Grasedyck, L., Löbbert, C., Wittum, G., Nägel, A., Schulz, V., Siebenborn, M., Krause, R., Benedusi, P., Küster, U., Dick, B.: Space and Time Parallel Multigrid for Optimization and Uncertainty Quantification in PDE Simulations. (2016).
Dick, B., Vogel, A., Khabi, D., Rupp, M., Küster, U., Wittum, G.: Utilization of empirically determined energy-optimal CPU-frequencies in a numerical simulation code. Computing and Visualization in Science.17,89-97 (2015).
In order to enable exascale computing, concepts for substantial energy savings are required. Dynamic voltage and frequency scaling (DVFS) is widely known to provide suitable energy saving potentials. However, the customarily utilized DVFS mechanism of the Linux kernel determines clock frequencies solely based on an idle time analysis. In contrast to this, we use an empirical approach based on preparatory measurements of the energy consumption at all available frequencies. From the resulting data we deduce energy-optimal frequencies, which are used in subsequent production runs. The described methodology can be deployed with routine granularity to account for varying code characteristics. For evaluation purposes, the approach is applied to the UG4 numerical simulation software. First results exhibit an average energy saving potential of approximately 10% while increasing the runtime by about 19%.