首页|An isolated symmetrical 2T2R cell enabling high precision and high density for RRAM-based in-memory computing

An isolated symmetrical 2T2R cell enabling high precision and high density for RRAM-based in-memory computing

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In-memory computing(IMC),leveraging emerging memories,holds significant promise in over-coming 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 map-ping 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 signifi-cant.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.

RRAM2T2Rmulti-level storageweight asymmetryin-memory computing

Yaotian LING、Zongwei WANG、Yuhang YANG、Lin BAO、Shengyu BAO、Qishen WANG、Yimao CAI、Ru HUANG

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School of Integrated Circuits,Beijing Advanced Innovation Center for Integrated Circuits,Peking University,Beijing 100871,China

State Key Laboratory of Information Photonics and Optical Communications,Beijing University of Posts and Telecommunications,Beijing 100876,China

National Key Research and Development Program of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaBeijing Natural Science FoundationBeijing Nova Program"111"Project

2019YFB2205401618340016202540161927901L22300420220484113B18001

2024

10.1007/s11432-023-3887-0

中国科学:信息科学(英文版)
中国科学院

中国科学:信息科学(英文版)

CSTPCDEI
影响因子：0.715
ISSN：1674-733X
年,卷(期)：2024.67(5)
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