Compact and fast machine learning accelerator for IoT devices / Hantao Huang and Hao Yu
نوع المادة : نصاللغة: الإنجليزية السلاسل:Computer architecture and design methodologiesالناشر:Singapore : Springer, 2019وصف:ix, 149 pages : illustrations ; 24 cmنوع المحتوى:- text
- unmediated
- volume
- 9789811333224
- Q325.5 .H836 2019
نوع المادة | المكتبة الحالية | رقم الطلب | رقم النسخة | حالة | تاريخ الإستحقاق | الباركود | |
---|---|---|---|---|---|---|---|
كتاب | UAE Federation Library | مكتبة اتحاد الإمارات General Collection | المجموعات العامة | Q325.5 .H836 2019 (إستعراض الرف(يفتح أدناه)) | C.1 | Library Use Only | داخل المكتبة فقط | 30030000003754 | ||
كتاب | UAE Federation Library | مكتبة اتحاد الإمارات General Collection | المجموعات العامة | Q325.5 .H836 2019 (إستعراض الرف(يفتح أدناه)) | C.2 | المتاح | 30030000003753 |
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
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