Abstract
As we move towards exa-scale computing, energy is becoming increasingly important, even in the high performance computing arena. However, the simple equation, Energy = Power \(\times \) Time, suggests that optimizing for speed already optimizes for energy, under the assumption that Power is constant. When power is not constant, a strategy that achieves energy savings at the cost of slower execution is Dynamic Voltage and Frequency Scaling (DVFS). However, DVFS is currently applicable only to the processor, and the entire system has many other sources of power dissipation. We show that there is little to gain in compilers by trying to trade off speed for energy using DVFS. It is best to produce code that runs full-throttle, completing as quickly as possible, an approach called “race to sleep.” Our result is based on analyses of a high-level energy model that characterizes energy consumption, related to survey of power consumption trends of recent processors for both desktop and server, as well as Cray supercomputers.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Derivations are not shown, as they are similar (but slightly more complicated) to the derivation from Eq. 3.
References
80plus power supplies. www.plugloadsolutions.com/80PlusPowerSupplies.aspx
Anandtech. www.anandtech.com
Cray products. www.cray.com/Products/Products.aspx
Specpower, published at www.spec.org as of 6 May 2012. SPEC and the benchmark name SPECpower_ssj2008 are registered trademarks of the Standard Performance Evaluation Corporation. For more information about SPECpower_ssj2008. www.spec.org/power_ssj2008/
Intel\(^{\textregistered }\) Turbo Boost Technology in Intel\(^{\textregistered }\) Core™ Microarchitecture (Nehalem) based processors. White paper, November 2008
Bergman, K., Borkar, S., Campbell, D., Carlson, W., Dally, W., Denneau, M., Franzon, P., Harrod, W., Hill, K., Hiller, J., et al.: Exascale computing study: technology challenges in achieving exascale systems. Technical report, Defense Advanced Research Projects Agency Information Processing Techniques Office (DARPA IPTO) (2008)
Bircher, W., John, L.: Complete system power estimation: a trickle-down approach based on performance events. In: Proceedings of the IEEE International Symposium on Performance Analysis of Systems & Software, pp. 158–168 (2007)
Chandrakasan, A., Sheng, S., Brodersen, R.: Low-power CMOS digital design. IEEE J. Solid-State Circ. 27(4), 473–484 (1992)
Chen, G., Malkowski, K., Kandemir, M., Raghavan, P.: Reducing power with performance constraints for parallel sparse applications. In: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium, p. 8 (2005)
Cho, S., Melhem, R.: Corollaries to Amdahl’s law for energy. IEEE Comput. Archit. Lett. 7(1), 25–28 (2008)
Cho, S., Melhem, R.: On the interplay of parallelization, program performance, and energy consumption. IEEE Trans. Parallel Distrib. Syst. 21(3), 342–353 (2010)
Chun, B., Iannaccone, G., Iannaccone, G., Katz, R., Lee, G., Niccolini, L.: An energy case for hybrid datacenters. ACM SIGOPS Oper. Syst. Rev. 44(1), 76–80 (2010)
David, H., Fallin, C., Gorbatov, E., Hanebutte, U., Mutlu, O.: Memory power management via dynamic voltage/frequency scaling. Memory 300, 400 (2011)
Dawson-Haggerty, S., Krioukov, A., Culler, D.: Power optimization - a reality check, Technical Report UCB/EECS-2009-140. Technical report, EECS Department, University of California, Berkeley (2009)
Fan, X., Weber, W., Barroso, L.: Power provisioning for a warehouse-sized computer. ACM SIGARCH Comput. Archit. News 35, 13–23 (2007)
Freeh, V., Kappiah, N., Lowenthal, D., Bletsch, T.: Just-in-time dynamic voltage scaling: exploiting inter-node slack to save energy in MPI programs. J. Parallel Distrib. Comput. 68(9), 1175–1185 (2008)
Ge, R., Feng, X., Song, S., Chang, H., 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)
