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

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...

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Autores principales: Zhang, Kun, Jia, Xiaotao, Cao, Kaihua, Wang, Jinkai, Zhang, Yue, Lin, Kelian, Chen, Lei, Feng, Xueqiang, Zheng, Zhenyi, Zhang, Zhizhong, Zhang, Youguang, Zhao, Weisheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9069383/
https://www.ncbi.nlm.nih.gov/pubmed/35229495
http://dx.doi.org/10.1002/advs.202103357
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author Zhang, Kun
Jia, Xiaotao
Cao, Kaihua
Wang, Jinkai
Zhang, Yue
Lin, Kelian
Chen, Lei
Feng, Xueqiang
Zheng, Zhenyi
Zhang, Zhizhong
Zhang, Youguang
Zhao, Weisheng
author_facet Zhang, Kun
Jia, Xiaotao
Cao, Kaihua
Wang, Jinkai
Zhang, Yue
Lin, Kelian
Chen, Lei
Feng, Xueqiang
Zheng, Zhenyi
Zhang, Zhizhong
Zhang, Youguang
Zhao, Weisheng
author_sort Zhang, Kun
collection PubMed
description 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.
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spelling pubmed-90693832022-05-09 High On/Off Ratio Spintronic Multi‐Level Memory Unit for Deep Neural Network Zhang, Kun Jia, Xiaotao Cao, Kaihua Wang, Jinkai Zhang, Yue Lin, Kelian Chen, Lei Feng, Xueqiang Zheng, Zhenyi Zhang, Zhizhong Zhang, Youguang Zhao, Weisheng Adv Sci (Weinh) Research Articles 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. John Wiley and Sons Inc. 2022-02-20 /pmc/articles/PMC9069383/ /pubmed/35229495 http://dx.doi.org/10.1002/advs.202103357 Text en © 2022 The Authors. Advanced Science published by Wiley‐VCH GmbH https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Zhang, Kun
Jia, Xiaotao
Cao, Kaihua
Wang, Jinkai
Zhang, Yue
Lin, Kelian
Chen, Lei
Feng, Xueqiang
Zheng, Zhenyi
Zhang, Zhizhong
Zhang, Youguang
Zhao, Weisheng
High On/Off Ratio Spintronic Multi‐Level Memory Unit for Deep Neural Network
title High On/Off Ratio Spintronic Multi‐Level Memory Unit for Deep Neural Network
title_full High On/Off Ratio Spintronic Multi‐Level Memory Unit for Deep Neural Network
title_fullStr High On/Off Ratio Spintronic Multi‐Level Memory Unit for Deep Neural Network
title_full_unstemmed High On/Off Ratio Spintronic Multi‐Level Memory Unit for Deep Neural Network
title_short High On/Off Ratio Spintronic Multi‐Level Memory Unit for Deep Neural Network
title_sort high on/off ratio spintronic multi‐level memory unit for deep neural network
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9069383/
https://www.ncbi.nlm.nih.gov/pubmed/35229495
http://dx.doi.org/10.1002/advs.202103357
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