摘要
随着信息化时代的发展,大数据、物联网、云计算、5G通信、人工智能等技术的应用对计算速度和计算能效提出了更高的要求。传统的冯·诺依曼计算架构因存算分离引发“存储墙”和“功耗墙”问题而不再满足智能大数据应用场景快、准、智的响应需求。综述了人工神经形态器件与电路的国内外发展概况,主要包括两种技术路线,一种是基于传统成熟CMOS技术的SRAM或DRAM构建,其原型器件在信息存储方面属于易失型;另一种是基于非易失性Flash器件或新型存储器件、新材料构建。最后,对人工神经形态器件的未来发展进行了总结与展望。
With the development of information age,the applications of big data,internet of things,cloud computing,5G communication,artificial intelligence and other technologies,higher requirements for computing speed and computing energy efficiency are put forward.The traditional von Neumann computing architecture can no longer meet the requirements of fast,accurate and intelligent response of intelligent big data application scenarios because of the separation of storage and computing,which leads to the problem of"storage wall"and"power consumption wall".This paper summarizes the development of artificial neural morphology devices and circuits at home and abroad,including two technical routes.One is SRAM or DRAM based on traditional mature CMOS technology,and its prototype device belongs to volatile type in information storage;the other is based on nonvolatile flash devices or new memory devices or new materials.Finally,the future development of artificial neural morphological devices is summarized and prospected.
作者
张玲
刘国柱
于宗光
ZHANG Ling;LIU Guozhu;YU Zongguang(China Electronics Technology Group Corporation No.58 Research Institute,Wuxi 214035,China;School of Electronic Science and Engineering,Southeast University,Nanjing 210096,China)
出处
《电子与封装》
2021年第6期1-14,共14页
Electronics & Packaging
关键词
突触
神经元
神经形态
人工智能
synapses
neurons
neural morphology
artificial intelligence