Fast motion estimation for HEVC on graphics processing unit (GPU)

Abstract

The recent video compression standard, HEVC (high efficiency video coding), will most likely be used in various applications in the near future. However, the encoding process is far too slow for real-time applications. At the same time, computing capabilities of GPUs (graphics processing units) have become more powerful in these days. In this paper, we have proposed a GPU-based parallel motion estimation (ME) algorithm to enhance the performance of an HEVC encoder. A frame is partitioned into two subframes for pipelined execution to improve GPU utilization. The flow chart is redetermined to solve data hazards in the pipelined execution. Two new methods are introduced in the proposed ME: decision of a representative search center position (RSCP) and warp-based concurrent parallel reduction (WCPR). A RSCP employs motion vectors of a co-located CTU in a previously encoded frame to solve a dependency problem in parallel computation with negligible coding loss. WCPR concurrently executes several parallel reduction operations, which increases the thread utilization from 20 to 89 % without any thread synchronization. The proposed encoder can make the portion of ME in the encoder negligible with 2.2 % bitrate increase against the HEVC test model (HM) encoder. In terms of ME, the proposed ME is 130.7 times faster than that of the HM encoder.

Maximum A Posteriori Estimation-based Adaptive Search Range Decision for Accelerating HEVC Motion Estimation on GPU

“…GPU_ASR can remove deta dependency between CTUs shown in Fig. 1 with a negligible RD penalty, which enhances the performance as compared to our previous work [33]. There are three main contributions in this paper as compared to our previous work.…”

“…For a HEVC ME, Lee and his colleagues proposed the GPU-based parallel ME algorithm for HEVC [33]. They partitioned a frame into two subframes for high pipelined execution in the GPU.…”

“…, where mv is the current motion vector and scv is the search center vector. The SCP is determined by the RSCP decision method introduced in [33]. Furthermore, they insisted that the MVD is more closely related to the search region than the motion vector since the search region is set around the SCP.…”

“…Nowadays, there have been many researches on implementing a parallel processing-based video encoder in order to achieve very high encoding performace [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35]. One of them is to use a Graphics Processing Unit (GPU) for ME [26][27][28][29][30][31][32][33][34][35]. Since various search patterns are not preferable for parallel environment such as GPU due to both their irregular data flow and data dependency [8,14], they have generally adopt full search algorithm which searches all the points within a search range (SR).…”

“…The rest of the paper is organized as follows: in Section 2 briefly introduces the previously presented GPU-based ME algorithm [33] and ASR decision algorithms for HEVC ME. Section 3 shows details about our approach.…”