Parametrized dataflow scenarios

Mladen Skelin, Marc Geilen, F. Catthoor, Sverre Hendseth

Research output: Book/ReportReportAcademic

6 Citations (Scopus)
174 Downloads (Pure)


Although well-suited for capturing concurrency in streaming applications, purely dataflow-based models of computation are lacking in expressing intricate control requirements that many modern streaming applications have. Consequently, a number of modeling approaches combining dataflow and finite-state machines has been proposed. However, these FSM/dataflow hybrids struggle with capturing the ne-grained data-dependent dynamics of modern streaming applications.
In this article, we enrich the set of such FSM/dataflow hybrids with a novel formalism that uses parameterized dataflow as the concurrency model. We call the model FSM-based parameterized scenario-aware dataflow (PFSM-SADF). Through the use of parameterized dataflow, the formalism can capture the application ne-grained data-dependent dynamics while the enveloping FSM enables the capturing of the application control flow. We demonstrate the
application of our modeling framework to synchronous dataflow (SDF), for which we propose a worst-case performance analysis framework based on the Max-plus algebraic semantics of SDF and the theory of Max-plus automata. We show that using the novel hybrid one can give tighter bounds on worst-case performance metrics such as throughput and latency for streaming applications exposing fine-grained dynamic behavior embedded inside a control-flow structure then by using the existing hybrids. We evaluate our approach on a realistic case-study from the multimedia domain.
Original languageEnglish
Place of PublicationEindhoven
PublisherEindhoven University of Technology
Number of pages42
Publication statusPublished - 16 Nov 2015

Publication series

NameES Reports
PublisherEindhoven University of Technology
ISSN (Electronic)1574-9517


  • Synchronous dataflow
  • (max,+) algebra
  • parametrized dataflow
  • scenario-aware dataflow


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