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Exam
:
NCP-AIO
Title
: NVIDIA Certified
Professional AI Operations
https://www.passcert.com/NCP-AIO.html
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1.A data scientist is training a deep learning model and notices slower than expected training times. The
data scientist alerts a system administrator to inspect the issue. The system administrator suspects the
disk IO is the issue.
What command should be used?
A. tcpdump
B. iostat
C. nvidia-smi
D. htop
Answer: B
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
To diagnose disk IO performance issues, the system administrator should use theiostatcommand, which
reports CPU statistics and input/output statistics for devices and partitions. It helps identify bottlenecks in
disk throughput or latency affecting application performance.
tcpdumpis used for network traffic analysis, not disk IO.
nvidia-smimonitors NVIDIA GPU status but not disk IO.
htopshows CPU, memory, and process usage but provides limited disk IO details.
Therefore,iostatis the appropriate tool to assess disk IO performance and diagnose bottlenecks impacting
training times.
2.A system administrator of a high-performance computing (HPC) cluster that uses an InfiniBand fabric for
high-speed interconnects between nodes received reports from researchers that they are experiencing
unusually slow data transfer rates between two specific compute nodes. The system administrator needs
to ensure the path between these two nodes is optimal.
What command should be used?
A. ibtracert
B. ibstatus
C. ibping
D. ibnetdiscover
Answer: A
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
To verify the optimal communication path and diagnose issues between two nodes in an InfiniBand fabric,
theibtracertcommand is used. It traces the route that InfiniBand packets take through the fabric,
identifying each hop and any potential bottlenecks or faulty links along the path.
ibstatusprovides status information about local InfiniBand devices and ports.
ibpingtests connectivity and latency between nodes.
ibnetdiscoverdiscovers and prints the topology of the InfiniBand fabric but does not trace specific paths.
Therefore,ibtracertis the appropriate tool for path optimization verification between two compute nodes.
3.You are tasked with deploying a DOCA service on an NVIDIA BlueField DPU in an air-gapped data
center environment. The DPU has the required BlueField OS version (3.9.0 or higher) installed, and you
have access to the necessary container image from NVIDIA's NGC catalog. However, you need to ensure
that the deployment process is successful without an internet connection.
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Which of the following steps should you take to deploy the DOCA service on the DPU?
A. Install Docker on the DPU, pull the container directly from NGC, and run it using ‘docker run’ with
appropriate environment variables.
B. Pull the container image from NGC using Docker and modify the YAML file before deployment.
C. Manually download the container image and YAML file beforehand, transfer them to the DPU, and
deploy using Kubernetes with standalone Kubelet.
D. Use the host system’s Docker engine to pull the container image and deploy it on the DPU via SSH.
Answer: C
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In an air-gapped environment where the DPU has no internet connectivity, direct pulling of container
images from NVIDIA’s NGC catalog is not possible. The recommended approach is tomanually download
the required container image and YAML deployment filesfrom a connected system, then transfer these
files to the DPU. Deployment is then performed using Kubernetes with a standalone Kubelet on the DPU,
which can deploy the preloaded container image offline. This ensures the deployment proceeds
successfully without internet access.
4.A system administrator needs to scale a Kubernetes Job to 4 replicas.
What command should be used?
A. kubectl stretch job --replicas=4
B. kubectl autoscale deployment job --min=1 --max=10
C. kubectl scale job --replicas=4
D. kubectl scale job -r 4
Answer: C
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
The correct command to scale a Kubernetes Job to a specific number of replicas iskubectl scale job -replicas=4. This explicitly sets the number of desired pod instances for the Job resource. The other
commands are either invalid (stretch), apply to Deployments rather than Jobs (autoscale deployment), or
use incorrect syntax (-r).
5.An administrator is troubleshooting a bottleneck in a deep learning run time and needs consistent data
feed rates to GPUs.
Which storage metric should be used?
A. Disk I/O operations per second (IOPS)
B. Disk free space
C. Sequential read speed
D. Disk utilization in performance manager
Answer: C
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
When troubleshooting performance bottlenecks related to feeding data consistently to GPUs during deep
learning workloads, the key storage metric to consider is sequential read speed. Deep learning training
typically involves streaming large datasets sequentially from storage to GPUs. The sequential read speed
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measures how fast data can be read in a continuous stream, directly impacting the ability to keep GPUs
fed without stalls.
