دورية أكاديمية
Analog monolayer SWCNTs-based memristive 2D structure for energy-efficient deep learning in spiking neural networks
| العنوان: | Analog monolayer SWCNTs-based memristive 2D structure for energy-efficient deep learning in spiking neural networks |
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| المؤلفون: | Heba Abunahla, Yawar Abbas, Anteneh Gebregiorgis, Waqas Waheed, Baker Mohammad, Said Hamdioui, Anas Alazzam, Moh’d Rezeq |
| المصدر: | Scientific Reports, Vol 13, Iss 1, Pp 1-9 (2023) |
| بيانات النشر: | Nature Portfolio, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Medicine LCC:Science |
| مصطلحات موضوعية: | Medicine, Science |
| الوصف: | Abstract Advances in materials science and memory devices work in tandem for the evolution of Artificial Intelligence systems. Energy-efficient computation is the ultimate goal of emerging memristor technology, in which the storage and computation can be done in the same memory crossbar. In this work, an analog memristor device is fabricated utilizing the unique characteristics of single-wall carbon nanotubes (SWCNTs) to act as the switching medium of the device. Via the planar structure, the memristor device exhibits analog switching ability with high state stability. The device’s conductance and capacitance can be tuned simultaneously, increasing the device's potential and broadening its applications' horizons. The multi-state storage capability and long-term memory are the key factors that make the device a promising candidate for bio-inspired computing applications. As a demonstrator, the fabricated memristor is deployed in spiking neural networks (SNN) to exploit its analog switching feature for energy-efficient classification operation. Results reveal that the computation-in-memory implementation performs Vector Matrix Multiplication with 95% inference accuracy and few femtojoules per spike energy efficiency. The memristor device presented in this work opens new insights towards utilizing the outstanding features of SWCNTs for efficient analog computation in deep learning systems. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2045-2322 |
| Relation: | https://doaj.org/toc/2045-2322 |
| DOI: | 10.1038/s41598-023-48529-z |
| URL الوصول: | https://doaj.org/article/22b4332afa704cf1aeaa88a2113b6c76 |
| رقم الأكسشن: | edsdoj.22b4332afa704cf1aeaa88a2113b6c76 |
| قاعدة البيانات: | Directory of Open Access Journals |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 20452322 |
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| DOI: | 10.1038/s41598-023-48529-z |