Abstract
Large-scale distributed systems (e.g., datacenters, HPC systems, clouds, large-scale networks, etc.) consume and will consume enormous amounts of energy. Therefore, accurately monitoring the power and energy consumption of these systems is increasingly more unavoidable. The main novelty of this contribution is the analysis and evaluation of different external and internal power monitoring devices tested using two different computing systems, a server and a desktop machine. Furthermore, we also provide experimental results for a variety of benchmarks which exercise intensively the main components (CPU, Memory, HDDs, and NICs) of the target platforms to validate the accuracy of the equipment in terms of power dispersion and energy consumption. This paper highlights that external wattmeters do not offer the same measures as internal wattmeters. Thanks to the high sampling rate and to the different measured lines, the internal wattmeters allow an improved visualization of some power fluctuations. However, a high sampling rate is not always necessary to understand the evolution of the power consumption during the execution of a benchmark.
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
Notes
- 1.
- 2.
Advanced Configuration and Power Interface. Revision 5.0. http://www.acpi.info/
- 3.
iperf: http://iperf.fr
- 4.
- 5.
- 6.
References
Hsu, C.H., Feng, W.C., Archuleta, J.S.: Towards efficient supercomputing: a quest for the right metric. In: Proceedings of the High Performance Power-Aware Computing, Workshop (2005)
Dongarra, J., et al.: The international ExaScale software project roadmap. Int. J. High Perform. Comput. Appl. 25(1), 3–60 (2011)
Feng, W., Feng, X., Ge, R.: Green supercomputing comes of age. IT Prof. 10(1), 17–23 (2008)
Laros III, J.H., Pedretti, K.T., Kelly, S.M., Shu, W., Vaughan, C.T.: Energy based performance tuning for large scale high performance computing systems. In: Proceedings of the Symposium on High Performance Computing, HPC ’12, San Diego, CA, USA, pp. 6:1–6:10 (2012)
Alonso, P., Dolz, M.F., Igual, F.D., Mayo, R., Quintana-Ortí, E.S.: DVFS-control techniques for dense linear algebra operations on multi-core processors. Comput. Sci. - R&D 27(4), 289–298 (2012)
Alonso, P., Dolz, M.F., Mayo, R., Quintana-Ortí, E.S.: Energy-efficient execution of dense linear algebra algorithms on multi-core processors. In: Cluster Computing, May 2012
Feng, W., Cameron, K.: The green500 list: encouraging sustainable supercomputing. Computer 40(12), 50–55 (2007)
Ltaief, H., Luszczek, P., Dongarra, J.: Profiling high performance dense linear algebra algorithms on multicore architectures for power and energy efficiency. Comput. Sci. 27(4), 277–287 (2012)
Subramaniam, B., Feng, W.: The green index: a metric for evaluating system-wide energy efficiency in HPC systems. In: 8th IEEE Workshop on High-Performance, Power-Aware Computing, Shanghai, China, May 2012
Ge, R., Feng, X., Song, S., Chang, H.C., Li, D., Cameron, K.W.: Powerpack: energy profiling and analysis of high-performance systems and applications. IEEE Trans. Parallel Distrib. Syst. 21(5), 658–671 (2010)
Subramaniam, B., Feng, W.: Statistical power and performance modeling for optimizing the energy efficiency of scientific computing. In: Proceedings of the 2010 IEEE/ACM International Conference on Green Computing and Communications, GREENCOM, Washington, DC, USA, pp. 139–146. IEEE Computer Society (2010)
Alonso, P., Badia, R.M., Labarta, J., Barreda, M., Dolz, M.F., Mayo, R., Quintana-Ortí, E.S., Reyes, R.: Tools for power-energy modelling and analysis of parallel scientific applications. In: 41st International Conference on Parallel Processing - ICPP, pp. 420–429 (2012)
Acknowledgments
This research was supported by the European COST Actions IC804 (“Energy efficiency in large scale distributed systems") and IC805 (“Complex HPC systems"). Authors from Universitat Jaume I were also supported by project CICYT TIN2011-23283 and FEDER.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Diouri, M.E.M. et al. (2013). Solving Some Mysteries in Power Monitoring of Servers: Take Care of Your Wattmeters!. In: Pierson, JM., Da Costa, G., Dittmann, L. (eds) Energy Efficiency in Large Scale Distributed Systems. EE-LSDS 2013. Lecture Notes in Computer Science(), vol 8046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40517-4_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-40517-4_1
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40516-7
Online ISBN: 978-3-642-40517-4
eBook Packages: Computer ScienceComputer Science (R0)