Optimizing HEVC CABAC Decoding with a Context Model Cache and Application-Specific Prefetching

Abstract

Context-based Adaptive Binary Arithmetic Coding is the entropy coding module in the most recent JCT-VC video coding standard HEVC/H.265. As in the predecessor H.264/AVC, CABAC is a well-known throughput bottleneck due to its strong data dependencies. Beside other optimizations, the replacement of the context model memory by a smaller cache has been proposed, resulting in an improved clock frequency. However, the effect of potential cache misses has not been properly evaluated. Our work fills this gap and performs an extensive evaluation of different cache configurations. Furthermore, it is demonstrated that application-specific context model prefetching can effectively reduce the miss rate and make it negligible. Best overall performance results were achieved with caches of two and four lines, where each cache line consists of four context models. Four cache lines allow a speed-up of 10% to 12% for all video configurations while two cache lines improve the throughput by 9% to 15% for high bitrate videos and by 1% to 4% for low bitrate videos.