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 in | E-Business and Telecommunications pp. 393 - 417 |
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Main Authors | , , , |
Format | Book Chapter |
Language | English |
Published |
Cham
Springer International Publishing
2015
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Series | Communications in Computer and Information Science |
Subjects | |
Online Access | Get full text |
ISBN | 9783319259147 3319259148 |
ISSN | 1865-0929 1865-0937 |
DOI | 10.1007/978-3-319-25915-4_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. |
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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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Copyright | Springer International Publishing Switzerland 2015 |
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DOI | 10.1007/978-3-319-25915-4_21 |
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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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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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