Is this a hardware or a software issue?

Hardware failures can look like either layer depending on the symptom. The discriminator is the resolution of the symptom to the recommended fix: if applying the steps under "How to fix it" eliminates the symptom, this is a software/configuration class issue regardless of the hardware it surfaced on. Repeat the fix on a fresh node to confirm.

How long does the fix typically take?

Most resolutions from this entry take 10 to 30 minutes of engineer time once the diagnosis is confirmed. Long fixes come from skipping the diagnosis step and chasing apparent symptoms (validation drift, memory growth, slow throughput) instead of the actual root cause listed above. Apply the fix in a small experiment first, then roll it forward.

Does this affect inference or only training?

Primarily this is a hardware failure observed during training, but the same misconfiguration can leak into downstream evaluation and serving. Treat the prevention checklist as a guardrail: any pipeline that touches a trained checkpoint should re-validate the failure mode before promoting the model.

What's the cheapest way to confirm this is the problem?

Cheapest signal: reproduce the symptom on a 1-GPU toy run with the same configuration. If the toy run exhibits the same behavior, the cause is the configuration rather than the cluster. If only the multi-GPU run is affected, the failure is a distributed interaction, so Server Chassis is the most likely layer to inspect.

Can the Denpex platform detect this automatically?

Yes. Denpex correlates the symptoms in this entry against your training logs in real time and surfaces the failure taxonomy, root cause, and exact remediation command on the console. Three full diagnoses are included free during signup, and the encyclopedia entry you are reading is generated from the same signal library that powers the platform.

What related failures should I check next?

Closely related failures cluster around #Xid Error. After applying this fix, validate against the related entries below to confirm no overlapping cause is masking as this one. Engineers routinely discover that the dominant failure mode is actually a second, sibling failure compounded on top.

Will this recur after the fix?

Applied once with the prevention checklist, this failure does not recur under normal operation. The recurring variant most engineers encounter is the re-emergence of the same symptom on a different model or stack after Xid Error is upgraded. Pin compatible versions and rerun the prevention smoke test on every dependency change.

Is there a fingerprint I can monitor?

Yes. Under high load (e.g., LLM training or heavy batch inference), a specific GPU stops responding. is the highest-signal fingerprint. Wire a metric or alert on that signal (or its absence after the fix) so you can detect the recurrence automatically. The Denpex platform encodes this exact fingerprint and surfaces it directly in the dashboard.

What is the official documentation that covers this?

Reference documentation is listed in the References section at the bottom of this entry. The most authoritative URLs are the upstream framework docs and the issue trackers cited; the Denpex entry synthesizes both into the executive, engineer, and on-call perspectives so each audience can act without reading every linked source.

Does this entry include working code?

Yes. The "Code Examples" section contains copy-paste-ready snippets that target the most common stacks (PyTorch, Hugging Face Trainer, DeepSpeed, Megatron-LM, vLLM/Transformers). Each snippet is annotated with why it works so you can adapt the pattern to your own framework without losing fidelity.

Xid 43: Watchdog Timeout due to PSU Transient Spikes

Q: What does this failure look like in production?

In production this failure typically appears during the first tens-to-hundreds of training steps: loss curves become non-monotonic, validation metrics plateau above the baseline, and downstream checkpoints either diverge or fail to improve. Engineers frequently misread it as data drift when the underlying mechanism is during heavy compute operations, modern gpus (like the a100 or h100) experience massive microsecond-level power spikes. if the power supply unit (psu) or the 12v pcie power cables cannot handle the transient load, the gpu voltage drops. this physical brownout stalls the gpu clocks, tripping the internal driver watchdog timer, which reports an xid 43 (stopped processing) and resets the channel.. Validating against the symptom list in this entry is the fastest way to confirm the diagnosis.

Q: How does this scale from 1 GPU to 1000 GPUs?

At single-GPU scale the symptom usually looks like slow convergence or a single anomalous loss value. At 64+ GPU scale, distributed interactions amplify during heavy compute operations, modern gpus (like the a100 or h100) experience massive microsecond-level power spikes. if the power supply unit (psu) or the 12v pcie power cables cannot handle the transient load, the gpu voltage drops. this physical brownout stalls the gpu clocks, tripping the internal driver watchdog timer, which reports an xid 43 (stopped processing) and resets the channel. through collectives, and the failure can manifest as a full job abort. Always reproduce the fix at the smallest cluster configuration that still exhibits the symptom before promoting to production scale.

During heavy compute operations, modern GPUs (like the A100 or H100) experience massive microsecond-level power spikes. If the Power Supply Unit (PSU) or the 12V PCIe power cables cannot handle the transient load, the GPU voltage drops. This physical brownout stalls the GPU clocks, tripping the internal driver watchdog timer, which reports an Xid 43 (stopped processing) and resets the channel.

