NCP-AIO NVIDIA AI Operations exact Exam Questions

NVIDIA AI Operations

Last Update 19 hours ago Total Questions : 66

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Question # 4

A Fleet Command system administrator wants to create an organization user that will have the following rights:

For locations - read only

For Applications - read/write/admin

For Deployments - read/write/admin

For Dashboards - read only

What role should the system administrator assign to this user?

Fleet Command Operator

Fleet Command Admin

Fleet Command Supporter

Fleet Command Viewer

Question # 5

A system administrator notices that jobs are failing intermittently on Base Command Manager due to incorrect GPU configurations in Slurm. The administrator needs to ensure that jobs utilize GPUs correctly.

How should they troubleshoot this issue?

Increase the number of GPUs requested in the job script to avoid using unconfigured GPUs.

Check if MIG (Multi-Instance GPU) mode has been enabled incorrectly and reconfigure Slurm accordingly.

Verify that non-MIG GPUs are automatically configured in Slurm when detected, and adjust configurations if needed.

Ensure that GPU resource limits have been correctly defined in Slurm’s configuration file for each job type.

Question # 6

Which two (2) ways does the pre-configured GPU Operator in NVIDIA Enterprise Catalog differ from the GPU Operator in the public NGC catalog? (Choose two.)

It is configured to use a prebuilt vGPU driver image.

It supports Mixed Strategies for Kubernetes deployments.

It automatically installs the NVIDIA Datacenter driver.

It is configured to use the NVIDIA License System (NLS).

It additionally installs Network Operator.

Question # 7

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?

Reducing stripe count for large files would decrease parallelism, likely worsening performance for large sequential I/O operations.

Separate metadata-intensive operations and large sequential I/O operations by using different storage pools for each type of workload.

Increase the number of Object Storage Targets (OSTs) to handle more metadata operations.

Disable GPUDirect Storage (GDS) during peak hours to reduce I/O load on the Lustre file system.

Question # 8

An organization only needs basic network monitoring and validation tools.

Which UFM platform should they use?

UFM Enterprise

UFM Telemetry

UFM Cyber-AI

UFM Pro

Question # 9

You are managing a deep learning workload on a Slurm cluster with multiple GPU nodes, but you notice that jobs requesting multiple GPUs are waiting for long periods even though there are available resources on some nodes.

How would you optimize job scheduling for multi-GPU workloads?

Reduce memory allocation per job so more jobs can run concurrently, freeing up resources faster for multi-GPU workloads.

Ensure that job scripts use --gres=gpu: and configure Slurm’s backfill scheduler to prioritize multi-GPU jobs efficiently.

Set up separate partitions for single-GPU and multi-GPU jobs to avoid resource conflicts between them.

Increase time limits for smaller jobs so they don’t interfere with multi-GPU job scheduling.

Question # 10

An administrator is troubleshooting issues with an NVIDIA Unified Fabric Manager Enterprise (UFM) installation and notices that the UFM server is unable to communicate with InfiniBand switches.

What step should be taken to address the issue?

Reboot the UFM server to refresh network connections.

Install additional GPUs in the UFM server to boost connectivity.

Disable the firewall on the UFM server to allow communication.

Verify the subnet manager configuration on the InfiniBand switches.