Data centres for IoT applications: The M2DC approach (Invited paper)

Oleksiak A, Porrmann M, Hagemeyer J, et al. Data centres for IoT applications: The M2DC approach (Invited paper). In: 2016 International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS). IEEE; 2016: 293-299.The Modular Microserver DataCentre (M2DC) project investigates, develops and demonstrates a modular, highly-efficient, cost-optimized server architecture composed of heterogeneous micro server computing resources, being able to be tailored to meet requirements from various application domains, including the Internet of Things. M2DC is built on three main pillars: a flexible server architecture that can be easily customised, maintained and updated; advanced management strategies and system efficiency enhancements (SEE); well-defined interfaces to surrounding software data centre ecosystem

M2DC-A novel heterogeneous hyperscale microserver platform

The Modular Microserver Datacentre (M2DC) project targets the development of a new class of energy-efficient TCO-optimized appliances with built-in efficiency and dependability enhancements. The appliances will be easy to integrate with a broad ecosystem of management software and fully software defined to enable optimization for a variety of future demanding applications in a cost-effective way. The highly flexible M2DC server platform will enable customization and smooth adaptation to various types of applications, while advanced management strategies and system efficiency enhancements (SEE) will be used to improve energy efficiency, performance, security, and reliability. Data center capable abstraction of the underlying heterogeneity of the server is provided by an OpenStack-based middleware. In this chapter, we focus in particular on the architecture of the server platform including a dedicated high-speed, low latency communication infrastructure, give a short introduction into the software stack including thermal management strategies, and provide an overview of the targeted applications

VEDLIoT: Very Efficient Deep Learning in IoT

Kaiser M, Griessl R, Kucza N, et al. VEDLIoT: Very Efficient Deep Learning in IoT. In: Institut of Electrical and Electronics Engineers (IEEE), ed. DATE '22: Proceedings of the 2022 Conference & Exhibition on Design, Automation & Test in Europe. Leuven: European Design and Automation Association; 2022: 963-968

VEDLIoT: Very Efficient Deep Learning in IoT

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