Accelerating HEVC using heterogeneous platforms
The high efficiency video coding (HEVC) standard achieves double compression efficiency compared with H.264/advanced video coding at the cost of huge computational complexity. Parallelizing HEVC encoding is an efficient way of fulfilling this computational requirement. The parallelization algorithms considered in HEVC, such as Tiles or wavefront parallel processing (WPP), rely on creating picture partitions that can be processed concurrently in a multi-core architecture. However, this paper focuses on the design of a heterogeneous parallel architecture composed of a graphic processing unit (GPU) plus a multi-core central processing unit (CPU) to take advantage of these techniques. Experimental results indicate that our approach outperforms WPP in terms of speed-up and reduces the delay introduced by alternative techniques such as the group of pictures-based processing pattern. Moreover, the proposed algorithms obtain speed-up values of over \(4 \times \) on an Intel quad-core CPU and an NVIDIA GPU with negligible quality losses.
hevc parallelization gpu multicore heterogeneous computing