MAPPING SCALABLE VIDEO CODING DECODER ON MULTI-CORE STREAM PROCESSORS

Scalable Video Coding (SVC) is an advanced video compression technique that can support temporal, spatial, and quality scalability to terminals with different network conditions. SVC adopts layered coding techniques to improve coding efficiency for spatial and quality scalability. Upsampling and inter-layer prediction are two important mechanisms to remove redundant information between different layers. However, upsampling occupying around 75% memory bandwidth of SVC decoder results in serious performance degradation, especially for applications with high resolutions. Moreover, inter-layer prediction with complex scheduling leads to difficulties when mapping the SVC decoder in parallel. In this paper, we propose a method to parallelize the SVC decoder on a multi-core stream processor platform in both efficiency and flexibility. We focus on mapping issues of spatial scalability supporting with various resolutions of decoded frames. The experiment result proves the proposed design for SVC decoder reduces 95% memory bandwidth of the upsampling module in JSVM, performed on a single general-purpose processor.