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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.15537 |
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| _version_ | 1866908412814557184 |
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| author | Shpilker, Polina Pouchard, Line |
| author_facet | Shpilker, Polina Pouchard, Line |
| contents | Modern workflows run on increasingly heterogeneous computing architectures and with this heterogeneity comes additional complexity. We aim to apply the FAIR principles for research reproducibility by developing software to collect metadata annotations for workflows run on HPC systems. We experiment with two possible formats to uniformly store these metadata, and reorganize the collected metadata to be as easy to use as possible for researchers studying their workflow performance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_15537 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Automatic Metadata Capture and Processing for High-Performance Workflows Shpilker, Polina Pouchard, Line Distributed, Parallel, and Cluster Computing Modern workflows run on increasingly heterogeneous computing architectures and with this heterogeneity comes additional complexity. We aim to apply the FAIR principles for research reproducibility by developing software to collect metadata annotations for workflows run on HPC systems. We experiment with two possible formats to uniformly store these metadata, and reorganize the collected metadata to be as easy to use as possible for researchers studying their workflow performance. |
| title | Automatic Metadata Capture and Processing for High-Performance Workflows |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2506.15537 |