Compact and Fast Machine Learning Accelerator for IoT Devices

This book presents the latest techniques for machine learning based data analytics on IoT edge devices. A comprehensive literature review on neural network compression and machine learning accelerator is presented from both algorithm level optimization and hardware architecture optimization. Coverag...

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Bibliographic Details
Main Authors: Huang, Hantao (Author), Yu, Hao (Author)
Corporate Author: SpringerLink (Online service)
Format: e-Book
Language:English
Published: Singapore : Springer Nature Singapore : 2019.
Imprint: Springer,
Edition:1st ed. 2019.
Series:Computer Architecture and Design Methodologies,
Subjects:
Computational intelligence.
Microprocessors.
Computer architecture.
Mathematical optimization.
Computational Intelligence.
Processor Architectures.
Optimization.
Online Access:Full-text access
Description
Summary:This book presents the latest techniques for machine learning based data analytics on IoT edge devices. A comprehensive literature review on neural network compression and machine learning accelerator is presented from both algorithm level optimization and hardware architecture optimization. Coverage focuses on shallow and deep neural network with real applications on smart buildings. The authors also discuss hardware architecture design with coverage focusing on both CMOS based computing systems and the new emerging Resistive Random-Access Memory (RRAM) based systems. Detailed case studies such as indoor positioning, energy management and intrusion detection are also presented for smart buildings.
Physical Description:IX, 149 p. 76 illus., 61 illus. in color. online resource.
ISBN:9789811333231
ISSN:2367-3486
DOI:10.1007/978-981-13-3323-1

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