Hardware Architectures for Deep Learning (Materials, Circuits and Devices) - Tapa dura

 
9781785617683: Hardware Architectures for Deep Learning (Materials, Circuits and Devices)
Tapa dura
ISBN 10: 1785617680 ISBN 13: 9781785617683
Editorial: Institution of Engineering and Technology, 2020

Sinopsis

This book presents and discusses innovative ideas in the design, modelling, implementation, and optimization of hardware platforms for neural networks.

The rapid growth of server, desktop, and embedded applications based on deep learning has brought about a renaissance in interest in neural networks, with applications including image and speech processing, data analytics, robotics, healthcare monitoring, and IoT solutions. Efficient implementation of neural networks to support complex deep learning-based applications is a complex challenge for embedded and mobile computing platforms with limited computational/storage resources and a tight power budget. Even for cloud-scale systems it is critical to select the right hardware configuration based on the neural network complexity and system constraints in order to increase power- and performance-efficiency.

Hardware Architectures for Deep Learning provides an overview of this new field, from principles to applications, for researchers, postgraduate students and engineers who work on learning-based services and hardware platforms.

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Acerca de los autores

Masoud Daneshtalab is a tenured associate professor at Mälardalen University (MDH) in Sweden, an adjunct professor at Tallinn University of Technology (TalTech) in Estonia, and sits on the board of directors of Euromicro. His research interests include interconnection networks, brain-like computing, and deep learning architectures. He has published over 300-refereed papers.



Mehdi Modarressi is an assistant professor at the Department of Electrical and Computer Engineering, University of Tehran, Iran. He is the founder and director of the Parallel and Network-based Processing research laboratory at the University of Tehran, where he leads several industrial and research projects on deep learning-based embedded system design and implementation.

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Editorial
Institution of Engineering and Technology
Año de publicación
2020
Idioma
Inglés
ISBN 10 
1785617680
ISBN 13 
9781785617683
Encuadernación
Tapa dura
Número de páginas
328
Editor
Daneshtalab Masoud, Modarressi Mehdi
Contacto del fabricante
no disponible
Persona responsable
no disponible