Gpu Parallel Program Development by Soyata Tolga (32 results)
Language: English
Published by Routledge 2020
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
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Published by Routledge 2020
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
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Published by Routledge 2020
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
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Language: English
Published by Chapman and Hall/CRC 2018
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
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Language: English
Published by Chapman and Hall/CRC 2018
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
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Language: English
Published by Chapman and Hall/CRC 2018
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
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Language: English
Published by Routledge 2020
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
- Softcover
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Published by Routledge 2020
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
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Condition: New. pp. 476.
Language: English
Published by Routledge 2020
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
- Softcover
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Language: English
Published by Routledge 2020
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
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Language: English
Published by Routledge 2020
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
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Condition: New. pp. 476.
Language: English
Published by Taylor & Francis Ltd 2020
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
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Language: English
Published by Chapman and Hall/CRC 2018
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
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Language: English
Published by Chapman and Hall/CRC 2018
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
- Hardcover
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Language: English
Published by Taylor & Francis Group 2018
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
- Hardcover
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Language: English
Published by Chapman and Hall/CRC 2018
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
- Hardcover
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Language: English
Published by Chapman & Hall 2020
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
- Softcover
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Paperback. Condition: Brand New. 476 pages. 10.00x7.01x1.10 inches. In Stock.
Language: English
Published by Chapman & Hall 2018
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
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Language: English
Published by Chapman and Hall/CRC 2018
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
- Hardcover
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Language: English
Published by Chapman and Hall/CRC 2018
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
- Hardcover
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Language: English
Published by Taylor & Francis Inc 2018
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
- Hardcover
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Language: English
Published by Chapman and Hall/CRC 2020
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
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Taschenbuch. Condition: Neu. GPU Parallel Program Development Using CUDA | Tolga Soyata | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2020 | Chapman and Hall/CRC | EAN 9780367572242 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Language: English
Published by Taylor & Francis Group 2018
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
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Language: English
Published by Taylor & Francis Group 2018
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
- Hardcover
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Language: English
Published by CRC Press 2018
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
- Hardcover
Seller: moluna, Greven, Germanymoluna
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Gebunden. Condition: New. Tolga Soyata is an associate professor in the Electrical and Computer Engineering department of SUNY Albany.GPU Parallel Program Development using CUDA teaches GPU programming by showing the diffe.
Language: English
Published by CRC Press 2020
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
- Softcover
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Language: English
Published by CRC Press 2020
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
- Softcover
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Language: English
Published by Chapman And Hall/CRC Jun 2020 2020
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
- Softcover
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -GPU Parallel Program Development using CUDA teaches GPU programming by showing the differences among different families of GPUs. This approach prepares the reader for the next generation and future generations of GPUs. The book emph…asizes concepts that will remain relevant for a long time, rather than concepts that are platform-specific. At the same time, the book also provides platform-dependent explanations that are as valuable as generalized GPU concepts. The book consists of three separate parts; it starts by explaining parallelism using CPU multi-threading in Part I. A few simple programs are used to demonstrate the concept of dividing a large task into multiple parallel sub-tasks and mapping them to CPU threads. Multiple ways of parallelizing the same task are analyzed and their pros/cons are studied in terms of both core and memory operation.Part II of the book introduces GPU massive parallelism. The same programs are parallelized on multiple Nvidia GPU platforms and the same performance analysis is repeated. Because the core and memory structures of CPUs and GPUs are different, the results differ in interesting ways. The end goal is to make programmers aware of all the good ideas, as well as the bad ideas, so readers can apply the good ideas and avoid the bad ideas in their own programs.Part III of the book provides pointer for readers who want to expand their horizons. It provides a brief introduction to popular CUDA libraries (such as cuBLAS, cuFFT, NPP, and Thrust),the OpenCL programming language, an overview of GPU programming using other programming languages and API libraries (such as Python, OpenCV, OpenGL, and Apple's Swift and Metal,) and the deep learning library cuDNN. 478 pp. Englisch.
Language: English
Published by CRC Press 2020
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
- Softcover
- Print on Demand
Seller: moluna, Greven, Germanymoluna
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Tolga Soyata is an associate professor in the Electrical and Computer Engineering department of SUNY Albany.GPU Parallel Program Development using CUDA teaches GPU programming by showing th.
Language: English
Published by Taylor & Francis, Chapman And Hall/CRC 2018
Series: Chapman & Hall/CRC Computational Science, Book 25 of 27. Book 25 of 27 - Chapman & Hall/CRC Computational Science
- Hardcover
- Print on Demand
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -GPU Parallel Program Development using CUDA teaches GPU programming by showing the differences among different families of GPUs. This approach prepares the reader for the next generation and future generations of GPUs. The book emphasizes…concepts that will remain relevant for a long time, rather than concepts that are platform-specific. At the same time, the book also provides platform-dependent explanations that are as valuable as generalized GPU concepts. The book consists of three separate parts; it starts by explaining parallelism using CPU multi-threading in Part I. A few simple programs are used to demonstrate the concept of dividing a large task into multiple parallel sub-tasks and mapping them to CPU threads. Multiple ways of parallelizing the same task are analyzed and their pros/cons are studied in terms of both core and memory operation.Part II of the book introduces GPU massive parallelism. The same programs are parallelized on multiple Nvidia GPU platforms and the same performance analysis is repeated. Because the core and memory structures of CPUs and GPUs are different, the results differ in interesting ways. The end goal is to make programmers aware of all the good ideas, as well as the bad ideas, so readers can apply the good ideas and avoid the bad ideas in their own programs.Part III of the book provides pointer for readers who want to expand their horizons. It provides a brief introduction to popular CUDA libraries (such as cuBLAS, cuFFT, NPP, and Thrust),the OpenCL programming language, an overview of GPU programming using other programming languages and API libraries (such as Python, OpenCV, OpenGL, and Apple's Swift and Metal,) and the deep learning library cuDNN. 476 pp. Englisch.
