Non-Volatile In-Memory Computing by Spintronics [[electronic resource] /] / by Hao Yu, Leibin Ni, Yuhao Wang

• Autore: Yu Hao
• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
• Edizione: 1st ed. 2017.
• Descrizione fisica: 1 online resource (XIII, 147 p.)
• Disciplina: 620
• Soggetto topico: 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
• Persona (resp. second.): NiLeibin; WangYuhao
• Nota di contenuto: Preface -- Acknowledgments -- Introduction -- Non-volatile Spintronic Device and Circuit -- In-memory Data Encryption -- In-memory Data Analytics -- Authors' Biographies .
• Sommario/riassunto: 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.
• Titolo autorizzato: Non-volatile in-memory computing by spintronics
• ISBN: 3-031-02032-4
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910808511703321
• Lo trovi qui: Univ. Federico II
• Serie: Synthesis Lectures on Emerging Engineering Technologies, . 2381-1439