Hierarchical Static Scheduling of Dataflow Graphs onto Multiple Processors
José Luis Pino and Edward A. Lee
Proceedings of the IEEE International Conference on Acoustics, Speech, and Signa
l Processing, Detroit, MI
May 1995
ABSTRACT
In this paper we discuss a hierarchical scheduling framework to reduce the compl
exity of scheduling synchronous dataflow (SDF) graphs onto multiple processors.
The core of this framework is a clustering technique that reduces the number of
actors before expanding the SDF graph into an directed acyclic graph (DAG). The
internals of the clusters are then scheduled with uniprocessor SDF schedulers which can optimize for memory usage. The clustering is done in such a manner as to
leave ample parallelism exposed for the multiprocessor scheduler. We illustrate
this framework with a real-time example that has been constructed in Ptolemy.
