Towards new energy efficiency limits of High Performance Clusters

In recent years performance of High Performance Computing Clusters took precedence over their power consumption. However, costs of energy and demand for ecologically acceptable IT solutions are higher than ever before, therefore a need for HPC clusters with acceptable power consumption becomes increasingly important. Consequently, the Green500 list, which takes into account both performance and power consumption of HPC clusters, almost reached the popularity of the Top500 list. Interestingly, the Green500 list is not an opponent to Top500 list; its core idea is to complement the Top500. Therefore, the Top500 list still serves as the basis for the Green500 list, and its numbers regarding measured HPL performance, are a basis for calculating the Green500 list. Indeed, the Green500 is the Top500 list ordered by HPL measured performance per Watt. Rmax numbers gained from High Performance Linpack benchmarks serve as performance input parameters, and total power consumed during execution of HPL on a certain HPC clusters is a power consumption parameter. The critical question remains: how to measure the consumed power correctly? This paper proposes that if it is not possible to measure the consumed power, one can still use maximum power consumption numbers rated from hardware vendors to find at least the lower bound green efficiency of HPC clusters. The main idea behind this approach is that Rmax values found on Top500 list never achieve Rpeak theoretical values, and that even most efficient HPL benchmark can never utilize computing nodes at their maximum. Furthermore by comparing MFLOPS/W results we gained with those found on Green500 list, we noted the excellent efficiency of the new HPC Isabella cluster recently powered on at University Computing Centre in Zagreb, ranking in just behind University of North Carolina KillDevil Top500 super cluster.

[1]  Wu-chun Feng,et al.  Making a case for a Green500 list , 2006, Proceedings 20th IEEE International Parallel & Distributed Processing Symposium.

[2]  Jack J. Dongarra,et al.  The LINPACK Benchmark: past, present and future , 2003, Concurr. Comput. Pract. Exp..

[3]  Wu-chun Feng,et al.  The Green Index: A Metric for Evaluating System-Wide Energy Efficiency in HPC Systems , 2012, 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum.

[4]  Drasko Tomic,et al.  Running High Performance Linpack on CPUGPU clusters , 2012, 2012 Proceedings of the 35th International Convention MIPRO.

[5]  Drasko Tomic Spectral performance evaluation of parallel processing systems , 2002 .

[6]  Drasko Tomic,et al.  Semidefinite optimization of High Performance Linpack on heterogeneous cluster , 2013, 2013 36th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).

[7]  Wu-chun Feng,et al.  Emerging Trends on the Evolving Green500: Year Three , 2011, 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum.