A 3-D Bank Memory System for Low-Power Neural Network Processing Achieved by Instant Context Switching and Extended Power Gating Time-Reference-Cited by-同舟云学术

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A 3-D Bank Memory System for Low-Power Neural Network Processing Achieved by Instant Context Switching and Extended Power Gating Time

Published:2024 Issue: Volume:12 Page:486-494
ISSN:2168-6734
Container-title:IEEE Journal of the Electron Devices Society
language:
Short-container-title:IEEE J. Electron Devices Soc.

Author:

Toyotaka Kouhei¹^ORCID,Yakubo Yuto¹,Furutani Kazuma¹,Katagiri Haruki²,Fujita Masashi¹,Ando Yoshinori³,Nakura Toru⁴^ORCID,Yamazaki Shunpei⁵^ORCID

Affiliation:

1. CAD Division, Semiconductor Energy Laboratory Company Ltd., Atsugi, Japan

2. Equipment Division, Semiconductor Energy Laboratory Company Ltd., Atsugi, Japan

3. NOS Development Division, Semiconductor Energy Laboratory Company Ltd., Atsugi, Japan

4. Graduate School of Engineering, Fukuoka University, Fukuoka, Japan

5. Semiconductor Energy Laboratory Company Ltd., Atsugi, Japan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6245494/10416702/10568946.pdf?arnumber=10568946

Reference32 articles.

1. Edge Intelligence: The Confluence of Edge Computing and Artificial Intelligence

2. Towards Security and Privacy for Edge AI in IoT/IoE based Digital Marketing Environments

3. Edge Intelligence: Challenges and Opportunities

4. Exploiting Near-Memory Processing Architectures for Bayesian Neural Networks Acceleration

5. NEMO-CNN: An Efficient Near-Memory Accelerator for Convolutional Neural Networks

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