An artificial neural network chip based on two-dimensional semiconductor

被引:0
|
作者
Shunli Ma [1 ]
Tianxiang Wu [1 ]
Xinyu Chen [1 ]
Yin Wang [1 ]
Hongwei Tang [1 ]
Yuting Yao [1 ]
Yan Wang [1 ]
Ziyang Zhu [2 ]
Jianan Deng [2 ]
Jing Wan [2 ]
Ye Lu [2 ]
Zhengzong Sun [1 ]
Zihan Xu [3 ]
Antoine Riaud [1 ]
Chenjian Wu [4 ]
David Wei Zhang [1 ]
Yang Chai [5 ]
Peng Zhou [1 ]
Junyan Ren [1 ]
Wenzhong Bao [1 ]
机构
[1] State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University
[2] State Key Laboratory of ASIC and System, School of Information Science and Technology, Fudan University
[3] Shenzhen Sixcarbon Technology
[4] School of Electronic and Information Engineering, Soochow University
[5] Department of Applied Physics, The Hong Kong Polytechnic University
基金
中国国家自然科学基金; 上海市自然科学基金;
关键词
D O I
暂无
中图分类号
TP183 [人工神经网络与计算]; TN40 [一般性问题];
学科分类号
摘要
Recently,research on two-dimensional (2D) semiconductors has begun to translate from the fundamental investigation into rudimentary functional circuits.In this work,we unveil the first functional MoS2artificial neural network (ANN) chip,including multiply-and-accumulate (MAC),memory and activation function circuits.Such MoS2ANN chip is realized through fabricating 818 field-effect transistors (FETs) on a wafer-scale and high-homogeneity MoS2film,with a gate-last process to realize top gate structured FETs.A 62-level simulation program with integrated circuit emphasis (SPICE) model is utilized to design and optimize our analog ANN circuits.To demonstrate a practical application,a tactile digit sensing recognition was demonstrated based on our ANN circuits.After training,the digit recognition rate exceeds 97%.Our work not only demonstrates the protentional of 2D semiconductors in wafer-scale integrated circuits,but also paves the way for its future application in AI computation.
引用
收藏
页码:270 / 277
页数:8
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