Optimizing HEVC CABAC Decoding with a Context Model Cache and Application-Specific Prefetching

Philipp Habermann, C. C. Chi, M. Alvarez-Mesa, B. Juurlink
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引用次数: 1

Abstract

Context-based Adaptive Binary Arithmetic Coding is the entropy coding module in the most recent JCT-VC video coding standard HEVC/H.265. As in the predecessor H.264/AVC, CABAC is a well-known throughput bottleneck due to its strong data dependencies. Beside other optimizations, the replacement of the context model memory by a smaller cache has been proposed, resulting in an improved clock frequency. However, the effect of potential cache misses has not been properly evaluated. Our work fills this gap and performs an extensive evaluation of different cache configurations. Furthermore, it is demonstrated that application-specific context model prefetching can effectively reduce the miss rate and make it negligible. Best overall performance results were achieved with caches of two and four lines, where each cache line consists of four context models. Four cache lines allow a speed-up of 10% to 12% for all video configurations while two cache lines improve the throughput by 9% to 15% for high bitrate videos and by 1% to 4% for low bitrate videos.
优化HEVC CABAC解码与上下文模型缓存和应用程序特定的预取
基于上下文的自适应二进制算术编码是最新JCT-VC视频编码标准HEVC/H.265中的熵编码模块。与之前的H.264/AVC一样,由于其强大的数据依赖性,CABAC是众所周知的吞吐量瓶颈。除了其他优化之外,还建议用较小的缓存替换上下文模型内存,从而提高时钟频率。然而,潜在的缓存丢失的影响还没有得到适当的评估。我们的工作填补了这一空白,并对不同的缓存配置进行了广泛的评估。此外,应用上下文模型预取可以有效地降低脱靶率,使其可以忽略不计。使用两行和四行缓存可以获得最佳的总体性能结果,其中每条缓存行由四个上下文模型组成。对于所有视频配置,四条缓存线允许10%到12%的速度提升,而两条缓存线对于高比特率视频可以提高9%到15%的吞吐量,对于低比特率视频可以提高1%到4%的吞吐量。
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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