Energy-aware job scheduler for high-performance computing

Computer Science - Research and Development - Tập 27 - Trang 265-275 - 2011
Olli Mämmelä1, Mikko Majanen1, Robert Basmadjian2, Hermann De Meer2, André Giesler3, Willi Homberg3
1VTT Technical Research Centre of Finland, Oulu, Finland
2University of Passau, Passau, Germany
3Jülich Supercomputing Centre, Jülich, Germany

Tóm tắt

In recent years energy-aware computing has become a major topic, not only in wireless and mobile devices but also in devices using wired technology. The ICT industry is consuming an increasing amount of energy and a large part of the consumption is generated by large-scale data centers. In High-Performance Computing (HPC) data centers, higher performance equals higher energy consumption. This has created incentives on exploring several alternatives to reduce the energy consumption of the system, such as energy-efficient hardware or the Dynamic Voltage and Frequency Scaling (DVFS) technique. This work presents an energy-aware scheduler that can be applied to a HPC data center without any changes in hardware. The scheduler is evaluated with a simulation model and a real-world HPC testbed. Our experiments indicate that the scheduler is able to reduce the energy consumption by 6–16% depending on the job workload. More importantly, there is no significant slowdown in the turnaround time or increase in the wait time of the job. The results hereby evidence that our approach can be beneficial for HPC data center operators without a large penalty on service level agreements.

Tài liệu tham khảo

http://www.hynix.com/products/consumer/consumer_sub.jsp?menuNo=1&m=2&s=1&menu3=01&RK=03&RAM_NAME=DDR2%20SDRAM&SUB_RAM=1Gb http://www.kingston.com/hyperx/products/khx_ddr2.asp http://www.samsung.com/global/business/semiconductor/productList.do?fmly_id=696&xFmly_id=695 Bailey Lee C, Schwartzman Y, Hardy J, Snavely A (2005) Are user runtime estimates inherently inaccurate? In: Job scheduling strategies for parallel processing. Lecture notes in computer science, vol 3277, pp 253–263. Springer, Berlin. http://dx.doi.org/10.1007/11407522_14 Barroso L, Holzle U (2007) The case for energy-proportional computing. Computer 40(12):33–37. doi:10.1109/MC.2007.443 Basmadjian R, Ali N, Niedermeier F, de Meer H, Giuliani G (2011) A methodology to predict the power consumption of servers in data centers. In: Proceedings of the 2nd international conference on energy-efficient computing and networking 2011 (e-Energy). ACM, New York Bianzino A, Chaudet C, Larroca F, Rossi D, Rougier J (2010) Energy-aware routing: a reality check. In: GLOBECOM workshops (GC Wkshps). IEEE Press, New York, pp 1422–1427. doi:10.1109/GLOCOMW.2010.5700172 Cirne W, Berman F (2001) A comprehensive model of the supercomputer workload. In: IEEE international workshop on workload characterization (WWC-4), pp 140–148. doi:10.1109/WWC.2001.990753 http://www.raritan.de/px-5000/px-5528/tech-specsde/: Raritan Etinski M, Corbalan J, Labarta J, Valero M (2010) Utilization driven power-aware parallel job scheduling. Comput Sci Res Dev 25:207–216. http://dx.doi.org/10.1007/s00450-010-0129-x. 10.1007/s00450-010-0129-x Fan X, Weber WD, Barroso LA (2007) Power provisioning for a warehouse-sized computer. In: Proceedings of the 34th annual international symposium on computer architecture (ISCA’07). ACM, New York, pp 13–23. http://doi.acm.org/10.1145/1250662.1250665 http://www.mpiforum.org/docs/: Mpi Freeh VW, Lowenthal DK, Pan F, Kappiah N, Springer R, Rountree BL, Femal ME (2007) Analyzing the energy-time trade-off in high-performance computing applications. IEEE Trans Parallel Distrib Syst 18:835–848. doi:10.1109/TPDS.2007.1026 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 Girolamo MD, Giuliani G, Egea JCL, Homberg W, Giesler A, Lent R, Mahmoodi T, Sannelli D, Salden A, Georgiadou V, Dang MQ, de Meer H, Basmadjian R, Klingert S, Schulze T (2011) Pilot evaluation of energy control plug-in inside single data centers. Deliverable D-6.2 v8.0, FIT4Green. FP7-ICT-2009-4-249020–FIT4Green/D-6.2, http://www.fit4green.eu/ Hikita J, Hirano A, Nakashima H (2008) Saving 200 KW and $200 k/year by power-aware job/machine scheduling. In: IEEE international symposium on parallel and distributed processing (IPDPS 2008), pp 1–8. doi:10.1109/IPDPS.2008.4536218 Hsu Ch, Feng Wc (2005) A power-aware run-time system for high-performance computing. In: Proceedings of the 2005 ACM/IEEE conference on supercomputing (SC’05). IEEE Computer Society, Washington, p 1. http://dx.doi.org/10.1109/SC.2005.3 http://alasir.com/software/ramspeed/: Ramspeed http://inet.omnetpp.org/: Inet framework http://omnetpp.org/: Omnet++ network simulation framework http://www.almico.com/speedfan.php: Speedfan http://www.coker.com.au/bonnie++/: Bonnie++ http://www.gartner.com/it/page.jsp?id=503867: Gartner newsroom—press release http://www.netlib.org/linpack/: Linpack http://www.streambench.org/: Stream http://www.top500.org/lists/2010/11/highlights: Top500 supercomputer sites Lent R (2010) Simulating the power consumption of computer networks. In: 15th IEEE international workshop on computer aided modeling, analysis and design of communication links and networks (CAMAD), pp 96–100. doi:10.1109/CAMAD.2010.5686955 Liu Y, Zhu H (2010) A survey of the research on power management techniques for high-performance systems. Softw Pract Exp 40:943–964. http://dx.doi.org/10.1002/spe.v40:11 http://www.clusterresources.com/pages/products/torque-resourcemanager.php/: Torque http://www.openmpi.org/: Openmp Pinheiro E, Bianchini R, Carrera EV, Heath T (2001) Load balancing and unbalancing for power and performance in cluster-based systems. In: Proceedings of the workshop on compilers and operating systems for low power (COLP) Ranganathan P, Rivoire S, Moore J (2009) Models and metrics for energy-efficient computing. Adv Comput 75:159–233 Restrepo J, Gruber C, Machuca C (2009) Energy profile aware routing. In: IEEE international conference on communications workshops, pp 1–5. doi:10.1109/ICCW.2009.5208041 Rivoire S, Ranganathan P, Kozyrakis C (2008) A comparison of high-level full-system power models. In: Proceedings of the conference on power aware computing and systems (HotPower’08). http://portal.acm.org/citation.cfm?id=1855610.1855613 Rivoire S, Shah M, Ranganatban P, Kozyrakis C, Meza J (2007) Models and metrics to enable energy-efficiency optimizations. Computer 40(12):39–48. doi:10.1007/s00450-011-0189-6