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.