EE-HPC a Framework for Energy Efficient HPC System Management

Energy consumption has become a major cost factor in the procurement and operation of large scale HPC data centers. In addition, funding bodies and governments are starting to focus on assessment and improvement of energy efficiency, as well as reducing the overall environmental impact of data centers, like carbon usage reduction. The goal of the EE-HPC project is to develop a targeted job specific control and optimization of the hardware to enable a more efficient energy usage of HPC systems. The project started at the end of 2022 and builds upon the existing stable software components ClusterCockpit [1] and LIKWID [2] developed by FAU. It provides a simple, robust, secure and scalable monitoring & energy control framework for hybrid HPC cluster management. The EE-HPC project is developing energy aware software components that will be integrated with ClusterCockpit for power monitoring and reducing the energy consumption of the system. The framework is complemented with an instrumentation library for fine grained analysis, phase detection and tuning of MPI & OpenMP regions. The effectiveness of the approach is evaluated against a set of representative HPC applications ranging from molecular dynamics to earth system modelling.