Energy Aware Scheduling Study on BlueWonder

Abstract

Power consumption of the world's leading supercomputers is of the order of tens of MegaWatts (MW). Therefore, energy efficiency and power management of High Performance Computing (HPC) systems are among the main goals of the HPC community. This paper presents our study of managing energy consumption of supercomputers with the use of the energy aware workload management software IBM Platform Load Sharing Facility (LSF). We analyze energy consumption and workloads of the IBM NextScale Cluster, BlueWonder, located at the Daresbury Laboratory, STFC, UK. We describe power management algorithms implemented as Energy Aware Scheduling (EAS) policies in the IBM Platform LSF software. We show the effect of the power management policies on supercomputer efficiency and power consumption using experimental as well as simulated data from scientific workloads on the BlueWonder supercomputer. We observed energy saving of up to 12% from EAS policies.