HPC at German Universities - Data analysis references

This dataset contains the structured results of a systematic document analysis of High-Performance Computing (HPC)-related courses offered by German academic institutions (universities and universities of applied sciences, UAS). The analysis was conducted based on publicly available module handbooks and course catalogs. For each institution, the dataset includes: The number of identified HPC-related courses The explicit occurrence of predefined HPC topic categories within course descriptions (e.g., MPI, OpenMP, GPU computing, performance theory, performance practice, resource management, debugging, storage systems, cluster usage, Linux/Unix command line) The existence of local HPC cluster infrastructures Publicly available information on cluster characteristics (e.g., CPU core counts, GPU presence, Top500 status where applicable) Sources (websites, module handbooks) The dataset reflects only information explicitly documented in official course descriptions and publicly accessible infrastructure sources at the time of data collection. It does not assess actual teaching practices or undocumented course content. This dataset enables quantitative analysis of the thematic orientation of HPC education in Germany and supports research on the relationship between curricular design and infrastructural availability.