Multifunctional computing-in-memory SRAM cells based on two-surface-channel MoS2 transistors

Fan Wang; Jiayi Li; Zhenhan Zhang; Yi Ding; Yan Xiong; Xiang Hou; Huawei Chen; Peng Zhou

doi:10.1016/j.isci.2021.103138

Multifunctional computing-in-memory SRAM cells based on two-surface-channel MoS₂ transistors

iScience. 2021 Sep 16;24(10):103138. doi: 10.1016/j.isci.2021.103138. eCollection 2021 Oct 22.

Authors

Fan Wang¹, Jiayi Li¹, Zhenhan Zhang¹, Yi Ding¹, Yan Xiong¹, Xiang Hou¹, Huawei Chen¹, Peng Zhou¹

Affiliation

¹ State Key Laboratory of ASIC and System, Fudan University, Shanghai, 200433, China.

Abstract

Driven by technologies such as machine learning, artificial intelligence, and internet of things, the energy efficiency and throughput limitations of the von Neumann architecture are becoming more and more serious. As a new type of computer architecture, computing-in-memory is an alternative approach to alleviate the von Neumann bottleneck. Here, we have demonstrated two kinds of computing-in-memory designs based on two-surface-channel MoS₂ transistors: symmetrical 4T2R Static Random-Access Memory (SRAM) cell and skewed 3T3R SRAM cell, where the symmetrical SRAM cell can realize in-memory XNOR/XOR computations and the skewed SRAM cell can achieve in-memory NAND/NOR computations. Furthermore, since both the memory and computing units are based on two-surface-channel transistors with high area efficiency, the two proposed computing-in-memory SRAM cells consume fewer transistors, suggesting a potential application in highly area-efficient and multifunctional computing chips.

Keywords: Devices; Engineering; Nanotechnology.