Experimental Verification of Uncoupled Memristive Cellular Nonlinear Network by Processing the EDGE Detection Task

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

Abstract

The Cellular Nonlinear Network (CNN) is a powerful paradigm in analog computing. As pure-CMOS based CNN Universal Machine faces the von Neumann bottleneck, the integration of memristive devices with their non-volatile memory properties is of major interest. These networks are called Memristor-CNNs (M-CNNs). Moreover, the integration of memristors brings richer dynamics into the network, such that M-CNNs are highly suitable for neuromorphic computing tasks. This paper presents the experimental verification of a processing unit of an uncoupled M-CNN design with a valance change mechanism (VCM) based memristor. We outline a simple measurement strategy to study M-CNNs with real-world devices and provide compelling evidence that the results of the M-CNN processing element are stored in a non-volatile manner. This work further offers crucial insights into design considerations of M-CNN networks.

Details

OriginalspracheEnglisch
TitelProceedings of the 18th ACM International Symposium on Nanoscale Architectures, NANOARCH 2023
Herausgeber (Verlag)Association for Computing Machinery
ISBN (elektronisch)9798400703256
PublikationsstatusVeröffentlicht - 18 Dez. 2023
Peer-Review-StatusJa

Publikationsreihe

ReiheACM International Conference Proceeding Series

Konferenz

Titel18th ACM International Symposium on Nanoscale Architectures
KurztitelNANOARCH 2023
Veranstaltungsnummer18
Dauer18 - 20 Dezember 2023
Webseite
OrtTechnische Universität Dresden
StadtDresden
LandDeutschland

Externe IDs

ORCID /0000-0001-7436-0103/work/154191788