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OverviewExa-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. Full Product DetailsAuthor: Hao Yu , Leibin Ni , Yuhao WangPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Weight: 0.322kg ISBN: 9783031009044ISBN 10: 3031009045 Pages: 147 Publication Date: 02 December 2016 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Language: English Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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