Disk I/O operations per second (IOPS) measures random read/write operations and is less relevant for
large sequential data streams in AI workloads.
Disk free space indicates available storage capacity but does not impact data feed rate.
Disk utilization in performance manager shows overall usage but does not specify the speed or
consistency of data feed.
Therefore, focusing on sequential read speed (option C) is critical for ensuring consistent,
high-throughput data feeding to GPUs, minimizing bottlenecks in deep learning runtime environments.
This is consistent with NVIDIA AI Operations best practices for system performance optimization and
troubleshooting storage-related issues in AI infrastructure.
6.You are an administrator managing a large-scale Kubernetes-based GPU cluster using Run: AI.
To automate repetitive administrative tasks and efficiently manage resources across multiple nodes,
which of the following is essential when using the Run:AI Administrator CLI for environments where
automation or scripting is required?
A. Use the runai-adm command to directly update Kubernetes nodes without requiring kubectl.
B. Use the CLI to manually allocate specific GPUs to individual jobs for better resource management.
C. Ensure that the Kubernetes configuration file is set up with cluster administrative rights before using
the CLI.
D. Install the CLI on Windows machines to take advantage of its scripting capabilities.
Answer: C
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
When automating tasks with the Run:AI Administrator CLI, it is essential to ensure that theKubernetes
configuration file (kubeconfig)is correctly set up with cluster administrative rights. This enables the CLI to
interact programmatically with the Kubernetes API for managing nodes, resources, and workloads
efficiently. Without proper administrative permissions in the kubeconfig, automated operations will fail due
to insufficient rights.
Manual GPU allocation is typically handled by scheduling policies rather than CLI manual assignments.
The CLI does not replacekubectlcommands entirely, and installation on Windows is not a critical
requirement.
The Run:AI Administrator CLI requires a Kubernetes configuration file with cluster-administrative rights in
order to perform automation or scripting tasks across the cluster. Without those rights, the CLI cannot
manage nodes or resources programmatically.
7.A system administrator is looking to set up virtual machines in an HGX environment with NVIDIA Fabric
Manager.
What three (3) tasks will Fabric Manager accomplish? (Choose three.)
A. Configures routing among NVSwitch ports.
B. Installs GPU operator
C. Coordinates with the NVSwitch driver to train NVSwitch to NVSwitch NVLink interconnects.
D. Coordinates with the GPU driver to initialize and train NVSwitch to GPU NVLink interconnects.
E. Installs vGPU driver as part of the Fabric Manager Package.
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Answer: A C D
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
NVIDIA Fabric Manager is responsible for managing the fabric interconnect in HGX systems, including:
Configuring routing among NVSwitch ports (A)to optimize communication paths.
Coordinating with the NVSwitch driver to train NVSwitch-to-NVSwitch NVLink interconnects (C)for
high-speed link setup.
Coordinating with the GPU driver to initialize and train NVSwitch-to-GPU NVLink interconnects (D)
ensuring optimal connectivity between GPUs and switches.
Installing the GPU operator and vGPU driver is typically handled separately and not part of Fabric
Manager’s core tasks.
8.A system administrator is experiencing issues with Docker containers failing to start due to volume
mounting problems. They suspect the issue is related to incorrect file permissions on shared volumes
between the host and containers.
How should the administrator troubleshoot this issue?
A. Use the docker logs command to review the logs for error messages related to volume mounting and
permissions.
B. Reinstall Docker to reset all configurations and resolve potential volume mounting issues.
C. Disable all shared folders between the host and container to prevent volume mounting errors.
D. Reduce the size of the mounted volumes to avoid permission conflicts during container startup.
Answer: A
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
The first step to troubleshoot Docker container volume mounting issues is tocheck the container
logsusingdocker logsfor detailed error messages, including those related to permissions. This provides
direct insight into the cause of the failure. Reinstalling Docker or disabling shared folders are drastic steps
and may not address the root cause. Volume size reduction is unrelated to permission conflicts.
9.An instance of NVIDIA Fabric Manager service is running on an HGX system with KVM. A System
Administrator is troubleshooting NVLink partitioning.
