EECluster: an Energy-Efficient Tool for managing HPC Clusters

• Cocaña-Fernández, Alberto ^[1] ; Ranilla, Jose ; Sánchez, Luciano
  1. [1] Universidad de Oviedo

     Universidad de Oviedo

     Oviedo, España

     
• Localización: Annals of Multicore and GPU Programming: AMGP, ISSN 2341-3158, Vol. 3, Nº. 1, 2016, págs. 15-24
• Idioma: inglés
• Enlaces
  • Texto completo (pdf)
• Resumen

  • High Performance Computing clusters have become a very important element in research, academic and industrial communities because they are an excellent platform for solving a wide range of problems through parallel and distributed applications. Nevertheless, this high performance comes at the price of consuming large amounts of energy, which combined with notably increasing electricity prices are having an important economical impact, driving up power and cooling costs and forcing IT companies to reduce operation costs. To reduce the high energy consumptions of HPC clusters we propose a tool, named EECluster, for managing the energy-efficient allocation of the cluster resources, that works with both OGE/SGE and PBS/TORQUE Resource Management Systems (RMS) and whose decision-making mechanism is tuned automatically in a machine learning approach. Experimental studies have been made using actual workloads from the Scientific Modelling Cluster at Oviedo University and the academic-cluster used by the Oviedo University for teaching high performance computing subjects to evaluate the results obtained with the adoption of this tool

