VEDLIoT is a project that aims to develop a framework for the next generation internet of things (IoT) based on IoT devices that collaboratively solve complex deep learning applications across distributed systems. The project will improve the performance and cost ratio of AI processing by distributing hardware across the entire chain from embedded devices to the cloud. It will also increase the safety, health and well-being of users through accelerating AI methods for user-home interaction. The project will develop a cognitive IoT platform, deep learning toolchain, and DL accelerators to enable this vision over its three year timeline starting in November 2020.

1. Pedro Trancoso and Jens Hagemeyer
Chalmers University of Technology & Bielefeld University
VEDLIoT
Very Efficient Deep Learning in IoT
18 January 2021
Project Overview

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FUTURE…
▪ Deep Learning: Solve more challenging & complex
problems
▪ Everywhere: transportation & industry & home
▪ Systems: Performance + security & privacy & robustness
Motivation
VEDLIoT offers a framework for the next generation internet
based on IoT devices that collaboratively solve complex DL
applications across a distributed system

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VEDLIoT Overview
Start date: November 2020
Project coordinator

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▪ Improve performance/cost ratio – AI processing hardware distributed over the entire chain
Use case: Automotive

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▪ Edge devices to be used in distributed systems – DL for high-level understanding from sensor
Use case: Industrial IoT

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▪ Increase safety, health and well being of residents – acceleration of AI methods for demand-
oriented user-home interaction
Use case: Smart Home / Assisted Living

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▪ Enabling the rapid convergence of the fast pace innovation on the hardware and software
Deep Learning Toolchain

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▪ End of Moore’s law & dark silicon – Domain Specific Architectures (DSA)
▪ Efficient, flexible, scalable accelerators for the compute continuum
▪ Algotecture – DL algorithm + computer architecture co-design
DL Accelerators

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Cognitive IoT Platform
• Heterogeneous, modular, scalable microserver system
• Different technology concepts for improving: computing power density, cost-effectiveness,
maintainability, and reliability for the full spectrum of IoT, from embedded devices over the edge
towards the cloud
x86
GPU
ML-ASIC
ARM v8
GPU SoC
FPGA
SoC
RISC-V
FPGA
VEDLIOT Cognitive IoT
Platform

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Simulation platform for IoT
• Open source framework for software/hardware co-development with CI-driven testing capabilities, as
well as metrics for measuring efficiency of ML workloads
• Enables development and continuous testing of VEDLIoT’s security features and its robustness
• Renode is available to all project members and future users of VEDLIoT and will include a simulated
model of the RISC-V-based FPGA SoC platform developed as part of the VEDLIoT project

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Expected Impacts
• Scientific progress enabling novel, future semi-autonomous IoT applications
• Long-term evolution of next-generation IoT infrastructures and service platforms technologies –
hardware, platforms, tools, applications
• Human-centred IoT evolution (improving usability and user acceptance), through strengthened security
and user control
• Maintain an active ecosystem of all relevant IoT stakeholders
• Emerging or future standards and pre-normative activities
• Propose and mobilise key IoT players in security and privacy

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The fun has just started!
▪ Follow our work!
 https://twitter.com/VEDLIoT
 https://www.linkedin.com/company/vedliot/
 https://vedliot.eu
▪ Be part of it
 Open call at project mid-term
 Allow early use and evaluation of VEDLIoT
technology