Spintronics-Based Neuromorphic Computing

2024
ISBN: 978-981-97-4444-2
Verlag: Springer Nature Singapore

Buch, Englisch, 126 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 415 g

Reihe: Springer Tracts in Electrical and Electronics Engineering

The book discusses almost all aspects of spintronics-based neuromorphic computing, starting from a very basic level, and will be of interest to both spintronics and neuromorphic computing communities. The chapters also cover most simulation and experimental studies reported recently by researchers worldwide on this topic. The book includes an introductory chapter on nanomagnetism and spin physics and another on neural network algorithms (covering both the machine-learning and neuroscience aspects of these algorithms). These introductory chapters will help the readers build their background and truly appreciate the recent research results on spintronics-based neuromorphic computing, presented in the later chapters of the book. Various numerical simulation exercises are also provided in the book.

Zielgruppe

Research

Autoren/Hrsg.

Bhowmik, Debanjan

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Regelungstechnik
• Naturwissenschaften Physik Thermodynamik Festkörperphysik, Kondensierte Materie
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Technische Mechanik | Werkstoffkunde
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle

Inhaltsverzeichnis

Why Spintronics-Based Neuromorphic Computing?.- Introduction to Nanomagnetism and Spintronics.- Introduction to Computing.- Introduction to Neural Networks.- Ferromagnetic Domain-Wall Devices as Synapses and Neurons.- Design of Non-Spiking Neural Networks with Domain-Wall Devices.- Design of Spiking Neural Networks with Domain-Wall Devices.- Spintronic Oscillators and Their Synchronization Properties.- Neuromorphic Computing using Spintronic Oscillators.- Neural Networks and Probabilistic Computing Through Stochastic Magnetic Switching.

Über Autor(innen)

Debanjan Bhowmik is an Associate Professor in the Department of Electrical Engineering at the Indian Institute of Technology Bombay. Earlier, he was an Assistant Professor in the Indian Institute of Technology Delhi from 2017 to 2021, and an Assistant Professor in the Indian Institute of Technology Bombay from 2022 to 2023. He completed his Ph.D. from the Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA, in 2015. He completed his B. Tech., Department of Electrical Engineering from the Indian Institute of Technology, Kharagpur, India, in 2010. His research areas are specialized energy-efficient hardware for artificial intelligence (neuromorphic computing), nanomagnetism and spintronics, computational neuroscience, and quantum computing for artificial intelligence/machine learning. He has published several research papers in international journals of repute in these areas.