Experimental Verification of Uncoupled Memristive Cellular Nonlinear Network by Processing the EDGE Detection Task
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen › Begutachtung
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
Originalsprache | Englisch |
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Titel | Proceedings of the 18th ACM International Symposium on Nanoscale Architectures, NANOARCH 2023 |
Herausgeber (Verlag) | Association for Computing Machinery |
ISBN (elektronisch) | 9798400703256 |
Publikationsstatus | Veröffentlicht - 18 Dez. 2023 |
Peer-Review-Status | Ja |
Publikationsreihe
Reihe | ACM International Conference Proceeding Series |
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Konferenz
Titel | 18th ACM International Symposium on Nanoscale Architectures |
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Kurztitel | NANOARCH 2023 |
Veranstaltungsnummer | 18 |
Dauer | 18 - 20 Dezember 2023 |
Webseite | |
Ort | Technische Universität Dresden |
Stadt | Dresden |
Land | Deutschland |
Externe IDs
ORCID | /0000-0001-7436-0103/work/154191788 |
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ORCID | /0000-0002-2367-5567/work/168720267 |