Device‐Algorithm Co‐Optimization for an On‐Chip Trainable Capacitor‐Based Synaptic Device with IGZO TFT and Retention‐Centric Tiki‐Taka Algorithm

Device‐Algorithm Co‐Optimization for an On‐Chip Trainable Capacitor‐Based Synaptic Device with IGZO TFT and Retention‐Centric Tiki‐Taka Algorithm

Abstract Analog in‐memory computing synaptic devices are widely studied for efficient implementation of deep learning. However, synaptic devices based on resistive memory have difficulties implementing on‐chip training due to the lack of means to control the amount of resistance change and large dev...

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Bibliographic Details
Main Authors: Jongun Won, Jaehyeon Kang, Sangjun Hong, Narae Han, Minseung Kang, Yeaji Park, Youngchae Roh, Hyeong Jun Seo, Changhoon Joe, Ung Cho, Minil Kang, Minseong Um, Kwang‐Hee Lee, Jee‐Eun Yang, Moonil Jung, Hyung‐Min Lee, Saeroonter Oh, Sangwook Kim, Sangbum Kim
Format: Article
Language:English
Published: Wiley 2023-10-01
Series:Advanced Science
Subjects:
device‐algorithm co‐optimization
indium gallium zinc oxide thin film transistor (IGZO TFT)
in‐memory computing
neuromorphic
tiki‐taka algorithm
Online Access:https://doi.org/10.1002/advs.202303018

Internet

https://doi.org/10.1002/advs.202303018

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