NCP-AIO Latest Exam Tips, New NCP-AIO Practice Materials

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NVIDIA AI Operations Sample Questions (Q79-Q84):

NEW QUESTION # 79
After installing Kubernetes on your NVIDIA hosts using BCM, you notice that the GPU metrics are not being collected by your monitoring system (e.g., Prometheus). You've confirmed that the NVIDIA Device Plugin is running correctly and GPUs are accessible to containers.
What is the next MOST likely component to investigate and how would you address it?

Answer: D

Explanation:
The NVIDIA Data Center GPU Manager (DCGM) exporter is specifically designed to collect and expose GPU metrics in a format that Prometheus can consume. If GPU metrics are not being collected, the DCGM exporter is the most likely culprit. The other options are less directly related to GPU metric collection. Option A pertains more to core Kubernetes metrics, option C relates to generic prometheus service discovery which isn't specialized to GPU data. Logging drivers and API throttling are less likely to directly block metrics collection.


NEW QUESTION # 80
You are deploying BCM in a high-availability (HA) configuration. What considerations are critical for ensuring data consistency and minimal downtime during a failover scenario?

Answer: A,B,D

Explanation:
In a HA configuration, a highly available database cluster is crucial for data consistency. A load balancer distributes traffic across multiple BCM instances, ensuring availability even if one instance fails. An automatic failover mechanism ensures minimal downtime by automatically switching to a backup instance. Sharing a common storage volume is generally not recommended due to potential data corruption issues. Regular backups are important but are more relevant for disaster recovery than immediate failover.


NEW QUESTION # 81
You are responsible for deploying a deep learning model for real-time inference using Triton Inference Server from NGC. Latency is a critical requirement. Which of the following optimization techniques can you employ to minimize inference latency?

Answer: A,C,D,E

Explanation:
A, B, C and E are correct. Increasing instances allows for parallel processing. Dynamic batching improves throughput. Reducing precision accelerates computation. Model optimization enhances GPU utilization. D is generally incorrect; CUDA graphs typically improve performance by reducing kernel launch overhead.


NEW QUESTION # 82
You are managing a high-performance computing environment. Users have reported storage performance degradation, particularly during peak usage hours when both small metadata- intensive operations and large sequential I/O operations are being performed simultaneously.
You suspect that the mixed workload is causing contention on the storage system.
Which of the following actions is most likely to improve overall storage performance in this mixed workload environment?

Answer: B

Explanation:
Separating metadata-intensive workloads and large sequential I/O operations onto different storage pools isolates contention points and optimizes performance for each workload type.
Metadata operations benefit from dedicated resources optimized for small, random access, while large sequential I/O requires high-throughput storage. This separation minimizes conflicts and improves overall system responsiveness.


NEW QUESTION # 83
A new researcher needs access to GPU resources but should not have permission to modify cluster settings or manage other users.
What role should you assign them in Run:ai?

Answer: D

Explanation:
In Run:ai, roles are assigned based on levels of permissions. The L1 Researcher role is designed for users who need access to GPU resources for running jobs and experiments but should not have administrative rights over cluster settings or other users. This role ensures researchers can use resources without affecting cluster configurations or user management. Other roles like Department Administrator, Application Administrator, or Research Manager have broader privileges, including managing users and settings, which are not appropriate for the new researcher's requirements.


NEW QUESTION # 84
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