NCA-AIIO Question 95
Select 3A data center running NVIDIA AI workloads is experiencing intermittent performance degradation during model training. The operations team suspects resource contention and wants to implement a monitoring solution to identify the root cause. Which tools or techniques should they prioritize to effectively monitor and manage this issue?
- A
Utilize NVIDIA DCGM (Data Center GPU Manager) to monitor GPU utilization and health metrics.
- B
Deploy NVIDIA Nsight Systems to analyze kernel-level GPU performance.
- C
Implement periodic manual logs of CPU and GPU utilization using basic OS tools like top and nvidia-smi.
- D
Leverage telemetry and alerting features of NVIDIA Cloud Native Technologies like GPU Operator.
- E
Rely solely on hardware-level monitoring tools provided by the server vendor.
Show answer and explanation
Correct answers: A, B, D
Explanation
Effective AI data center management and monitoring require leveraging specialized tools that provide deep insights into GPU utilization, health, and performance. NVIDIA DCGM and Nsight Systems are critical for monitoring and analyzing GPU-related metrics, while GPU Operator enhances monitoring in cloud-native environments. Basic OS tools and vendor-provided hardware monitoring are insufficient on their own for the complexity of AI workloads.
- A. Correct.
NVIDIA DCGM is specifically designed for monitoring GPU health, utilization, and performance in data center environments, making it an essential tool for identifying resource contention in NVIDIA AI workloads.
- B. Correct.
NVIDIA Nsight Systems provides detailed insights into kernel-level performance, which can help pinpoint GPU-related bottlenecks during model training.
- C. Incorrect.
While basic OS tools like top and nvidia-smi are useful for quick checks, they are not sufficient for comprehensive monitoring in a data center environment handling complex AI workloads.
- D. Correct.
NVIDIA Cloud Native Technologies, such as GPU Operator, integrate with Kubernetes and provide advanced telemetry and alerting capabilities, which are critical for proactive monitoring and management.
- E. Incorrect.
Relying solely on hardware-level tools from the server vendor can limit visibility into GPU-specific metrics and AI workload performance, which are better addressed by NVIDIA tools.