GreenHPC: a novel framework to measure energy consumption on HPC applications

Abstract

Energy consumption on systems that have a continuous power source is tightly-related to both the computing time of an application and its required CPU load. Considering the scope of HPC applications which commonly have a time precision in nano or milliseconds, we observe a lack of systems that combine appropriate sampling rate, low intrusiveness and low cost. In this context, this article presents a model called GreenHPC that uses a hall effect sensor to precisely capture current with an arbitrary timeslice on HPC applications. Its scientific contribution relies on analyzing the energy consumption at a cluster scale, without application intrusiveness, showing the impact of maintaining idle nodes or turning them off for energy saving. Furthermore, considering the use of GreenHPC over the execution of a seismic wave application, we also present the number of employed processors which present the best energy consumption index. Finally, we have used the obtained results to infer a model to estimate energy consumption of HPC applications. All the developed work has a special concern on reproducibility, so all data and hardware schematics are available for download at 1.