Non-Volatile In-Memory Computing by Spintronics (Synthesis Lectures on Emerging Engineering Technologies)

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.

Prof. Hao Yu received Ph.D. degree from the Electrical Engineering Department, University of California, Los Angeles (UCLA) in 2007. He was a Senior Research Staff at Berkeley Design Automation (BDA). Since October 2009, he has been an assistant professor at the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. His primary research interest is CMOS emerging technologies at nano-tera scale for energy-efficient data analytics and data links with more than 10M-USD research grant. He has written 200 top-tier peer-reviewed publications, 5 books, and 6 book chapters. Dr. Yu received the Best Paper Award from the ACM Transactions on Design Automation of Electronic Systems (TODAES) in 2010, and Inventor Award from Semiconductor Research Cooperation (SRC) in 2009. He is an associate editor and technical program committee member of many journals and conferences.