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Communication-aware scheduling algorithms for synchronous dataflow graphs on multicore systems

Synchronous dataflow graphs are widely used to model digital signal processing and multimedia applications. Self-timed execution is an efficient methodology for the analysis and scheduling of synchronous dataflow graphs. In this paper, we propose a communication-aware self-timed execution approach to solve the problem of scheduling synchronous dataflow graphs on multicore systems with communication delays. Based on this communication-aware self-timed execution approach, four communication-aware scheduling algorithms are proposed using different allocation rules. The proposed algorithms are experimentally evaluated in terms of throughput and runtime using realistic applications.