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High On/Off Ratio Spintronic Multi‐Level Memory Unit for Deep Neural Network.

Authors :
Zhang, Kun
Jia, Xiaotao
Cao, Kaihua
Wang, Jinkai
Zhang, Yue
Lin, Kelian
Chen, Lei
Feng, Xueqiang
Zheng, Zhenyi
Zhang, Zhizhong
Zhang, Youguang
Zhao, Weisheng
Source :
Advanced Science. May2022, Vol. 9 Issue 13, p1-8. 8p.
Publication Year :
2022

Abstract

Spintronic devices are considered as one of the most promising technologies for non‐volatile memory and computing. However, two crucial drawbacks, that is, lack of intrinsic multi‐level operation and low on/off ratio, greatly hinder their further application for advanced computing concepts, such as deep neural network (DNN) accelerator. In this paper, a spintronic multi‐level memory unit with high on/off ratio is proposed by integrating several series‐connected magnetic tunnel junctions (MTJs) with perpendicular magnetic anisotropy (PMA) and a Schottky diode in parallel. Due to the rectification effect on the PMA MTJ, an on/off ratio over 100, two orders of magnitude higher than intrinsic values, is obtained under proper proportion of alternating current and direct current. Multiple resistance states are stably achieved and can be reconfigured by spin transfer torque effect. A computing‐in‐memory architecture based DNN accelerator for image classification with the experimental parameters of this proposal to evidence its application potential is also evaluated. This work can satisfy the rigorous requirements of DNN for memory unit and promote the development of high‐accuracy and robust artificial intelligence applications. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21983844
Volume :
9
Issue :
13
Database :
Academic Search Index
Journal :
Advanced Science
Publication Type :
Academic Journal
Accession number :
156712916
Full Text :
https://doi.org/10.1002/advs.202103357