Multi-Threaded Syntax Element Partitioning for Parallel Entropy Decoding

Strong demand for high resolution video services leads to active studies on high speed video processing. Especially, widespread deployment of multi-core systems accelerates researches on high resolution video processing based on parallelization of multimedia software. Even if parallelization of other decoding steps on a multi-core platform may improve performance, entropy decoding often becomes a performance bottleneck since it should be processed sequentially. To resolve this concern, parallel entropy coding algorithms have been proposed. Syntax element partitioning is an algorithm for parallelization of Context Adaptive Binary Arithmetic Coding (CABAC). In this paper, we propose Multi-Threaded Syntax Element Partitioning (MT-SEP) for parallel entropy decoding. One major advantage of software parallel video decoding over hardware implementations will be that versatile video codecs can be implemented flexibly. We parallelized the KTA 2.7 decoder with the proposed technique on an Intel Quad-Core platform. We achieved up to 56% performance improvement using the proposed version of syntax element partitioning.This research was supported by the MKE(The Ministry of Knowledge Economy), Korea, under the ITRC(Information Technology Research Center) support program supervised by the NIPA(National IT Industry Promotion Agency) (NIPA-2011-C1090-1131-0009), Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education, Science and Technology(2010-0024164), Seoul R& BD Program(JP100031C093211)