New multilevel parallelism management for multimedia processors

This paper presents a new parallelism manager for multimedia multiprocessors. An analysis of new multimedia applications shows that the available parallelism moves from the data-level to the control-level. New architectures are required to be able to extract this kind of dynamic parallelism. Our proposed parallelism management describes the parallelism with a topological description of the task dependence graph. It allows to describe various and complex parallelism patterns. This parallelism description is separated from the program code to allow the task manager to decode it in parallel with the task execution. The task manager is based on a queue bank that stores the task graph. Control commands are inserted in the task dependence graph to allow a dynamic modification of this graph, depending on the processed data. Simulations on classical multiprocessing benchmarks show that in case of simple parallelism, we have similar performances than classical systems. However, the performances on complex applications are improved up to 12%. Multimedia applications have also been simulated. The results show that our task manager can efficiently handle complex dynamic parallelism structures.