Heath, T., Pinheiro, E., Hom, J., Kremer, U., Bianchini, R.: Application transformations for energy and performance-aware device management. In: Proceedings of the 2002 International Conference on Parallel Architectures and Compilation Techniques, pp. 121–130 (2002)
Hsu, C., Feng, W.: A power-aware run-time system for high-performance computing. In: Proceedings of the 2005 ACM/IEEE Conference on Supercomputing, p. 1 (2005)
Hsu, C., Kremer, U.: The design, implementation, and evaluation of a compiler algorithm for CPU energy reduction. In: Proceedings of the ACM SIGPLAN 2003 Conference on Programming Language Design and Implementation, p. 48 (2003)
Kadayif, I., Kandemir, M., Chen, G., Vijaykrishnan, N., Irwin, M., Sivasubramaniam, A.: Compiler-directed high-level energy estimation and optimization. ACM Trans. Embed. Comput. Syst. (TECS) 4(4), 850 (2005)
Kim, E., Yum, K., Link, G., Vijaykrishnan, N., Kandemir, M., Irwin, M., Yousif, M., Das, C.: Energy optimization techniques in cluster interconnects. In: Proceedings of the 2003 International Symposium on Low Power Electronics and Design, pp. 459–464 (2003)
Kim, N., Austin, T., Blaauw, D., Mudge, T., Flautner, K., Hu, J., Irwin, M., Kandemir, M., Narayanan, V.: Leakage current: Moore’s law meets static power. Computer 36(12), 75 (2003)
Koomey, J.G., Belady, C., Patterson, M., Santos, A., Lange, K.D.: Assessing trends over time in performance, costs, and energy use for servers. Technical report, Lawrence Berkeley National Laboratory, Stanford University, Microsoft Corpotation, Intel Corporation, Hewlett-Packard Corporation (2009)
Le Sueur, E., Heiser, G.: Dynamic voltage and frequency scaling: the laws of diminishing returns. In: Proceedings of the 2010 International Conference on Power Aware Computing and Systems, pp. 1–8 (2010)
Li, F., Chen, G., Kandemir, M.: Compiler-directed voltage scaling on communication links for reducing power consumption. In: Proceedings of the 2005 IEEE/ACM International Conference on Computer-Aided Design, p. 460 (2005)
Mahesri, A., Vardhan, V.: Power consumption breakdown on a modern laptop. In: Falsafi, B., VijayKumar, T.N. (eds.) PACS 2004. LNCS, vol. 3471, pp. 165–180. Springer, Heidelberg (2005)
Meisner, D., Gold, B.T., Wenisch, T.F.: Powernap: eliminating server idle power. In: Proceedings of the 14th International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 205–216 (2009)
Seng, J.S., Tullsen, D.M.: The effect of compiler optimizations on pentium 4 power consumption. In: Proceedings of the 7th Workshop on Interaction Between Compilers and Computer Architectures, pp. 51–56 (2003)
Sinha, A., Chandrakasan, A.: Jouletrack-a web based tool for software energy profiling. In: Proceedings of the 38th Design Automation Conference, pp. 220–225 (2001)
Subramaniam, B., Feng, W.: Understanding power measurement implications in the green500 list. In: Green Computing and Communications, 2010 IEEE/ACM International Conference on & International Conference on Cyber, Physical and Social Computing, pp. 245–251 (2010)
Tiwari, V., Singh, D., Rajgopal, S., Mehta, G., Patel, R., Baez, F.: Reducing power in high-performance microprocessors. In: Proceedings of the 35th Design Automation Conference, p. 737 (1998)
Wenning, T., MacDonald, M.: High performance computing data center metering protocol. Federal Energy Management Program, US Department of Energy, Resources on Data Center Energy Efficiency (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Yuki, T., Rajopadhye, S. (2014). Folklore Confirmed: Compiling for Speed \(=\) Compiling for Energy. In: Cașcaval, C., Montesinos, P. (eds) Languages and Compilers for Parallel Computing. LCPC 2013. Lecture Notes in Computer Science(), vol 8664. Springer, Cham. https://doi.org/10.1007/978-3-319-09967-5_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-09967-5_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09966-8
Online ISBN: 978-3-319-09967-5
eBook Packages: Computer ScienceComputer Science (R0)