A unified programming model for time- and data-driven embedded applications

Gabriela Breaban, Sander Stuijk, Kees Goossens

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Samenvatting

Modern embedded systems encompass a fast increasing range of applications, spanning from automotive to multimedia, and industrial automation. To tackle the increasing design complexity, the model-based design paradigm promotes the use of Models of Computation (MoCs) to capture the essential application properties. Existing MoCs are split between the event/time-triggered paradigm and the data-driven paradigm. However, time and data are two inter-related dimensions that are essential for defining the correct application behavior. In this paper we advocate a unified MoC that integrates the notions of time and data while accounting for imperfect clocks. We present the formal properties of our model and show how the Synchronous Data Flow (SDF) MoC can be used to analyze the time performance guarantees.

Originele taal-2Engels
Titel26th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2018
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's26-33
Aantal pagina's8
ISBN van elektronische versie9781538649756
DOI's
StatusGepubliceerd - 6 jun 2018
Evenement26th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP 2018) - Cambridge, Verenigd Koninkrijk
Duur: 21 mrt 201823 mrt 2018
Congresnummer: 26
http://www.pdp2018.org/
http://www.pdp2018.org/

Congres

Congres26th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP 2018)
Verkorte titelPDP 2018
LandVerenigd Koninkrijk
StadCambridge
Periode21/03/1823/03/18
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Citeer dit

Breaban, G., Stuijk, S., & Goossens, K. (2018). A unified programming model for time- and data-driven embedded applications. In 26th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2018 (blz. 26-33). Piscataway: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/PDP2018.2018.00013