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NCP-AIO Latest Exam Questions, Valid NCP-AIO Test Duration

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NCP-AIO Latest Exam Questions, Valid NCP-AIO Test Duration

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NVIDIA NCP-AIO Exam Syllabus Topics:
TopicDetails
Topic 1
  • Installation and Deployment: This section of the exam measures the skills of system administrators and addresses core practices for installing and deploying infrastructure. Candidates are tested on installing and configuring Base Command Manager, initializing Kubernetes on NVIDIA hosts, and deploying containers from NVIDIA NGC as well as cloud VMI containers. The section also covers understanding storage requirements in AI data centers and deploying DOCA services on DPU Arm processors, ensuring robust setup of AI-driven environments.
Topic 2
  • Troubleshooting and Optimization: NVIThis section of the exam measures the skills of AI infrastructure engineers and focuses on diagnosing and resolving technical issues that arise in advanced AI systems. Topics include troubleshooting Docker, the Fabric Manager service for NVIDIA NVlink and NVSwitch systems, Base Command Manager, and Magnum IO components. Candidates must also demonstrate the ability to identify and solve storage performance issues, ensuring optimized performance across AI workloads.
Topic 3
  • Workload Management: This section of the exam measures the skills of AI infrastructure engineers and focuses on managing workloads effectively in AI environments. It evaluates the ability to administer Kubernetes clusters, maintain workload efficiency, and apply system management tools to troubleshoot operational issues. Emphasis is placed on ensuring that workloads run smoothly across different environments in alignment with NVIDIA technologies.
Topic 4
  • Administration: This section of the exam measures the skills of system administrators and covers essential tasks in managing AI workloads within data centers. Candidates are expected to understand fleet command, Slurm cluster management, and overall data center architecture specific to AI environments. It also includes knowledge of Base Command Manager (BCM), cluster provisioning, Run.ai administration, and configuration of Multi-Instance GPU (MIG) for both AI and high-performance computing applications.

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NVIDIA AI Operations Sample Questions (Q30-Q35):NEW QUESTION # 30
You are managing a cluster with multiple nodes connected via NVLink and NVSwitch. After a network outage, some of the NVLink connections are showing as 'degraded' in 'nvsm show links'. What steps should you take to attempt to restore the connections to their optimal state? (Select TWO correct answers)
  • A. Run 'nvsm repair linkS on the affected nodes.
  • B. Reboot all nodes in the cluster simultaneously.
  • C. Restart the 'nvsm' service on all nodes.
  • D. Check physical NVLink cable connections for damage or looseness.
  • E. Update the BIOS on all servers.
Answer: C,D
Explanation:
Restarting the 'nvsm' service can help re-establish the connections. Checking the physical cable connections is crucial to ensure they are secure and undamaged. 'nvsm repair links' is not a valid command. Rebooting the entire cluster may be necessary in some situations, but it's a more disruptive step to take initially. A BIOS update is unlikely to solve the problem if it arose after a network outage.

NEW QUESTION # 31
You're using BCM to manage a cluster and need to upgrade the Kubernetes version. What considerations are critical to ensure a smooth upgrade process?
  • A. Drain nodes before upgrading them to minimize application downtime.
  • B. Back up the etcd database before starting the upgrade.
  • C. Test the upgrade in a staging environment before applying it to the production cluster.
  • D. Update the NVIDIA drivers and container runtime on all nodes after the Kubernetes upgrade.
  • E. Ensure all worker nodes have sufficient resources (CPU, memory) for the new Kubernetes version.
Answer: A,B,C,E
Explanation:
Backing up etcd is crucial for rollback. Resource sufficiency prevents upgrade failures. Testing in staging identifies potential issues. Draining minimizes downtime. NVIDIA drivers should ideally be checked for compatibility and potentially updated before the Kubernetes upgrade.

NEW QUESTION # 32
You are deploying a cloud VMI container using Terraform. How would you define a resource to provision an NVIDIA GPU-enabled instance on AWS?
  • A.
  • B. Terraform cannot be used to provision GPU-enabled instances.
  • C.
  • D.
  • E. Use packer instead of Terraform.
Answer: A
Explanation:
Option A provides the correct Terraform configuration for provisioning a GPU-enabled instance on AWS. It uses the 'aws_instance' resource, specifies a GPU-enabled instance type (e.g., 'g4dn.xlarge'), and includes necessary tags. Other options are not valid or not correct syntax.

NEW QUESTION # 33
You are troubleshooting an issue where a container inside a pod is unable to access the NVIDIA GPU. The NVIDIA Device Plugin is running, and the pod is requesting 'nvidia.com/gpu: 1'. What are the potential causes for this issue?
  • A. The NVIDIA drivers are not correctly installed on the host node.
  • B. The NVIDIA Container Toolkit is not installed or configured properly.
  • C. The SELinux policy is preventing the container from accessing the GPU device.
  • D. The container image does not include the necessary NVIDIA libraries.
  • E. The GPU is already fully utilized by other pods on the node.
Answer: A,B,C,D
Explanation:
The correct answers are A, B, C, and D. Several factors can prevent a container from accessing the GPU. Incorrectly installed NVIDIA drivers (A) mean the device plugin cannot function. A misconfigured NVIDIA Container Toolkit (B) prevents the correct GPU passthrough. Missing NVIDIA libraries in the container image (C) lead to runtime errors. SELinux policies (D) can block device access. While E is possible, it usually leads to scheduling failures rather than the pod running without GPU access. The scheduler should prevent over-subscription.

NEW QUESTION # 34
You are deploying BCM on a Kubernetes cluster that utilizes a custom ingress controller What configuration changes might be necessary to ensure external access to the BCM web interface?
  • A. Update the BCM Helm chart to automatically configure the ingress controller.
  • B. Create a custom resource definition (CRD) for BCM in the ingress controller.
  • C. Modify the BCM service type to 'LoadBalancer'.
  • D. Disable the default ingress controller and use the custom ingress controller exclusively.
  • E. Configure the ingress controller to forward traffic to the BCM service on the appropriate port (typically 3000).
Answer: E
Explanation:
The primary configuration change required is to configure the ingress controller to forward traffic to the BCM service. This typically involves creating an ingress resource that defines the hostname and path for accessing the BCM web interface and maps it to the BCM service on the correct port (usually 3000). Changing the service type to 'LoadBalancer' might work, but it's less flexible and might not be compatible with all ingress controllers. Custom CRDs and disabling the default controller are generally unnecessary.

NEW QUESTION # 35
......
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