Work-in-progress: code-size-aware mapping for synchronous dataflow graphs on multicore systems

Synchronous Dataflow Graphs (SDFGs) are widely used to model streaming applications (e.g. digital signal processing applications), which are commonly executed by embedded systems. The usage of on-chip resources is always strictly constrained in embedded systems. As the cost of instruction memory is a significant part of on-chip resource costs, code size reduction is an effective way to control the overall costs of on-chip resources. In this work, a codesize- aware mapping heuristic is proposed to decrease the code size for SDFGs on multicore systems. The mapping heuristic is jointly used with a self-timed scheduling heuristic to decrease the code size of the original schedule. In preliminary experiments, the proposed heuristic achieves significant code size reduction for all the tested SDFGs without affecting throughput.