A Comparison of Synchronous and Cyclo-Static Dataflow
Thomas M. Parks, José Luis Pino and Edward A. Lee
Proceedings of the Asilomar Conference on Signals, Systems, and Computers
Pacific Grove, CA, October 29-November 1, 1995
ABSTRACT
We compare synchronous dataflow (SDF) and cyclo-static dataflow
(CSDF), which are each special cases of a model of computation we call
dataflow process networks. In SDF, actors have static firing rules:
they consume and produce a fixed number of data tokens in each
firing. This model is well suited to multirate signal processing
applications and lends itself to efficient, static scheduling,
avoiding the run-time scheduling overhead incurred by general
implementations of process networks. In CSDF, which is a
generalization of SDF, actors have cyclicly changing firing rules. In
some situations, the added generality of CSDF can unnecessarily
complicate scheduling. We show how higher-order functions can be used
to transform a CSDF graph into a SDF graph, simplifying the scheduling
problem. In other situations, CSDF has a genuine advantage over SDF:
sim-pler precedence constraints. We show how this makes it possible to
eliminate unnecessary computations and expose additional
parallelism. We use digital sample rate conversion as an example to
illustrate these advantages of CSDF.