Tools for assessing and optimizing the energy requirements of high performance scientific computing software
This work addresses energy efficiency in high-performance computing, which is incremental as it builds on existing tools to include energy considerations.
The paper tackles the problem of optimizing high-performance scientific computing software by extending the Score-P measurement infrastructure to assess and optimize energy requirements alongside performance, aiming to balance energy consumption and run time through an objective function.
Score-P is a measurement infrastructure originally designed for the analysis and optimization of the performance of HPC codes. Recent extensions of Score-P and its associated tools now also allow the investigation of energy-related properties and support the user in the implementation of corresponding improvements. Since it would be counterproductive to completely ignore performance issues in this connection, the focus should not be laid exclusively on energy. We therefore aim to optimize software with respect to an objective function that takes into account energy and run time.