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Compositionality in scenario-aware dataflow: a rendezvous perspective

Published:19 June 2018Publication History
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Abstract

Finite-state machine-based scenario-aware dataflow (FSM-SADF) is a dynamic dataflow model of computation that combines streaming data and finite-state control. For the most part, it preserves the determinism of its underlying synchronous dataflow (SDF) concurrency model and only when necessary introduces the non-deterministic variation in terms of scenarios that are represented by SDF graphs. This puts FSM-SADF in a sweet spot in the trade-off space between expressiveness and analyzability.

However, FSM-SADF supports no notion of compositionality, which hampers its usability in modeling and consequent analysis of large systems.

In this work we propose a compositional semantics for FSM-SADF that overcomes this problem.

We base the semantics of the composition on standard composition of processes with rendezvous communication in the style of CCS or CSP at the control level and the parallel, serial and feedback composition of SDF graphs at the dataflow level.

We evaluate the approach on a case study from the multimedia domain.

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    • Published in

      cover image ACM SIGPLAN Notices
      ACM SIGPLAN Notices  Volume 53, Issue 6
      LCTES '18
      June 2018
      112 pages
      ISSN:0362-1340
      EISSN:1558-1160
      DOI:10.1145/3299710
      Issue’s Table of Contents
      • cover image ACM Conferences
        LCTES 2018: Proceedings of the 19th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems
        June 2018
        112 pages
        ISBN:9781450358033
        DOI:10.1145/3211332

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      Publication History

      • Published: 19 June 2018

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