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Parallel and Distributed Processing Symposium, International (2008)
Miami, FL, USA
Apr. 14, 2008 to Apr. 18, 2008
ISBN: 978-1-4244-1693-6
pp: 1-8
Shoaib Kamil , LBNL/UC Berkeley, USA
John Shalf , LBNL/NERSC, USA
Erich Strohmaier , LBNL/CRD, USA
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 systems 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 in-situ 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 projected 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.

S. Kamil, J. Shalf and E. Strohmaier, "Power efficiency in high performance computing," 2008 IEEE International Parallel & Distributed Processing Symposium(IPDPS), Miami, FL, 2008, pp. 1-8.
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