Power characterisation of shared-memory hpc systems

Energy consumption has become one of the greatest challenges in the eld of High Performance Computing (HPC). Besides its impact on the environment, energy is a limiting factor for the HPC. Keeping the power consumption of a system below a threshold is one of the great problems; and power prediction can help to solve it. The power characterisation can be used to know the power behaviour of the system under study, and to be a support to reach the power prediction. Furthermore, it could be used to design power-aware application programs. In this article we propose a methodology to characterise the power consumption of shared-memory HPC systems. Our proposed methodology involves the nding of in uence factors on power consumed by the systems. It is similar to previous works, but we propose an in-deep approach that can help us to get a better power characterisation of the system. We apply our methodology to characterise an Intel server platform and the results show that we can nd a more extended set of in uence factors on power consumption. Eje: Workshop Procesamiento distribuido y paralelo (WPDP) Red de Universidades con Carreras en Informática (RedUNCI)