Analysis of data from high performance computing (HPC) systems to improve HPC operations and research is an unsolved problem. This project addresses the challenge of HPC data analysis in a reproducible and legal manner. The data originates in the HPC systems of the consortium: NEMO at University of Freiburg (NEMO-UniFR), sciCORE at University of Basel (sciCORE‑UniBas), and HPC at University of Strasbourg (HPC‑UniStra).
The goals of the project are to analyze the data collected at NEMO‑UniFR to improve their research and operations activities, and to offer monitoring, operational, and research insights to also improve the sciCORE-UniBas and HPC-UniStra activities. The proposed approach entails: monitoring of systems and applications; legal compliance via de-identification and anonymization; and data analysis. The methods used include: HPC monitoring, legal controlling, de‑identification, anonymization, data aggregation, data mining, and insight extraction.
The outcome will be solutions for improving the HPC operations and research of three Eucor HPC centers and satisfy the data protection and privacy requirements. The solutions are significant and transferable to other Eucor member institutions for the benefit of no/minimal legislative inquiries and data management overhead.