Dynamic dataflow graphs
bookPart
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, enableinvoke dataflow, dynamic polyhedral process networks, scenario aware dataflow, and a stream-based function actor model.
Topics
TNO Identifier
954484
ISBN
9781461468592 ; 9781461468585
Publisher
Springer New York
Source title
Handbook of Signal Processing Systems: Second Edition
Pages
905-944
Files
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