Yu, Hao.
Non-Volatile In-Memory Computing by Spintronics [electronic resource] / by Hao Yu, Leibin Ni, Yuhao Wang. - 1st ed. 2017. - XIII, 147 p. online resource. - Synthesis Lectures on Emerging Engineering Technologies, 2381-1439 . - Synthesis Lectures on Emerging Engineering Technologies, .
Preface -- Acknowledgments -- Introduction -- Non-volatile Spintronic Device and Circuit -- In-memory Data Encryption -- In-memory Data Analytics -- Authors' Biographies .
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.
9783031020322
10.1007/978-3-031-02032-2 doi
Engineering.
Electrical engineering.
Electronic circuits.
Computers.
Materials science.
Surfaces (Technology).
Thin films.
Technology and Engineering.
Electrical and Electronic Engineering.
Electronic Circuits and Systems.
Computer Hardware.
Materials Science.
Surfaces, Interfaces and Thin Film.
T1-995
620
Non-Volatile In-Memory Computing by Spintronics [electronic resource] / by Hao Yu, Leibin Ni, Yuhao Wang. - 1st ed. 2017. - XIII, 147 p. online resource. - Synthesis Lectures on Emerging Engineering Technologies, 2381-1439 . - Synthesis Lectures on Emerging Engineering Technologies, .
Preface -- Acknowledgments -- Introduction -- Non-volatile Spintronic Device and Circuit -- In-memory Data Encryption -- In-memory Data Analytics -- Authors' Biographies .
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.
9783031020322
10.1007/978-3-031-02032-2 doi
Engineering.
Electrical engineering.
Electronic circuits.
Computers.
Materials science.
Surfaces (Technology).
Thin films.
Technology and Engineering.
Electrical and Electronic Engineering.
Electronic Circuits and Systems.
Computer Hardware.
Materials Science.
Surfaces, Interfaces and Thin Film.
T1-995
620