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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

Authors :
Kouhei Toyotaka
Yuto Yakubo
Kazuma Furutani
Haruki Katagiri
Masashi Fujita
Yoshinori Ando
Toru Nakura
Shunpei Yamazaki
Source :
IEEE Journal of the Electron Devices Society, Vol 12, Pp 486-494 (2024)
Publication Year :
2024
Publisher :
IEEE, 2024.

Abstract

Using a 3-D monolithic stacking memory technology of crystalline oxide semiconductor (OS) transistors, we fabricated a test chip having AI accelerator (ACC) memory for weight data of a neural network (NN), backup memory of flip-flops (FF), and CPU memory storing instructions and data. These memories are composed of two-layer OS transistors on Si CMOS, where memories in each layer correspond to a bank. In this structure, bank switching of the ACC memory and the FF backup memory work together, and thus inference of different NNs is switched with low latency and low power so that the power gating standby time can be extended. Consequently, a 92% reduction in power consumption is achieved in inference at a frame rate of 60 fps as compared with a chip using static random access memory (SRAM) as the ACC memory.

Details

Language :
English
ISSN :
21686734
Volume :
12
Database :
Directory of Open Access Journals
Journal :
IEEE Journal of the Electron Devices Society
Publication Type :
Academic Journal
Accession number :
edsdoj.4442c6379e414681ae1cfd2d32125415
Document Type :
article
Full Text :
https://doi.org/10.1109/JEDS.2024.3418036