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Experimental Evaluation of Probabilistic Execution-Time Modeling and Analysis Methods for SDF Applications on MPSoCs

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 11733)


Early validation of software running on multi-processor platforms is fundamental to guarantee that real-time constraints will be fully met. In the domain of timing analysis probabilistic simulation techniques tackle the problem of scalability. However, creation of probabilistic SystemC models remains a difficult task and is not well supported for multi-processors systems. In this paper we present a modeling workflow that will then be used for an experimental evaluation of probabilistic simulation techniques. For the modeling process a measurement-based approach is proposed to favor the creation of trustful models. The evaluated probabilistic simulation techniques demonstrate good potential to deliver fast yet accurate estimations for multi-processor systems.


  • Statistical Model Checking
  • Probabilistic SystemC model
  • Multi processor

This work has been partially sponsored by the DAAD (PETA-MC project under grant agreement 57445418) with funds from the Federal Ministry of Education and Research (BMBF). This work has also been partially sponsored by CampusFrance (PETA-MC project under grant agreement 42521PK) with funds from the French ministry of Europe and Foreign Affairs (MEAE) and by the French ministry for Higher Education, Research and Innovation (MESRI).

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Stemmer, R., Vu, HD., Grüttner, K., Le Nours, S., Nebel, W., Pillement, S. (2019). Experimental Evaluation of Probabilistic Execution-Time Modeling and Analysis Methods for SDF Applications on MPSoCs. In: Pnevmatikatos, D., Pelcat, M., Jung, M. (eds) Embedded Computer Systems: Architectures, Modeling, and Simulation. SAMOS 2019. Lecture Notes in Computer Science(), vol 11733. Springer, Cham.

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  • Print ISBN: 978-3-030-27561-7

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