Abstract
Optimization of energy consumption is a key issue for future HPC. Evaluation of energy consumption requires a fine-grained power measurement. Additional useful information is obtained when performing these measurements at component level. In this paper we describe a setup which allows to perform fine-grained power measurements up to a 1 ms resolution at component level on IBM POWER (IBM and POWER are trademarks of IBM in USA and/or other countries.) machines. We further developed a plug-in for VampirTrace that allows us to correlate these power measurements with application performance characteristics, e.g. obtained by hardware performance counters. This environment enables us to generate both power and performance profiles. Such profiles provide valuable input to develop future strategies for improving workload-driven energy usage per performance. We show in comparison with power profiles of coarser granularity that these fine-grained measurements are necessary to capture the dynamics of power switching.
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References
Brochard L, Panda R, Vemuganti S (2010) Optimizing performance and energy of hpc applications on power7. Comput Sci Res Dev 25(3–4):135–140. http://www.springerlink.com/index/10.1007/s00450-010-0123-3
Floyd M, Allen-Ware M, Rajamani K, Brock B, Lefurgy C, Drake A, Pesantez L, Gloekler T, Tierno J, Bose P, Buyuktosunoglu A (2011) Introducing the adaptive energy management features of the power7 chip. IEEE MICRO 31(2):60–75. doi:10.1109/MM.2011.29
Ge R, Feng X, Song S, Chang HC, Li D, Cameron K (2010) PowerPack: energy profiling and analysis of high-performance systems and applications. IEEE Trans Parallel Distrib Syst 21(5):658–671. doi:10.1109/TPDS.2009.76
Geimer M, Wolf F, Wylie BJN, Ábrahám E, Becker D, Mohr B (2010) The scalasca performance toolset architecture. Concurr Comput, Pract Exp 22(6):702–719. doi:10.1002/cpe.1556
Hennecke M, Frings W, Homberg W, Zitz A, Knobloch M, Böttiger H (2012) Measuring power consumption on ibm blue gene/p. Comput Sci Res Dev. doi:10.1007/s00450-011-0192-y
Kamil S, Shalf J, Strohmaier E (2008) Power efficiency in high performance computing. In: IEEE international symposium on parallel and distributed processing, pp 1–8
Knüpfer A, Brunst H, Doleschal J, Jurenz M, Lieber M, Mickler H, Müller MS, Nagel WE (2008) The vampir performance analysis tool-set. In: Tools for high performance computing. Proceedings of the 2nd international workshop on parallel tools. Springer, Berlin, pp 139–155
Knüpfer A, Rössel C, an Mey D, Biersdorff S, Diethelm K, Eschweiler D, Geimer M, Gerndt M, Lorenz D, Malony AD, Nagel WE, Oleynik Y, Philippen P, Saviankou P, Schmidl D, Shende SS, Tschüter R, Wagner M, Wesarg B, Wolf F (2012) Score-P—A joint performance measurement run-time infrastructure for periscope, scalasca, TAU, and vampir. In: Proc. of 5th parallel tools, Workshop, 2011, Dresden, Germany. Springer, Berlin, pp 79–91
Lefurgy C, Wang X, Ware M (2007) Server-level power control. In: Proceedings of the IEEE international conference on autonomic computing (ICAC)
Lively C, Wu X, Taylor V, Moore S, Chang HC, Cameron K (2011) Energy and performance characteristics of different parallel implementations of scientific applications on multicore systems. Int J High Perform Comput Appl 25(3):342–350. doi:10.1177/1094342011414749
Minartz T, Molka D, Knobloch M, Krempel S, Ludwig T, Nagel WE, Mohr B, Falter H (2012) Eeclust: energy-efficient cluster computing. In: Bischof C, Hegering HG, Nagel WE, Wittum G (eds) Competence in high performance computing 2010. Springer, Berlin, pp 111–124. doi:10.1007/978-3-642-24025-6_10
Schöne R, Tschüter R, Ilsche T, Hackenberg D (2011) The vampirtrace plugin counter interface: introduction and examples. In: Proceedings of the 2010 conference on parallel processing, Euro-Par 2010. Springer, Berlin, pp 501–511
Sutmann G, Westphal L, Bolten M (2010) Particle based simulations of complex systems with mp2c: hydrodynamics and electrostatics. AIP Conf Proc 1281(1):1768–1772. doi:10.1063/1.3498216
Terpstra D, Jagode H, You H, Dongarra J (2010) Collecting performance data with papi-c. In: Müller MS, Resch MM, Schulz A, Nagel WE (eds) Tools for high performance computing 2009. Springer, Berlin, pp 157–173. doi:10.1007/978-3-642-11261-4_11
Winkel M, Speck R, Hübner H, Arnold L, Krause R, Gibbon P (2012) A massively parallel, multi-disciplinary Barnes–hut tree code for extreme-scale n-body simulations. Comput Phys Commun 183(4):880–889. doi:10.1016/j.cpc.2011.12.013
Acknowledgements
These results were obtained using the IBM Automated Measurement of Systems for Temperature and Energy Reporting software. We gratefully acknowledge useful discussions with and support by Charles Lefurgy from IBM Research in Austin, TX. This work was funded by the state of North Rhine-Westfalia (“Anschubfinanzierung zum Aufbau des Exascale Innovation Center (EIC)”)
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Knobloch, M., Foszczynski, M., Homberg, W. et al. Mapping fine-grained power measurements to HPC application runtime characteristics on IBM POWER7. Comput Sci Res Dev 29, 211–219 (2014). https://doi.org/10.1007/s00450-013-0245-5
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DOI: https://doi.org/10.1007/s00450-013-0245-5