On Combining Wavefront and Tile Parallelism with a Novel GPU-Friendly Fast Search

Abstract

As the necessity of supporting ever-increasing demands in video resolution leads to new video coding standards, the challenge of harnessing their computational overhead becomes important. Such overhead stems not only from the increased image data due to higher resolutions but also from the coding techniques per se that are introduced by each standard to improve compression. All modern standards in the field of video coding offer high compression efficiency, but this is achieved by increasing the computational complexity of the encoding part. Ultra-High-Definition (UHD) videos, bring new encoding implementation schemes that are being recommended for CPU and GPU parallelization. Therefore, several works are published to achieve better performance and reduce encoding complexity. Following this idea, we proposed and evaluated a hybrid encoding scheme that utilizes the constant growth of the CPU power with the massive GPU popularity in parallel. Taking advantage of the encoding schemes from the leading video coding standards, such as High-Efficiency Video Coding (HEVC) and Versatile Video Coding (VVC), which support parallel processing thru Wavefront or Tiling, in our work, we combined both of them at the same time as a whole, and in addition, we introduced a GPU-friendly fast search algorithm that is highly parallel and alternative to the default non-parallel TZ-Search. Through an experimental evaluation with common test sequences, the proposed GPU Fast Motion Estimation with our previous Wavefront per Tile Parallelism (WTP) was shown to provide valid trade-off between speedup and video coding efficiency, effectively combining the best of two worlds, i.e., WTP using CPUs and parallel Motion Estimation with GPUs.