research-article

A framework to schedule parametric dataflow applications on many-core platforms

Authors:

Vagelis Bebelis,

Alain GiraultAuthors Info & Claims

ACM SIGPLAN Notices, Volume 49, Issue 5

Pages 125 - 134

https://doi.org/10.1145/2666357.2597819

Published: 12 June 2014 Publication History

Abstract

Dataflow models, such as SDF, have been effectively used to program streaming applications while ensuring their liveness and boundedness. Yet, industrials are struggling to design the next generation of high definition video applications using these models. Such applications demand new features such as parameters to express dynamic input/output rate and topology modifications. Their implementation on modern many-core platforms is a major challenge.

We tackle these problems by proposing a generic and flexible framework to schedule streaming applications designed in a parametric dataflow model of computation. We generate parallel as soon as possible (ASAP) schedules targeted to the new STHORM many-core platform of STMicroelectronics. Furthermore, these schedules can be customized using user-defined ordering and resource constraints.

The parametric dataflow graph is associated with generic or user-defined specific constraints aimed at minimizing timing, buffer sizes, power consumption, or other criteria. The scheduling algorithm executes with minimal overhead and can be adapted to different scheduling policies just by adding some constraints. The safety of both the dataflow graph and constraints can be checked statically and all schedules are guaranteed to be bounded and deadlock free. We illustrate the scheduling capabilities of our approach using a real world application: the VC-1 video decoder for high definition video streaming.

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Cited By

Bouakaz AFradet PGirault A(2017)A Survey of Parametric Dataflow Models of ComputationACM Transactions on Design Automation of Electronic Systems10.1145/299953922:2(1-25)Online publication date: 20-Jan-2017
https://dl.acm.org/doi/10.1145/2999539
Mohaqeqi MAbdullah JYi W(2016)Modeling and Analysis of Data Flow Graphs Using the Digraph Real-Time Task ModelProceedings of the 21st Ada-Europe International Conference on Reliable Software Technologies --- Ada-Europe 2016 - Volume 969510.1007/978-3-319-39083-3_2(15-29)Online publication date: 13-Jun-2016
https://dl.acm.org/doi/10.1007/978-3-319-39083-3_2
Fradet PGirault AKrishnaswamy RNicollin XShafiei A(2022)RDF: A Reconfigurable Dataflow Model of ComputationACM Transactions on Embedded Computing Systems10.1145/354497222:1(1-30)Online publication date: 29-Oct-2022
https://dl.acm.org/doi/10.1145/3544972
Show More Cited By

Index Terms

A framework to schedule parametric dataflow applications on many-core platforms
1. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language types
        Data flow languages
  2. Software organization and properties
    1. Contextual software domains
      1. Operating systems
        Process management
        Scheduling

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Information

Published In

cover image ACM SIGPLAN Notices

ACM SIGPLAN Notices Volume 49, Issue 5

LCTES '14

May 2014

162 pages

ISSN:0362-1340

EISSN:1558-1160

DOI:10.1145/2666357

Editors:
Mark W. Bailey
Hamilton College, Clinton, NY
,
Rajeev Balasubramonian
University of Utah
,
Al Davis
University of Utah
,
Sarita Adve
University of Illinois at Urbana-Champ

Issue’s Table of Contents

LCTES '14: Proceedings of the 2014 SIGPLAN/SIGBED conference on Languages, compilers and tools for embedded systems
June 2014
174 pages
ISBN:9781450328777
DOI:10.1145/2597809
General Chair:
Youtao Zhang
University of Pittsburgh, USA
,
Program Chair:
Prasad Kulkarni
University of Kansas, USA

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 June 2014

Published in SIGPLAN Volume 49, Issue 5

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Cited By

Bouakaz AFradet PGirault A(2017)A Survey of Parametric Dataflow Models of ComputationACM Transactions on Design Automation of Electronic Systems10.1145/299953922:2(1-25)Online publication date: 20-Jan-2017
https://dl.acm.org/doi/10.1145/2999539
Mohaqeqi MAbdullah JYi W(2016)Modeling and Analysis of Data Flow Graphs Using the Digraph Real-Time Task ModelProceedings of the 21st Ada-Europe International Conference on Reliable Software Technologies --- Ada-Europe 2016 - Volume 969510.1007/978-3-319-39083-3_2(15-29)Online publication date: 13-Jun-2016
https://dl.acm.org/doi/10.1007/978-3-319-39083-3_2
Fradet PGirault AKrishnaswamy RNicollin XShafiei A(2022)RDF: A Reconfigurable Dataflow Model of ComputationACM Transactions on Embedded Computing Systems10.1145/354497222:1(1-30)Online publication date: 29-Oct-2022
https://dl.acm.org/doi/10.1145/3544972
Fradet PGirault AKrishnaswamy RNicollin XShafiei A(2019)RDF: Reconfigurable Dataflow2019 Design, Automation & Test in Europe Conference & Exhibition (DATE)10.23919/DATE.2019.8714987(1709-1714)Online publication date: Mar-2019
https://doi.org/10.23919/DATE.2019.8714987
Fradet PGirault AJamshidian LNicollin XShafiei A(2018)Lossy Channels in a Dataflow Model of ComputationPrinciples of Modeling10.1007/978-3-319-95246-8_15(254-266)Online publication date: 20-Jul-2018
https://doi.org/10.1007/978-3-319-95246-8_15
Skelin MGeilen MCatthoor FHendseth S(2017)Parameterized Dataflow ScenariosIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2016.259722336:4(669-682)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1109/TCAD.2016.2597223
Skelin MGeilen MCatthoor FHendseth S(2017)Worst-case performance analysis of SDF-based parameterized dataflowMicroprocessors & Microsystems10.1016/j.micpro.2016.12.00452:C(439-460)Online publication date: 1-Jul-2017
https://dl.acm.org/doi/10.1016/j.micpro.2016.12.004
Do XLouise SCohen AFanucci LTeich J(2016)Transaction parameterized dataflowProceedings of the 2016 Conference on Design, Automation & Test in Europe10.5555/2971808.2972029(960-965)Online publication date: 14-Mar-2016
https://dl.acm.org/doi/10.5555/2971808.2972029
Mohaqeqi MAbdullah JYi W(2016)Modeling and Analysis of Data Flow Graphs Using the Digraph Real-Time Task ModelProceedings of the 21st Ada-Europe International Conference on Reliable Software Technologies --- Ada-Europe 2016 - Volume 969510.1007/978-3-319-39083-3_2(15-29)Online publication date: 13-Jun-2016
https://dl.acm.org/doi/10.1007/978-3-319-39083-3_2
Skelin MGeilen MCatthoor FHendseth SGirault AGuan N(2015)Parametrized dataflow scenariosProceedings of the 12th International Conference on Embedded Software10.5555/2830865.2830876(95-104)Online publication date: 4-Oct-2015
https://dl.acm.org/doi/10.5555/2830865.2830876
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