Efficient Software Synthesis for Dynamic Single Appearance Scheduling of Synchronous Dataflow

Synchronous dataflow (SDF) is a widely-used model of computation for digital signal processing and multimedia applications. In this letter, we propose an automatic approach to synthesize efficient software from SDF models with improved runtime efficiency. Our synthesis technique is based on dynamic single-appearance scheduling (dynSAS), which generates software with minimized code size, the same as traditional single-appearance schedule (SAS), while requires much less buffer memory space. We enhance dynSAS systematically to reduce control flow overhead and increase memory utilization. Experiment results show that our approach can generate efficient software with enhanced runtime performance compared to related techniques.