An overview of next-generation architectures for machine learning: Roadmap, opportunities and challenges in the IoT era

Muhammad Shafique, Theocharis Theocharides, Christos Savvas Bouganis, Muhammad Abdullah Hanif, Faiq Khalid, Rehan Hafiz, Semeen Rehman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The number of connected Internet of Things (IoT) devices are expected to reach over 20 billion by 2020. These range from basic sensor nodes that log and report the data to the ones that are capable of processing the incoming information and taking an action accordingly. Machine learning, and in particular deep learning, is the de facto processing paradigm for intelligently processing these immense volumes of data. However, the resource inhibited environment of IoT devices, owing to their limited energy budget and low compute capabilities, render them a challenging platform for deployment of desired data analytics. This paper provides an overview of the current and emerging trends in designing highly efficient, reliable, secure and scalable machine learning architectures for such devices. The paper highlights the focal challenges and obstacles being faced by the community in achieving its desired goals. The paper further presents a roadmap that can help in addressing the highlighted challenges and thereby designing scalable, high-performance, and energy efficient architectures for performing machine learning on the edge.

Original languageEnglish (US)
Title of host publicationProceedings of the 2018 Design, Automation and Test in Europe Conference and Exhibition, DATE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages827-832
Number of pages6
ISBN (Electronic)9783981926316
DOIs
StatePublished - Apr 19 2018
Event2018 Design, Automation and Test in Europe Conference and Exhibition, DATE 2018 - Dresden, Germany
Duration: Mar 19 2018Mar 23 2018

Publication series

NameProceedings of the 2018 Design, Automation and Test in Europe Conference and Exhibition, DATE 2018
Volume2018-January

Other

Other2018 Design, Automation and Test in Europe Conference and Exhibition, DATE 2018
CountryGermany
CityDresden
Period3/19/183/23/18

Keywords

  • Convolutional Neural Networks
  • Deep Learning
  • IoT
  • Machine Learning

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Hardware and Architecture
  • Software
  • Information Systems and Management

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