Novel Efficient HEVC Decoding Solution on General-Purpose Processors

Although the emerging video coding standard High Efficiency Video Coding (HEVC) successfully doubles the compression efficiency of H.264/AVC, its growing computational complexity makes real-time decoding of high-definition HEVC videos a very challenging issue for the existing personal computers and...

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Vydáno v:IEEE transactions on multimedia Ročník 16; číslo 7; s. 1915 - 1928
Hlavní autoři: Duan, Yizhou, Sun, Jun, Yan, Leju, Chen, Keji, Guo, Zongming
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.11.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:1520-9210, 1941-0077
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Abstract Although the emerging video coding standard High Efficiency Video Coding (HEVC) successfully doubles the compression efficiency of H.264/AVC, its growing computational complexity makes real-time decoding of high-definition HEVC videos a very challenging issue for the existing personal computers and mobile devices. In this paper, a systematical, efficient HEVC decoding solution on general processors is provided, consisting of structure-level, data-level, and task-level approaches. First, a redesigned overall structure of a HEVC decoder with data redundancy reduction mechanism is introduced, which cuts down basic data operation cost and achieves an average decoding speedup of 2.37 × compared to the HM 10.0 decoder. On this basis, novel single-instruction multiple-data (SIMD) algorithms such as low-complexity motion compensation, transpose-free transform, symmetric deblocking filter, and parallel-index sample adaptive offset are developed, which further parallelize the data operations of each decoding task and bring another 2.67 × decoding speedup. Finally, a frame-based task-level parallel framework is employed with a flexible entry scheme to efficiently support the simultaneous processing of multiple decoding tasks for different HEVC parallel strategies. The overall solution achieves decoding fps of 40-75 for 4k HEVC videos on the Intel i7-2600 3.4 GHz quad-core processor (4-thread decoding) and 35-55 for 720p videos on the ARM Cortex-A9 1.2 GHz duo-core processor (2-thread decoding). This proposal is the recommended cross-platform HEVC decoding solution of Intel, AMD, and Cisco, and has provided HEVC service to over 1500 million people in China via the Xunlei Kankan video client.
AbstractList Although the emerging video coding standard High Efficiency Video Coding (HEVC) successfully doubles the compression efficiency of H.264/AVC, its growing computational complexity makes real-time decoding of high-definition HEVC videos a very challenging issue for the existing personal computers and mobile devices. In this paper, a systematical, efficient HEVC decoding solution on general processors is provided, consisting of structure-level, data-level, and task-level approaches. First, a redesigned overall structure of a HEVC decoder with data redundancy reduction mechanism is introduced, which cuts down basic data operation cost and achieves an average decoding speedup of [Formula Omitted] compared to the HM 10.0 decoder. On this basis, novel single-instruction multiple-data (SIMD) algorithms such as low-complexity motion compensation, transpose-free transform, symmetric deblocking filter, and parallel-index sample adaptive offset are developed, which further parallelize the data operations of each decoding task and bring another [Formula Omitted] decoding speedup. Finally, a frame-based task-level parallel framework is employed with a flexible entry scheme to efficiently support the simultaneous processing of multiple decoding tasks for different HEVC parallel strategies. The overall solution achieves decoding fps of 40-75 for 4k HEVC videos on the Intel i7-2600 3.4 GHz quad-core processor (4-thread decoding) and 35-55 for 720p videos on the ARM Cortex-A9 1.2 GHz duo-core processor (2-thread decoding). This proposal is the recommended cross-platform HEVC decoding solution of Intel, AMD, and Cisco, and has provided HEVC service to over 1500 million people in China via the Xunlei Kankan video client.
Although the emerging video coding standard High Efficiency Video Coding (HEVC) successfully doubles the compression efficiency of H.264/AVC, its growing computational complexity makes real-time decoding of high-definition HEVC videos a very challenging issue for the existing personal computers and mobile devices. In this paper, a systematical, efficient HEVC decoding solution on general processors is provided, consisting of structure-level, data-level, and task-level approaches. First, a redesigned overall structure of a HEVC decoder with data redundancy reduction mechanism is introduced, which cuts down basic data operation cost and achieves an average decoding speedup of 2.37 compared to the HM 10.0 decoder. On this basis, novel single-instruction multiple-data (SIMD) algorithms such as low-complexity motion compensation, transpose-free transform, symmetric deblocking filter, and parallel-index sample adaptive offset are developed, which further parallelize the data operations of each decoding task and bring another 2.67 decoding speedup. Finally, a frame-based task-level parallel framework is employed with a flexible entry scheme to efficiently support the simultaneous processing of multiple decoding tasks for different HEVC parallel strategies. The overall solution achieves decoding fps of 40-75 for 4k HEVC videos on the Intel i7-2600 3.4 GHz quad-core processor (4-thread decoding) and 35-55 for 720p videos on the ARM Cortex-A9 1.2 GHz duo-core processor (2-thread decoding). This proposal is the recommended cross-platform HEVC decoding solution of Intel, AMD, and Cisco, and has provided HEVC service to over 1500 million people in China via the Xunlei Kankan video client.
Although the emerging video coding standard High Efficiency Video Coding (HEVC) successfully doubles the compression efficiency of H.264/AVC, its growing computational complexity makes real-time decoding of high-definition HEVC videos a very challenging issue for the existing personal computers and mobile devices. In this paper, a systematical, efficient HEVC decoding solution on general processors is provided, consisting of structure-level, data-level, and task-level approaches. First, a redesigned overall structure of a HEVC decoder with data redundancy reduction mechanism is introduced, which cuts down basic data operation cost and achieves an average decoding speedup of 2.37 × compared to the HM 10.0 decoder. On this basis, novel single-instruction multiple-data (SIMD) algorithms such as low-complexity motion compensation, transpose-free transform, symmetric deblocking filter, and parallel-index sample adaptive offset are developed, which further parallelize the data operations of each decoding task and bring another 2.67 × decoding speedup. Finally, a frame-based task-level parallel framework is employed with a flexible entry scheme to efficiently support the simultaneous processing of multiple decoding tasks for different HEVC parallel strategies. The overall solution achieves decoding fps of 40-75 for 4k HEVC videos on the Intel i7-2600 3.4 GHz quad-core processor (4-thread decoding) and 35-55 for 720p videos on the ARM Cortex-A9 1.2 GHz duo-core processor (2-thread decoding). This proposal is the recommended cross-platform HEVC decoding solution of Intel, AMD, and Cisco, and has provided HEVC service to over 1500 million people in China via the Xunlei Kankan video client.
Author Keji Chen
Leju Yan
Yizhou Duan
Jun Sun
Zongming Guo
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SubjectTerms Algorithm design and analysis
Algorithms
Coding
Computation
Decoders
Decoding
Encoding
high efficiency video coding (HEVC)
Mathematical models
Processors
Program processors
SIMD
Tasks
Transforms
video codecs
Video coding
Title Novel Efficient HEVC Decoding Solution on General-Purpose Processors
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