Compact and Fast Machine Learning Accelerator for IoT Devices
Seiten
2018
|
1st ed. 2019
Springer Verlag, Singapore
978-981-13-3322-4 (ISBN)
Springer Verlag, Singapore
978-981-13-3322-4 (ISBN)
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.
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 |
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