230093China Key Laboratory of Microelectronic Devices and Integrated Technology Institute of Microelectronics of Chinese Academy of SciencesBeijing 100084China Institute of Industrial Science The University of TokyoTokyoJapan

With the rapid development of machine learning,the demand for high-efficient computing becomes more and more *** break the bottleneck of the traditional Von Neumann architecture,computing-in-memory(CIM)has attracted increasing attention in recent *** this work,to provide a feasible CIM solution for the large-scale neural networks(NN)requiring continuous weight updating in online training,a flash-based computing-in-memory with high endurance(10^(9) cycles)and ultrafast programming speed is *** the one hand,the proposed programming scheme of channel hot electron injection(CHEI)and hot hole injection(HHI)demonstrate high linearity,symmetric potentiation,and a depression process,which help to improve the training speed and *** the other hand,the low-damage programming scheme and memory window(MW)optimizations can suppress cell degradation effectively with improved computing *** after 109 cycles,the leakage current(I_(off))of cells remains sub-10pA,ensuring the large-scale computing ability of *** characterizations are done on read disturb to demonstrate its robust *** processing CIFAR-10 tasks,it is evident that~90%accuracy can be achieved after 109 cycles in both ResNet50 and VGG16 *** results suggest that flash-based CIM has great potential to overcome the limitations of traditional Von Neumann architectures and enable high-performance NN online training,which pave the way for further development of artificial intelligence(AI)accelerators.

关键词： NOR flash memory computing-in-memory endurance neural network online training

Thin film ferroelectric photonic-electronic memory

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Light(Science & Applications) 2024年第10期13卷 2251-2262页

作者： Gong Zhang Yue chen Zijie Zheng Rui Shao Jiuren Zhou Zuopu Zhou Leming Jiao Jishen Zhang Haibo Wang Qiwen Kong chen Sun Kai Ni Jixuan Wu jiezhi chen Xiao Gong Department of Electrical and Computer Engineering National University of SingaporeSingapore 119077Singapore Department of Microelectronic Engineering Rochester Institute of TechnologyRochesterNY 14623USA School of Information Science and Engineering Shandong UniversityJinan 250100China

To reduce system complexity and bridge the interface between electronic and photonic circuits,there is a high demand for a non-volatile memory that can be accessed both electrically and ***,practical solutions are still lacking when considering the potential for large-scale complementary metal-oxide semiconductor compatible ***,we present an experimental demonstration of a non-volatile photonic-electronic memory based on a 3-dimensional monolithic integrated ferroelectric-silicon ring *** successfully demonstrate programming and erasing the memory using both electrical and optical methods,assisted by optical-to-electrical-to-optical *** memory cell exhibits a high optical extinction ratio of 6.6 dB at a low working voltage of 5 V and an endurance of 4×10^(4) ***,the multi-level storage capability is analyzed in detail,revealing stable performance with a raw bit-error-rate smaller than 5.9×10^(−2).This ground-breaking work could be a key technology enabler for future hybrid electronic-photonic systems,targeting a wide range of applications such as photonic interconnect,high-speed data communication,and neuromorphic computing.

关键词： resonator electronic ferroelectric

Flash-based in-memory computing for stochastic computing in image edge detection

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Journal of Semiconductors 2023年第5期44卷 145-149页

作者： Zhaohui Sun Yang Feng Peng Guo Zheng Dong Junyu Zhang Jing Liu Xuepeng Zhan Jixuan Wu jiezhi chen School of Information Science and Engineering(ISE) Shandong UniversityQingdao 266000China Shandong Sinochip Semiconductors Co.Ltd Jinan 250101China Neumem Co. LtdHefei 230088China Key Laboratory of Microelectronic Devices and Integrated Technology Institute of Microelectronics of Chinese Academy of SciencesBeijing 100029China

The“memory wall”of traditional von Neumann computing systems severely restricts the efficiency of data-intensive task execution,while in-memory computing(IMC)architecture is a promising approach to breaking the *** variations and instability in ultra-scaled memory cells seriously degrade the calculation accuracy in IMC architectures,stochastic computing(SC)can compensate for these shortcomings due to its low sensitivity to cell ***,massive parallel computing can be processed to improve the speed and efficiency of the *** this paper,by designing logic functions in NOR flash arrays,SC in IMC for the image edge detection is realized,demonstrating ultra-low computational complexity and power consumption(25.5 fJ/pixel at 2-bit sequence length).More impressively,the noise immunity is 6 times higher than that of the traditional binary method,showing good tolerances to cell variation and reliability degradation when implementing massive parallel computation in the array.

