Spatio-Temporal Parallelization Scheme for HEVC Encoding on Multi-Computer Systems

Alexandre Mercat, Sami Ahovainio, Jarno Vanne
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Abstract

High Efficiency Video Coding (HEVC) sets the scene for economic video transmission and storage, but its inherent computational complexity calls for efficient parallelization techniques. This paper introduces and compares three different parallelization strategies for HEVC encoding on multi-computer systems: 1) spatial parallelization scheme, where input video frames are divided into slices and distributed among available computers; 2) temporal parallelization scheme, where input video is distributed among computers in groups of consecutive frames; 3) spatio-temporal parallelization scheme that combines the proposed spatial and temporal approaches. All these three schemes were benchmarked as part of the practical Kvazaar open-source HEVC encoder. Our experimental results on 2–5 computer configurations show that using the spatial scheme gives 1.65×–2.90× speedup at the cost of 4.16%–13.09% bitrate loss over a single-computer setup. The respective speedup with temporal parallelization is 1.86×–3.26× without any coding overhead. The spatio-temporal scheme with 2 slices was shown to offer the best load-balancing with 1.81×–3.55× speedups and a constant coding loss of 4.16%.
多机系统上HEVC编码的时空并行化方案
高效视频编码(HEVC)为视频的经济传输和存储奠定了基础,但其固有的计算复杂性要求高效的并行化技术。本文介绍并比较了多机系统上HEVC编码的三种不同并行化策略:1)空间并行化方案,将输入视频帧分割成片并分布在可用的计算机上;2)时间并行化方案,将输入视频按连续帧分组分布在计算机之间;3)结合时空方法的时空并行化方案。这三种方案都作为实用的Kvazaar开源HEVC编码器的一部分进行了基准测试。我们在2-5台计算机配置上的实验结果表明,与单台计算机设置相比,使用空间方案可以以4.16%-13.09%的比特率损失为代价获得1.65×-2.90×加速。在没有任何编码开销的情况下,时间并行化的相应加速是1.86×-3.26×。2片的时空方案提供了最佳的负载平衡,速度提高1.81×-3.55×,编码损失恒定为4.16%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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