Modeling Image Processing Systems with Homogeneous Parameterized Dataflow Graphs

Abstract

We describe a new dataflow model called homogeneous parameterized dataflow (HPDF). This form of dynamic dataflow graph takes advantage of the fact that in a large number of image processing applications, data production and consumption rates, though dynamic, are equal across graph edges for any particular iteration, which leads to a homogeneous rate of actor execution, even though data production and consumption values are dynamic and vary across graph edges. We discuss existing dataflow models and formulate in detail the HPDF model. We develop examples of applications that are described naturally in terms of HPDF semantics and present experimental results that demonstrate the efficacy of the HPDF approach.