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A Bin-Based Bitstream Partitioning Approach for Parallel CABAC Decoding in Next Generation Video Coding

Context-based Adaptive Binary Arithmetic Coding (CABAC) is one of the main throughput bottlenecks in video decoding due to its sequential nature and the lack of data-level parallelism. High-level parallelization techniques can be used in most state-of-the-art video codecs, but they usually require a full replication of the decoding hardware and decrease the coding efficiency. We present a Bin-based Bitstream Partitioning (B3P) scheme to enable additional thread-level parallelism in CABAC decoding. Binary symbols are distributed over eight bitstream partitions that can be decoded simultaneously. The implementation and evaluation are based on the High Efficiency Video Coding Standard (HEVC/H.265). Significant speedups up to 8.5x are achieved for CABAC decoding while only 9.2% extra cell area is required and the bitstream overhead remains below 1% for high bitrates. The B3P hardware decoder can process up to 3.94 Gbins/s. Compared to state-of-the-art related work, we achieve higher throughput with slightly lower hardware cost and similar coding efficiency.