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Gravitational wave parameter inference pipelines operate on data containingunknown sources on distributed hardware with unreliable performance. For onespecific analysis pipeline (RIFT), we have developed a flexible tool(RUNMON-RIFT) to mitigate the most common challenges introduced by these twouncertainties. On the one hand, RUNMON provides several mechanisms to identifyand redress unreliable computing environments. On the other hand, RUNMONprovides mechanisms to adjust pipeline-specific run settings, including priorranges, to ensure the analysis completes and encompasses the physical sourceparameters. We demonstrate both general features with two controlled examples.

RUNMON-RIFT: Adaptive Configuration and Healing for Large-Scale Parameter Inference