Abstract
Many techniques have previously been proposed for using low-level CPU Performance Monitoring Counters in power estimation models. In this paper, we present some common myths of these techniques, and their potential impact. Such myths include: (1) sampling rate can be ignored; (2) thermal effects are neutral; and (3) memory events correlate well with power. We aim to raise the awareness of these interesting issues, which existing power modeling techniques usually do not address. Our discussions provide some guidance to avoid these myths and their effects through detailed specification of software and hardware configurations.
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Notes
- 1.
Institute for Information Industry, http://web.iii.org.tw/, who we thank for providing this measurement equipment.
References
Watts up? operators manual. https://www.wattsupmeters.com/secure/downloads/manual_rev_9_corded0812.pdf
Anandtech, Overclocking CPU/GPU/Memory Stability Testing Guidelines. http://forums.anandtech.com/showthread.php?p=34255681
Overclockers, Reconciling CPU Temperature Measures. http://www.overclockers.com/reconciling-cpu-temperature-measures/
Ubuntu Manuals, CPUburn. http://manpages.ubuntu.com/manpages/precise/man1/cpuburn.1.html
O.A.R. Board, OpenMP Application Program Interface Version 3.0, May 2008
AMD. BIOS and Kernel Developer’s Guide (BKDG) For AMD Family 10h Processors (2009)
IPMItool. http://ipmitool.sourceforge.net/
Singh, K., Bhadauria, M., McKee, S.A.: Real time power estimation and thread scheduling via performance counters. SIGARCH Comput. Architect. News 37(2), 46–55 (2008)
Rotem, E., Naveh, A., Rajwan, D., Ananthakrishnan, A., Weissmann, E.: Power Management Architecture of the 2nd Generation Intel Core microarchitecture, formerly codenamed Sandy Bridge. In: Hot Chips: A Symposium on High Performance Chips, August 2011
Wang, S., Chen, H., Shi, W.: SPAN: a software power analyzer for multicore computer systems. Sustain. Comput. Inf. Syst. 1(1), 23–34 (2011)
Alonso, P., Badia, R.M., Labarta, J., Barreda, M., Dolz, M.F., Mayo, R., Quintana-Orti, E.S., Reyes, R.: Tools for power and energy analysis of parallel scientific applications. In: Proceedings of International Conference on Parallel Processing (ICPP), September 2012
Bertran, R., Gonzlez, M., Martorell, X., Navarro, N., Ayguade, E.: Decomposable and responsive power models for multicore processors using performance counters. In: Proceedings of the 24th ACM International Conference on Supercomputing, ICS 2010, Tsukuba, Ibaraki, Japan, pp. 147–158. ACM (2010)
Chen, X., Xu, C., Dick R., Mao, Z.: Performance and power modeling in a multi-programmed multi-core environment. In: Proceedings of the 47th Design Automation Conference, pp. 813–818. ACM (2010)
Da Costa, G., Hlavacs, H.: Methodology of measurement for energy consumption of applications. In: 2010 11th IEEE/ACM International Conference on Grid Computing (GRID). IEEE (2010)
Kansal, A., Zhao, F., Liu, J., Kothari, N., Bhattacharya, A.A.: Virtual machine power metering and provisioning. In: Proceedings of the 1st ACM Symposium on Cloud, Computing, pp. 39–50 (2010)
Dhiman, G., Mihic, K., Rosing, T.: A system for online power prediction in virtualized environments using Gaussian mixture models. In: Proceedings of the 47th ACM IEEE Design Automation Conference, pp. 807–812. ACM (2010)
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This work was partially supported by the COST (European Cooperation in Science and Technology) framework, under Action IC0804.
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Mair, J., Huang, Z., Eyers, D., Zhang, H. (2013). Myths in PMC-Based Power Estimation. 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_3
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DOI: https://doi.org/10.1007/978-3-642-40517-4_3
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