For mount sinai minerva infrastructure and platform teams

Mount Sinai Minerva: LSF resource limit, GPU process or storage failure?

Connect the first useful exception with the relevant runtime evidence. Was the Minerva process stopped by an LSF resource limit?

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Why this workflow may fit Mount Sinai Minerva

Mount Sinai Minerva documents LSF job management, queues, partitions and storage for research computing. Scheduler outcomes and worker exceptions differ.

Read the official Mount Sinai Minerva workflow reference Mount Sinai Minerva additional implementation context

Evaluation scope: Preserve the LSF scheduler boundary. Submit no patient information, regulated datasets or private research payloads. Use approved redacted evidence. No native integration, automatic repair or current outage is implied.

Prepared from public materials. This is a proposed evaluation, not a report of an incident at Mount Sinai Minerva or an endorsement.

Selectable demo logs are shared examples, not logs from Mount Sinai Minerva. Upload a shareable incident from your own workflow to evaluate the fit.

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Replay a resolved Mount Sinai Minerva 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.

training_logs.txt

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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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No credit card. No automatic subscription. See whether Denpex helps with an incident you already understand.

Start your free 30-day Team evaluation

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 one incident your team already resolved with the first failure, cited evidence and remaining questions. Was the Minerva process stopped by an LSF resource limit? Only assign a rank, device or safe recovery state when the submitted evidence establishes it.

Was the Minerva process stopped by an LSF resource limit?

Evidence to compare: LSF termination reason, requested resources and first application exception.

A scheduler-enforced limit differs from device allocation failure. Match the LSF reason to its resource before changing a GPU workload or importing Slurm advice.

Did host memory or device memory run out?

Evidence to compare: Container or scheduler host-memory limit, process kill evidence and first allocation exception.

Host memory and device memory are different resources. A host-memory kill needs different evidence from a GPU allocator failure; identify the failed operation before changing a limit.

What evidence is approved for the support handoff?

Evidence to compare: Redacted job metadata, first exception and the permitted log-sharing boundary.

A public workflow grants no permission to export private data. Review approved operational excerpts without customer payloads, credentials or research datasets.

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.