Coarse Grain Parallelization of H.264 Video Decoder and Memory Bottleneck in Multi-Core Architectures
Fine grain methods for parallelization of the H.264 decoder have good latency performance and less memory usage. However, they could not reach the scalability of coarse grain approaches although assuming a well-designed entropy decoder which can feed the increasing number of parallel working cores. The authors would like to introduce a GOP (Group Of Pictures) level approach due to its high scalability, mentioning solution approaches for the well-known memory issues. Their design revokes the need to a scanner for GOP start-codes which was used in the earlier methods.