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Efficient Processing Of Deep Neural Networksexcerpt 1st Vivienne Sze

  • SKU: BELL-11209612
Efficient Processing Of Deep Neural Networksexcerpt 1st Vivienne Sze
$ 31.00 $ 45.00 (-31%)

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Efficient Processing Of Deep Neural Networksexcerpt 1st Vivienne Sze instant download after payment.

Publisher: Morgan and Company
File Extension: PDF
File size: 1.87 MB
Pages: 82
Author: Vivienne Sze, Yu-Hsin Chen, Tien-Ju Yang, Joel S. Emer
ISBN: 9781681738321, 1681738325
Language: English
Year: 2020
Edition: 1st

Product desciption

Efficient Processing Of Deep Neural Networksexcerpt 1st Vivienne Sze by Vivienne Sze, Yu-hsin Chen, Tien-ju Yang, Joel S. Emer 9781681738321, 1681738325 instant download after payment.

This book provides a structured treatment of the key principles and techniques for enabling efficient process- ing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the- art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve key metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems.

The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as formalization and organization of key concepts from contemporary work that provide insights that may spark new ideas.

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