Critical-Path-First based allocation of real-time streaming applications on 2D mesh-type multi-cores

Designing cost-efficient multi-core real-time systems requires efficient techniques to allocate applications to cores while satisfying their timing constraints. However, existing approaches typically allocate using a First-Fit algorithm, which does not consider the execution time and potential parallelism of paths in the applications, resulting in over-dimensioned systems. This work addresses this problem by proposing a new heuristic algorithm, Critical-Path-First, for the allocation of real-time streaming applications modeled as dataflow graphs on 2D mesh multi-core processors. The main criteria of the algorithm is to allocate paths that have the highest impact on the execution time of the application first. It is also able to exploit parallelism in the application by allocating parallel paths on different cores. Experimental evaluation shows that the proposed heuristic improves the resource utilization by allocating up to 7% more applications and it minimizes the average end-to-end worst-case response time of the allocated applications by up to 31%.