VEDLIoT: Very Efficient Deep Learning in IoT
| Autor(en): | Kaiser, M. Griessl, R. Kucza, N. Haumann, C. Tigges, L. Mika, K. Hagemeyer, J. Porrmann, F. Ruckert, U. Vor Dem Berge, M. Krupop, S. Porrmann, M. Tassemeier, M. Trancoso, P. Qararyah, F. Zouzoula, S. Casimiro, A. Bessani, A. Cecilio, J. Andersson, S. Brunnegard, O. Eriksson, O. Weiss, R. McIerhofer, F. Salomonsson, H. Malekzadeh, E. Odman, D. Khurshid, A. Felber, P. Pasin, M. Schiavoni, V. Menetrey, J. Gugala, K. Zierhoffer, P. Knauss, E. Heyn, H. |
Herausgeber: | Bolchini, C. Verbauwhede, I. Vatajelu, I. |
Stichwörter: | Automation; Deep learning; Energy efficiency, Automotives; Design flows; Energy efficient; Hardware platform; Holistic approach; Micro-servers; Modulars; Safety and securities; Security challenges; Smart homes, Internet of things | Erscheinungsdatum: | 2022 | Herausgeber: | Institute of Electrical and Electronics Engineers Inc. | Journal: | Proceedings of the 2022 Design, Automation and Test in Europe Conference and Exhibition, DATE 2022 | Startseite: | 963 | Seitenende: | 968 | Zusammenfassung: | The VEDLIoT project targets the development of energy-efficient Deep Learning for distributed AIoT applications. A holistic approach is used to optimize algorithms while also dealing with safety and security challenges. The approach is based on a modular and scalable cognitive IoT hardware platform. Using modular microserver technology enables the user to configure the hardware to satisfy a wide range of applications. VEDLIoT offers a complete design flow for Next-Generation IoT devices required for collaboratively solving complex Deep Learning applications across distributed systems. The methods are tested on various use-cases ranging from Smart Home to Automotive and Industrial IoT appliances. VEDLIoT is an H2020 EU project which started in November 2020. It is currently in an intermediate stage with the first results available. © 2022 EDAA. |
Beschreibung: | Conference of 2022 Design, Automation and Test in Europe Conference and Exhibition, DATE 2022 ; Conference Date: 14 March 2022 Through 23 March 2022; Conference Code:179397 |
ISBN: | 9783981926361 | DOI: | 10.23919/DATE54114.2022.9774653 | Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130802370&doi=10.23919%2fDATE54114.2022.9774653&partnerID=40&md5=c8e222c059ea5f49deaa78c5cfb271c6 |
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