Non-Volatile In-Memory Computing by Spintronics
Overview
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.
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Details
- ISBN-13: 9783031009044
- ISBN-10: 3031009045
- Publisher: Springer
- Publish Date: December 2016
- Dimensions: 9.25 x 7.5 x 0.35 inches
- Shipping Weight: 0.65 pounds
- Page Count: 147
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