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Gpu Parallel Program Development by Soyata Tolga (29 results)
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Condition: As New. Unread book in perfect condition.
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Condition: New. pp. 476.
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Gpu Parallel Program Development Using Cuda
Book 25 of 27: Chapman & Hall/CRC Computational ScienceSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Condition: New. pp. 476.
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Gpu Parallel Program Development Using Cuda
Book 25 of 27: Chapman & Hall/CRC Computational ScienceSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Condition: New. pp. 476.
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GPU Parallel Program Development Using CUDA
Book 25 of 27: Chapman & Hall/CRC Computational ScienceLanguage: English
Published by Taylor & Francis Ltd, 2020
ISBN 10: 0367572249 ISBN 13: 9780367572242
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days. 881.
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GPU Parallel Program Development Using CUDA (Chapman & Hall/CRC Computational Science)
Book 25 of 27: Chapman & Hall/CRC Computational ScienceLanguage: English
Published by Chapman and Hall/CRC, 2018
ISBN 10: 1498750753 ISBN 13: 9781498750752
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Seller rating 5 out of 5 stars
Condition: Good. Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.
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GPU Parallel Program Development Using CUDA
Book 25 of 27: Chapman & Hall/CRC Computational ScienceLanguage: English
Published by Chapman and Hall/CRC, 2018
ISBN 10: 1498750753 ISBN 13: 9781498750752
Condition: As New. Unread book in perfect condition.
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GPU PARALLEL PROGRAM DEVELOPMENT USING CUDA
Book 25 of 27: Chapman & Hall/CRC Computational ScienceLanguage: English
Published by Taylor & Francis Group, 2018
ISBN 10: 1498750753 ISBN 13: 9781498750752
Condition: New.
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GPU Parallel Program Development Using CUDA
Book 25 of 27: Chapman & Hall/CRC Computational ScienceLanguage: English
Published by Chapman and Hall/CRC, 2018
ISBN 10: 1498750753 ISBN 13: 9781498750752
Condition: New.
-
GPU Parallel Program Development Using CUDA
Book 25 of 27: Chapman & Hall/CRC Computational ScienceLanguage: English
Published by Chapman and Hall/CRC, 2018
ISBN 10: 1498750753 ISBN 13: 9781498750752
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Paperback. Condition: Brand New. 476 pages. 10.00x7.01x1.10 inches. In Stock.
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Hardcover. Condition: Brand New. 440 pages. 10.00x7.00x1.25 inches. In Stock.
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GPU PARALLEL PROGRAM DEVELOPMENT USING CUDA
Book 25 of 27: Chapman & Hall/CRC Computational ScienceLanguage: English
Published by Taylor & Francis Group, 2018
ISBN 10: 1498750753 ISBN 13: 9781498750752
Condition: New.
-
GPU Parallel Program Development Using CUDA
Book 25 of 27: Chapman & Hall/CRC Computational ScienceLanguage: English
Published by Chapman and Hall/CRC, 2018
ISBN 10: 1498750753 ISBN 13: 9781498750752
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
-
GPU PARALLEL PROGRAM DEVELOPMENT USING CUDA
Book 25 of 27: Chapman & Hall/CRC Computational ScienceLanguage: English
Published by Taylor & Francis Group, 2018
ISBN 10: 1498750753 ISBN 13: 9781498750752
Condition: New.
-
GPU Parallel Program Development Using CUDA
Book 25 of 27: Chapman & Hall/CRC Computational ScienceLanguage: English
Published by Taylor & Francis Inc, 2018
ISBN 10: 1498750753 ISBN 13: 9781498750752
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Hardback. Condition: New. New copy - Usually dispatched within 4 working days.
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GPU Parallel Program Development Using CUDA
Book 25 of 27: Chapman & Hall/CRC Computational ScienceLanguage: English
Published by Chapman and Hall/CRC, 2020
ISBN 10: 0367572249 ISBN 13: 9780367572242
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.
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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.
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GPU Parallel Program Development Using CUDA
Book 25 of 27: Chapman & Hall/CRC Computational ScienceLanguage: English
Published by Taylor & Francis Feb 2018, 2018
ISBN 10: 1498750753 ISBN 13: 9781498750752
Buch. Condition: Neu. Neuware.
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Gpu Parallel Program Development Using Cuda
Book 25 of 27: Chapman & Hall/CRC Computational ScienceSeller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
£ 60.08
£ 5.87 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketPAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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GPU Parallel Program Development Using CUDA
Book 25 of 27: Chapman & Hall/CRC Computational ScienceLanguage: English
Published by Chapman And Hall/CRC Jun 2020, 2020
ISBN 10: 0367572249 ISBN 13: 9780367572242
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
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 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. 478 pp. Englisch.
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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.
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GPU Parallel Program Development Using CUDA
Book 25 of 27: Chapman & Hall/CRC Computational ScienceLanguage: English
Published by Taylor & Francis, Chapman And Hall/CRC, 2018
ISBN 10: 1498750753 ISBN 13: 9781498750752
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
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.
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GPU Parallel Program Development Using CUDA
Book 25 of 27: Chapman & Hall/CRC Computational ScienceLanguage: English
Published by Chapman And Hall/CRC, 2020
ISBN 10: 0367572249 ISBN 13: 9780367572242
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book teaches GPU programming by introducing CPU multi-threaded programming and bases GPU massively-parallel programming on this foundation. The differences among families of GPUs are also studied. The book also explores CUDA libraries, OpenCL, GPU programming with other languages and API libraries, and the deep learning library cuDNN.
