Abstract
Software-Mapping, i.e. the mapping of software elements to hardware components, is especially in the context of embedded multi-core systems a rather complex task. Usually, it is not sufficient to allocate tasks to hardware, since further types of allocations, e.g. communications to data paths or data to memories, exist. Accordingly, these allocations have a crucial impact on the performance. Since it is required to fulfill several constraints, e.g. deadlines or task ordering, it is furthermore necessary to select those allocations that result in a valid, but also efficient mapping. Such efficiency is usually not achieved by executing the application as quick as possible but e.g. as reliable or energy saving as possible. This can be achieved by using mathematical methods, e.g. Integer Linear Programming (ILP). ILP allows describing the mapping problem in terms of equations, which will be optimized towards a specific goal.
This work describes an exemplary integration of an existing mathematical method for embedded multi-core software to hardware mapping into the AMALTHEA Tool Platform, including its evaluation as well as adaptation, in order to provide an automated software mapping functionality.
The work leading to these results has been founded by the Federal Ministry for Education and Research (BMBF) under Grant 01|S14029K within the ITEA3 EU-Project AMALTHEA4public.
Notes
- 1.
File format used to store linear programing or mixed integer programing problems.
- 2.
Least common multiple of all periods among the tasks.
- 3.
Time required for a single cycle.
References
AMALTHEA Tool Platform. http://www.amalthea-project.org/
Aleti, A., Buhnova, B., Grunske, L., Koziolek, A., Meedeniya, I.: Software architecture optimization methods: a systematic literature review. IEEE Trans. Softw. Eng. 39, 658–683 (2013)
Drozdowski, M.: Scheduling for Parallel Processing. Computer Communications and Networks. Springer, London (2009)
Grigoriev, A., Sviridenko, M., Uetz, M.: Machine scheduling with resource dependent processing times. Math. Program. 110, 209–228 (2007)
Cordes, D., Engel, M., Neugebauer, O., Marwedel, P.: Automatic extraction of pipeline parallelism for embedded heterogeneous multi-core platforms. In: 2013 International Conference on Compilers, Architecture and Synthesis for Embedded Systems (CASES), pp. 1–10 (2013)
Zhang, Y., Hu, X.S., Chen, D.Z.: Task scheduling and voltage selection for energy minimization. In: Proceedings of the 39th annual Design Automation Conference, pp. 183–188. ACM (2002)
oj! Algorithms Website. http://ojalgo.org/
AMALTHEA: D3.4 - Prototypical Implementation of Selected Concepts. https://itea3.org/project/amalthea.html
Sprunt, B., Sha, L., Lehoczky, J.: Aperiodic task scheduling for hard-real-time systems. Real-Time Syst. 1, 27–60 (1989)
Yang, H., Ha, S.: ILP based data parallel multi-task mapping/scheduling technique for MPSoC. In: International SoC Design Conference (ISOCC), pp. 134–137 (2008)
Ishihara, T., Yasuura, H.: Voltage scheduling problem for dynamically variable voltage processors. In: International Symposium on Low Power Electronics and Design, pp. 197–202. IEEE (1998)
Li, P., Guo, S.: Energy minimization on thread-level speculation in multicore systems. In: 2010 Ninth International Symposium on Parallel and Distributed Computing (ISPDC), pp. 125–132 (2010)
Frey, P.: A timing model for real-time control-systems and its application on simulation and monitoring of AUTOSAR systems. http://vts.uni-ulm.de/doc.asp?id=7505
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Krawczyk, L., Wolff, C., Fruhner, D. (2015). Automated Distribution of Software to Multi-core Hardware in Model Based Embedded Systems Development. In: Dregvaite, G., Damasevicius, R. (eds) Information and Software Technologies. ICIST 2015. Communications in Computer and Information Science, vol 538. Springer, Cham. https://doi.org/10.1007/978-3-319-24770-0_28
Download citation
DOI: https://doi.org/10.1007/978-3-319-24770-0_28
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-24769-4
Online ISBN: 978-3-319-24770-0
eBook Packages: Computer ScienceComputer Science (R0)