多层次细粒度并行HEVC帧内模式选择算法

Multi-Level and Fine-Grained Parallel HEVC Intra Mode Decision Method

在众核平台上并行加速是解决高效视频编码(high efficiency video coding,HEVC)标准编码复杂度高的有效方法.传统的粗粒度并行方案如Tiles和WPP未能在并行度和编码质量之间取得较好的平衡,对编码质量影响较大或者并行度不高.充分挖掘HEVC帧内模式选择中的并行性,提出了一种在CTU内使用的多层次细粒度的帧内模式选择算法.具体说来,对帧内模式选择过程进行了子任务划分,分析并消除了相邻编码块之间多种阻碍并行计算的数据依赖关系,包括帧内预测参考像素依赖、预测模式依赖和熵编码依赖等,实现了同一个CTU内所有层次的细粒度编码块的代价计算和模式选择并行进行.将算法在Tile-Gx36平台上实现,实验结果表明此并行算法与HEVC参考代码HM相比能获得18倍的整体编码加速比而且编码质量损失较小(码率上升3%).

The coding mode space of high efficiency video coding（HEVC）is extremely large so it needs huge amount of computations for HEVC encoders to do mode decision（MD）.Parallelizing HEVC encoding on many-core platforms is an efficient and promising approach to fulfill the high computational demands.Traditional coarse-grained parallelizing schemes such as Tiles and wavefront parallel processing（WPP）either cause too much quality loss or can＇t afford a high parallelism degree.In this paper,the potential parallelism in HEVC intra MD process is exploited,and a multi-level and fine-grained highly parallel intra MD method which works in a coding tree unit（CTU）is proposed.Specifically,the intra MD process in a CTU is divided into six types of sub-tasks,and the data dependencies among adjacent blocks that hinder parallel processing are analyzed and removed,including intra prediction dependency,prediction mode dependency and entropy coding dependency;consequently the MD computation for all fine-grained coding blocks of different levels within the same CTU can be computed concurrently.The proposed parallel MD method is implemented on Tile-Gx36 platform.Experimental results show that the proposed parallel MD method gets an overall speed up of more than 18 xwith acceptable quality loss（about 3% bit-rate increasing）,compared with the nonparallel baseline HM.