Abstract
A comprehensive monitoring infrastructure is vital for upcoming heterogeneous, adaptive many-core systems. In order to enable required self-organising capabilities, a monitoring infrastructure has to provide self-awareness. Unfortunately, traditional approaches to monitoring, like hardware performance counters, lack required flexibility and are not suitable for self-organising systems.
We therefore present a flexible, hierarchical monitoring infrastructure for heterogeneous adaptive computing systems being able to provide a detailed and pristine view of the system state. On lower level, an associative counter array performs sustained monitoring of individual components of the system and provides this information to high level instances. These instances analyse and evaluate this information, and finally realise self-awareness. For this purpose, we employ a flexible, rule-based approach for runtime evaluation and classification of the system state. Further system instances, such as the task scheduler, may use the classified state as well as gathered information to realise self-x features, such as self-optimisation.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
HyperTransport™I/O Link Specification Revision 3.10 (2008). http://hypertransport.org/docucontrol/HTC20051222-00046-0028.pdf
Becker, J., Brändle, K., Brinkschulte, U., Henkel, J., Karl, W., Köster, T., Wenz, M., Wörn, H.: Digital on-demand computing organism for real-time systems. In: Karl, W., Becker, J., Großpietsch, K.-E., Hochberger, C., Maehle, E. (eds.) Workshop Proceedings of the 19th International Conference on Architecture of Computing Systems (ARCS’06). GI-Edition Lecture Notes in Informatics (LNI), vol. P81, pp. 230–245 (2006)
Buchty, R., Karl, W.: Design aspects of self-organizing heterogeneous multi-core architectures. In: Information Technology 5/2008 (Issue on Computer Architecture Challenges), pp. 293–299. Oldenbourg Wissenschaftsverlag, October 2008
Buchty, R., Kicherer, M., Kramer, D., Karl, W.: An embrace-and-extend approach to managing the complexity of future heterogeneous systems. In: SAMOS ’09: Proceedings of the 9th International Workshop on Embedded Computer Systems: Architectures, Modeling, and Simulation, pp. 227–236. Springer, Berlin (2009)
Buchty, R., Kramer, D., Karl, W.: An organic computing approach to sustain-ed real-time monitoring. In: Proceedings of WCC2008/BICC (IFIP Vol. 268), pp. 151–162. Springer, Berlin (2008). ISBN 978-0-387-09654-4
Kluge, F., Mische, J., Uhrig, S., Ungerer, T.: Building adaptive embedded systems by monitoring and dynamic loading of application module. In: Workshop on Adaptive and Reconfigurable Embedded Systems, St. Louis, MO, USA, April 2008
Fröning, H., Nüessle, M., Slogsnat, D., Litz, H., Brüning, U.: The HTX-board: a rapid prototyping station. In: 3rd Annual FPGAWorld Conference (2006)
Guthaus, M.R., Ringenberg, J.S., Ernst, D., Austin, T.M., Mudge, T., Brown, R.B.: Mibench: A free, commercially representative embedded benchmark suite. In: Proceedings of the Workload Characterization, 2001. WWC-4. 2001 IEEE International Workshop, pp. 3–14. IEEE Comput. Soc., Washington, DC (2001)
Merkel, A., Bellosa, F.: Task activity vectors: a new metric for temperature-aware scheduling. In: Eurosys ’08: Proceedings of the 3rd ACM SIGOPS/EuroSys European Conference on Computer Systems 2008, pp. 1–12. ACM, New York (2008)
Mucci, P.J., Browne, S., Deane, C., Ho, G.: PAPI: A portable interface to hardware performance counters. In: Proceedings of the Department of Depense HPCMP User Group Conference (1999)
Müller-Schloer, C.: Organic computing: on the feasibility of controlled emergence. In: CODES+ISSS ’04: Proceedings of the 2nd IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis, pp. 2–5. ACM, New York (2004)
Nowak, F., Kicherer, M., Buchty, R., Karl, W.: Delivering guidance information in heterogeneous systems. In: Beigl, M., Cyzorla-Almeida, F.J. (eds.) ARCS 2010 Workshop Proceedings, pp. 95–101. VDE, February 2010
Sprunt, B.: Pentium 4 performance-monitoring features. In: IEEE Micro, pp. 72–82 (2002)
Sprunt, B.: The basics of performance-monitoring hardware. In: IEEE Micro, pp. 64–71 (2002)
Trumler, W., Pietzowski, A., Satzger, B., Ungerer, T.: Adaptive self-optimization in distributed dynamic environments. In: International Conference on Self-Adaptive and Self-Organizing Systems, 320–323 (2007)
Zeppenfeld, J., Herkersdorf, A.: Autonomic workload management for multi-core processor systems. In: International Conference on Architecture of Computing Systems, ARCS, Hannover, Germany, pp. 49–60 (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer Basel AG
About this chapter
Cite this chapter
Kramer, D., Buchty, R., Karl, W. (2011). Monitoring and Self-awareness for Heterogeneous, Adaptive Computing Systems. In: Müller-Schloer, C., Schmeck, H., Ungerer, T. (eds) Organic Computing — A Paradigm Shift for Complex Systems. Autonomic Systems, vol 1. Springer, Basel. https://doi.org/10.1007/978-3-0348-0130-0_10
Download citation
DOI: https://doi.org/10.1007/978-3-0348-0130-0_10
Publisher Name: Springer, Basel
Print ISBN: 978-3-0348-0129-4
Online ISBN: 978-3-0348-0130-0
eBook Packages: Computer ScienceComputer Science (R0)