[Sep-2025] NCP-AIO Pre-Exam Practice Tests Exam Questions and Answers for NVIDIA-Certified Professional Study Guide [Q33-Q57]

QUESTION 33
What is the primary purpose of using a container runtime interface (CRI) with BCM and Kubernetes in an AI environment?

QUESTION 34
When using GPUDirect RDMA for inter-GPU communication, what component MUST be supported by the network interface card (NIC) to ensure optimal performance?

QUESTION 35
Consider the following Dockerfile snippet:

QUESTION 36
You observe that ‘nvsm’ is consuming a significant amount of CPU resources, even when the system is idle. You suspect that the high CPU usage is due to excessive logging. How can you reduce the logging verbosity of ‘nvsm’?

QUESTION 37
You are deploying a Deep Learning model as a service using Triton Inference Server within a VMI container on Google Cloud Platform (GCP). You want to leverage TensorRT for optimized inference performance. Which of the following steps are necessary to ensure TensorRT is properly configured and used?

QUESTION 38
You are using CUDA-Aware MPI for a distributed deep learning training job. After implementing CUDA-Aware MPI, you observe no performance improvement compared to regular MPI. What is the MOST likely reason?

QUESTION 39
You are managing a Kubernetes cluster running GPU-accelerated AI workloads. You need to ensure that sensitive data, such as API keys and database credentials, used by these workloads is securely managed and accessible only to authorized pods. What are the best practices and Kubernetes features for achieving this?

QUESTION 40
You want to upgrade your BCM installation to the latest version. What is the recommended approach for upgrading BCM in a production environment?

QUESTION 41
An organization has multiple containers and wants to view STDIN, STDOUT, and STDERR I/O streams of a specific container.
What command should be used?

QUESTION 42
You are managing an on-premises cluster using NVIDIA Base Command Manager (BCM) and need to extend your computational resources into AWS when your local infrastructure reaches peak capacity.
What is the most effective way to configure cloudbursting in this scenario?

QUESTION 43
Describe a scenario where using MIG (Multi-lnstance GPU) on an NVIDIAAI 00 GPU within a Kubernetes cluster would be most beneficial. Explain why MIG is advantageous in that specific use case.

QUESTION 44
You are deploying a stateful application to your Kubernetes cluster running on NVIDIA hardware provisioned through BCM. This application requires direct access to a persistent volume on a high-performance NVMe drive. Which of the following methods is MOST appropriate for providing this access while ensuring high performance and data consistency?

QUESTION 45
When deploying BCM using Helm, which Helm chart parameter controls the resource limits for the BCM pods (CPU and Memory)?

QUESTION 46
You are tasked with deploying a deep learning framework container from NVIDIA NGC on a stand-alone GPU-enabled server.
What must you complete before pulling the container? (Choose two.)

QUESTION 47
A user reports that their AI training job running on a BCM-managed cluster is experiencing slow 1/0 performance. What steps would you take to diagnose and resolve the issue, considering the potential involvement of storage?

QUESTION 48
A data scientist reports that a Run.ai job is consistently crashing with a ‘SIGKILL’ signal. After verifying that the job is not exceeding its resource limits (CPU, memory, GPU), what is the MOST likely reason for this signal, and how can you diagnose it further within the Run.ai environment?

QUESTION 49
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?

QUESTION 50
You are using BCM to manage a Kubernetes cluster with multiple GPU nodes. You need to enable GPU monitoring using Prometheus and the NVIDIA DCGM exporter. Outline the steps required to accomplish this. Choose the correct sequence:

QUESTION 51
You need to configure BCM to send alerts when a GPU’s temperature exceeds a critical threshold. Where would you configure this alerting policy within BCM?

QUESTION 52
You need to monitor the GPU utilization of individual MIG instances on your NVIDIAA100 GPU. Which of the following tools or methods can provide granular monitoring data for each MIG instance?

QUESTION 53
You are deploying a PyTorch container from NGC that utilizes Tensor Cores. How can you verify that Tensor Cores are being effectively used during inference?

QUESTION 54
You’re using Kubernetes with persistent volumes (PVs) backed by a network file system (NFS) to store your AI model checkpoints. You’ve noticed that checkpoint saving operations are slow and intermittently fail. After investigation, you suspect that the issue might be related to NFS locking. How can you diagnose and potentially resolve this issue?

QUESTION 55
You are tasked with deploying a TensorFlow container from NGC on a Kubernetes cluster. The container requires specific NVIDIA drivers and libraries. Which of the following steps are essential to ensure successful deployment and GPU utilization?

QUESTION 56
You have a Run.ai cluster integrated with NVIDIA’s Cluster Manager (ACM). A data scientist reports that their job is being preempted frequently, even though they have a high-priority quot a. What are the MOST likely reasons for this preemption, assuming ACM is configured correctly?

QUESTION 57
After updating the NVIDIA drivers on your NVSwitch-connected GPU server, ‘nvsm’ fails to start. The log file shows the following error: ‘Failed to initialize NVML’. Which of the following actions is MOST likely to resolve the issue?