Dynamic Dataflow Graphs - Signal Processing Systems - page 887

Dynamic Dataflow Graphs

Shuvra S. Bhattacharyya, Ed F. Deprettere, and Bart D. Theelen

Abstract Much of the work to date on dataflow models for signal processing
system design has focused on decidable dataflow models that are best suited for
one-dimensional signal processing. This chapter reviews more general dataflow
modeling techniques that are targeted to applications that include multidimensional
signal processing and dynamic dataflow behavior. As dataflow techniques are
applied to signal processing systems that are more complex, and demand increasing
degrees of agility and flexibility, these classes of more general dataflow models are
of correspondingly increasing interest. We first provide a motivation for dynamic
dataflow models of computation, and review a number of specific methods that
have emerged in this class of models. Our coverage of dynamic dataflow models
in this chapter includes Boolean dataflow, CAL, parameterized dataflow, enable-
invoke dataflow, dynamic polyhedral process networks, scenario aware dataflow,
and a stream-based function actor model.

1 Motivation for Dynamic DSP-Oriented Dataflow Models

The decidable dataflow models covered in [ 31 ] are useful for their predictability,
strong formal properties, and amenability to powerful optimization techniques.
However, for many signal processing applications, it is not possible to represent

S.S. Bhattacharyya ( )
University of Maryland, College Park, MD, USA
e-mail: [e-mail]
E.F. Deprettere
Leiden University, Leiden, The Netherlands
e-mail: [e-mail]
B.D. Theelen
Embedded Systems Innovation by TNO, Eindhoven, The Netherlands
e-mail: [e-mail]