An overseer control methodology for data adaptable embedded systems

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The performance of software algorithms can be improved by performing those algorithms on specialized embedded hardware. However, complex algorithms that rely on input data at runtime for configuration have a combinatorial explosion of possible configurations, which has historically put hardware acceleration out of reach for applications wishing to serve large configuration spaces. Data adaptable embedded systems overcome this limitation by allowing for hardware reconfiguration during runtime, but the complexity of the specification of these systems is difficult to manage with traditional techniques. In this paper, a modeling approach is discussed in order to concurrently model two aspects of the final system: dependencies between algorithm tasks, and desired hardware configurations for each task. The contribution of the work is the model-based generation of hardware and software tasks, as well as a control scheme customized to each model that oversees the dynamic reconfiguration process.

Original languageEnglish (US)
Title of host publicationProceedings of the 6th International Workshop on Multi-Paradigm Modeling, MPM 2012
Pages25-30
Number of pages6
DOIs
StatePublished - Dec 1 2012
Event6th International Workshop on Multi-Paradigm Modeling, MPM 2012 - Innsbruck, Austria
Duration: Oct 1 2012Oct 1 2012

Publication series

NameProceedings of the 6th International Workshop on Multi-Paradigm Modeling, MPM 2012

Other

Other6th International Workshop on Multi-Paradigm Modeling, MPM 2012
CountryAustria
CityInnsbruck
Period10/1/1210/1/12

Keywords

  • Data adaptability
  • Domain specific modeling
  • Model-based design

ASJC Scopus subject areas

  • Modeling and Simulation

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  • Cite this

    Whitsitt, S., Sprinkle, J., & Lysecky, R. (2012). An overseer control methodology for data adaptable embedded systems. In Proceedings of the 6th International Workshop on Multi-Paradigm Modeling, MPM 2012 (pp. 25-30). (Proceedings of the 6th International Workshop on Multi-Paradigm Modeling, MPM 2012). https://doi.org/10.1145/2508443.2508448