Buch, Englisch, 147 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 320 g
Reihe: Synthesis Lectures on Emerging Engineering Technologies
Buch, Englisch, 147 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 320 g
Reihe: Synthesis Lectures on Emerging Engineering Technologies
ISBN: 978-3-031-00904-4
Verlag: Springer International Publishing
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.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Technik Allgemein Technik: Allgemeines
- Mathematik | Informatik EDV | Informatik Technische Informatik
- Technische Wissenschaften Maschinenbau | Werkstoffkunde Technische Mechanik | Werkstoffkunde
- Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Bauelemente, Schaltkreise
- Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
Weitere Infos & Material
Preface.- Acknowledgments.- Introduction.- Non-volatile Spintronic Device and Circuit.- In-memory Data Encryption.- In-memory Data Analytics.- Authors' Biographies.
