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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	Physical Layer Management: Covers configuring BlueField network platform devices and setting up Multi-Instance GPU (MIG) partitioning for AI and HPC workloads.
Topic 4	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 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 (Q144-Q149):

NEW QUESTION # 144
A cluster administrator is preparing to update the firmware on a DGX H100 system, including the GPU tray (baseboard). What is the correct sequence of steps to perform a safe and successful firmware upgrade?

A. Stop all GPU activity, update and reboot the BMC, update motherboard and tray components, perform a cold reset, and verify completion.
B. Update the GPU tray first, then the motherboard tray, and reboot the BMC after all updates are complete.
C. Update the BMC and skip the GPU tray and motherboard tray updates if the system appears healthy.
D. Perform a cold reset, stop all GPU activity, update and reboot the BMC, update motherboard and tray components, and verify completion.

Answer: A

NEW QUESTION # 145
After upgrading the NGC CLI using 'pip install -upgrade nvidia-cli' , some commands are no longer working as expected, producing errors related to missing modules. What is the most likely reason for this issue and how can you resolve it?

A. The upgrade process might have corrupted the NGC CLI installation. Reinstall the package using 'pip install -force-reinstall nvidia-cli'.
B. The Python environment used by the NGC CLI might be broken or inconsistent. Create a new virtual environment and reinstall the NGC CLI in the new environment.
C. The NGC CLI upgrade introduced breaking changes. Review the NGC CLI release notes and update your scripts accordingly.
D. The host's operating system must be re-imaged.
E. The system's PATH variable has not been updated to reflect the new NGC CLI installation location. Update the PATH variable accordingly.

Answer: B,C

Explanation:
Breaking changes in the NGC CLI upgrade (B) are a possibility, requiring script updates. An inconsistent Python environment (C) can also cause issues after an upgrade. Reinstalling (A) or updating the PATH (D) might not resolve the issue if the environment itself is the problem. OS re-imaging is highly unnecessary (E).

NEW QUESTION # 146
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. ibstat, then sminfo
B. sminfo, then smpquery NI
C. sminfo, then smpquery ND
D. ibnetdiscover, then ibsim

Answer: C

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 # 147
You've installed a DGX A100 server During the initial hardware validation, you observe that one of the GPUs is consistently reporting lower performance compared to the others. Which troubleshooting steps should you take, in the CORRECT order, to diagnose the problem?

A. 1. Check the power supply connections. 2. Check GPU temperature. 3. Reseat the GPIJ. 4. Run GPU diagnostics.
B. 1. Run GPU diagnostics. 2. Reseat the GPIJ. 3. Check GPU temperature. 4. Update the GPU driver.
C. 1. Reseat the GPU. 2. Check GPU temperature. 3. Update the GPU driver. 4. Run GPU diagnostics.
D. 1. Check GPU temperature. 2. Reseat the GPU. 3. Run GPU diagnostics. 4. Update the GPU driver.
E. 1. Update the GPU driver. 2. Run GPU diagnostics. 3. Check GPU temperature. 4. Reseat the GPIJ.

Answer: D

Explanation:
Checking temperature is crucial first to avoid damaging the GPU if it's overheating. Reseating addresses potential connectivity issues. Running diagnostics identifies hardware faults. Updating the driver should be done after hardware checks to ensure the card isn't faulty.

NEW QUESTION # 148
During East-West fabric validation on a 64-GPU cluster, an engineer runs all_reduce_perf and observes an algorithm bandwidth of 350 GB/s and bus bandwidth of 656 GB/s. What does this indicate about the fabric performance?

A. Critical failure; bus bandwidth exceeds hardware capabilities
B. Inconclusive; rerun with point-to-point tests
C. Optimal performance; bus bandwidth near theoretical peak for NDR InfiniBand
D. Suboptimal performance; algorithm bandwidth should match bus bandwidth

Answer: C

Explanation:
An all_reduce_perf result showing around 350 GB/s algorithm bandwidth and 656 GB/s bus bandwidth indicates strong collective communication performance for a 64-GPU NDR InfiniBand fabric. The bus bandwidth being near the expected peak confirms the East-West fabric is performing optimally and GPUDirect RDMA paths are healthy.

NEW QUESTION # 149
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