Hardware Architectures for Deep Learning by Mehdi Modarressi

Hardware Architectures for Deep Learning by Mehdi Modarressi

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Summary

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.

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Hardware Architectures for Deep Learning by Mehdi Modarressi

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.