摘要
AI development has brought great success to upgrading the information age.At the same time,the large-scale artificial neural network for building AI systems is thirsty for computing power,which is barely satisfied by the conventional computing hardware.In the post-Moore era,the increase in computing power brought about by the size reduction of CMOS in very large-scale integrated circuits(VLSIC)is challenging to meet the growing demand for AI computing power.To address the issue,technical approaches like neuromorphic computing attract great attention because of their feature of breaking Von-Neumann architecture,and dealing with AI algorithms much more parallelly and energy efficiently.Inspired by the human neural network architecture,neuromorphic computing hardware is brought to life based on novel artificial neurons constructed by new materials or devices.Although it is relatively difficult to deploy a training process in the neuromorphic architecture like spiking neural network(SNN),the development in this field has incubated promising technologies like in-sensor computing,which brings new opportunities for multidisciplinary research,including the field of optoelectronic materials and devices,artificial neural networks,and microelectronics integration technology.The vision chips based on the architectures could reduce unnecessary data transfer and realize fast and energy-efficient visual cognitive processing.This paper reviews firstly the architectures and algorithms of SNN,and artificial neuron devices supporting neuromorphic computing,then the recent progress of in-sensor computing vision chips,which all will promote the development of AI.
作者
杨玉波
赵吉哲
刘胤洁
华夏扬
王天睿
郑纪元
郝智彪
熊兵
孙长征
韩彦军
王健
李洪涛
汪莱
罗毅
Yubo Yang;Jizhe Zhao;Yinjie Liu;Xiayang Hua;Tianrui Wang;Jiyuan Zheng;Zhibiao Hao;Bing Xiong;Changzheng Sun;Yanjun Han;Jian Wang;Hongtao Li;Lai Wang;Yi Luo(Department of Electronic Engineering,Tsinghua University,Beijing 100084,China;Beijing National Research Center for Information Science and Technology,Tsinghua University,Beijing 100084,China)
基金
Project supported in part by the National Key Research and Development Program of China(Grant No.2021YFA0716400)
the National Natural Science Foundation of China(Grant Nos.62225405,62150027,61974080,61991443,61975093,61927811,61875104,62175126,and 62235011)
the Ministry of Science and Technology of China(Grant Nos.2021ZD0109900 and 2021ZD0109903)
the Collaborative Innovation Center of Solid-State Lighting and Energy-Saving Electronics
Tsinghua University Initiative Scientific Research Program.
作者简介
Yubo Yang,contributed equally;Jizhe Zhao,contributed equally;Yinjie Liu,contributed equally;Corresponding Author:Lai Wang,E-mail:wanglai@mail.tsinghua.edu.cn;Corresponding Author:Yi Luo,E-mail:luoy@tsinghua.edu.cn。
