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2015 Ninth International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS) (2015)
Santa Catarina, Brazil
July 8, 2015 to July 10, 2015
ISBN: 978-1-4799-8869-3
pp: 110-117
ABSTRACT
The increasing demand for computational resources has led to a significant growth of data center facilities. A major concern has appeared regarding energy efficiency and consumption in servers and data centers. The use of flexible and scalable server power models is a must in order to enable proactive energy optimization strategies. This paper proposes the use of Evolutionary Computation to obtain a model for server dynamic power consumption. To accomplish this, we collect a significant number of server performance counters for a wide range of sequential and parallel applications, and obtain a model via Genetic Programming techniques. Our methodology enables the unsupervised generation of models for arbitrary server architectures, in a way that is robust to the type of application being executed in the server. With our generated models, we are able to predict the overall server power consumption for arbitrary workloads, outperforming previous approaches in the state-of-the-art.
INDEX TERMS
Servers, Radiation detectors, Power demand, Mathematical model, Hardware, Benchmark testing, Computational modeling
CITATION

J. C. Hilburg, M. Zapater, J. L. Martin, J. M. Moya and J. L. Rodrigo, "Using Grammatical Evolution Techniques to Model the Dynamic Power Consumption of Enterprise Servers," 2015 Ninth International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS), Santa Catarina, Brazil, 2015, pp. 110-117.
doi:10.1109/CISIS.2015.16
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