Neuromorphic Computing Principles and Organization - Tapa dura

Acerca del autor

Dr. Abderazek Ben Abdallah received his Ph.D. in computer engineering from The University of Electro-Communications in Tokyo in 2002. From April 2014to March 2022, he served as the Head of the Computer Engineering Division at the University of Aizu, Japan. Since April 2022, he has held the position of Dean at the School of Computer Science and Engineering at the University of Aizu. Currently, Dr. Ben Abdallah is a Full Professor at the University of Aizu. He is the author of four books and holds six registered and eight provisional Japanese patents. Additionally, he has published over 150 peer-reviewed journal articles and conference papers. His research interests span adaptive and self-organizing systems, neuromorphic computing, interconnection networks, and AI-powered cyber-physical systems. Dr. Ben Abdallah is a Senior Member of both the IEEE and ACM, reflecting his significant contributions to computer engineering.

Dr. Khanh N. Dang currently serves as an Associate Professor in the Department of Computer Science and Engineering at the University of Aizu. He earned his Ph.D. from the University of Aizu and his M.Sc. from the University of Paris XI. Dr. Dang has published numerous peer-reviewed journal articles and presented his work at various conferences. He is also the author of one book and holds several provisional patents in Japan. Dr. Dang’s research areas include Network-on-Chips (NoC), 3DIntegrated Circuits (3D-ICs), neuromorphic computing, and fault-tolerant systems. Within these fields, he focuses on developing efficient communication architectures and enhancing the reliability and performance of multi-core processors. In neuromorphic computing, he explores the implementation of brain-inspired algorithms to create more efficient and intelligent systems. He is a member of IEEE.

De la contraportada

The second edition of Neuromorphic Computing Principles and Organization delves deeply into neuromorphic computing, focusing on designing fault-tolerant, scalable hardware for spiking neural networks. Each chapter includes exercises to enhance understanding. All existing chapters have been meticulously revised, and a new chapter on advanced neuromorphic prosthesis design serves as a comprehensive case study.

The book starts with an overview of neuromorphic systems and fundamental artificial neural network concepts. It explores artificial neurons, neuron models, storage technologies, inter-neuron communication, learning mechanisms, and design approaches. Detailed discussions cover challenges in constructing spiking neural networks and emerging memory technologies. A dedicated chapter addresses circuits and architectures, including Network-on-Chip (NoC) fabric, Address Event Representation (AER), memory access methods, and photonic interconnects.

Reliability issues, recovery methods for multicore systems, and reconfigurable designs supporting multiple applications are examined. The book also describes the hardware-software design of a three-dimensional neuromorphic processor, focusing on high integration density, minimal spike delay, and scalable design. The book concludes with a comprehensive review of neuromorphic systems, providing a detailed analysis of the field and an overarching understanding of the key concepts discussed throughout the text.