RUNMON-RIFT: Adaptive configuration and healing for large-scale parameter inference
| العنوان: | RUNMON-RIFT: Adaptive configuration and healing for large-scale parameter inference |
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| المؤلفون: | R. Udall, J. Brandt, G. Manchanda, A. Arulanandan, J. Clark, J. Lange, R. O’Shaughnessy, L. Cadonati |
| المصدر: | Astronomy and Computing. 42:100664 |
| بيانات النشر: | Elsevier BV, 2023. |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Space and Planetary Science, FOS: Physical sciences, Astronomy and Astrophysics, General Relativity and Quantum Cosmology (gr-qc), Astrophysics - Instrumentation and Methods for Astrophysics, Instrumentation and Methods for Astrophysics (astro-ph.IM), General Relativity and Quantum Cosmology, Computer Science Applications |
| الوصف: | Gravitational wave parameter inference pipelines operate on data containing unknown sources on distributed hardware with unreliable performance. For one specific analysis pipeline (RIFT), we have developed a flexible tool (RUNMON-RIFT) to mitigate the most common challenges introduced by these two uncertainties. On the one hand, RUNMON provides several mechanisms to identify and redress unreliable computing environments. On the other hand, RUNMON provides mechanisms to adjust pipeline-specific run settings, including prior ranges, to ensure the analysis completes and encompasses the physical source parameters. We demonstrate both general features with two controlled examples. Comment: 9 pages, 2 figures |
| تدمد: | 2213-1337 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6df5b8df653e46616c9d7bebc367b4d3Test https://doi.org/10.1016/j.ascom.2022.100664Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....6df5b8df653e46616c9d7bebc367b4d3 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 22131337 |
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