Architecture of Computing Systems (Lecture Notes in Computer ...

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172 M.F. Dolz et al. at the inactive time with average of inactive intervals (roughly 1,856 h), we can conclude that nodes were down a considerable period of time for this particular workload. This high value indicates that nodes have been deactivated for long periods of time and, therefore, the decision of keeping them down is feasible. The result also demonstrates that, for this particular workload, it is more convenient to turn nodes off than to keep them active using, e.g., DVFS, as the time needed to reactivate a node is negligible compared with the period of time they remain inactive. 5 Summary and Conclusions This paper describes the components of an energy saving module for the Sun R○ Grid Engine queue system and Rocks R○ Clusters operating system. By turning on only those nodes that are actually needed at a given time during the execution of a batch of jobs, the module may yield substantial energy savings. The module is highly configurable: Specifically, a node can be turned on if a lack of resources for a particular job is detected, the average waiting time of the jobs is greater than a threshold, or the number of enqueued jobs exceeds a threshold. On the other hand, a node can be turned off if the idle time exceeds a threshold, the waiting time of enqueued jobs is lower than a threshold, or the current jobs can be served using a smaller number of nodes. In addition, there are also options to select candidate nodes to be powered on, and strict levels which can produce a considerable energy savings. As expected, choosing the best policy depends on the type of jobs that are submitted to the system and the configuration of the cluster. Thus, the energy saving module is just a tool easily configurable but its performance will ultimately depend on the system administrator’s expertise. As future work we plan to adapt the module to the Portable Batch System (PBS), developing a Roll for the Rocks R○ system, and extend the module to extract real energy consumption on each node using Watts Up? power meters [21] attached at the private cluster network. The energy saving system is currently in operation in the HPC clusters of the High Performance Computing & Architectures research group of UJI. References 1. U.S. Environmental Protection. Report to congress on server and data center energy efficiency, public law 109-431. Agency ENERGY STAR Program (August 2007), http://www.energystar.gov/ia/partners/prod development/ EPA Datacenter Report Congress Final1.pdf 2. Kim, E.-J., Link, G., Yum, K.H., Narayanan, V., Kandemir, M., Irwin, M.J., Das, C.R.: A holistic approach to designing energy-efficient cluster interconnects. IEEE Trans. on Computers 54(6), 660–671 (2005)
EnergySaving Cluster Roll: Power Saving System for Clusters 173 3. Supermicro Computer Inc. Supermicro ofrece HPC de alta densidad con Microsoft Windows compute cluster server 2003. PR Newswire Europe Ltd. (March 2007), http://www.prnewswire.co.uk/cgi/news/release?id=192954 4. Liu, Y., Yang, H., Dick, R.P., Wang, H., Shang, L.: Thermal vs energy optimization for DVFS-enabled processors in embedded systems. In: International 8th Symposium on Quality Electronic Design (ISQED 2007), March 2007, pp. 204–209 (2007) 5. Ge, R., Feng, X., Cameron, K.W.: Performance-constrained distributed DVS scheduling for scientific applications on power-aware clusters. In: Conference on High Performance Networking and Computing Proceedings of the 2005 ACM/IEEE conference on Supercomputing, p. 34 (2005) 6. Rountree, B., Lownenthal, D.K., de Supinski, B.R., Schulz, M., Freeh, V.W., Bletsch, T.: Adagio: making DVS practical for complex HPC applications export. In: Proceedings of the 23rd international conference on Supercomputing (ICS 2009), pp. 460–469 (2009) 7. Xian, C., Lu, Y.-H., Li, Z.: Energy-aware scheduling for real-time multiprocessor systems with uncertain task execution time. In: Proc. 44th Annual Conf. Design Automation, San Diego, CA, USA, pp. 664–669. ACM, New York (2007) 8. Freeh, V.W., Pan, F., Lowenthal, D.K., Kappiah, N., Springer, R., Rountree, B.L., Femal, M.E.: Analyzing the energy-time tradeoff in high-performance computing applications. IEEE Transactions on Parallel and Distributed Systems 18(6), 835– 848 (2007) 9. Chase, J.S., Anderson, D.C., Thakar, P.N., Vahdat, A.M., Doyle, R.P.: Managing energy and server resources in hosting centres. In: Proc. 18th ACM Symp. Operating System Principles, Banff, Canada, pp. 103–116 (2001) 10. Pinheiro, E., Bianchini, R., Carrera, E.V., Heath, T.: Load balancing and unbalancing for power and performance in cluster-based systems. In: Workshop on Compilers and Operating Systems for Low Power (September 2001) 11. Elnozahy, E.N., Kistler, M., Rajamony, R.: Energy-efficient server clusters. In: Workshop on Mobile Computing Systems and Applications (February 2002) 12. Rocks-solid: Extension to ROCKS cluster that make your cluster more solid!, http://code.google.com/p/rocks-solid 13. Grid Engine project. PowerSaving, http://wiki.gridengine.info/wiki/index.php/PowerSaving 14. University of California. Rocks R○ Clusters, http://www.rocksclusters.org 15. Inc. Sun Microsystems. Sun R○ Grid Engine, http://gridengine.sunsource.net 16. van Rossum, G.: Python Reference Manual, http://docs.python.org/ref/ref.html 17. Wikipedia. WakeOnLAN, http://en.wikipedia.org/wiki/Wake-on-LAN 18. Linux man page ether-wake, http://linux.die.net/man/8/ether-wake 19. Bash, C., Forman, G.: Cool job allocation: Measuring the power savings of placing jobs at cooling-efficient locations in the data center. HP Laboratories Palo Alto (August 2007) 20. Linux man page shutdown, http://linux.die.net/man/8/shutdown 21. Watts Up? Meters. Watts Up? .Net, https://www.wattsupmeters.com
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Lecture Notes in Computer Science 5
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Volume Editors Christian Müller-Sc
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General Chair Organization Christia
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Organization IX Hartmut Schmeck Kar
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Keynote Table of Contents HyVM - Hy
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Abdullah, Tariq 174 Alima, Luc Onan
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