Static Optimal Scheduling for Synchronous Data Flow Graphs with Model Checking

Synchronous data flow graphs (SDFGs) are widely used to model digital signal processing and streaming media applications. In this paper, we present exact methods for static optimal scheduling and mapping of SDFGs on a heterogenous multiprocessor platform. The optimization criteria we consider are throughput and energy consumption, taking into account the combination of various constraints such as auto-concurrency and buffer sizes. We present a concise and flexible (priced) timed automata semantics of system models, which include an SDFG and a multiprocessor platform, and formulate the optimization goals as temporal logic formulas. The optimization and scheduling problems are then transformed to model checking problems, which are solved by UPPAAL (CORA). Thanks to the exhaustive exploration nature of model checking and the facility of the tools, we obtain two pareto-optimal schedules, one with an optimal throughput and a best energy consumption and another with an optimal energy consumption and a best throughput. The approach is applied to two real applications with different parameters. The case studies show that our approach can deal with moderate models within reasonable execution time and reveal the impacts of different constraints on optimization goals.