Parameterized Modeling and Scheduling of Dataflow Graphs
Bishnupriya Bhattacharya, Shuvra S. Bhattacharyya · University Libraries (University of Maryland) · 1999
Dataflow has proven to be an attractive computational model for programming DSP applications. A restricted version of dataflow, called Synchronous Dataflow (SDF) is particularly well-suited for modeling a large class of signal processing applications, as it offers strong formal properties and compile-time predictability. Efficient techniques have been developed for generating software implementations from an SDF graph that are geared towards various optimization objectives. However, the SDF model does not allow data-dependent flow of control or dynamically varying communication patterns between functional modules. This results in limited expressive power. Consequently, a variety of extensions to SDF have been developed, where the objective is to provide increased expressive power, while maintaining a significant part of the compile-time predictability of SDF, e.g., boolean dataflow, cyclo-dynamic dataflow, and bounded dynamic dataflow. In this report, we propose a parameterized dataflow framework that can be applied as a meta-modeling technique to an arbitrary dataflow model that satisfies