Quick answer

During heavy compute operations, modern GPUs (like the A100 or H100) experience massive microsecond-level power spikes.

Symptom: The node may completely freeze, or the affected GPU may fall off the bus entirely (leading to Xid 79).
Root cause: During heavy compute operations, modern GPUs (like the A100 or H100) experience massive microsecond-level power spikes. If the Power Supply Unit (PSU) or the 12V PCIe power cables cannot handle the transient load, the GPU voltage drops. This physical brownout stalls the GPU clocks, tripping the internal driver watchdog timer, which reports an Xid 43 (stopped processing) and resets the channel.
Recommended fix: Limit Maximum Power Draw sudo nvidia-smi -pl 250 Lowers the GPU power limit (e.g., to 250W), reducing the magnitude of power spikes and keeping the system stable until the PSU or cabling is upgraded.
How Denpex helps: Denpex investigates Xid 43: Watchdog Timeout due to PSU Transient Spikes 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 Error

What this failure is

Xid 43: Watchdog Timeout due to PSU Transient Spikes is a Hardware failure seen during ML training runs. During heavy compute operations, modern GPUs (like the A100 or H100) experience massive microsecond-level power spikes. If the Power Supply Unit (PSU) or the 12V PCIe power cables cannot handle the transient load, the GPU voltage drops. This physical brownout stalls the GPU clocks, tripping the internal driver watchdog timer, which reports an Xid 43 (stopped processing) and resets the channel. Common tags: Xid Error.

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Why it happens (the mechanism)

Because the software reports a channel reset or watchdog timeout, engineers assume their code got stuck in an infinite loop. They spend weeks profiling CUDA kernels when the issue is actually an inadequate power supply.

What you'll observe

NVRM: Xid (PCI:0000:81:00): 43, Ch 00000008, engmask 00000101
GPU stopped processing
Reset Channel Verification Error

Common symptoms and what they mean

Symptom	Why it happens
Under high load (e.g., LLM training or heavy batch inference), a specific GPU stops responding.	During heavy compute operations, modern GPUs (like the A100 or H100) experience massive microsecond-level power spikes. If the Power Supply Unit (PSU) or the 12V PCIe power cables cannot handle the transient load, the GPU voltage drops. This physical brownout stalls the GPU clocks, tripping the internal driver watchdog timer, which reports an Xid 43 (stopped processing) and resets the channel.
The node may completely freeze, or the affected GPU may fall off the bus entirely (leading to Xid 79).	During heavy compute operations, modern GPUs (like the A100 or H100) experience massive microsecond-level power spikes. If the Power Supply Unit (PSU) or the 12V PCIe power cables cannot handle the transient load, the GPU voltage drops. This physical brownout stalls the GPU clocks, tripping the internal driver watchdog timer, which reports an Xid 43 (stopped processing) and resets the channel.
nvidia-smi hangs or reports the GPU as lost.	During heavy compute operations, modern GPUs (like the A100 or H100) experience massive microsecond-level power spikes. If the Power Supply Unit (PSU) or the 12V PCIe power cables cannot handle the transient load, the GPU voltage drops. This physical brownout stalls the GPU clocks, tripping the internal driver watchdog timer, which reports an Xid 43 (stopped processing) and resets the channel.

Which systems are affected

Server Chassis
PSU
NVIDIA GPU

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.

✓Check power connections and ensure separate PCIe cables are used (no daisy-chaining/splitters).
✓Limit GPU clocks to artificially reduce power transients: sudo nvidia-smi -lgc 300,1200 and see if the crash stops.
✓Check baseboard management controller (BMC) or IPMI logs for power supply voltage drops.

Root cause

During heavy compute operations, modern GPUs (like the A100 or H100) experience massive microsecond-level power spikes. If the Power Supply Unit (PSU) or the 12V PCIe power cables cannot handle the transient load, the GPU voltage drops. This physical brownout stalls the GPU clocks, tripping the internal driver watchdog timer, which reports an Xid 43 (stopped processing) and resets the channel.

The fix and how to prevent it

Searchable error signature

search key

The node may completely freeze, or the affected GPU may fall off the bus entirely (leading to Xid 79).
nvidia-smi hangs or reports the GPU as lost.

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

The root cause is on this page and stays free. A free account adds the exact remediation steps, saved history, and the fix on every entry in the encyclopedia.

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Xid 43 in context

Xid 43 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.

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References

↗NVIDIA Hardware Troubleshooting: Xid 43

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