Hardware Architectures for Deep Learning
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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. |
| Note | Unavailable |