Hardware Architectures for Deep Learning by Masoud Daneshtalab

Hardware Architectures for Deep Learning by Masoud Daneshtalab

This book discusses innovative ideas in the design, modelling, implementation, and optimization of hardware platforms for neural networks. The book provides an overview of this emerging field, from principles to applications, for researchers, postgraduate students and engineers who work on learning-based services and hardware platforms.

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.

SKU	Unavailable
ISBN 13	9781785617683
ISBN 10	1785617680
Title	Hardware Architectures for Deep Learning
Author	Masoud Daneshtalab
Series	Materials Circuits And Devices
Condition	Unavailable
Binding Type	Hardback
Publisher	Institution of Engineering and Technology
Year published	2020-04-24
Number of pages	328
Cover note	Book picture is for illustrative purposes only, actual binding, cover or edition may vary.