Multiprocessor Scheduling of Synchronous Data Flow Graphs using Local Search Algorithms

Design space exploration (DSE) is the process of exploring design alternatives before implementing real-time multiprocessor systems. One part of DSE is scheduling of the applications the system is developed for and to evaluate the performance to ensure that the real-time requirements are satisfied. Many real-time systems today use multiprocessors and finding the optimal schedule for an application on a multiprocessor system is known to be an NP-hard problem. Such an optimization problem can be time-consuming which justifies the use of heuristics. This thesis presents an approach for scheduling applications onto multiprocessors using local search algorithms. The applications are represented by SDF-graphs and the assumed platform has homogeneous processors without constraints regarding communication delays, memory consumption or buffer sizes. The goal of this thesis project was to investigate if heuristic search algorithms could find sufficiently good solutions in a reasonable amount of time. Experimental results show that local search algorithms have potential of contributing to DSE by finding high-performance schedules with reduced search time compared to algorithms trying to find the optimal scheduling solution