NCA-AIIO Question 105
Select 4As an AI infrastructure engineer, you are tasked with monitoring the performance of GPUs in your data center. Which of the following metrics are key measures to monitor the health and performance of GPUs in a production environment?
- A
GPU utilization percentage
- B
Memory temperature
- C
Disk I/O throughput
- D
GPU memory usage
- E
CPU clock speed
- F
Power consumption
Show answer and explanation
Correct answers: A, B, D, F
Explanation
Effective GPU monitoring involves tracking metrics directly related to the GPU's health and performance. These include GPU utilization, memory temperature, memory usage, and power consumption. Monitoring these metrics ensures that the GPUs are operating efficiently and helps identify potential issues such as bottlenecks, overheating, or hardware inefficiencies. Other metrics like Disk I/O throughput or CPU clock speed are unrelated to GPU-specific monitoring and are not considered key measures for this purpose.
- A. Correct.
GPU utilization percentage is a critical metric that indicates how effectively the GPU is being used during workloads. Low utilization could signal under-utilization or inefficiencies.
- B. Correct.
Memory temperature is essential to monitor as overheating can lead to performance throttling or even hardware damage.
- C. Incorrect.
Disk I/O throughput is not directly related to GPU performance but rather to storage performance, so it is not a key GPU monitoring metric.
- D. Correct.
GPU memory usage is a key metric as it indicates how much of the available memory is being utilized. Insufficient memory can cause issues with larger workloads or models.
- E. Incorrect.
CPU clock speed is unrelated to GPU performance and is instead a measure of CPU performance.
- F. Correct.
Power consumption is vital to monitor as GPUs are power-intensive components, and excessive power draw can indicate inefficiencies or potential hardware issues.