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Xid 62: Internal microcontroller halt

Xid 62 reports an internal microcontroller halt. It does not by itself distinguish a driver or firmware defect from faulty hardware, and does not establish a CUDA memory leak.

Quick answer

Xid 62 reports an internal microcontroller halt. It does not by itself distinguish a driver or firmware defect from faulty hardware, and does not establish a CUDA memory leak.

Symptom
NVRM: Xid (PCI:0000:41:00.0): 62, pid=14092, 0000 00000000 00000000
Root cause
Xid 62 reports an internal microcontroller halt. It does not by itself distinguish a driver or firmware defect from faulty hardware, and does not establish a CUDA memory leak.
Recommended fix
Preserve nvidia-bug-report.sh output and kernel logs, drain work and stop GPU clients, then attempt a supported nvidia-smi --gpu-reset -i <id>. If reset fails, follow the platform reboot or power-cycle procedure. Validate the GPU before returning it to service.
How Denpex helps
Denpex investigates Xid 62: Internal microcontroller halt using the evidence you provide or your connected workload collects. Earlier rank, host or application evidence is needed to distinguish an initiating failure from a downstream report.
Hardware#xid#nvidia#firmware#gpu

What this failure is

Xid 62 reports an internal microcontroller halt. It does not by itself distinguish a driver or firmware defect from faulty hardware, and does not establish a CUDA memory leak.

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Why it happens (the mechanism)

Xid 62 reports an internal microcontroller halt. It does not by itself distinguish a driver or firmware defect from faulty hardware, and does not establish a CUDA memory leak. Use incident telemetry and the supported driver/firmware baseline to investigate the underlying mechanism.

What you'll observe

  • Xid 62 reports an internal microcontroller halt. It does not by itself distinguish a driver or firmware defect from faulty hardware, and does not establish a CUDA memory leak.
  • The event requires investigation; it does not establish every proposed downstream effect.

Common symptoms and what they mean

SymptomWhy it happens
Xid 62: Internal microcontroller haltXid 62 reports an internal microcontroller halt. It does not by itself distinguish a driver or firmware defect from faulty hardware, and does not establish a CUDA memory leak.
Record any accompanying application failure separately from this driver event.Xid 62 reports an internal microcontroller halt. It does not by itself distinguish a driver or firmware defect from faulty hardware, and does not establish a CUDA memory leak.

Which systems are affected

  • NVIDIA data center GPUs and the Linux driver
  • production-shaped multi-accelerator workloads
  • containerized and bare-metal deployments of the same stack

How to confirm this is the problem

Use this checklist to test the hypothesis against a small reproduction. No single line proves the root cause, so preserve the preceding events and compare one variable at a time.

  • ✓Preserve the literal Xid code and incident timestamp from kernel logs.
  • ✓Record nvidia-smi -q output, including GPU UUID, ECC and row-remapping details.
  • ✓Compare fresh counter deltas and diagnostics with the fleet baseline.

Root cause

  • Xid 62 reports an internal microcontroller halt. It does not by itself distinguish a driver or firmware defect from faulty hardware, and does not establish a CUDA memory leak.

The fix and how to prevent it

Searchable error signature

search key
NVRM: Xid (PCI:0000:41:00.0): 62, pid=14092, 0000 00000000 00000000

Use this text as a lookup key in logs and upstream issue trackers. It is not presented as a captured customer log. Confirm the cause from your own preceding events, versions, configuration and the cited references.

The fix and the prevention pattern

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Why the recommended fix works

A supported reset may restore the halted controller. Successful recovery does not prove that the underlying cause is fixed.

Code examples

snippet
# Read-only evidence collection
dmesg -T | grep -iE "NVRM|Xid|ECC"
nvidia-smi -q -d ECC,ROW_REMAPPER
# Preserve a GPU bug report before reset or reboot
sudo nvidia-bug-report.sh

Adapt the snippet to your framework. The same pattern holds for PyTorch Lightning, Hugging Face Trainer, DeepSpeed, Megatron-LM, and vLLM training wrappers. Where the wrapper exposes a config flag (for examplelr_scheduler_type in Trainer), prefer the flag over the imperative API to keep the schedule declarative and reproducible.

Best practices by model family

Model / StackRecommendationNotes
EvidenceKeep raw logsRecord GPU identity, timestamps and counter deltas.
RecoveryFollow the platform procedureStop affected work before disruptive diagnostics or reset.

With the fix vs without the fix

DimensionWith the fixWithout the fix
Event versus causeLiteral Xid plus supporting telemetryUnsupported hardware or workload attribution

Diagnostic note

“This guidance follows NVIDIA Xid documentation. A documented event meaning is not proof of permanent hardware failure or a diagnosis of application-level NaNs.”

Visual fingerprint

Evidence-led response
capture event -> identify GPU -> inspect counters and context -> supported recovery or diagnostics -> validate
Escalate unresolved or recurring faults with collected evidence.

Xid 62 in context

Xid 62 is one of a small set of codes the NVIDIA driver uses to report GPU faults, and the number is most of the diagnosis: it tells you whether you are looking at your own code, the driver, or a board that needs replacing.

Compare every Xid code side by side

Diagnose this failure in VS Code

Select the traceback or open the failed terminal, then run Denpex locally to see the initiating rank, collateral failures, exact fix, and verification command without uploading the log.

Install the free VS Code extension

Frequently asked questions

Questions engineers and on-call staff commonly ask about this failure.

Does this prove permanent hardware failure?
No. The code identifies an event; vendor investigation and diagnostics determine the underlying fault.
What should I do first?
Preserve nvidia-bug-report.sh output and kernel logs, drain work and stop GPU clients, then attempt a supported nvidia-smi --gpu-reset -i <id>. If reset fails, follow the platform reboot or power-cycle procedure. Validate the GPU before returning it to service.
When should I replace the GPU?
Escalate recurrence, rising error rates, exhausted remap capacity, or failed diagnostics to NVIDIA/OEM support. Replacement follows vendor investigation; no universal two-event or 30-day RMA rule is established here.

Don't just read the fix, diagnose your run

The encyclopedia tells you what went wrong. Denpex tells you what went wrong in YOUR training run. With your logs, your config, and your stack.