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NVIDIA NCP-AII Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 3	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.
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	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.

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NVIDIA AI Infrastructure Sample Questions (Q168-Q173):

NEW QUESTION # 168
ClusterKit's NCCL bandwidth test shows 350 GB/s on a 400G InfiniBand fabric. How should this result be interpreted?

A. Inconclusive; rerun with --stress=cpu to validate.
B. Suboptimal performance; requires FEC tuning to reach 380+ GB/s.
C. Critical failure; expected is ≥390 GB/s for HDR InfiniBand
D. Optimal performance, indicating healthy fabric and GPUDirect RDMA

Answer: D

Explanation:
A 350 GB/s NCCL bandwidth result on a 400G InfiniBand fabric indicates strong collective communication performance. This is consistent with a healthy fabric and effective GPUDirect RDMA operation during ClusterKit validation.

NEW QUESTION # 169
You have installed an NVIDIA ConnectX-7 network adapter in an A1 server and configured RDMA over Converged Ethernet (RoCE). During validation, you observe very high latency between two servers communicating over RoCE. Which of the following are potential causes? (Choose two)

A. Insufficient memory on the network adapter.
B. The network switch does not support RoCE.
C. The GPU driver is outdated.
D. The network cables are damaged.
E. Incorrect MTU size configuration on the network interfaces.

Answer: B,E

Explanation:
RoCE requires specific switch support and a properly configured MTU. Damaged cables could cause packet loss, but usually not consistently high latency. GPU drivers are irrelevant. Network adapter memory is unlikely to cause high latency unless extremely undersized, a less likely scenario than incorrect configuration or lack of RoCE support.

NEW QUESTION # 170
A user needs to configure NGC CLI to access resources across multiple organizations. What is the recommended command syntax to achieve this?

A. export NGC_CLI_ORG=org-name && ngc config set
B. ngc config list to manually edit the JSON configuration file.
C. ngc config set --org org-name --ace ace-name
D. ngc registry login --org org-name

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 # 171
What is the primary purpose of running a NCCL burn-in test on a new GPU cluster?

A. To benchmark the application-specific runtime performance of AI models using real user data and production training scripts.
B. To detect and resolve hardware or interconnect issues before production, by stressing GPU communication links.
C. To maximize the GPU utilization for machine learning workloads and to automatically tune deep learning frameworks.
D. To test if GPUs are properly detected by the operating system and have the right drivers installed.

Answer: B

Explanation:
NCCL burn-in stresses GPU-to-GPU communication paths across NVLink, PCIe, and the network fabric. Its main purpose is to expose hardware, cabling, fabric, GPUDirect RDMA, or interconnect stability issues before the cluster is released for production workloads.

NEW QUESTION # 172
What command sequence is used to identify the exact name of the server that runs as the master SM in a multi-node fabric?

A. sminfo, then smpquery ND
B. sminfo, then smpquery NI
C. ibstat, then sminfo
D. ibnetdiscover, then ibsim

Answer: A

Explanation:
In an InfiniBand fabric, the Subnet Manager (SM) is the "brain" of the network, responsible for discovering the topology, assigning Local Identifiers (LIDs), and calculating routing tables. In a multi-node fabric, there is typically one Master SM and several Standby SMs for high availability. To identify the master, the sminfo command is first used; it queries the fabric and returns the LID of the current Master SM. Once the LID is obtained, the engineer must map that numerical LID to a physical server name or Node Description. The smpquery ND (Node Description) command is then executed, targeting that specific LID. This sequence is vital for troubleshooting fabric-wide issues, as logs on the Master SM server provide the definitive record of sweeps, traps, and topology changes. Using smpquery NI (Node Info) would provide hardware-level details like the GUID and device ID, but it does not return the human-readable string (server name) defined in the Node Description, which is necessary for rapid identification in a crowded data center.

NEW QUESTION # 173
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