In recent years the power consumption of high-performance computing clusters has become a growing problem because the number and size of cluster installations has been rising. The high power consumption of clusters is a consequence of their design goal: High performance. With low utilization, cluster hardware consumes nearly as much energy as when it is fully utilized. Theoretically, in these low utilization phases cluster hardware can be turned off or switched to a lower power consuming state. We designed a model to estimate power consumption of hardware based on the utilization. Applications are instrumented to create utilization trace files for a simulator realizing this model. Different hardware components can be simulated using multiple estimation strategies. An optimal strategy determines an upper bound of energy savings for existing hardware without affecting the time-to-solution. Additionally, the simulator can estimate the power consumption of efficient hardware which is energy-proportional. This way the minimum power consumption can be determined for a given application. Naturally, this minimal power consumption provides an upper bound for any power saving strategy. After evaluating the correctness of the simulator several different strategies and energy-proportional hardware are compared.

@article{SOPCOEECHM10,
	author	 = {Timo Minartz and Julian Kunkel and Thomas Ludwig},
	title	 = {{Simulation of power consumption of energy efficient cluster hardware}},
	year	 = {2010},
	editor	 = {Thomas Ludwig},
	publisher	 = {Springer},
	address	 = {Berlin / Heidelberg, Germany},
	journal	 = {Computer Science - Research and Development},
	series	 = {3},
	pages	 = {165--175},
	issn	 = {1865-2034},
	doi	 = {http://dx.doi.org/10.1007/s00450-010-0120-6},
	abstract	 = {In recent years the power consumption of high-performance computing clusters has become a growing problem because the number and size of cluster installations has been rising. The high power consumption of clusters is a consequence of their design goal: High performance. With low utilization, cluster hardware consumes nearly as much energy as when it is fully utilized. Theoretically, in these low utilization phases cluster hardware can be turned off or switched to a lower power consuming state. We designed a model to estimate power consumption of hardware based on the utilization. Applications are instrumented to create utilization trace files for a simulator realizing this model. Different hardware components can be simulated using multiple estimation strategies. An optimal strategy determines an upper bound of energy savings for existing hardware without affecting the time-to-solution. Additionally, the simulator can estimate the power consumption of efficient hardware which is energy-proportional. This way the minimum power consumption can be determined for a given application. Naturally, this minimal power consumption provides an upper bound for any power saving strategy. After evaluating the correctness of the simulator several different strategies and energy-proportional hardware are compared.},
	url	 = {http://www.springerlink.com/content/r21r2376730p7161/fulltext.pdf},
}