Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Ferro‐floating memory: Dual‐mode ferroelectric floating memory and its application to in‐memory computingopen access

Authors
Park, SangyongOh, SeyongLee, DongyoungPark, Jin-Hong
Issue Date
Sep-2022
Publisher
Wiley
Keywords
artificial synaptic device; dual-mode operation mechanism; ferroelectric floating memory; in-memory computing; multi-stages conductance; reconfigurable operation range
Citation
InfoMat, v.4, no.11, pp 1 - 13
Pages
13
Indexed
SCIE
SCOPUS
Journal Title
InfoMat
Volume
4
Number
11
Start Page
1
End Page
13
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/112917
DOI
10.1002/inf2.12367
ISSN
2567-3165
Abstract
Various core memory devices have been proposed for utilization in future in-memory computing technology featuring high energy efficiency. Flash memory is considered as a viable choice owing to its high integration density, stability, and reliability, which has been verified by commercialized products. However, its high operating voltage and slow operation speed issues caused by the tunneling mechanism make its adoption in in-memory computing applications difficult. In this paper, we introduce a dual-mode memory device named “ferro-floating memory”, fabricated using van der Waals (vdW) materials (h-BN, MoS2, and α-In2Se3). The vdW material, α-In2Se3, acts as a polarization control layer for the ferroelectric memory operation and charge storage layer for the conventional flash memory operation. Compared to the tunneling-based memory operation, the ferro-floating memory operates 1.9 and 3.3 times faster at 6.7 and 5.8 times lower operating voltages for programming and erasing operations, respectively. The dual-mode operation improves the linearity of conductance change by 5 times and the dynamic range by 48% through achieving conductance variation regions. Furthermore, we assess the effects of the variation in device operating voltage on neural networks and suggest a memory array operating scheme for maximizing the networks' performance through various training/inference simulations. (Figure presented.). © 2022 The Authors. InfoMat published by UESTC and John Wiley & Sons Australia, Ltd.
Files in This Item
Go to Link
Appears in
Collections
COLLEGE OF ENGINEERING SCIENCES > SCHOOL OF ELECTRICAL ENGINEERING > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher OH, SEYONG photo

OH, SEYONG
ERICA 공학대학 (SCHOOL OF ELECTRICAL ENGINEERING)
Read more

Altmetrics

Total Views & Downloads

BROWSE