An artificial neural network chip based on two-dimensional semiconductor

被引：1

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

来源：

ScienceBulletin | 2022年 / 67卷 / 03期

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：

080903 ; 081104 ; 0812 ; 0835 ; 1401 ; 1405 ;

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

页码：270 / 277

页数：8

共 50 条

[41] Two-Dimensional Fast Orthogonal Neural Network for Image Recognition
Stasiak, Bartlomiej
PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, PROCEEDINGS, 2009, 5856 : 653 - 660
[42] Chaotic neural network applied to two-dimensional motion control
Hiroyuki Yoshida
Shuhei Kurata
Yongtao Li
Shigetoshi Nara
Cognitive Neurodynamics, 2010, 4 : 69 - 80
[43] Two-dimensional learning strategy for multilayer feedforward neural network
Chow, TWS
Fang, Y
NEUROCOMPUTING, 2000, 34 (34) : 195 - 206
[44] Chaotic neural network applied to two-dimensional motion control
Yoshida, Hiroyuki
Kurata, Shuhei
Li, Yongtao
Nara, Shigetoshi
COGNITIVE NEURODYNAMICS, 2010, 4 (01) : 69 - 80
[45] Two-Dimensional Convolutional Neural Network-Based Signal Detection for OTFS Systems
Enku, Yosef K.
Bai, Baoming
Wan, Fei
Guyo, Chala U.
Tiba, Isayiyas N.
Zhang, Chunqiong
Li, Shuangyang
IEEE WIRELESS COMMUNICATIONS LETTERS, 2021, 10 (11) : 2514 - 2518
[46] Two-dimensional film-cooling effectiveness prediction based on deconvolution neural network
Wang, Yaning
Wang, Wen
Tao, Guocheng
Zhang, Xinshuai
Luo, Shirui
Cui, Jiahuan
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER, 2021, 129
[47] Accurate Two-dimensional Classification of Stellar Spectra with Artificial Neural Networks
Weaver, W. B.
Torres-Dodgen, A. V.
Astrophysical Journal, 487 (01):
[48] Accurate two-dimensional classification of stellar spectra with artificial neural networks
Weaver, WB
TorresDodgen, AV
ASTROPHYSICAL JOURNAL, 1997, 487 (02) : 847 - 857
[49] Modeling of Writing Process for Two-Dimensional Magnetic Recording and Performance Evaluation of Two-Dimensional Neural Network Equalizer
Yamashita, Masato
Okamoto, Yoshihiro
Nakamura, Yasuaki
Osawa, Hisashi
Miura, Kenji
Greaves, Simon J.
Aoi, Hajime
Kanai, Yasushi
Muraoka, Hiroaki
IEEE TRANSACTIONS ON MAGNETICS, 2012, 48 (11) : 4586 - 4589
[50] On-chip Stokes Polarimeter Based on a Two-dimensional Grating
Wei, Yanxian
Zhou, Hailong
Dong, Jianji
Zhang, Xinliang
2019 PHOTONICS & ELECTROMAGNETICS RESEARCH SYMPOSIUM - FALL (PIERS - FALL), 2019, : 1185 - 1190

← 1 2 3 4 5 →