By default, what is the GPU polling subsystem set to?
A. Every 1 second
B. Every 30 seconds
C. Every 60 seconds
D. Every 10 seconds
Answer: B
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In NVIDIA AI infrastructure, theNVIDIA Fabric Managerservice is responsible for managing GPU fabric
features such as NVLink partitioning on HGX systems. This service periodically polls the GPUs to monitor
and manage NVLink states. By default, the GPU polling subsystem is set toevery 30 secondsto balance
timely updates with system resource usage.
This polling interval allows the Fabric Manager to efficiently detect and respond to changes or issues in
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the NVLink fabric without excessive overhead or latency. It is a standard default setting unless specifically
configured otherwise by system administrators.
This default behavior aligns with NVIDIA’s system management guidelines for HGX platforms and is
referenced in NVIDIA AI Operations materials concerning fabric management and troubleshooting of
NVLink partitions.
10.Which of the following correctly identifies the key components of a Kubernetes cluster and their roles?
A. The control plane consists of the kube-apiserver, etcd, kube-scheduler, and kube-controller-manager,
while worker nodes run kubelet and kube-proxy.
B. Worker nodes manage the kube-apiserver and etcd, while the control plane handles all container
runtimes.
C. The control plane is responsible for running all application containers, while worker nodes manage
network traffic through etcd.
D. The control plane includes the kubelet and kube-proxy, and worker nodes are responsible for running
etcd and the scheduler.
Answer: A
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Kubernetes architecture, thecontrol planeis composed of several core components including
thekube-apiserver, etcd(the cluster’s key-value store),kube-scheduler, andkube-controller-manager.
These manage the overall cluster state, scheduling, and orchestration of workloads. Theworker nodesare
responsible for running the actual containers and include thekubelet(agent that communicates with the
control plane) and kube-proxy (handles network routing for services). Other options incorrectly assign
these components or roles.
11.Your organization is running multiple AI models on a single A100 GPU using MIG in a multi-tenant
environment. One of the tenants reports a performance issue, but you notice that other tenants are
unaffected.
What feature of MIG ensures that one tenant's workload does not impact others?
A. Hardware-level isolation of memory, cache, and compute resources for each instance.
B. Dynamic resource allocation based on workload demand.
C. Shared memory access across all instances.
D. Automatic scaling of instances based on workload size.
Answer: A
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
NVIDIA's Multi-Instance GPU (MIG) technology provideshardware-level isolationof critical GPU resources
such as memory, cache, and compute units for each GPU instance. This ensures that workloads running
in one instance are fully isolated and cannot interfere with the performance of workloads in other
instances, supporting multi-tenancy without contention.
12.After completing the installation of a Kubernetes cluster on your NVIDIA DGX systems using BCM,
how can you verify that all worker nodes are properly registered and ready?
A. Run kubectl get nodes to verify that all worker nodes show a status of “Ready”.
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B. Run kubectl get pods to check if all worker pods are running as expected.
C. Check each node manually by logging in via SSH and verifying system status with systemctl.
Answer: A
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
The standard method to verify that worker nodes are correctly registered and ready in a Kubernetes
cluster is to runkubectl get nodes. This command lists all nodes and their statuses. Nodes showing a
status of “Ready” indicates they are properly connected and available to schedule workloads. Checking
pods or manual SSH is not the direct or reliable way to verify node readiness.
13.An organization only needs basic network monitoring and validation tools.
Which UFM platform should they use?
A. UFM Enterprise
B. UFM Telemetry
C. UFM Cyber-AI
D. UFM Pro
Answer: B
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
The UFM Telemetry platform provides basic network monitoring and validation capabilities, making it
suitable for organizations that require foundational insight into their network status without advanced
analytics or AI-driven cybersecurity features. Other platforms such as UFM Enterprise or UFM Pro offer
broader or more advanced functionalities, while UFM Cyber-AI focuses on AI-driven cybersecurity.
14.A system administrator needs to configure and manage multiple installations of NVIDIA hardware
ranging from single DGX BasePOD to SuperPOD.
Which software stack should be used?
A. NetQ
B. Fleet Command
C. Magnum IO
D. Base Command Manager
Answer: D
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