For purdue rcac gautschi infrastructure and model engineering teams

Purdue Gautschi GPU job: idle, stalled or missing monitoring data?

Compare job phase and worker progress with the telemetry interval. Distinguish an application stall from delayed monitoring records before requesting hardware intervention.

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Why this workflow may fit Purdue RCAC Gautschi

Purdue RCAC documents per-job GPU utilization, memory and power monitoring on Gautschi. It also explains that job data may appear after a collection delay. Existing telemetry supplies context, but an absent listing alone is not a failed GPU job.

Read the official Purdue RCAC Gautschi workflow reference

Evaluation scope: RCAC already provides monitoring. Denpex adds a submitted-log interpretation comparison, not an independent telemetry feed or a guarantee of performance diagnosis from a single utilization sample.

Prepared from public materials. This is a proposed evaluation, not a report of an incident at Purdue RCAC Gautschi or an endorsement.

Selectable demo logs are shared examples, not logs from Purdue RCAC Gautschi. Upload a shareable incident from your own workflow to evaluate the fit.

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Replay a resolved Purdue RCAC Gautschi workflow incident

Upload your log file. Review the selected evidence and masking, then run diagnosis. Keep the original log for any follow-up questions.

Before uploading, review cloud data handling and local options.

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Upload your log file. Large files are processed in your browser. Only selected evidence is submitted when you run diagnosis.

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Up to 50 diagnoses a day for 30 days. Verify your work email to activate an eligible company evaluation, then replay a resolved incident and compare the evidence and next steps with your team's confirmed cause.

What a useful evaluation should establish

Compare the first failure, quoted evidence and unresolved questions with an incident your team has already resolved. Begin with this question: Does the telemetry cover the affected job interval? Only attribute a process, rank, device or recovery state when the submitted evidence establishes it.

Does the telemetry cover the affected job interval?

Evidence to compare: Job ID, sampling timestamps and the monitoring collection window.

Missing or delayed records cannot by themselves establish idleness. Confirm coverage before interpreting the chart or a job absent from the list.

Is the worker computing or waiting?

Evidence to compare: Progress logs and available data-loading or collective timestamps.

Low utilization can reflect loading, synchronization or a stopped process. The next check depends on the phase evidence, not a universal utilization threshold.

Is the comparison fair?

Evidence to compare: A healthy interval with matching workload, allocation and run settings.

Performance attribution needs comparable conditions. Record what differs and what remains unknown rather than inventing a failure probability or a throughput guarantee.

Use Denpex alongside your existing telemetry tools to investigate submitted incident evidence. With monitoring configured on a supported plan, detected failures can trigger alerts and an automatic diagnosis from the captured evidence.

Inside Denpex

See the evidence, not just the claim

Follow the causal chain, inspect the quoted evidence and prepare the next handoff. These actual product captures use founder-account examples and the VS Code extension, with the source identified under each image. Open a capture to inspect it at full size.