基于Tilera-GX36多核平台的HEVC解码细粒度多级并行算法

Yi Li, D. Hu, Wenxiang Zhang
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引用次数: 1

摘要

本文提出了一种用于HEVC解码的细粒度多级并行算法,重点研究了像素重构和环内滤波两个模块。首先,在像素重构模块中,波前并行处理(WPP)等基于CTU行并行解码算法可能会出现解码线程间负载不平衡的问题,因为不同CTU行内的CTU处理复杂度可能存在较大差异。为了解决这一问题,我们提出了一种基于WPP的细粒度并行算法。然后,在ILF模块中提出了一种快速融合ILF算法,该算法通过一种新的类cpu处理单元实现了DBF与SAO之间的深度耦合。此外,流水线并行技术的引入降低了两个模块之间的延迟。我们的方法在Tilera-GX36多核平台上实现,每个任务由一个线程绑定到一个单独的核上执行,充分利用了并行计算的性能。实验结果表明,所提算法的加速速度分别是现有算法的1.2倍、1.13倍和1.8倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fine Granular Multilevel Parallel Algorithm for HEVC Decoding Based on Tilera-GX36 Multi-core Platform
This paper presents a fine granular multilevel parallel algorithm for HEVC decoding, which is focus on two modules: the pixel reconstruction and the in-loop filter (ILF). Firstly, in the pixel reconstruction module, the problem of unbalanced load among decoding threads may occur in parallel decoding algorithm based on CTU rows, like wavefront parallel processing (WPP), because there may be big differences in the processing complexity of CTUs within various CTU rows. In order to solve this issue, we propose a fine granular parallel algorithm based on WPP. Then, a fast fusion ILF algorithm has been presented in the ILF module, which realizes the deep coupling between DBF and SAO by a new CTU-like process unit. Furthermore, the introduction of pipeline parallel technology makes a latency reduction between the two modules. We implement our method on Tilera-GX36 multi-core platform, each task executed by a thread bound to a separate core, which makes full use of the parallel computing performance. The experimental results show that the speedup of our proposed algorithms are 1.2, 1.13 and 1.8 times higher than that of those previous schemes respectively.
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