Abstract
Performance is a key aspect of many embedded systems, embedded data processing systems in particular. System performance can typically only be measured in the later stages of system development. To avoid expensive re-work in the final stages of development, it is essential to have accurate performance estimations in the early stages. For this purpose, we present a model-based approach to performance engineering that is integrated with the well-known V-model for system development. Our approach emphasizes model accuracy and is demonstrated using five embedded data-processing cases from the digital printing domain. We show how lightweight models can be used in the early stages of system development to estimate the influence of design changes on system performance.
This work is partially supported by the ITEA2 project 11013 PROMES.
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Notes
- 1.
The phrase “predict the past, explore the future” originates from [16].
References
Amdahl, G.M.: Validity of the single processor approach to achieving large scale computing capabilities. In: AFIPS spring joint computer conference (1967)
Balarin, F., et al.: Hardware-Software Co-design of Embedded Systems: The POLIS Approach. Kluwer, Norwell (1997)
Balsamo, S., di Marco, A., Inverardi, P., Simeoni, M.: Model-based performance prediction in software development: a survey. IEEE Trans. Softw. Eng. 30(5), 295–310 (2004)
Beckers, J.M.J., Muller, G.J., Heemels, W.P.H., Bukkems, B.H.M.: Effective industrial modeling for high-tech systems: the example of happy flow. In: INCOSE International Symposium, vol. 17, issue 1 (2007)
Bohlin, T.P.: Practical Grey-box Process Identification: Theory and Applications. Springer, Berlin (2015)
Eclipse Foundation: Eclipse website (2015). http://www.eclipse.org/
Embedded Systems Innovation by TNO: Trace website (2015). http://trace.esi.nl
Fishman, G.S.: Discrete-Event Simulation: Modeling, Programming, and Analysis. Springer, New York (2001)
Forsberg, K., Mooz, H.: The relationship of system engineering to the project cycle. In: INCOSE International Symposium, vol. 1, issue 1 (1991)
Hendriks, M., et al.: A blueprint for system-level performance modeling of software-intensive embedded systems. Int. J. Softw. Tools Technol, Transfer (2014)
Hendriks, M. et al.: Analyzing execution traces - critical-path analysis and distance analysis. Submitted to STTT (2015)
Kruchten, P.B.: The \(4+1\) view model of architecture. IEEE Softw. 12(6), 42–50 (1995)
Montgomery, D.C., Peck, E.A., Vining, G.G.: Introduction to Linear Regression Analysis, 3rd edn. Wiley, New York (2001)
Muller, G.J.: CAFCR: a multi-view method for embedded systems architecting; balancing genericity and specificity. Ph.D. thesis, Delft University of Technology (2004)
Mussbacher, G., Amyot, D., Breu, R., Bruel, J.-M., Cheng, B.H.C., Collet, P., Combemale, B., France, R.B., Heldal, R., Hill, J., Kienzle, J., Schöttle, M., Steimann, F., Stikkolorum, D., Whittle, J.: The Relevance of Model-Driven Engineering Thirty Years from Now. In: Dingel, J., Schulte, W., Ramos, I., Abrah\ {a}o, S., Insfran, E. (eds.) MODELS 2014. LNCS, vol. 8767, pp. 183–200. Springer, Heidelberg (2014)
Parappurath, V.V., Voeten, J.P.M., Kotterink, K.C.: Calibration error bound estimation in performance modeling. In: Euromicro Conference on Digital System Design (2013)
PassMark Software: CPU Mark - Single Thread Performance (2015). https://www.cpubenchmark.net/singleThread.html
Pimentel, A.D., Thompson, M., Polstra, S., Erbas, C.: Calibration of abstract performance models for system-level design space exploration. J. Signal Process. Syst. 50(2), 99–114 (2008)
Smith, C.U., Williams, L.G.: Software performance engineering. In: Lavagno, L., Martin, G., Selic, B. (eds.) UML for Real: Design of Embedded Real-Time Systems, pp. 343–365. Springer, Heidelberg (2003)
Voeten, J. et al.: Predicting timing performance of advanced mechatronics control systems. In: IEEE 35th Annual Computer Software and Applications Conference Workshops (COMPSACW) (2011)
Westland, J.C.: The cost of errors in software development: evidence from industry. J. Syst. Softw. 62, 1–9 (2002)
Williams, L.G., Smith, C.U.: Making the business case for software performance engineering. In: 29th International Computer Measurement Group Conference. pp. 349–358. Computer Measurement Group (2003)
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Hendriks, M. et al. (2015). Performance Engineering for Industrial Embedded Data-Processing Systems. In: Abrahamsson, P., Corral, L., Oivo, M., Russo, B. (eds) Product-Focused Software Process Improvement. PROFES 2015. Lecture Notes in Computer Science(), vol 9459. Springer, Cham. https://doi.org/10.1007/978-3-319-26844-6_29
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