Video processing using GPU-accelerator under desktop virtualization environment

The desktop virtualization environment could propose a solution for the high-definition video processing, which used multi-GPU collaboration and parallel computing. The multi-GPU parallel encoding computing is often implemented by multi-threads mode. Based on the analysis of the GPU multi-level storage structure, and data transmission between CPU and GPU, pinned memory (zero-copy memory) and shared memory approaches are used to shorten the time of encoded video data transmission between devices. In this paper the latest support low-latency remote display's GPU and H.264 compression standard are used for the desktop virtualization environment. The experimental results show that the usage of CPU and the transmission bandwidth has been significantly decreased, and the performance of virtual environments has been improved.