After 15 years of exponential improvement in microprocessor clock rates, the physical principles allowing for Dennard scaling, which enabled performance improvements without a commensurate increase in power consumption, have all but ended. Until now, most HPC system have not focused on power efficiency. However, as the cost of power reaches parity with capital costs, it is increasingly important to compare systems with metrics based on the sustained performance per watt. Therefore we need to establish practical methods to measure power consumption of such systems insitu in order to support such metrics. Our study provides power measurements for various computational loads on the largest scale HPC systems ever involved in such an assessment. This study demonstrates clearly that, contrary to conventional wisdom, the power consumed while running the High Performance Linpack (HPL) benchmark is very close to the power consumed by any subset of a typical compute-intensive scientiﬁc workload. Therefore, HPL, which in most cases cannot serve as a suitable workload for performance measurements, can be used for the purposes of power measurement. Furthermore, we show through measurements on a large scale system that the power consumed by smaller subsets of the system can be pro jected straightforwardly and accurately to estimate the power consumption of the full system. This allows a less invasive approach for determining the power consumption of large-scale systems.
even being in the top 10. The ﬁrst petaﬂop-scale systems, expected to debut in 2008, will draw 2-7 megawatts of power. Projections for exaﬂop-scale computing systems, expected in 2016-2018, range from 60-130 megawatts . Therefore, fewer sites in the US will be able to host the largest scale computing systems due to limited availability of facilities with sufficient power and cooling capabilities. Following this trend, over time an ever increasing proportion of an HPC center’s budget will be needed for supplying power to these systems.