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3D neural network by monolithic integration of rram array with IGZO FET

  • Masaharu Kobayashi
  • , Jixuan Wu
  • , Fei Mo
  • , Saraya Takuya
  • , Toshiro Hiramoto
  • The University of Tokyo

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

We have developed monolithic integration of RRAM array and oxide semiconductor channel access transistor in 3D stack, achieved uniform memory characteristics of 1T1R cells at each layer, and demonstrated basic functionality of XNOR operation as in-memory computing for binary neural network AI applications. The impact of RRAM bit error rate on neural network is also investigated. 3D neural network built by this architecture enables area-efficient, low-power and low-latency computing in machine learning accelerator.

源语言英语
主期刊名PRiME 2020
主期刊副标题Metal Organic Frameworks (MOFs), Covalent Organic Frameworks (COFs), and Porous Hybrid Materials: Characterization, Technology, Bio-Applications, and Emerging Devices 2 -and- Nonvolatile Memories and Artificial Neural Networks
编辑E. Redel, H. Baumgart, G. Wittstock, C. Woll, H. Kitagawa, M. D. Allendorf, P. Falcaro, S. Shingubara, S. S. Nonnenmann, J. Rupp, G. Adam, R. Dittmann, Y. Yang, B. Magyari-Kope, K. Kobayashi, H. Shima, Y. Saito, J. G. Park, G. Bersuker
出版商IOP Publishing Ltd.
57-61
页数5
版本8
ISBN(电子版)9781607689034
DOI
出版状态已出版 - 2020
已对外发布
活动Pacific Rim Meeting on Electrochemical and Solid State Science 2020, PRiME 200 - Honolulu, 美国
期限: 4 10月 20209 10月 2020

丛书

姓名ECS Transactions
编号8
98
ISSN(印刷版)1938-6737
ISSN(电子版)1938-5862

会议

会议Pacific Rim Meeting on Electrochemical and Solid State Science 2020, PRiME 200
国家/地区美国
Honolulu
时期4/10/209/10/20

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