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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	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 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	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 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 (Q113-Q118):

NEW QUESTION # 113
A system administrator installed a new GPU. The system has booted but the GPU is not recognized by the OS. What is likely missing?

A. OFED driver
B. cache drives
C. CPU driver
D. scheduler

Answer: A

Explanation:
If newly installed NVIDIA hardware is not recognized properly by the operating system, the required NVIDIA/Mellanox driver stack must be present. The OFED driver package provides the low-level support needed for supported NVIDIA networking/accelerated hardware to be detected and used correctly.

NEW QUESTION # 114
A team is validating a DGX BasePOD deployment. Using cmsh, they run a command to check GPU health across all nodes. What indicates that the system is ready for AI workloads?

A. At least half of the GPUs report Status_Health = OK
B. The command output is ignored if the system powers on without errors.
C. All GPUs report Status_Health = OK and Health = OK for each device.
D. Only the head node's GPUs need to be healthy.

Answer: C

Explanation:
A DGX BasePOD is ready for AI workloads only when GPU health checks pass across the cluster. Seeing Status_Health = OK and Health = OK for every GPU confirms that all GPU devices are detected, healthy, and available for workload scheduling.

NEW QUESTION # 115
You are replacing a faulty NVIDIA Tesla V 100 GPU in a server. After physically installing the new GPU, the system fails to recognize it. You've verified the power connections and seating of the card. Which of the following steps should you take next to troubleshoot the issue?

A. Reinstall the operating system to ensure proper driver installation.
B. Immediately RMA the new GPU as it is likely defective.
C. Check if the new GPU requires a different driver version than the currently installed one and update if needed.
D. Disable and re-enable the GPU slot in the system BIOS.
E. Update the system BIOS and BMC firmware to the latest versions.

Answer: C,E

Explanation:
After verifying the physical installation, the next steps are to ensure the system's firmware is up-to-date and that the correct drivers are installed. Older BIOS/BMC firmware may not properly recognize newer GPUs, and incorrect drivers will prevent the GPU from functioning correctly. RMAing the new GPU or reinstalling the OS prematurely are inefficient troubleshooting steps. The system BIOS may have an option to disable and enable the GPU slot, but that would be rare.

NEW QUESTION # 116
You are tasked with installing a DGX A100 server. After racking and connecting power and network cables, you power it on, but the BMC (Baseboard Management Controller) is not accessible via the network. You have verified the network cable is connected and the switch port is active. What are the MOST likely causes and initial troubleshooting steps you should take?

A. The network switch port is not configured for the correct VLAN. Verify the switch port configuration to ensure it is on the same VLAN as the BMC.
B. The BMC IP address is not configured or is on a different subnet. Check the BMC's network configuration using the DGX's front panel or via serial console. Verify DHCP is enabled and functioning or manually configure a static IP address.
C. The BMC is not powered on because the main power supply is faulty. Verify the power supply LEDs are lit and providing power to the system.
D. The BMC firmware is corrupted and needs to be reflashed using a USB drive. Check the DGX support site for the latest BMC firmware.
E. The BMC is faulty and needs to be replaced. Contact NVIDIA support for RMA.

Answer: A,B

Explanation:
The most likely causes are network configuration issues (incorrect IP, subnet, or VLAN). The BMC requires a valid IP configuration and network connectivity to be accessible. While other options are possible, they are less common as initial causes.

NEW QUESTION # 117
Consider the following simplified CUDA code snippet intended to perform a vector addition:
What are critical steps to validate that this code is correctly utilizing the GPU hardware and producing accurate results?

A. All of the above
B. Run the code with 'cuda-memchecK to detect memory access errors or race conditions.
C. Ensure that 'blocksPerGrid' and 'threadsPerBlock' are appropriately chosen to maximize GPU occupancy, potentially using the NVIDIA CUDA Occupancy Calculator.
D. Use 'cudaDeviceSynchronize()' after launching the kernel to ensure the GPU computations are complete before copying data back to the host.
E. After the 'cudaMemcpy' from device to host, compare the 'c' array to a CPU-based vector addition result to verify correctness.

Answer: A

Explanation:
All options highlight important validation steps. Optimizing block/thread configuration maximizes GPU utilization. Verifying results against a CPU-based calculation ensures correctness. 'cudaDeviceSynchronize()' guarantees GPU computations are finished before data transfer. 'cuda-memcheck' detects memory errors. Failing to do any of these could lead to subtle errors or performance bottlenecks.

NEW QUESTION # 118
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