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作 者:Yaotian LING Zongwei WANG Yuhang YANG Lin BAO Shengyu BAO Qishen WANG Yimao CAI Ru HUANG
机构地区:[1]School of Integrated Circuits,Beijing Advanced Innovation Center for Integrated Circuits,Peking University,Beijing 100871,China [2]State Key Laboratory of Information Photonics and Optical Communications,Beijing University of Posts and Telecommunications,Beijing 100876,China
出 处:《Science China(Information Sciences)》2024年第5期283-290,共8页中国科学(信息科学)(英文版)
基 金:supported by National Key Research and Development Program of China(Grant No.2019YFB2205401);National Natural Science Foundation of China(Grant Nos.61834001,62025401,61927901);Beijing Natural Science Foundation(Grant No.L223004);Beijing Nova Program(Grant No.20220484113);“111”Project(Grant No.B18001).
摘 要:In-memory computing(IMC),leveraging emerging memories,holds significant promise in overcoming memory limitations and improving energy efficiency.However,the prevailing IMC array structure based on serially connected transistors and memory cells(1T1R/2T2R),along with the signed weight mapping scheme,can lead to asymmetrical weight sensing issues(AWS)due to electrical asymmetry within the 1T1R/2T2R structure,particularly in highly scaled cells where the transistor’s resistance becomes significant.In this paper,we propose and fabricate an electrically symmetric memory cell based on a physically isolated 2T2R structure for IMC.This design aims to enhance the precision and density of RRAM-based IMC arrays.The 2T2R cells are manufactured using the back-end-of-line(BEOL)process of a commercial 40 nm technology platform.The feasibility of this design is verified through measured and simulated results,showcasing its capability to address the issue of AWS.Compared to conventional 2T2R cells,this design achieves a considerably smaller transistor footprint without compromising accuracy,while also improving integration density by 42.2%.These innovative memory cell advancements have the potential to further advance high-energy-efficient IMC technology.
关 键 词:RRAM 2T2R multi-level storage weight asymmetry in-memory computing
分 类 号:TP333[自动化与计算机技术—计算机系统结构]
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