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NVIDIA NCP-AII Exam Syllabus Topics:

Topic	Details
Topic 1	System and Server Bring-up: Covers end-to-end physical setup of GPU-based AI infrastructure, including BMC OOB TPM configuration, firmware upgrades, hardware installation, and power and cooling validation to ensure servers are workload-ready.
Topic 2	Control Plane Installation and Configuration: Covers deploying the software stack including Base Command Manager, OS, Slurm Enroot Pyxis, NVIDIA GPU and DOCA drivers, container toolkit, and NGC CLI.
Topic 3	Troubleshoot and Optimize: Covers identifying and replacing faulty hardware components such as GPUs, network cards, and power supplies, along with performance optimization for AMD Intel servers and storage.
Topic 4	Physical Layer Management: Covers configuring BlueField network platform devices and setting up Multi-Instance GPU (MIG) partitioning for AI and HPC workloads.
Topic 5	Cluster Test and Verification: Covers full cluster validation through HPL and NCCL benchmarks, NVLink and fabric bandwidth tests, cable and firmware checks, and burn-in testing using HPL, NCCL, and NeMo.

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NVIDIA AI Infrastructure Sample Questions (Q68-Q73):

NEW QUESTION # 68
For an NVIDIA Enterprise Al Factory with 256 GPUs, which storage solution characteristic is most critical to validate during scaling tests?

A. Consistent per-node throughput ≥8 GiB/s.
B. RAID rebuild times under disk failure.
C. Maximum 4K random read IOPS exceeding 1 million.
D. Single-node write performance during idle clusters.

Answer: A

Explanation:
At 256 GPUs, the key storage scaling concern is whether every compute node can sustain the required throughput concurrently. Consistent per-node throughput of at least 8 GiB/s validates that the storage system can keep GPUs fed with training data at scale without becoming a bottleneck.

NEW QUESTION # 69
In a large-scale InfiniBand fabric, you need to implement a mechanism to prioritize traffic for a specific application that requires low latency and high bandwidth. You want to leverage Quality of Service (QOS) to achieve this. Which of the following steps are essential to properly configure QOS in this scenario? (Select THREE)

A. Disable Adaptive Routing (AR) to ensure that the application's traffic always takes the shortest path.
B. Configure VLAN tagging on the application's traffic to isolate it from other traffic.
C. Map the application's traffic to a specific traffic class with appropriate priority settings within the InfiniBand switches.
D. Configure Weighted Fair Queueing (WFQ) or Strict Priority Queueing on the egress ports of the InfiniBand switches to prioritize the application's traffic class.
E. Mark the application's traffic with appropriate DiffServ Code Point (DSCP) values.

Answer: C,D,E

Explanation:
Effective QOS requires traffic classification (DSCP marking), mapping to appropriate traffic classes with priority settings, and configuring queueing mechanisms (WFQ/Strict Priority Queueing) on egress ports to enforce the priority. VLAN tagging is useful for network segmentation but not directly for QOS. Disabling AR might reduce path diversity, but could also lead to congestion if the shortest path is already heavily utilized.

NEW QUESTION # 70
A BlueField-2 DPU is being used to accelerate storage access via NVMe-oF. You notice high CPU utilization on the host server, despite the DPU. What is the MOST likely cause and the MOST effective initial troubleshooting step?

A. Insufficient memory allocated to the BlueField DPIJ; Increase memory allocation via the BMC.
B. Firmware mismatch between the host NIC driver and the BlueField DPU firmware; Upgrade both to the latest compatible versions.
C. The host is still handling a significant portion of the 1/0 processing due to incorrect offload settings; Check the NVMe-oF initiator settings and verify that offload is enabled.
D. Incorrect NVMe-oF target configuration on the storage array; Check target NQN and discovery settings.
E. Incorrect RoCE configuration; Verify RoCE version and MTU settings using 'roce_util'.

Answer: C

Explanation:
The MOST likely cause of high host CPU utilization with a DPIJ accelerating NVMe-oF is that the host is still handling significant I/O processing. The initial step is to verify NVMe-oF initiator offload settings to ensure the DPIJ is actually handling the workload. Checking target configuration or RoCE, while important, wouldn't directly address high host CPU if the offload isn't working in the first place.

NEW QUESTION # 71
You've deployed a GPU-accelerated application in Kubernetes using the NVIDIA device plugin. However, your pods are failing to start with an error indicating that they cannot find the NVIDIA libraries. Which of the following could be potential causes of this issue? (Multiple Answers)

A. The application container image does not include the necessary NVIDIA libraries.
B. The 'nvidia-container-runtime' is not configured as the default runtime for Docker/containerd.
C. The NVIDIA drivers are not installed on the host node.
D. The GPU's compute capability is not sufficient for the workload.
E. The NVIDIA device plugin is not properly configured in the Kubernetes cluster.

Answer: A,B,C,E

Explanation:
If pods cannot find NVIDIA libraries, it could be because the drivers are missing on the host, the container runtime is not configured to use the NVIDIA runtime, the NVIDIA device plugin is misconfigured preventing GPU discovery and allocation, or the application container image does not include the NVIDIA libraries. E is likely incorrect, if the GPU's compute capability is insufficient then the app would likely start, but throw an error when trying to use the GPU.

NEW QUESTION # 72
You are tasked with updating the NVIDIA drivers on a cluster of servers running a critical A1 training workload. To minimize downtime and ensure a smooth transition, what is the best approach for performing the driver update?

A. Update the drivers only on the head node of the cluster, as the compute nodes will automatically inherit the new drivers.
B. Utilize a containerized approach with driver containers and orchestrate a rolling redeployment.
C. Perform a rolling update, updating one server at a time while migrating workloads to the remaining servers.
D. Simultaneously update the drivers on all servers in the cluster during a maintenance window.
E. Create a new cluster with the updated drivers and migrate the workload after thorough testing.

Answer: B,C,E

Explanation:
A rolling update minimizes downtime by updating servers one at a time. Creating a new cluster and migrating allows for thorough testing before impacting the production environment. Containerizing the driver and using rolling redeployments offers increased control and minimizes dependency issues. Simultaneously updating all servers results in significant downtime, and the head node's drivers are not automatically propagated to the compute nodes.

NEW QUESTION # 73
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