MVSE: A Multi-core Video decoder System level analytics Engine

Multi-core platform has become a trend in hand-held embedded systems, such as smartphone and tablet. To improve the video decoding performance by using the multiple cores, one of parallel algorithms should be adopted. However, different parallel algorithm should be selected for different video standard on different platform. Therefore, an engine to estimate performance on a target platform from existing single-thread video decoder is very helpful. This paper proposes a Multi-core Video decoder System level analytics Engine (MVSE) to estimate the performance on a target multi-core platform. In the MVSE, a general video decoder runs according to profiling data and macroblock information by three major parallel algorithms. The profiling data and macroblock information are obtained from existing single-thread video decoder so that the MVSE can support different video standard. The MVSE runs on target platform to consider the effect of memory access contention and cache intercommunication, which are traditionally difficult to estimate. Our experimental result shows the MVSE estimation is accuracy enough. The estimation results from MVSE shows the best speedup ratio is 1.7 times in a dual-core platform and 2.9 times in a quad-core platform for H.264 720p decoding. In addition, MVSE is also helpful for hardware and software co-design in heterogeneous computing. The experimental results show the best performance is improved by VLD hardware, and the speedup ratio is 2.3 times in a dual-core platform and 3.9 times in a quad-core platform.