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9783746731001: High-performance Video Decoding using Graphics Processing Units

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ISBN 10 : 3746731003 ISBN 13 : 9783746731001

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Langue: anglais
ISBN 10: 3746731003
ISBN 13: 9783746731001
Reliure: Tapa blanda
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High-performance Video Decoding using Graphics Processing Units

Biao Wang

Edit� par Epubli Jun 2018, 2018

ISBN 10 : 3746731003 ISBN 13 : 9783746731001

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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The increasing demand of decoding high-quality videos can lead to a challenging com-putational requirement for conventional Central Processing Unit (CPU) architectures.Graphics Processing Units (GPUs) in general provide higher computational powerthan CPUs. Efficient GPU execution, however, requires massive parallelism and little ex-ecuting divergence, two criteria are not fully met by all video decoding kernels. This thesisexploits how GPUs can be effectively used in video decoding applications. The challengesinclude proper workload distribution between the CPU and GPU, task optimizations ontwo heterogeneous devices, and efficient communication between them.A complete parallel HEVC decoder was proposed for heterogeneous CPU+GPUsystems. We exploited available decoding parallelism on the CPU, GPU, and between thetwo devices simultaneously. On top of the parallel design, two workload balancing schemeswere implemented, in order to adapt computation resource variation on CPU and GPU.In addition, an energy measurement module was developed for energy efficiency analysis.Evaluated results showed that suitable decoding kernels can be accelerated substan-tially (up to 28.2�) on GPUs at the kernel level. At the application level, using GPUarchitecture can provide significant acceleration when only a low number (1 to 8) of CPUcores are available. On a system consisting of an NVIDIA Titan X Maxwell GPU and anIntel Xeon E5-2699v3 CPU, with four CPU cores, the proposed HEVC decoder delivers167 frames per second for 4K videos, corresponding to a speedup of 2.2� over the state-of-the-art CPU decoder using four CPU cores. When more CPU cores (>8) are employed,the benefit of using GPU vanishes and the performance is eventually outperformed by theCPU decoder due to GPU overloading. With respect to energy, because of its high powerconsumption GPU architecture is not as efficient as the CPU for HEVC decoding. 176 pp. Englisch. N� de r�f. du vendeur 9783746731001

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High-performance Video Decoding using Graphics Processing Units

Wang, Biao

Edit� par epubli, 2018

ISBN 10 : 3746731003 ISBN 13 : 9783746731001

Neuf Couverture souple

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Vendeur : moluna, Greven, Allemagne

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The book describes how the Graphics Processing Units (GPUs) can be used to accelerate video decoding applications.The increasing demand of decoding high-quality videos can lead to a challenging com-putational requirement for conventional Central Process. N� de r�f. du vendeur 385787568

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High-performance Video Decoding using Graphics Processing Units : Dissertationsschrift

Biao Wang

Edit� par Epubli, 2018

ISBN 10 : 3746731003 ISBN 13 : 9783746731001

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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The increasing demand of decoding high-quality videos can lead to a challenging com-putational requirement for conventional Central Processing Unit (CPU) architectures.Graphics Processing Units (GPUs) in general provide higher computational powerthan CPUs. Efficient GPU execution, however, requires massive parallelism and little ex-ecuting divergence, two criteria are not fully met by all video decoding kernels. This thesisexploits how GPUs can be effectively used in video decoding applications. The challengesinclude proper workload distribution between the CPU and GPU, task optimizations ontwo heterogeneous devices, and efficient communication between them.A complete parallel HEVC decoder was proposed for heterogeneous CPU+GPUsystems. We exploited available decoding parallelism on the CPU, GPU, and between thetwo devices simultaneously. On top of the parallel design, two workload balancing schemeswere implemented, in order to adapt computation resource variation on CPU and GPU.In addition, an energy measurement module was developed for energy efficiency analysis.Evaluated results showed that suitable decoding kernels can be accelerated substan-tially (up to 28.2�) on GPUs at the kernel level. At the application level, using GPUarchitecture can provide significant acceleration when only a low number (1 to 8) of CPUcores are available. On a system consisting of an NVIDIA Titan X Maxwell GPU and anIntel Xeon E5-2699v3 CPU, with four CPU cores, the proposed HEVC decoder delivers167 frames per second for 4K videos, corresponding to a speedup of 2.2� over the state-of-the-art CPU decoder using four CPU cores. When more CPU cores (>8) are employed,the benefit of using GPU vanishes and the performance is eventually outperformed by theCPU decoder due to GPU overloading. With respect to energy, because of its high powerconsumption GPU architecture is not as efficient as the CPU for HEVC decoding. N� de r�f. du vendeur 9783746731001

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