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3-D Stacked Synapse Array Based on Charge-Trap Flash Memory for Implementation of Deep Neural Networks.

Authors :
Park, Yu Jeong
Kwon, Hui Tae
Kim, Boram
Lee, Won Joo
Wee, Dae Hoon
Choi, Hyun-Seok
Park, Byung-Gook
Lee, Jong-Ho
Kim, Yoon
Source :
IEEE Transactions on Electron Devices. Jan2019, Vol. 66 Issue 1, p420-427. 8p.
Publication Year :
2019

Abstract

This paper proposes a synaptic device based on charge-trap flash memory that has good CMOS compatibility and superior reliability characteristics compared with other synaptic devices. Using hot-electron injection and hot-hole injection, we designed operation methods to implement gradual conductance modulation and spike-timing-dependent plasticity. We demonstrate the feasibility of the device for neuromorphic applications through both a device-level technology computer-aided design simulation and a system-level MATLAB simulation. For the first time, we also propose a 3-D stacked synapse array and present the structure, operation, and process methods. The proposed array architecture features a small area and low process cost and could be a novel solution for neuromorphic systems for implementing deep neural networks. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00189383
Volume :
66
Issue :
1
Database :
Academic Search Index
Journal :
IEEE Transactions on Electron Devices
Publication Type :
Academic Journal
Accession number :
137215182
Full Text :
https://doi.org/10.1109/TED.2018.2881972