Efficient Processing Deep Neural by Sze Vivienne (9 results)
Language: English
Published by Springer (edition 1), 2020
Series: Book 5 of 7 - Synthesis Lectures on Computer Architecture
- Softcover
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Paperback. Condition: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
Language: English
Published by Springer, 2020
Series: Book 5 of 7 - Synthesis Lectures on Computer Architecture
- Softcover
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Condition: New. 1st edition NO-PA16APR2015-KAP.
Language: English
Published by Springer, 2020
Series: Book 5 of 7 - Synthesis Lectures on Computer Architecture
- Softcover
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Taschenbuch. Condition: Neu. Efficient Processing of Deep Neural Networks | Vivienne Sze (u. a.) | Taschenbuch | Synthesis Lectures on Computer Architecture | xxi | Englisch | 2020 | Springer | EAN 9783031006388 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[a…t]springer[dot]com | Anbieter: preigu.
Language: English
Published by Springer, 2020
Series: Book 5 of 7 - Synthesis Lectures on Computer Architecture
- Softcover
- Print on Demand
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Condition: new. Questo è un articolo print on demand.
Language: English
Published by Springer International Publishing Jun 2020, 2020
Series: Book 5 of 7 - Synthesis Lectures on Computer Architecture
- Softcover
- Print on Demand
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, incl…uding 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. 356 pp. Englisch.
Language: English
Published by Springer, 2020
Series: Book 5 of 7 - Synthesis Lectures on Computer Architecture
- Softcover
- Print on Demand
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Language: English
Published by Springer, 2020
Series: Book 5 of 7 - Synthesis Lectures on Computer Architecture
- Softcover
- Print on Demand
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Language: English
Published by Springer, Berlin|Springer International Publishing|Morgan & Claypool|Springer, 2020
Series: Book 5 of 7 - Synthesis Lectures on Computer Architecture
- Softcover
- Print on Demand
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) app…lications, including computer .
Language: English
Published by Springer, Springer Jun 2020, 2020
Series: Book 5 of 7 - Synthesis Lectures on Computer Architecture
- Softcover
- Print on Demand
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, includin…g 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 344 pp. Englisch.
