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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: GPU Resource Management | 15% | - Multi-Instance GPU (MIG) configuration
|
| Topic 2: Software Stack Deployment | 25% | - NVIDIA software components
|
| Topic 3: System and Server Bring-up | 20% | - Hardware installation and validation
|
| Topic 4: Networking and Storage Configuration | 20% | - Storage integration
|
| Topic 5: Validation, Troubleshooting and Optimization | 20% | - Troubleshooting and maintenance
|
>> Exam NVIDIA NCP-AII Duration <<
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NEW QUESTION # 163
A system administrator needs to install a container toolkit and successfully run the following commands:
sudo apt-get update
sudo apt-get install -y nvidia-container-toolkit
sudo nvidia-ctk runtime configure --runtime docker
What step should be taken next to finish the installation?
Answer: C
Explanation:
The nvidia-ctk runtime configure command is a crucial step that modifies the Docker daemon configuration file (/etc/docker/daemon.json) to register the nvidia runtime. However, the Docker daemon only reads this configuration file during its initialization phase. Even though the toolkit is installed and the configuration file is updated, Docker will not be able to spawn GPU-accelerated containers until the service is refreshed.
Executing sudo systemctl restart docker (or the equivalent for your container engine) is the mandatory final step. This forces Docker to reload its settings and recognize the NVIDIA Container Runtime as a valid option.
Without this restart, attempting to run a container with the --gpus all flag will result in an error stating that the
"nvidia" runtime is not found or is unconfigured. This is a common point of failure in automated AI infrastructure deployments where the configuration script finishes, but the service state remains stale.
NEW QUESTION # 164
When installing multiple NVIDIA GPUs, which of the following factors are MOST important to consider regarding PCIe slot configuration?
(Choose two)
Answer: C,E
Explanation:
The number of PCIe lanes directly impacts bandwidth. Direct CPU connection minimizes latency. Slot color and numbering are usually irrelevant. Same PCIe Gen isn't critical as long as minimum requirements are met.
NEW QUESTION # 165
A network engineer is tasked with configuring the management, storage, and compute networks for a new DGX BasePOD deployment. Which statement best describes the network segmentation required for optimal operation?
Answer: A
Explanation:
NVIDIA DGX BasePOD and SuperPOD reference architectures mandate strict network segmentation to ensure performance, security, and manageability.
* Compute Network: Typically InfiniBand (or high-speed Spectrum-X Ethernet), dedicated solely to GPU-to-GPU collective communications (NCCL).
* Storage Network: A high-bandwidth Ethernet or InfiniBand fabric specifically for data ingestion and model checkpointing, often utilizing GPUDirect Storage (GDS).
* Management Network: Used for standard cluster administration, SSH, and software orchestration (e.g., Bright Cluster Manager or Kubernetes control plane traffic).
* Out-of-Band (OOB) Network: A physically isolated network connected to the BMC ports for low-level system monitoring, power control, and remote console access, even when the OS is down.
A single VLAN (Option A) would cause massive congestion during training, as storage and management traffic would compete with high-frequency compute packets. The four-network model ensures that a " storm " in the storage fabric does not prevent an administrator from accessing the system via the management or OOB networks, which is essential for maintaining an AI Factory at scale.
NEW QUESTION # 166
A user needs to configure NGC CLI to access resources across multiple organizations. What is the recommended command syntax to achieve this?
Answer: C
Explanation:
ngc config set --org org-name --ace ace-name configures the NGC CLI context for a specific organization and ACE, allowing the user to access resources associated with multiple organizational contexts.
NEW QUESTION # 167
During the setup of a new GPU cluster, you want to validate the GPUs to ensure they meet performance and reliability standards. What would demonstrate performance standards are met?
Answer: A
Explanation:
DCGM diagnostics and gpu-burn validate GPU reliability and performance under sustained load.
These tools stress the GPUs, monitor health and error conditions, and help confirm that the devices can operate within expected performance and stability standards before production use.
NEW QUESTION # 168
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