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| 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 | - 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 | - 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 4 | - 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 5 | - Physical Layer Management: Covers configuring BlueField network platform devices and setting up Multi-Instance GPU (MIG) partitioning for AI and HPC workloads.
|
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NVIDIA AI Infrastructure Sample Questions (Q32-Q37):
NEW QUESTION # 32
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?
- A. A single VLAN for all types of network traffic.
- B. Two networks: one for management and one for compute.
- C. Four networks: compute, storage, out-of-band, and management.
Answer: C
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 # 33
You are deploying a BlueField-3 DPU within a secure environment. You are required to enable secure boot to prevent unauthorized firmware from being loaded. Which steps are typically involved in enabling secure boot on a BlueField-3 DPU, starting from a factory- default state? (Select TWO)
- A. Generate cryptographic keys and enroll them in the DPIJ's IJEFI firmware using tools provided by NVIDIA or Mellanox.
- B. Update the DPU's BMC firmware to the latest version.
- C. Flash the BlueField-3 DPIJ with a secure boot-enabled OS image that is signed with the enrolled keys.
- D. Install the latest version of the Mellanox OFED drivers on the host server.
- E. Configure the server's BIOS to enable UEFI boot mode.
Answer: A,C
Explanation:
The crucial steps are generating and enrolling cryptographic keys in the DPIJ's UEFI firmware, which establishes the chain of trust, and flashing the DPIJ with a secure boot-enabled OS image signed with those keys. Without these, secure boot won't function correctly. While updating the BMC firmware (E) is generally a good practice, and enabling IJEFI boot mode in the server's BIOS (C) is necessary for UEFI in general, they are not specific steps for enabling secure boot on the DPIJ itself . Installing host drivers (A) is also irrelevant to secure boot.
NEW QUESTION # 34
An engineer needs to validate NVLink Switch functionality on a DGX H100 system with 8 GPUs. Which NCCL command verifies intra-node NVLink bandwidth?
- A. all_reduce_perf -b 8 -e 16G -f 2 -g 4 with NCCL_TESTS_SPLIT="MOD 2"
- B. broadcast_perf -b 8 -e 16G -f 2 -g 8 without split configuration
- C. all_reduce_perf -b 8 -e 16G -f 2 -g 8 with NCCL_TESTS_SPLIT="OR 0x7"
- D. all_reduce_perf -b 8 -e 16G -f 2 -g 1 repeated 8 times
Answer: C
Explanation:
The NVIDIA Collective Communications Library (NCCL) "Tests" are used to verify the maximum achievable bandwidth of the interconnects. On a DGX H100, the GPUs are connected via a dedicated high- bandwidthNVLink Switch fabric(NVLink 4), which provides significantly higher throughput than PCIe. To validate the intra-node (within a single server) performance, the all_reduce_perf test is used. The command in Option D is specifically designed to stress all 8 GPUs (-g 8) across a wide range of message sizes (8 bytes to
16G). The use of the environment variable NCCL_TESTS_SPLIT with the bitwise "OR" or "AND" masks allows the engineer to isolate specific traffic patterns or groups of GPUs to ensure the NVLink switches are distributing the load evenly. For a standard 8-GPU H100 tray, achieving a "Bus Bandwidth" of ~450 GB/s to
900 GB/s (depending on the precision and message size) confirms that the NVLink fabric is operating at its theoretical peak. Using only 4 GPUs (Option B) or 1 GPU (Option C) would not provide a complete picture of the NVLink switch bisection bandwidth.
NEW QUESTION # 35
An administrator notices that a server is not collecting telemetry data such as traffic flows, performance faults, and events. In which network does this information flow?
- A. In-band management
- B. Storage
- C. Compute
- D. InfiniBand management
Answer: D
Explanation:
Telemetry such as fabric traffic flows, performance counters, faults, and events is collected through the InfiniBand management path. If this data is not being collected, the InfiniBand management network should be checked for connectivity, configuration, and service issues.
NEW QUESTION # 36
You're setting up a cluster with 8 NVIDIA A100 GPUs. Each GPU needs to read 4GB/s from storage to keep it fully utilized. The network connecting the storage and compute nodes has a bandwidth of 25GB/s. What is the maximum number of GPUs that can be simultaneously saturated with data without exceeding the network bandwidth?
Answer: A
Explanation:
Each GPU requires 4GB/s of bandwidth. The network has a bandwidth of 25GB/s. Therefore, the maximum number of GPUs that can be saturated is 25GB/s / 4GB/s per GPU = 6.25 GPUs. Since you can't have a fraction of a GPU, the answer is 6 GPUs.
NEW QUESTION # 37
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