Non-Volatile In-Memory Computing by Spintronics

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.

Professor 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. Leibin Ni received a B.S. degree in microelectronics from Shanghai Jiao Tong University, Shanghai, China in 2014. He is currently pursuing a Ph.D. degree from the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. His current research interests include emerging nonvolatile memory platform and big-data in-memory computing. Dr Yuhao Wang received a B.S. degree in microelectronics engineering from Xi'an Jiao Tong University, Xi'an, China in 2011, and a Ph.D. degree in 2015 from the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. He is currently a senior R&D engineer at Synopsys, Mountain View, CA, USA. His research interests include EDA topics related to emerging non-volatile memory design flow and hardware optimization with emphasis on energy efficiency.