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Towards Application Energy Measurement and Modelling Tool Support

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Parallel Computing Technologies (PaCT 2015)

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Abstract

We present a prototype toolkit for researchers to accurately measure and model their application’s power and energy usage. We provide an analysis of a matrix multiplication application using our api libhclenergy.

This research is supported by the Structured PhD in Simulation Science which is funded by the Programme for Research in Third Level Institutions (PRTLI) Cycle 5 and co-funded by the European Regional Development Fund. This work is partially supported by EU under the COST Program Action IC1305: Network for Sustainable Ultrascale Computing (NESUS).

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References

  1. Adaptive Computing, I: Torque resource manager (2015). http://www.adaptivecomputing.com/products/open-source/torque/

  2. H.P.C., et al.: Acpi v4.0a (2010). http://www.acpi.info/DOWNLOADS/ACPIspec40a.pdf

  3. AMD: Bios and kernel developerś guide(bkdg) for amd family 15h models 00h–0fh processors (2013). http://amd-dev.wpengine.netdna-cdn.com/wordpress/media/2012/10/42301_15h_Mod_00h0Fh_BKDG1.pdf

  4. Balouek, D., et al.: Adding virtualization capabilities to the Grid’5000 testbed. In: Ivanov, Ivan I., van Sinderen, Marten, Leymann, Frank, Shan, Tony (eds.) CLOSER 2012. CCIS, vol. 367, pp. 3–20. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  5. Barrachina, S., Barreda, M., Catalán, S., Dolz, M.F., Fabregat, G., Mayo, R., Quintana-Ortí, E.S.: An integrated framework for power-performance analysis of parallel scientific workloads. In: ENERGY 2013, The Third International Conference on Smart Grids, Green Communications and IT Energy-Aware Technologies, pp. 114–119 (2013)

    Google Scholar 

  6. Basmadjian, R., Ali, N., Niedermeier, F., de Meer, H., Giuliani, G.: A methodology to predict the power consumption of servers in data centres. In: Proceedings of the 2nd International Conference on Energy-Efficient Computing and Networking, pp. 1–10. ACM (2011)

    Google Scholar 

  7. Bedard, D., Lim, M.Y., Fowler, R., Porterfield, A.: Powermon: fine-grained and integrated power monitoring for commodity computer systems. In: Proceedings of the IEEE SoutheastCon 2010 (SoutheastCon), pp. 479–484, March 2010

    Google Scholar 

  8. Cabrera, A., Almeida, F., Arteaga, J., Blanco, V.: Measuring energy consumption using EML (energy measurement library). Comput. Sci. Res. Dev. 30(2), 135–143 (2015). http://dx.doi.org/10.1007/s00450-014-0269-5

    Article  Google Scholar 

  9. Clarke, D., Zhong, Z., Rychkov, V., Lastovetsky, A.: Fupermod: a software tool for the optimization of data-parallel applications on heterogeneous platforms. J. Supercomput. 69(1), 61–69 (2014)

    Article  Google Scholar 

  10. David, H., Gorbatov, E., Hanebutte, U.R., Khanna, R., Le, C.: Rapl: memory power estimation and capping. In: 2010 ACM/IEEE International Symposium on Low-Power Electronics and Design (ISLPED), pp. 189–194, August 2010

    Google Scholar 

  11. Dunkels, A., Osterlind, F., Tsiftes, N., He, Z.: Software-based on-line energy estimation for sensor nodes. In: Proceedings of the 4th Workshop on Embedded Networked Sensors, pp. 28–32. ACM (2007)

    Google Scholar 

  12. Economou, D., Rivoire, S., Kozyrakis, C., Ranganathan, P.: Full-system power analysis and modeling for server environments. In: Proceedings of Workshop on Modeling, Benchmarking, and Simulation, pp. 70–77 (2006)

    Google Scholar 

  13. Fan, X., Weber, W.D., Barroso, L.A.: Power provisioning for a warehouse-sized computer. ACM SIGARCH Comput. Archit. News 35(2), 13–23 (2007)

    Article  Google Scholar 

  14. Galassi, M., et al.: Gnu Scientific Library Reference Manual, 3rd edn. Network Theory Ltd., Bristol (2009). http://www.gnu.org/software/gsl/manual/gsl-ref.ps.gz

