Multi-level Parallelization of Advanced Video Coding on Hybrid CPU plus GPU Platforms

A dynamic model for parallel H.264/AVC video encoding on hybrid GPU+CPU systems is proposed. The entire inter-prediction loop of the encoder is parallelized on both the CPU and the GPU, and a computationally efficient model is proposed to dynamically distribute the computational load among these processing devices on hybrid platforms. The presented model includes both dependency aware task scheduling and load balancing algorithms. According to the obtained experimental results, the proposed dynamic load balancing model is able to push forward the computational capabilities of these hybrid parallel platforms, achieving a speedup of up to 2 when compared with other equivalent state-of-the-art solutions. With the presented implementation, it was possible to encode 25 frames per second for HD 1920x1080 resolution, even when exhaustive motion estimation is considered.