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A 1.8mW Perception Chip with Near-Sensor Processing Scheme for Low-Power AIoT Applications

  • Zheyu Liu
  • , Erxiang Ren
  • , Li Luo
  • , Qi Wei
  • , Xing Wu
  • , Xueqing Li
  • , Fei Qiao*
  • , Xin Jun Liu
  • , Huazhong Yang
  • *此作品的通讯作者
  • Tsinghua University
  • Beijing Jiaotong University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

In the past few years, the demand for intelligence of IoT front-end devices has dramatically increased. However, such devices face challenges of limited on-chip resources and strict power or energy constraints. Recent progress in binarized neural networks has provided promising solutions for front-end processing system to conduct simple detection and classification tasks by making trade-offs between the processing quality and the computation complexity. In this paper, we propose a mixed-signal perception chip, in which an ADC-free 32x32 image sensor and a BNN processing array are directly integrated with a 180nm standard CMOS process. Taking advantage of the ADC-free processing architecture, the whole processing system only consumes 1.8mW power, while providing up to 545.4 GOPS/W energy efficiency. The implementation performance and energy efficiency are comparable with the state-of-the-art designs in much more advanced CMOS technologies. This work provides a promising alternative for low-power IoT intelligent applications.

源语言英语
主期刊名Proceedings - 2019 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2019
出版商IEEE Computer Society
447-452
页数6
ISBN(电子版)9781538670996
DOI
出版状态已出版 - 7月 2019
活动18th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2019 - Miami, 美国
期限: 15 7月 201917 7月 2019

出版系列

姓名Proceedings of IEEE Computer Society Annual Symposium on VLSI, ISVLSI
2019-July
ISSN(印刷版)2159-3469
ISSN(电子版)2159-3477

会议

会议18th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2019
国家/地区美国
Miami
时期15/07/1917/07/19

联合国可持续发展目标

此成果有助于实现下列可持续发展目标:

  1. 可持续发展目标 7 - 经济适用的清洁能源
    可持续发展目标 7 经济适用的清洁能源

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