Developer builds free GPU pre-flight tool after silent CPU fallback cost six hours of billed compute

A developer running ML training jobs on Vast.ai discovered four silent failures — including CUDA falling back to CPU undetected, model weights repeatedly downloading to ephemeral storage, a mismatched Accelerate config producing garbage output, and a dirty dataset with over 28,000 duplicate rows — none of which threw exceptions. The issues collectively wasted significant paid GPU compute time and days of debugging before root causes were identified. Interviews with 13 ML engineers revealed these problems are widespread, with nine having lost checkpoints to ephemeral disk and enterprise teams resorting to hand-written bash scripts as workarounds. In response, the developer built ComputeFence, an open-source CLI tool that runs a 30-second pre-flight diagnostic checking GPU visibility, cache path persistence, Accelerate configuration, and disk headroom before a paid job launches. The tool is free, MIT licensed, available via pip, and compatible with major bare metal GPU providers including RunPod, Vast.ai, and Lambda Labs.