Parallelizing MPEG video encoding using multiprocessors

Many computer applications are currently using digital video. Recent advances in digital imaging and faster networking infrastructure made this technology very popular, not only for entertainment, but also in health and education applications. However, high quality video requires more storage space and communication bandwidth than traditional data. To deal with this problem, most of the digital video encoding techniques use a compression scheme. The MPEG committee has defined widely used standards for digital video encoding providing high quality images and high compression rates. However, real-time MPEG encoding also demands high computational power, usually far beyond traditional sequential computers can provide. Fortunately, the algorithms compliant to the MPEG standard can be parallelized. In this work, we propose a novel and simple shared-memory parallel algorithm for MPEG-1 video encoding based on the parallel execution of different coarse grained tasks (read pictures, write coded frames, I, P, and B frames coding). Two synchronization strategies are implemented and experimental results show that encoding rates of 43 frames per second are achieved, which is almost 50% better than the real-time encoding standard rate (30 frames per second)