Abstract
The deployment of automotive software on a multicore processor includes the task of mapping executables to cores. Given the number of possible solutions, integrators have to solve a complex problem. Considering multiple, often conflicting goals like minimizing task response times and memory consumption, complexity further increased with the advent of multicore processors. We present a model-based approach for deriving design rules supporting integrators with statically mapping tasks to a multicore ECU. First, an evolutionary algorithm is used to sample the design space. For each sample, a model-based analysis is performed, resulting in the required fitness values according to the system metric objectives. Finally, subsets of the sample population are used to derive deployment guidelines by evaluating similarities between highly ranked solutions. This reduces the number of solutions to be considered by the integrators by orders of magnitude. In a case-study, we demonstrate the developed approach on an artificial automotive engine management system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
AUTOSAR - AUTomotive Open System ARchitecture, http://www.autosar.org
AMALTHEA - Model Based Open Source Development Environment for Automotive Multi Core Systems, http://www.amalthea-project.org
BTF Specification V2.1.3, Eclipse Auto IWG, http://wiki.eclipse.org/Auto_IWG#Documents
Timing-Architects, TA Tool Suite Version 14.1.0. TA Academic & Research License Program, http://www.timing-architects.com
Leung, J.Y.-T., Whitehead, J.: On the Complexity of Fixed-Priority Scheduling of Periodic Real-Time Tasks. In: Performance Evaluation, vol. (2), pp. 237–250 (1982)
Rajkumar, R., Sha, L., Lehoczky, J.P.: Real-Time Synchronization Protocols for Multiprocessors. In: RTSS, vol. 88, pp. 259–269 (1988)
Coffman, E.G., Garey, M.R., Johnson, D.S.: Approximation algorithms for bin packing: A survey. In: Approximation Algorithms for NP-Hard Problems, pp. 46–93 (1996)
Mehiaoui, A., Tucci-Piergiovanni, S., Babau, J., Lemarchand, L.: Optimizing the Deployment of Distributed Real-Time Embedded Applications. In: 18th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA). IEEE (2012)
Kienberger, J., Minnerup, P., Kuntz, S., Bauer, B.: Analysis and Validation of AUTOSAR Models. In: MODELSWARD (2014)
Claraz, D., Kuntz, S., Margull, U., Niemetz, M., Wirrer, G.: Deterministic Execution Sequence in Component Based Multi-Contributor Powertrain Control Systems. In: Proceedings of ERTS, Toulouse (2012)
Deb, K.: Multi-objective optimization. In: Search Methodologies, vol. 10 (2005)
Scheidenmann, K.D., Knapp, M., Stellwag, C.: Load Balancing in AUTOSAR-Multicore-Systemen. In: Elektroniknet, 3/2010, pp. 22–25 (2010)
Buttazzo, G.: Hard real-time computing systems: predictable scheduling algorithms and applications (2005)
Burns, A.: A survey of hard real-time scheduling algorithms and schedulability analysis techniques for multiprocessor systems. In: Techreport YCS-2009-443, University of York, Department of Computer Science (2009)
Scheickl, O., Rudorfer, M.: Automotive Real Rime Development Using a Timing-augmented AUTOSAR Specification. In: Proceedings of Embedded Real Time Software and Systems Conference, ERTS (2008)
Raab, P., Mottok, J., Meier, H.: OSEK-RTOS für Jedermann (Teil 1). In: Embedded Software Engineering Report, p. 14 (September 2009)
König, F., Boers, D., Slomka, F., Margull, U., Niemetz, M., Wirrer, G.: Application specific performance indicators for quantitative evaluation of the timing behavior for embedded real-time systems. In: Proceedings of the Conference on Design, Automation and Test in Europe (2009)
Chakraborty, S., Künzli, S., Thiele, L.: A general framework for analysing system properties in platform-based embedded system designs. In: Proceedings of the 6th Design, Automation and Test in Europe (DATE) Conference, pp. 190–195 (2003)
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 182–197 (April 2002)
Konak, A., Coit, D.W., Smith, A.E.: Multi-objective optimization using genetic algorithms: A tutorial. Reliability Engineering & System Safety 91(9), 992–1007 (2006)
Gries, M.: Methods for evaluating and covering the design space during early design development. Integration, the VLSI Journal 38(2), 131–183 (2004)
Monot, A., Navet, N.: Multicore scheduling in automotive ECUs. In: Proceedings of Embedded Real Time Software and Systems Conference, ERTS (2010)
Deubzer, M., Mottok, J., Margull, U., Niemetz, M., Wirrer, G.: Efficient Scheduling of Reliable Automotive Multi-core Systems with PD2 by Weakening PFAIR Tasksystem Requirements. In: Proceedings of the Automotive Safety & Security (2010)
Sailer, A., Schmidhuber, S., Deubzer, M., Alfranseder, M., Mucha, M., Mottok, J.: Optimizing the Task Allocation Step for Multi-Core Processors within AUTOSAR. In: Proceedings of the IEEE International Conference on Applied Electronics (2013)
Helm, C., Deubzer, M., Mottok, J.: Multicore Memory Architectures in Real-Time Systems. In: Proceedings of the Applied Research Conference (2013)
Carpenter, J., Funk, S., Holman, P., Srinivasan, A., Anderson, J., Baruah, S.: A categorization of real-time multiprocessor scheduling problems and algorithms. In: Handbook on Scheduling Algorithms, Methods, and Models (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Schmidhuber, S., Deubzer, M., Mader, R., Niemetz, M., Mottok, J. (2014). Towards the Derivation of Guidelines for the Deployment of Real-Time Tasks on a Multicore Processor. In: Ortmeier, F., Rauzy, A. (eds) Model-Based Safety and Assessment. IMBSA 2014. Lecture Notes in Computer Science, vol 8822. Springer, Cham. https://doi.org/10.1007/978-3-319-12214-4_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-12214-4_12
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12213-7
Online ISBN: 978-3-319-12214-4
eBook Packages: Computer ScienceComputer Science (R0)