VEDLIOT: 在IOT中非常高效的深层学习 (VEDLIoT: Very Efficient Deep Learning in IoT)

Martin Kaiser,Rene Griessl,Nils Kucza,Carola Haumann,Lennart Tigges,Kevin Mika,Jens Hagemeyer,Florian Porrmann,Ulrich Rückert,Micha vor dem Berge,Stefan. Krupop,Mario Porrmann,Marco Tassemeier,Pedro Trancoso,Fareed Quararyah,Stavroula Zouzoula,Antonio Casimiro,Alysson Bessani,Jose Cecilio,Stefan Andersson,Oliver Brunnegard,Olof Eriksson,Roland Weiss,Franz Meierhöfer,Hans Salomonsson,Elaheh Malekzadeh,Daniel Ödman,Anum Khurshid,Pascal Felber,Marcelo Pasin,Valerio Schiavoni,Jämes Ménétrey,Karol Gugula,Piotr Zierhoffer,Eric Knauss,Hans-Martin Heyn

from arxiv, 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

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.

翻译：VEDLIOT项目的目标是为分布式AIOT应用开发节能深度学习,采用整体方法优化算法,同时应对安全和安保挑战,该方法基于模块和可扩展的认知IOT硬件平台,使用模块式微服务器技术使用户能够配置硬件以满足范围广泛的各种应用。VEDLIOT为在分布式系统中协作解决复杂的深层学习应用所需的下一代光学IOT设备提供了完整的设计流程。这些方法在从智能住宅到汽车和工业IOT电器的各种使用情况中进行测试。VEDLIOT是2020年11月开始的欧盟H20项目,目前处于中间阶段,有初步成果。