Calculating User-Centric Carbon Footprints for HPC

Sustainable computing necessitates metrics for calculating carbon emissions of HPC systems and applications. While some established metrics focus on the data center level targeting HPC operators, any publicly reported data is too unspecific and untimely for HPC users. HPC users are often left only with the ability to estimate based on generic and sometimes arbitrarily chosen parameters. This paper fills a research gap by providing a methodology for HPC operators to calculate user-centric operational carbon footprints. Three carbon accounting levels are defined, focussing on ease of applicability for initial adoption and incrementally increasing reporting accuracy and time resolution. We apply this methodology to two German HPC centers, providing a variability analysis for the calculation parameters. The results reveal significant hourly, daily, and monthly fluctuations in the carbon intensity of the German energy mix and the clusters' power consumption, as well as hourly and monthly trends for the power usage effectiveness if free air cooling is employed.