GPU Based High Definition Parallel Video Codec Optimization in Mobile Device
Baichuan Su, Bo Hao Cheng, Junliang Chen · IEEE Transactions on Mobile Computing · 2022
With the explosive growth of various intelligent device and the rapid development of wireless network communication technology, most people prefer to use video applications on smart devices. However, the main challenges when using video codec technology on mobile devices are: 1) The explosive growth of multimedia applications has caused the allocation of computing resources to become an important issue; 2) high power consumption and limited battery power; 3) high cpu utilization causes the system to be unresponsive. In this paper, aGPU basedHigh DefinitionParallelVideoCodec (GHPVC) is proposed, which is a low energy consumption and high efficient video codec on mobile devices. First, Frame Data Management model and Prediction Model Selector model are proposed in order to get higher data transmission efficiency and parallel execution efficiency. Second, a GPU based Parallel ME module is proposed because the ME module is the most power-consuming and computationally intensive module in video codec. The GHPVC is proposed on the basis of conforming to the H.264 standard. Moreover and experimentally evaluated for different GPU devices on different mobile devices. Experimental results show that compared with the existing H.264 scheme, the proposed GHPVC not only has significant improvement in codec performance, but also effectively reduces energy consumption and CPU utilization.