A Low Energy Oxide-Based Electronic Synaptic Device for Neuromorphic Visual Systems with Tolerance to Device Variation

被引:467
作者
Yu, Shimeng [1 ,2 ]
Gao, Bin [3 ]
Fang, Zheng [5 ]
Yu, Hongyu [4 ]
Kang, Jinfeng [3 ]
Wong, H. -S. Philip [1 ,2 ]
机构
[1] Stanford Univ, Dept Elect Engn, Stanford, CA 94305 USA
[2] Stanford Univ, Ctr Integrated Syst, Stanford, CA 94305 USA
[3] Peking Univ, Inst Microelect, Beijing 100871, Peoples R China
[4] South Univ Sci & Technol China, Shenzhen 518055, Peoples R China
[5] ASTAR, Inst Microelect, Singapore 117685, Singapore
关键词
resistive switching; oxide RRAM; synaptic devices; neuromorphic computing; artificial visual systems; SWITCHING PARAMETER VARIATION; SPIKING NEURONS; PLASTICITY; SYNAPSES; DESIGN; MEMORY;
D O I
10.1002/adma.201203680
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Neuromorphic computing is an emerging computing paradigm beyond the conventional digital von Neumann computation. An oxide-based resistive switching memory is engineered to emulate synaptic devices. At the device level, the gradual resistance modulation is characterized by hundreds of identical pulses, achieving a low energy consumption of less than 1 pJ per spike. Furthermore, a stochastic compact model is developed to quantify the device switching dynamics and variation. At system level, the performance of an artificial visual system on the image orientation or edge detection with 16 348 oxide-based synaptic devices is simulated, successfully demonstrating a key feature of neuromorphic computing: tolerance to device variation. [GRAPHICS] .
引用
收藏
页码:1774 / 1779
页数:6
相关论文
共 31 条
  • [1] Efficient Hybrid CMOS-Nano Circuit Design for Spiking Neurons and Memristive Synapses with STDP
    Afifi, Ahmad
    Ayatollahi, Ahmad
    Raissi, Farshid
    Hajghassem, Hasan
    [J]. IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, 2010, E93A (09) : 1670 - 1677
  • [2] Ananthanarayanan R., 2009, ACM IEEE C HIGH PERF
  • [3] [Anonymous], 1985, VOLUNTARY MOVEMENT
  • [4] Short-Term Memory to Long-Term Memory Transition in a Nanoscale Memristor
    Chang, Ting
    Jo, Sung-Hyun
    Lu, Wei
    [J]. ACS NANO, 2011, 5 (09) : 7669 - 7676
  • [5] HfOx/TiOx/HfOx/TiOx Multilayer-Based Forming-Free RRAM Devices With Excellent Uniformity
    Fang, Z.
    Yu, H. Y.
    Li, X.
    Singh, N.
    Lo, G. Q.
    Kwong, D. L.
    [J]. IEEE ELECTRON DEVICE LETTERS, 2011, 32 (04) : 566 - 568
  • [6] Govoreanu B, 2011, 2011 IEEE INTERNATIONAL ELECTRON DEVICES MEETING (IEDM)
  • [7] On the Switching Parameter Variation of Metal-Oxide RRAM-Part I: Physical Modeling and Simulation Methodology
    Guan, Ximeng
    Yu, Shimeng
    Wong, H. -S. Philip
    [J]. IEEE TRANSACTIONS ON ELECTRON DEVICES, 2012, 59 (04) : 1172 - 1182
  • [8] A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity
    Indiveri, G
    Chicca, E
    Douglas, R
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2006, 17 (01): : 211 - 221
  • [9] Nanoscale Memristor Device as Synapse in Neuromorphic Systems
    Jo, Sung Hyun
    Chang, Ting
    Ebong, Idongesit
    Bhadviya, Bhavitavya B.
    Mazumder, Pinaki
    Lu, Wei
    [J]. NANO LETTERS, 2010, 10 (04) : 1297 - 1301
  • [10] Kawahara A., 2012, 2012 IEEE International Solid-State Circuits Conference (ISSCC), P432, DOI 10.1109/ISSCC.2012.6177078