No Maintained Lightweight GPU Job Queue for Single-Node ML Experiments
Researchers and ML practitioners running experiments on a single GPU machine lack a simple, maintained tool to queue and serialize GPU jobs. Existing options are either unmaintained (task-spooler) or vastly over-engineered for single-node use (Slurm, Kubernetes). The gap sits between ad-hoc shell scripts and full cluster schedulers, with no clear community-maintained standard filling it.
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Problem descriptions, scores, analysis, and solution blueprints may be updated as new community data becomes available.