Compact and Fast Machine Learning Accelerator for IoT Devices

Hantao Huang, Hao Yu (Autoren)

Buch | Hardcover

149 Seiten

2018 | 2019 ed.
Springer Verlag, Singapore
978-981-13-3322-4 (ISBN)

Artikel merken

This book presents the latest techniques for machine learning based data analytics on IoT edge devices. 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.

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.

Computing on Edge Devices in Internet-of-things (IoT).- The Rise of Machine Learning in IoT system.- Least-squares-solver for Shadow Neural Network.- Tensor-solver for Deep Neural Network.- Distributed-solver for Networked Neural Network.- Conclusion.

Erscheinungsdatum	28.12.2018
Reihe/Serie	Computer Architecture and Design Methodologies
Zusatzinfo	61 Illustrations, color; 15 Illustrations, black and white; IX, 149 p. 76 illus., 61 illus. in color.
Verlagsort	Singapore
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
	Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik
	Technik
ISBN-10	981-13-3322-X / 981133322X
ISBN-13	978-981-13-3322-4 / 9789811333224
Zustand	Neuware