Browsing by Author "Wu, Ming -Hung"

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Sub-nA Low-Current HZO Ferroelectric Tunnel Junction for High-Performance and Accurate Deep Learning Acceleration
(2019-01-01)
Wu, Tzu-Yun
;
Huang, Hsin-Hui
;
Chu, Yueh-Hua
;
Chang, Chih-Cheng
;
Wu, Ming -Hung
This paper presents a unique opportunity of HZO ferroelectric tunnel junction (FTJ) for in-memory computing. The device operates at an extremely low sub-nA current while simultaneously achieving 50-ns fast switching, > 10(7) cycling endurance, > 10-yr retention, minimal variability, and analog state modulation. We analyze an FTJ-based deep binary neural network. It achieves better accuracy and remarkable 702, 101, and 7 x 10(4) times improvements in power, area, and energy area product efficiency compared with those using NVMs with a typical mu A cell current designed for fast memory access.