VEDLIoT: Next generation accelerated AIoT systems and applications
Autor(en): | Mika, Kevin Griessl, René Kucza, Nils Porrmann, Florian Kaiser, Martin Tigges, Lennart Hagemeyer, Jens Trancoso, Pedro Azhar, Muhammad Waqar Qararyah, Fareed Zouzoula, Stavroula Ménétrey, Jämes Pasin, Marcelo Felber, Pascal Marcus, Carina Brunnegard, Oliver Eriksson, Olof Salomonsson, Hans Ödman, Daniel Ask, Andreas Casimiro, Antonio Bessani, Alysson Carvalho, Tiago Gugala, Karol Zierhoffer, Piotr Latosinski, Grzegorz Tassemeier, Marco Porrmann, Mario Heyn, Hans-Martin Knauss, Eric Mao, Yufei Meierhöfer, Franz |
Stichwörter: | Acceleration; Artificial intelligence of thing; Artificial Intelligence of Things (AIoT); Automation; Deep learning; Distributed Artificial Intelligence; Distributed Attestation and Security; Energy efficiency; Energy efficient; Heterogeneous computing; Holistic approach; Internet of things; Learning systems; Machine learning; Machine Learning (ML); Machine-learning; Reconfigurable and Heterogeneous Computing; Reconfigurable architectures; Reconfigurable computing; Reconfigurable hardware; Reconfigurable- computing | Erscheinungsdatum: | 2023 | Herausgeber: | Association for Computing Machinery, Inc | Journal: | Proceedings of the 20th ACM International Conference on Computing Frontiers 2023, CF 2023 | Startseite: | 291 – 296 | Zusammenfassung: | The VEDLIoT project aims to develop energy-efficient Deep Learning methodologies for distributed Artificial Intelligence of Things (AIoT) applications. During our project, we propose a holistic approach that focuses on optimizing algorithms while addressing safety and security challenges inherent to AIoT systems. The foundation of this approach lies in a modular and scalable cognitive IoT hardware platform, which leverages microserver technology to enable users to configure the hardware to meet the requirements of a diverse array of applications. Heterogeneous computing is used to boost performance and energy efficiency. In addition, the full spectrum of hardware accelerators is integrated, providing specialized ASICs as well as FPGAs for reconfigurable computing. The project's contributions span across trusted computing, remote attestation, and secure execution environments, with the ultimate goal of facilitating the design and deployment of robust and efficient AIoT systems. The overall architecture is validated on use-cases ranging from Smart Home to Automotive and Industrial IoT appliances. Ten additional use cases are integrated via an open call, broadening the range of application areas. © 2023 Owner/Author. |
Beschreibung: | Cited by: 0; Conference name: 20th ACM International Conference on Computing Frontiers, CF 2023; Conference date: 9 May 2023 through 11 May 2023; Conference code: 191520; All Open Access, Bronze Open Access, Green Open Access |
ISBN: | 9798400701405 | DOI: | 10.1145/3587135.3592175 | Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169596487&doi=10.1145%2f3587135.3592175&partnerID=40&md5=efd601f49e0cd4b2b2e236d3681f6990 |
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geprüft am 23.05.2024