Static and Quasi-static Compositions of Stream Processing Applications from Dynamic Dataflow Programs

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Publication Details

List of Authors: Johan Ersfolk, Ghislain Roquier, Wictor Lund, Marco Mattavelli, Johan Lilius
Publication year: 2013
Journal: IEEE International Conference on Acoustics Speech and Signal Processing
Publisher: IEEE
Book title: 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing Proceedings
Journal acronym: INT CONF ACOUST SPEE
Start page: 2620
End page: 2624
Number of pages: 5
ISBN: 978-1-4799-0357-3
ISSN: 1520-6149


Dynamic dataflow models for their expressiveness properties have shown to represent more adequate and attractive solutions for describing state of the art signal processing applications. However, they are known to present potential run-time penalties when implementations are obtained by mapping and scheduling a dataflow network partition on a processing unit. In general terms, a completely static scheduling at compile-time of dynamic dataflow programs remains an unsolved problem. Several approaches for the composition of actors are promising approach that can significantly reduce the potential penalty of run-time scheduling thus increasing the overall performance of the system. This paper presents static and quasi-static composition techniques that results in a reduction of the portion of dynamic dataflow networks, by applying appropriate transformations to network partitions that after a specific analysis demonstrate to possess a predictable behaviour. Some experiments based on a video processing application ported on several system-on-chips show the achievable speedup corresponding to the reduction of the number of run-time scheduling decisions.


Actor Composition, Dataflow Process Network, Static and Quasi-Static Scheduling

Last updated on 2020-24-02 at 05:37