• Referencias bibliográficas
  • Buyya, R., Jin, H., Cortes, T.: Cluster computing. Future Generation Computer Systems 18(3), (2002).
  • Yeo, CheeShin and Buyya, Rajkumar and Pourreza, Hossein and Eskicioglu, Rasit and Graham, Peter and Sommers, F.: Cluster Computing: High-Performance,...
  • U.S. Environmental Protection Agency: Report to Congress on Server and Data Center Energy Efficiency Public Law 109-431. Technical report,...
  • Eurostat: Electricity and natural gas price statistics - Statistics Explained (2013). http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/Electricity_and_natural_gas_price_statistics#Further_Eurostat_information....
  • EIA: Electric Power Monthly - Energy Information Administration. http://www.eia.gov/electricity/monthly/. Accessed 07/04/14
  • Ebbers, Mike Archibald, M., da Fonseca, C.F.F., Griffel, M., Para, V., Searcy, M.: Smarter Data Centers: Achieving Greater Efficiency. Technical...
  • The Economist Intelligence Unit: IT and the environment A new item on the CIOs agenda? Technical report, The Economist (2007). http://www-03.ibm.com/services/ca/fr/green/pdf/SOLUTION_IT_it_and_the_environment.pdf
  • Hsu, C.-H., Kremer, U.: The design, implementation, and evaluation of a compiler algorithm for CPU energy reduction. ACM SIGPLAN Notices 38(5),...
  • Hsu, C.-H., Feng, W.-C.: A Power-Aware Run-Time System for High-Performance Computing. In: ACM/IEEE SC 2005 Conference (SC'05), pp. 1-1....
  • Freeh, V.W., Lowenthal, D.K., Pan, F., Kappiah, N., Springer, R., Rountree, B.L., Femal, M.E.: Analyzing the Energy-Time Trade-Off in High-Performance...
  • Lim, M., Freeh, V., Lowenthal, D.: Adaptive, Transparent Frequency and Voltage Scaling of Communication Phases in MPI Programs. In: ACM/IEEE...
  • Cheng, Y., Zeng, Y.: Automatic Energy Status Controlling with Dynamic Voltage Scaling in Power-Aware High Performance Computing Cluster. In:...
  • Ge, R., Feng, X., Feng, W.-c., Cameron, K.W.: CPU MISER: A Performance-Directed, Run-Time System for Power-Aware Clusters. In: 2007 International...
  • Huang, S., Feng, W.: Energy-Efficient Cluster Computing via Accurate Workload Characterization. In: 2009 9th IEEE/ACM International Symposium...
  • Chetsa, G.L.T., Lefrvre, L., Pierson, J.-M., Stolf, P., Da Costa, G.: A Runtime Framework for Energy Efficient HPC Systems without a Priori...
  • Alonso, P., Badia, R.M., Labarta, J., Barreda, M., Dolz, M.F., Mayo, R., Quintana-Orti, E.S., Reyes, R.: Tools for Power-Energy
  • Modelling and Analysis of Parallel Scientific Applications. In: 2012 41st International Conference on Parallel Processing, pp. 420-429. IEEE,...
  • Schubert, S., Kostic, D., Zwaenepoel, W., Shin, K.G.: Profiling Software for Energy Consumption. In: 2012 IEEE International Conference on...
  • Freeh, V.W., Lowenthal, D.K.: Using multiple energy gears in MPI programs on a power-scalable cluster. In: Proceedings of the Tenth ACM SIGPLAN...
  • Li, D., Nikolopoulos, D.S., Cameron, K., de Supinski, B.R., Schulz, M.: Power-aware MPI task aggregation prediction for high-end computing...
  • Xian, C., Lu, Y.-H., Li, Z.: A programming environment with runtime energy characterization for energy-aware applications. In: Proceedings...
  • Zong, Z., Ruan, X., Manzanares, A., Bellam, K., Qin, X.: Improving Energy-Efficiency of Computational Grids via Scheduling. In: Antonopoulos,...
  • Zong, Z., Nijim, M., Manzanares, A., Qin, X.: Energy efficient scheduling for parallel applications on mobile clusters. Cluster Computing...
  • Bash, C., Forman, G.: Cool job allocation: measuring the power savings of placing jobs at cooling-efficient locations in the data center,...
  • Tang, Q. and Gupta, S. K S and Varsamopoulos, G.: Energy-Efficient Thermal-Aware Task Scheduling for Homogeneous High-Performance Computing...
  • Pinheiro, E., Bianchini, R., Carrera, E.V., Heath, T.: Load balancing and unbalancing for power and performance in cluster-based systems....
  • Das, R., Kephart, J.O., Lefurgy, C., Tesauro, G., Levine, D.W., Chan, H.: Autonomic multi-agent management of power and performance in data...
  • Elnozahy, E.N., Kistler, M., Rajamony, R.: Energy-efficient server clusters, 179-197 (2002)
  • Berral, J.L., Goiri, I.n., Nou, R., Julià, F., Guitart, J., Gavaldà, R., Torres, J.: Towards energy-aware scheduling in data centers using...
  • Lang, W., Patel, J.M., Naughton, J.F.: On energy management, load balancing and replication. ACM SIGMOD Record 38(4), 35 (2010).
  • Garcia, D.F., Entrialgo, J., Garcia, J., Garcia, M.: A self-managing strategy for balancing response time and power consumption in heterogeneous...
  • Llamas, R.M., Garcia, D.F., Entrialgo, J.: A Technique for Self-Optimizing Scalable and Dependable Server Clusters under QoS Constraints....
  • Alvarruiz, F., de Alfonso, C., Caballer, M., Hernández, V.: An Energy Manager for High Performance Computer Clusters. In: 2012 IEEE 10th International...
  • Dolz, M.F., Fernández, J.C., Iserte, S., Mayo, R., Quintana-Ortí, E.S., Cotallo, M.E., Díaz, G.: EnergySaving Cluster experience in CETA-CIEMAT....
  • Xue, Z., Dong, X., Ma, S., Fan, S., Mei, Y.: An Energy-Efficient Management Mechanism for Large-Scale Server Clusters. In: The 2nd IEEE Asia-Pacific...
  • Cocaña-Fernández, A., Ranilla, J., Sánchez, L.: Energy-Efficient Allocation of Computing Node Slots in HPC Clusters through Evolutionary Multi-Criteria...
  • Cocañaa-Fernández, A., Ranilla, J., Sánchez, L.: Energy-Efficient Allocation of Computing Node Slots in HPC Clusters through Parameter Learning...