Replication Data for: Analyzing HPC Monitoring Data With a View Towards Efficient Resource Utilizationhttps://doi.org/10.26165/JUELICH-DATA/BDFBPQMaloney, SamuelSuarez, EstelaEicker, NorbertGuimarães, FilipeFrings, WolfgangJülich DATA2024-11-292024-11-29T14:15:45ZReplication Data for the analysis described in the IEEE/SBC SBAC-PAD 2024 paper "Analyzing HPC Monitoring Data With a View Towards Efficient Resource Utilization". Specifically, it contains the data and Python scripts used to generate Figures 2 through 9 in the paper, by computing the relevant cumulative distribution functions (CDFs) or other aggregations (for Figure 4) and then generating the associated plot. The data is contained in parquet files, using zstd compression; see the README file for more details.Computer and Information ScienceRuntime; High performance computing; Graphics processing units; Bandwidth; Computer architecture; Supercomputers; Robustness; Hardware; Resource management; Monitoring; HPC; Dynamic/Adaptive scheduling; Predictive analyticsEnglishS. Maloney, E. Suarez, N. Eicker, F. Guimarães, and W. Frings, “Analyzing HPC monitoring data with a view towards efficient resource utilization,” in 2024 IEEE 36th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), Hilo, HI, USA, Nov. 13–15, 2024, pp. 170–181, https://doi.org/10.1109/SBAC-PAD63648.2024.00023, doi, 10.1109/SBAC-PAD63648.2024.00023, https://doi.org/10.1109/SBAC-PAD63648.2024.00023Maloney, Samuel2024-11-292023-11-012023-11-302024-01-012024-01-01CC0CC0 Waiver