Experimental Verification of Uncoupled Memristive Cellular Nonlinear Network by Processing the EDGE Detection Task
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
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
Original language | English |
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Title of host publication | Proceedings of the 18th ACM International Symposium on Nanoscale Architectures, NANOARCH 2023 |
Publisher | Association for Computing Machinery |
ISBN (electronic) | 9798400703256 |
Publication status | Published - 18 Dec 2023 |
Peer-reviewed | Yes |
Publication series
Series | ACM International Conference Proceeding Series |
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Conference
Title | 18th ACM International Symposium on Nanoscale Architectures |
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Abbreviated title | NANOARCH 2023 |
Conference number | 18 |
Duration | 18 - 20 December 2023 |
Website | |
Location | Technische Universität Dresden |
City | Dresden |
Country | Germany |
External IDs
ORCID | /0000-0001-7436-0103/work/154191788 |
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ORCID | /0000-0002-2367-5567/work/168720267 |