HEVC Encoding Optimization Using Multicore CPUs and GPUs

Abstract

Although the High Efficiency Video Coding (HEVC) standard significantly improves the coding efficiency of video compression, it is unacceptable even in offline applications to spend several hours compressing 10 s of high-definition video. In this paper, we propose using a multicore central processing unit (CPU) and an off-the-shelf graphics processing unit (GPU) with 3072 streaming processors (SPs) for HEVC fast encoding, so that the speed optimization does not result in loss of coding efficiency. There are two key technical contributions in this paper. First, we propose an algorithm that is both parallel and fast for the GPU, which can utilize 3072 SPs in parallel to estimate the motion vector (MV) of every prediction unit (PU) in every combination of the coding unit (CU) and PU partitions. Furthermore, the proposed GPU algorithm can avoid coding efficiency loss caused by the lack of a MV predictor (MVP). Second, we propose a fast algorithm for the CPU, which can fully utilize the results from the GPU to significantly reduce the number of possible CU and PU partitions without any coding efficiency loss. Our experimental results show that compared with the reference software, we can encode high-resolution video that consumes 1.9% of the CPU time and 1.0% of the GPU time, with only a 1.4% rate increase.