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Part 1: Document Description
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Citation |
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Title: |
Replication Data for: Analyzing HPC Monitoring Data With a View Towards Efficient Resource Utilization |
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Identification Number: |
doi:10.26165/JUELICH-DATA/BDFBPQ |
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Distributor: |
Jülich DATA |
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Date of Distribution: |
2024-11-29 |
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Version: |
1 |
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Bibliographic Citation: |
Maloney, Samuel; Suarez, Estela; Eicker, Norbert; Guimarães, Filipe; Frings, Wolfgang, 2024, "Replication Data for: Analyzing HPC Monitoring Data With a View Towards Efficient Resource Utilization", https://doi.org/10.26165/JUELICH-DATA/BDFBPQ, Jülich DATA, V1 |
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Citation |
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Title: |
Replication Data for: Analyzing HPC Monitoring Data With a View Towards Efficient Resource Utilization |
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Identification Number: |
doi:10.26165/JUELICH-DATA/BDFBPQ |
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Authoring Entity: |
Maloney, Samuel (JSC) |
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Suarez, Estela (JSC) |
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Eicker, Norbert (JSC) |
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Guimarães, Filipe (JSC) |
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Frings, Wolfgang (JSC) |
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Distributor: |
Jülich DATA |
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Access Authority: |
Maloney, Samuel |
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Depositor: |
Maloney, Samuel |
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Date of Deposit: |
2024-11-29 |
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Study Scope |
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Keywords: |
Computer and Information Science, Runtime; High performance computing; Graphics processing units; Bandwidth; Computer architecture; Supercomputers; Robustness; Hardware; Resource management; Monitoring; HPC; Dynamic/Adaptive scheduling; Predictive analytics |
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Abstract: |
Replication 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. |
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Time Period: |
2023-11-01-2023-11-302024-01-01-2024-01-01 |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
CC0 Waiver |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Identification Number: |
10.1109/SBAC-PAD63648.2024.00023 |
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Bibliographic Citation: |
S. 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 |
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Label: |
booster_data.parquet |
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Notes: |
application/octet-stream |
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booster_data.parquet |
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application/octet-stream |
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cluster_data.parquet |
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application/octet-stream |
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cluster_data.parquet |
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application/octet-stream |
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gpu_data.parquet |
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application/octet-stream |
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gpu_data.parquet |
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application/octet-stream |
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__init__.cpython-311.pyc |
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application/octet-stream |
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__init__.cpython-312.pyc |
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application/octet-stream |
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__init__.py |
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text/x-python |
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paper.mplstyle |
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application/octet-stream |
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paper.pdf |
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Notes: |
application/pdf |
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plot_cdf_cpu.py |
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text/x-python |
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plot_cdf_durations.py |
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Notes: |
text/x-python |
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plot_cdf_gpu_power.py |
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text/x-python |
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plot_cdf_gpu.py |
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Notes: |
text/x-python |
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plot_cdf_IC.py |
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Notes: |
text/x-python |
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plot_cdf_mem.py |
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text/x-python |
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plot_cdf_sizes.py |
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Notes: |
text/x-python |
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plot_mem_intensity.py |
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Notes: |
text/x-python |
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README.md |
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Notes: |
text/markdown |