Non-Volatile In-Memory Computing by Spintronics

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Details

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.

Inhalt
Preface.- Acknowledgments.- Introduction.- Non-volatile Spintronic Device and Circuit.- In-memory Data Encryption.- In-memory Data Analytics.- Authors' Biographies .

Weitere Informationen

  • Allgemeine Informationen
    • Sprache Englisch
    • Anzahl Seiten 164
    • Herausgeber Springer International Publishing
    • Gewicht 320g
    • Untertitel Synthesis Lectures on Emerging Engineering Technologies
    • Autor Hao Yu , Yuhao Wang , Leibin Ni
    • Titel Non-Volatile In-Memory Computing by Spintronics
    • Veröffentlichung 02.12.2016
    • ISBN 3031009045
    • Format Kartonierter Einband
    • EAN 9783031009044
    • Jahr 2016
    • Größe H235mm x B191mm x T10mm
    • Lesemotiv Verstehen
    • GTIN 09783031009044

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