Dataflow process networks provide a versatile model of computation for specifying signal processingapplications in a platform independent fashion. This attractive feature of dataflow has lately been realized in dataflow programming tools that allow synthesizing the same application specification as both fixed hardware circuits and as software for programmable processors. However, in practice, the specification granularity of the dataflow program remains an arbitrary choice of the designer. Dataflow specifications of the same application with equivalent I/O behaviour can range from a single dataflow actor to a very fine grained network composed of elementary processing operations.
A very fine grained dataflow specification might result into a high performance implementation when synthesized as hardware, but might perform poorly when executed on a programmable processor. This article presents actor merging as one solution for this performance portability problem of dataflow programs. In contrast to previous work around actor merging, this article presents a methodology that can merge also dynamic dataflow actors. To support these claims, results of experiments on several processingplatforms and application examples ranging from telecommunications to video compression are reported.