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System-on-Chip Architectures for Data Analytics

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Handbook of Signal Processing Systems

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Abstract

Artificial Intelligence (AI) in Industry 4.0, intelligent transportation system, intelligent biomedical systems and healthcare, etc., plays an important role requiring complex algorithms. Deep learning in machine learning, for example, is a popular AI algorithm with high computational demands on EDGE platforms in Internet-of-Things applications. This chapter introduces the Algorithm/Architecture Co-Design system design methodology for concurrent design of an algorithm with highly efficient, flexible and low power architecture in constituting the Smart System-on-Chip design.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, National Cheng Kung University, Tainan City, Taiwan

    Gwo Giun (Chris) Lee & Chun-Fu Chen

  2. IBM T.J. Watson Research Center, Yorktown Heights, NY, USA

    Tai-Ping Wang

Authors
  1. Gwo Giun (Chris) Lee
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  2. Chun-Fu Chen
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  3. Tai-Ping Wang
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Corresponding author

Correspondence to Gwo Giun (Chris) Lee .

Editor information

Editors and Affiliations

  1. Department of ECE and UMIACS, University of Maryland, College Park, MD, USA

    Shuvra S. Bhattacharyya

  2. Leiden Embedded Research Center, Leiden University Leiden Institute Advanced Computer Science, Leiden, The Netherlands

    Ed F. Deprettere

  3. RWTH Aachen University Software for Systems on Silicon, Aachen, Germany

    Rainer Leupers

  4. Department of Pervasive Computing, Tampere University of Technology, Tampere, Finland

    Jarmo Takala

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Lee, G.G.(., Chen, CF., Wang, TP. (2019). System-on-Chip Architectures for Data Analytics. In: Bhattacharyya, S., Deprettere, E., Leupers, R., Takala, J. (eds) Handbook of Signal Processing Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-91734-4_15

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  • DOI: https://doi.org/10.1007/978-3-319-91734-4_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91733-7

  • Online ISBN: 978-3-319-91734-4

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