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Dataflow Programs Analysis and Optimization Using Model Predictive Control Techniques

Two Examples of Bounded Buffer Scheduling: Deadlock Avoidance and Deadlock Recovery Strategies

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Abstract

The analysis of the trace graphs generated by dataflow program executions has been shown to be an effective tool for exploring and optimizing the design space of application programs on manycore/multicore platforms. In this work a new approach aiming at finding bounded buffer size configurations for implementations generated by dataflow programs is presented. The introduced method is based on an original transformation procedure which converts the execution trace graph into an event driven linear system made up by a Petri Net. A control theoretic approach based on Model Predictive Control methodologies is then applied to the obtained Petri Net system in order to effectively explore the dataflow program design space and find nearly optimal buffer dimensioning solutions leading to a deadlock free program execution. Two real challenging design case examples, namely a JPEG and a MPEG HEVC decoder, are introduced to show the effectiveness of the introduced approach.

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Authors and Affiliations

  1. Dipartimento di Automatica e Informatica, Politecnico di Torino, Turin, Italy

    M. Canale

  2. EPFL SCI-STI-MM, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    S. Casale-Brunet, E. Bezati & M. Mattavelli

  3. Department of Computer Science, Lund University, Lund, Sweden

    J. Janneck

Authors
  1. M. Canale
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  2. S. Casale-Brunet
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  3. E. Bezati
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  4. M. Mattavelli
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  5. J. Janneck
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Corresponding author

Correspondence to S. Casale-Brunet.

Additional information

This work is supported by the Fonds National Suisse pour la Recherche Scientifique, under grant 200021.129960 and grant 200021.138214, and by the strategic research area ELLIIT.

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Canale, M., Casale-Brunet, S., Bezati, E. et al. Dataflow Programs Analysis and Optimization Using Model Predictive Control Techniques. J Sign Process Syst 84, 371–381 (2016). https://doi.org/10.1007/s11265-015-1083-4

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  • DOI: https://doi.org/10.1007/s11265-015-1083-4

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