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Early execution time-estimation through automatically generated timing models

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Abstract

Traditional timing analysis, such as worst-case execution time analysis, is normally applied only in the late stages of embedded system software development, when the hardware is available and the code is compiled and linked. However, preliminary timing estimates are often needed in early stages of system development as an essential prerequisite for the configuration of the hardware setup and dimensioning of the system. During this phase the hardware is often not available, and the code might not be ready to link. This article describes an approach to predict the execution time of software through an early, source-level timing analysis. A timing model for source code is automatically derived from a given combination of hardware architecture and compiler. The model is identified from measured execution times for a set of synthetic training programs, compiled for the hardware platform in question. It can be used to estimate the execution time for code running on the platform: the estimation is then done directly from the source code, without compiling and running it. Our experiments show that, using this model, we can predict the execution times of the final, compiled code surprisingly well. For instance, we achieve an average deviation of 8 % for a set of benchmark programs for the ARM7 architecture.

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Acknowledgments

This work was partially supported by VINNOVA through the TIMMO-2-USE project, by VINNOVA and ARTEMIS through the CHESS project, by the KK-Foundation through the TOCSYC project, Deutscher Akademischer Austauschdienst, and from the European Commission through the Lifelong Learning ERASMUS-Programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein. Finally, we are very grateful for the friendly help on GEM5 by Benedikt Huber from the Vienna University of Technology, and his support with the C2ALF translator.

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Authors and Affiliations

  1. Department of Computer Science, University of Applied Sciences, Darmstadt, Germany

    Peter Altenbernd

  2. School of Innovation, Design, and Engineering, Mälardalen University, Västerås, Sweden

    Jan Gustafsson & Björn Lisper

  3. Department of Computer Science, Nuremberg Institute of Technology, Nuremberg, Germany

    Friedhelm Stappert

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  1. Peter Altenbernd
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  2. Jan Gustafsson
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  3. Björn Lisper
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  4. Friedhelm Stappert
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Correspondence to Peter Altenbernd.

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Altenbernd, P., Gustafsson, J., Lisper, B. et al. Early execution time-estimation through automatically generated timing models. Real-Time Syst 52, 731–760 (2016). https://doi.org/10.1007/s11241-016-9250-7

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  • DOI: https://doi.org/10.1007/s11241-016-9250-7

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