NCP-AIO Troubleshooting and Optimization Practice Question
An AI operations team is troubleshooting a training job that crashes with a segmentation fault after several hours. The job uses multiple GPUs and NCCL for communication. System logs show no errors, but dmesg reveals repeated 'NVRM: Xid' errors. Which action should be taken first to diagnose the issue?
⚠ Common exam trap
The trap here is jumping to application-level debugging tools like NCCL_DEBUG when the system logs already point to a GPU-level fault via Xid errors.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Check the Xid error code in the NVIDIA documentation to identify the specific GPU fault.
Xid errors are logged by the NVIDIA driver and each code maps to a specific GPU fault. Interpreting the Xid code is the fastest way to understand whether the segmentation fault is due to a hardware issue, driver bug, or application error. This guides subsequent troubleshooting steps, such as replacing hardware or updating the driver.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Restart the NVIDIA driver with rmmod and modprobe commands.
Why it's wrong here
Restarting the driver might temporarily clear the error but does not diagnose the root cause. If the Xid error indicates a hardware failure, a driver restart could lead to data loss or further instability. It is not a diagnostic step but a remedial action. The first step should be to identify the fault via the Xid code before attempting any remediation.
- ✓
Check the Xid error code in the NVIDIA documentation to identify the specific GPU fault.
Why this is correct
Xid errors are reported by the NVIDIA driver and indicate GPU hardware or driver issues. Each Xid code corresponds to a specific fault, such as a corrupted memory access or a fallen off the bus error. Looking up the code in NVIDIA's documentation provides the exact cause and recommended actions. This is the most direct first step to diagnose the segmentation fault linked to GPU errors.
- ✗
Enable NCCL_DEBUG=INFO and re-run the job to capture detailed NCCL logs.
Why it's wrong here
Enabling NCCL_DEBUG=INFO provides detailed communication logs but does not directly address Xid errors, which are GPU hardware or driver errors. While NCCL logs might show where the job failed, the Xid errors indicate a lower-level GPU issue. The first step should be to interpret the Xid errors, as they point to the root cause. NCCL debugging is useful but secondary.
- ✗
Run nvidia-smi -q to check GPU temperature and power usage.
Why it's wrong here
Checking temperature and power can reveal thermal or power throttling, but Xid errors are not typically caused by throttling. They indicate more serious faults like ECC errors or illegal memory access. While nvidia-smi -q is a good general health check, it does not decode the Xid error. The specific Xid code must be interpreted first to understand the fault.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official NVIDIA exam blueprint
This NCP-AIO practice question is part of Courseiva's free NVIDIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the NCP-AIO exam.