    Google Scholar 

  15. Ge, R., Feng, X., Song, S., Chang, H.C., Li, D., Cameron, K.: Powerpack: energy profiling and analysis of high-performance systems and applications. IEEE Trans. Parallel Distrib. Syst. 21(5), 658–671 (2010)

    Article  Google Scholar 

  16. Hackenberg, D., Ilsche, T., Schone, R., Molka, D., Schmidt, M., Nagel, W.: Power measurement techniques on standard compute nodes: A quantitative comparison. In: 2013 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), pp. 194–204, April 2013

    Google Scholar 

  17. Heath, T., Diniz, B., Horizonte, B., Carrera, E.V., Bianchini, R.: Energy conservation in heterogeneous server clusters, pp. 186–195 (2005)

    Google Scholar 

  18. Hsu, C.H., Poole, S.: Power measurement for high performance computing: state of the art. In: 2011 International Green Computing Conference and Workshops (IGCC), pp. 1–6, July 2011

    Google Scholar 

  19. Intel Corporation: Intel manycore platform software stack (2015). https://software.intel.com/en-us/articles/intel-manycore-platform-software-stack-mpss

  20. Jung, G., Hiltunen, M.A., Joshi, K.R., Schlichting, R.D., Pu, C.: Mistral: dynamically managing power, performance, and adaptation cost in cloud infrastructures. In: 2010 IEEE 30th International Conference on Distributed Computing Systems (ICDCS), pp. 62–73. IEEE (2010)

    Google Scholar 

  21. Kansal, A., Zhao, F.: Fine-grained energy profiling for power-aware application design. ACM SIGMETRICS Perform. Eval. Rev. 36(2), 26 (2008). http://portal.acm.org/citation.cfm?doid=1453175.1453180

    Article  Google Scholar 

  22. Kim, K.H., Beloglazov, A., Buyya, R.: Power-aware provisioning of virtual machines for real-time cloud services. Concurrency Comput. Pract. Exp. 23(13), 1491–1505 (2011)

    Article  Google Scholar 

  23. Lai, Z., Lam, K.T., Wang, C.L., Su, J.: A power modelling approach for many-core architectures. In: 2014 10th International Conference on Semantics, Knowledge and Grids (SKG), pp. 128–132, August 2014

    Google Scholar 

  24. Mucci, P.J., Browne, S., Deane, C., Ho, G.: Papi: a portable interface to hardware performance counters. In: Proceedings of the Department of Defense HPCMP Users Group Conference, pp. 7–10 (1999)

    Google Scholar 

  25. Nvidia Corporation: Nvidia management library (2015). https://developer.nvidia.com/nvidia-management-library-nvml

  26. Sinha, A., Chandrakasan, A.P.: Jouletrack: a Web based tool for software energy profiling. In: Proceedings of the 38th Annual Design Automation Conference, pp. 220–225. ACM (2001)

    Google Scholar 

  27. Song, S., Su, C., Rountree, B., Cameron, K.W.: A simplified and accurate model of power-performance efficiency on emergent gpu architectures (2013)

    Google Scholar 

  28. Treibig, J., Hager, G., Wellein, G.: Likwid: a lightweight performance-oriented tool suite for x86 multicore environments. In: 2010 39th International Conference on Parallel Processing Workshops (ICPPW), pp. 207–216. IEEE (2010)

    Google Scholar 

  29. Zhao, Y.J., Govindan, R., Estrin, D.: Residual energy scan for monitoring sensor networks. In: 2002 IEEE Wireless Communications and Networking Conference, WCNC 2002, vol. 1, pp. 356–362. IEEE (2002)

    Google Scholar 

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Acknowledgment

Experiments presented in this paper were carried out using the Grid’5000 experimental testbed, being developed under the INRIA ALADDIN development action with support from CNRS, RENATER and several Universities as well as other funding bodies (see https://www.grid5000.fr).

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Correspondence to Kenneth O’Brien .

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O’Brien, K., Lastovetsky, A., Pietri, I., Sakellariou, R. (2015). Towards Application Energy Measurement and Modelling Tool Support. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 2015. Lecture Notes in Computer Science(), vol 9251. Springer, Cham. https://doi.org/10.1007/978-3-319-21909-7_10

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  • DOI: https://doi.org/10.1007/978-3-319-21909-7_10

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