SafeWall: A Risk-Aware Job Walltime Recommendation for HPC Scheduling
In high-performance computing (HPC), users must submit resource requirements for their jobs, with user-supplied walltime being a critical parameter. However, these estimates are notoriously inaccurate, as users tend to overestimate walltime to prevent the scheduler from terminating their jobs prematurely. While existing work on learning-based walltime prediction primarily focuses on maximizing prediction accuracy, such predictions are inherently risky for walltime recommendations. Specifically, underestimation leads to job termination before completion, resulting in lost progress and wasted resources. In this study, we present SafeWall, a novel recommendation method that adjusts walltime ...
| Authors | Kanglin Xu, Michael Papka, Zhiling Lan |
|---|---|
| Primary category | cs.DC |
| Published | 19 October 2026 |
| Last updated at source | 19 October 2026 |
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