Non-Volatile In-Memory Computing by Spintronics / by Hao Yu, Leibin Ni, Yuhao Wang.

Format:

Book

Author/Creator:

Yu, Hao., Author.

Ni, Leibin., Author.

Wang, Yuhao., Author.

Series:

Synthesis Lectures on Emerging Engineering Technologies, 2381-1439

Language:

English

Subjects (All):

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.

Local Subjects:

Technology and Engineering.

Electrical and Electronic Engineering.

Electronic Circuits and Systems.

Computer Hardware.

Materials Science.

Surfaces, Interfaces and Thin Film.

Physical Description:

1 online resource (XIII, 147 p.)

Edition:

1st ed. 2017.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2017.

Summary:

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.

Contents:

Preface

Acknowledgments

Introduction

Non-volatile Spintronic Device and Circuit

In-memory Data Encryption

In-memory Data Analytics

Authors' Biographies .

ISBN:

9783031020322

3031020324