Synthesis Lectures on Emerging Engineering Technologies

Yu, Hao; Ni, Leibin; Wang, Yuhao

Exa-scale computing needs to re-examine the existing hardware platform that can support intensive data-oriented computing. Since the main bottleneck is from memory, we aim to develop an energy-efficient in-memory computing platform in this book. First, the models of spin-transfer torque magnetic tunnel junction and racetrack memory are presented. Next, we show that the spintronics could be a candidate for future data-oriented computing for storage, logic, and interconnect. As a result, by utilizing spintronics, in-memory-based computing has been applied for data encryption and machine learning. The implementations of in-memory AES, Simon cipher, as well as interconnect are explained in details. In addition, in-memory-based machine learning and face recognition are also illustrated in this book.

Details

Published by: Springer

Publication Date: 2016-12-02

Format: Paperback

ISBN-13: 9783031009044

DOI: 10.1007/978-3-031-02032-2

Dimensions: 235cm x191cm

Pages: 147