Transaction Parameterized Dataflow: A model for context-dependent streaming applications

Static dataflow programming models are well suited to the development of embedded many-core systems. However, complex signal and media processing applications often display dynamic behavior that do not fit the classical static restrictions. We propose Transaction Parameterized Dataflow (TPDF), a new...

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Bibliographic Details
Main Authors: Xuan Khanh Do, Louise, Stephane, Cohen, Albert
Format: Conference Proceeding
Language:English
Subjects:
Automation
Digital media
Dynamical systems
Dynamics
Electronics
Integers
Programming
State of the art
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Summary:Static dataflow programming models are well suited to the development of embedded many-core systems. However, complex signal and media processing applications often display dynamic behavior that do not fit the classical static restrictions. We propose Transaction Parameterized Dataflow (TPDF), a new model of computation combining integer parameters - to express dynamic rates - and a new type of control actor - to allow topology changes and time constraints enforcement. We present static analyses for liveness and bounded memory usage. We also introduce a static scheduling heuristic to map TPDF to massively parallel embedded platforms. We validate the model and associated methods using a cognitive radio application, demonstrating significant buffer size and performance improvements compared to state of the art models including Cyclo-Static Dataflow (CSDF).
ISSN:1558-1101