关键词： in-memory computing stochastic computing NOR flash memory image edge detection

A 3D MCAM architecture based on flash memory enabling binary neural network computing for edge AI

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Science China(Information Sciences) 2024年第12期67卷 302-310页

作者： Maoying BAI Shuhao WU Hai WANG Hua WANG Yang FENG Yueran QI chengcheng WANG Zheng CHAI Tai MIN Jixuan WU Xuepeng ZHAN jiezhi chen School of Information Science and Engineering Shandong University Center for Spintronic and Quantum Systems State Key Laboratory for Mechanical Behavior of MaterialsSchool of Materials Science and Engineering Xi'an Jiaotong University

The in-memory computing(IMC) architecture implemented by non-volatile memory units shows great possibilities to break the traditional von Neumann bottleneck. In this paper, a 3D IMC architecture is proposed whose unit is based on a multi-bit content-addressable memory(MCAM). The MCAM unit is comprised of two 65 nm flash memory and two transistors(2Flash2T), which is reconfigurable and multifunctional for both data write/search and XNOR logic operation. Moreover, the MCAM array can also support the population count(POPCOUNT) operation, which can be beneficial for the training and inference process in binary neural network(BNN) computing. Based on the well-known MNIST dataset, the proposed 3D MCAM architecture shows a 98.63% recognition accuracy and a 300% noise-tolerant performance without significant accuracy deterioration. Our findings can provide the potential for developing highly energy-efficient BNN computing for complex artificial intelligence(AI) tasks based on flash-based MCAM units.

关键词： reconfigurable multifunction multi-bit content-addressable memory (MCAM) bitwise operation binary neural network edge AI flash memory in-memory computing (IMC)

Near-threshold-voltage operation in flash-based high-precision computing-in-memory to implement Poisson image editing

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Science China(Information Sciences) 2023年第12期66卷 261-266页

作者： Yang FENG Bing chen Mingfeng TANG Yueran QI Maoying BAI chengcheng WANG Hai WANG Xuepeng ZHAN Junyu ZHANG Jing LIU Jixuan WU jiezhi chen School of Information Science and Engineering Shandong University School of Micro-nano Electronics Zhejiang University Neumem Co. Ltd Key Laboratory of Microelectronic Devices and Integrated Technology Institute of Microelectronics of Chinese Academy of Sciences

We propose a NOR flash-based computing-in-memory(CIM) to implement high-precision(32-bit) Poisson image editing, including the gradient operations and Laplace operation. To meet the requirements of image processing, CIM operation schemes and reliabilities are carefully studied and optimized,showing that the power consumption at the near-threshold-voltage(NTV) region can be as low as 40 fJ/bit,which is two orders lower than working at the saturation region. High-temperature retention, as well as various disturbs, are also analyzed. The proposed CIM scheme can be applied as an energy-efficient approach to construct the high-precision image processing accelerator.

关键词： NOR flash memory computing-in-memory variation Poisson image editing

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纳电子器件的少电子输运性质及应用

固体电子学研究与进展 2006年第4期26卷 427-431页

作者：陈杰智施毅濮林刘明郑有炓南京大学物理系中国科学院微电子研究所纳米技术与新器件集成技术实验室北京100083

在介绍纳电子器件基本输运理论基础上,着重分析量子点结构器件模型,讨论了量子点上能级分立和电子填充的各种情况,以及电子自旋的影响,特别强调了纳米限制系统中局域态电子和非局域态电子相互作用特征。综述了目前纳电子器件的研究进展... 详细信息

在介绍纳电子器件基本输运理论基础上,着重分析量子点结构器件模型,讨论了量子点上能级分立和电子填充的各种情况,以及电子自旋的影响,特别强调了纳米限制系统中局域态电子和非局域态电子相互作用特征。综述了目前纳电子器件的研究进展及其应用。

关键词：纳电子器件少电子输运库仑阻塞近藤效应