VEDLIoT -- Next generation accelerated AIoT systems and applications
Abstract
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.
Cite
@article{arxiv.2305.05388,
title = {VEDLIoT -- Next generation accelerated AIoT systems and applications},
author = {Kevin Mika and René Griessl and Nils Kucza and Florian Porrmann and Martin Kaiser and Lennart Tigges and Jens Hagemeyer and Pedro Trancoso and Muhammad Waqar Azhar and Fareed Qararyah and Stavroula Zouzoula and Jämes Ménétrey and Marcelo Pasin and Pascal Felber and Carina Marcus and Oliver Brunnegard and Olof Eriksson and Hans Salomonsson and Daniel Ödman and Andreas Ask and Antonio Casimiro and Alysson Bessani and Tiago Carvalho and Karol Gugala and Piotr Zierhoffer and Grzegorz Latosinski and Marco Tassemeier and Mario Porrmann and Hans-Martin Heyn and Eric Knauss and Yufei Mao and Franz Meierhöfer},
journal= {arXiv preprint arXiv:2305.05388},
year = {2023}
}
Comments
This publication incorporates results from the VEDLIoT project, which received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 957197. CF'23: 20th ACM International Conference on Computing Frontiers, May 2023, Bologna, Italy