NCP-AIO Installation and Deployment Practice Question
Exhibit
nvidia-smi -q -d PERFORMANCE Performance State : P0 Clocks Throttle Reasons : Active Clocks Throttle Reason Sw Power Cap : Active Clocks Throttle Reason HW Slowdown : Not Active
Refer to the exhibit. An administrator notices poor performance in an AI training job. What is the most likely cause based on the CLI output?
⚠ Common exam trap
Candidates often mistake power capping errors for hardware faults or thermal overheating issues, ignoring the explicit 'Sw Power Cap' message in the telemetry output.
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
✓
The power limit is set too low for the current workload.
The output indicates that the GPU is currently throttling due to 'Sw Power Cap'. This means the software-defined power limit is restricting the GPU performance to stay within a specific wattage budget. This is common in densely packed servers or cloud environments where power infrastructure is shared. Monitoring power usage is vital because it directly impacts clock speeds, which in turn bottleneck training throughput and lengthen the time required for model convergence.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The GPU is overheating due to a fan failure.
Why it's wrong here
If the GPU were overheating, the 'HW Slowdown' or thermal throttling flags would be active. The current logs explicitly state that the hardware slowdown is not active, pointing the root cause toward a configured software limit rather than a physical cooling or hardware-level environmental issue in the chassis.
- ✓
The power limit is set too low for the current workload.
Why this is correct
The 'Sw Power Cap' status confirms that the GPU is limited by the current software configuration. To improve performance, the administrator should evaluate the power policy settings to determine if the wattage limit can be safely increased to allow the GPU to reach its maximum boost clock frequency.
- ✗
The GPU driver is corrupted or out of date.
Why it's wrong here
A corrupted driver usually results in failed device initialization, kernel panic, or complete lack of visibility into the GPU status via nvidia-smi. Since the device is successfully reporting performance states and throttle reasons, the driver is operational and communicating with the hardware correctly for power management.
- ✗
The workload is waiting for CPU memory allocation.
Why it's wrong here
While CPU memory bottlenecks can occur, they do not manifest as GPU power throttling events. This indicator is specifically related to the GPU's internal power management logic. A CPU bottleneck would be identified through system-level monitoring tools like top, htop, or iostat rather than GPU-specific power management metrics.
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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
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