Many-Core HEVC Encoding Based on Wavefront Parallel Processing and GPU-accelerated Motion Estimation

The High Efficiency Video Coding (HEVC) standard provides an outstanding compression performance and is thus ideally suited for Ultra High Definition (UHD) content. However, the complexity of the encoder is substantial and therefore highly optimized implementations are required to achieve reasonable...

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Published inE-Business and Telecommunications pp. 393 - 417
Main Authors Radicke, Stefan, Hahn, Jens-Uwe, Wang, Qi, Grecos, Christos
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing 2015
SeriesCommunications in Computer and Information Science
Subjects
Online AccessGet full text
ISBN9783319259147
3319259148
ISSN1865-0929
1865-0937
DOI10.1007/978-3-319-25915-4_21

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Abstract The High Efficiency Video Coding (HEVC) standard provides an outstanding compression performance and is thus ideally suited for Ultra High Definition (UHD) content. However, the complexity of the encoder is substantial and therefore highly optimized implementations are required to achieve reasonable speeds. For this purpose, high-level parallelization mechanisms like Wavefront Parallel Processing (WPP), can be used to leverage modern multi-core hardware. In this work, the WPP mechanism is theoretically analyzed and a non-intrusive implementation of it based on the reference test model HM-13.0 is presented. Furthermore, a novel extension for heterogeneous computing platforms called Heterogeneous WPP (HWPP) is proposed which largely increases the achievable speedups. To demonstrate the power of HWPP, a Graphics Processing Unit (GPU) accelerated Motion Estimation (ME) algorithm is integrated. Based on a large amount of experimental data, it is shown that the speedups achieved with WPP and HWPP reach up to 8.9 and 17.9 times, respectively.
AbstractList The High Efficiency Video Coding (HEVC) standard provides an outstanding compression performance and is thus ideally suited for Ultra High Definition (UHD) content. However, the complexity of the encoder is substantial and therefore highly optimized implementations are required to achieve reasonable speeds. For this purpose, high-level parallelization mechanisms like Wavefront Parallel Processing (WPP), can be used to leverage modern multi-core hardware. In this work, the WPP mechanism is theoretically analyzed and a non-intrusive implementation of it based on the reference test model HM-13.0 is presented. Furthermore, a novel extension for heterogeneous computing platforms called Heterogeneous WPP (HWPP) is proposed which largely increases the achievable speedups. To demonstrate the power of HWPP, a Graphics Processing Unit (GPU) accelerated Motion Estimation (ME) algorithm is integrated. Based on a large amount of experimental data, it is shown that the speedups achieved with WPP and HWPP reach up to 8.9 and 17.9 times, respectively.
Author Wang, Qi
Grecos, Christos
Radicke, Stefan
Hahn, Jens-Uwe
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Snippet The High Efficiency Video Coding (HEVC) standard provides an outstanding compression performance and is thus ideally suited for Ultra High Definition (UHD)...
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StartPage 393
SubjectTerms Graphics Processing Unit (GPU)
Heterogeneous WPP (HWPP)
High Efficiency Video Coding (HEVC)
Massively parallel computing
Motion Estimation (ME)
Wavefront Parallel Processing (WPP)
Title Many-Core HEVC Encoding Based on Wavefront Parallel Processing and GPU-accelerated Motion Estimation
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