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Stage-based frame-partitioned parallelization of H.264/AVC decoding

机译:H.264 / AVC解码的基于阶段的帧划分并行化

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摘要

Strong demands for high resolution video services lead to active studies on high speed video processing. Especially, widespread deployment of multi-core systems accelerates researches on high resolution video processing based on parallelization of multimedia software. In this paper, we propose a novel parallel H.264/AVC decoding scheme on a homogeneous multi-core platform. Parallelization of H.264/AVC decoding is challenging not only because parallelization may incur significant synchronization overhead but also because software may have complicated dependencies. To overcome such issues, we propose a novel approach called Stage-based Frame-Partitioned Parallelization (SFPP). In SFPP, we divide a frame into multiple partitions, and execute them in a pipelined fashion. To reduce synchronization overhead, a separate thread is allocated to each stage in the pipeline. In addition, an efficient memory reuse technique is used to reduce the memory requirement. To verify the effectiveness of the proposed approach, we parallelized FFmpeg H.264/AVC decoder with the proposed technique using OpenMP, and carried out experiments on an Intel Quad-Core platform. The proposed design performs better than FFmpeg H.264/AVC decoder before parallelization by 53%. We also reduced the amount of memory usage by 65% and 81% for a high-definition (HD) and a full high-definition (FHD) video, respectively compared with that of a popular existing method.
机译:对高分辨率视频服务的强烈需求导致人们积极研究高速视频处理。特别是,多核系统的广泛部署加速了基于多媒体软件并行化的高分辨率视频处理的研究。在本文中,我们提出了一种在同类多核平台上的新颖的并行H.264 / AVC解码方案。 H.264 / AVC解码的并行化具有挑战性,这不仅是因为并行化可能招致巨大的同步开销,而且还因为软件可能具有复杂的依赖性。为了克服这些问题,我们提出了一种新颖的方法,称为基于阶段的帧分区并行化(SFPP)。在SFPP中,我们将一个帧划分为多个分区,并以流水线方式执行它们。为了减少同步开销,将单独的线程分配给管道中的每个阶段。另外,有效的内存重用技术用于减少内存需求。为了验证所提出方法的有效性,我们使用OpenMP将FFmpeg H.264 / AVC解码器与所提出的技术并行化,并在Intel四核平台上进行了实验。提出的设计在并行化之前比FFmpeg H.264 / AVC解码器性能更好。与流行的现有方法相比,我们还将高清(HD)视频和完整高清(FHD)视频的内存使用量分别减少了65%和81%。

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