Cycle-static dataflow

Abstract

We present cycle-static dataflow (CSDF), which is a new model for the specification and implementation of digital signal processing algorithms. The CSDF paradigm is an extension of synchronous dataflow that still allows for static scheduling and, thus, a very efficient implementation of an application. In comparison with synchronous dataflow, it is more versatile because it also supports algorithms with a cyclically changing, but predefined, behavior. Our examples show that this capability results in a higher degree of parallelism and, hence, a higher throughput, shorter delays, and less buffer memory. Moreover, they indicate that CSDF is essential for modelling prescheduled components, like application-specific integrated circuits. Besides introducing the CSDF paradigm, we also derive necessary and sufficient conditions for the schedulability of a CSDF graph. We present and compare two methods for checking the liveness of a graph. The first one checks the liveness of loops, and the second one constructs a single-processor schedule for one iteration of the graph. Once the schedulability is tested, a makespan optimal schedule on a multiprocessor can be constructed. We also introduce the heuristic scheduling method of our graphical rapid prototyping environment (GRAPE)