摘要
近年来,物联网和人工智能等技术的发展对片上存储与智能计算的能效、密度以及性能提出了更高的要求。面对传统CMOS处理器的能效与密度瓶颈,以及传统冯·诺伊曼架构的“存储墙”瓶颈,以铁电晶体管(FeFET)为代表的新型非易失存储器(NVM)提供了新的机遇。FeFET具有非易失、高能效、高开关比等特点,非常适合低功耗、高密度场景下的存储与存算一体(CiM)应用,为数据密集型应用在边缘端的部署提供支持。该文回顾了FeFET的发展历程、结构、特性以及建模相关的工作,概述了FeFET存储器在电路结构和访存机制上的探索与优化。进一步地,该文还探讨了FeFET CiM在非易失计算、存内逻辑计算、矩阵向量乘法以及内容可寻址存储器上的应用。最后,该文从不同方面分析并展望了基于FeFET的存储与CiM电路的前景与挑战。
Recently,with the development of the Internet of Things and Artificial Intelligence,higher energy efficiency,density,and performance in on-chip memories and intelligent computing are required.Facing the energy efficiency and density bottleneck in conventional CMOS memories and the“memory wall”problem in the Von Neumann architecture,emerging Nonvolatile Memories(NVMs)such as Ferroelectric Field Effect Transistors(FeFETs)bring new opportunities to solve the challenges.FeFETs have the characteristics of non-volatility,ultra-low power,and high on-off ratio,which are very suitable for memories and Compute-in-Memory(CiM)in high-density,low-power scenarios and would support the implementation of data-intensive applications at the edge.This paper first reviews the development,structure,characteristics,and modeling of FeFETs.Then,the exploration and optimization of FeFET-based memories with different circuit structures and characteristics are discussed.Further,this paper summarizes the FeFET-based CiM circuits,including nonvolatile computing,logic-in-memory,matrix-vector multiplication,and content-addressable memories.Finally,the prospects and challenges of FeFET-based memory and CiM are analyzed.
作者
刘勇
李泰昕
祝希
杨华中
李学清
LIU Yong;LI Taixin;ZHU Xi;YANG Huazhong;LI Xueqing(Xinsheng Technology Co.,Ltd.,Beijing 100032,China;Department of Electronic Engineering,BNRist,Tsinghua University,Beijing 100084,China)
出处
《电子与信息学报》
EI
CSCD
北大核心
2023年第9期3083-3097,共15页
Journal of Electronics & Information Technology
基金
国家自然科学基金(U21B2030,92264204)。
关键词
铁电晶体管
铁电器件
存储器
存内计算
非易失存储器
Ferroelectric Field Effect Transistors(FeFETs)
Ferroelectric device
Memory
Compute-in-Memory(CiM)
Nonvolatile Memory(NVM)