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| Section | Weight | Objectives |
|---|---|---|
| Networking and Storage Configuration | 20% | - NVIDIA networking solutions
|
| System and Server Bring-up | 20% | - Firmware and system configuration
|
| GPU Resource Management | 15% | - GPU scheduling and optimization
|
| Validation, Troubleshooting and Optimization | 20% | - Troubleshooting and maintenance
|
| Software Stack Deployment | 25% | - NVIDIA software components
|
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NEW QUESTION # 46
A customer has just completed the first boot of their DGX system and is prompted to create an administrative user. What is the correct approach for setting up this user to ensure secure BMC and GRUB access?
Answer: A
Explanation:
During the initial "first boot" setup of an NVIDIA DGX system (such as the DGX H100 or A100), the installation wizard requires the creation of a primary administrative user. This account is pivotal because it is used not only for local OS login but is also synchronized to provide access to the Baseboard Management Controller (BMC) and the GRUB bootloader. NVIDIA best practices emphasize security by mandating the use of a unique, strong password. Using a lower-case username is a standard Linux convention that ensures compatibility across various authentication services. By setting this up correctly during the first boot, the system ensures that "out-of-band" management (via BMC) and "pre-boot" configuration (via GRUB) are protected from unauthorized access. Relying on default credentials (Option B) or weak passwords (Option D) is a significant security risk in AI infrastructure, as the BMC often has high-level control over power, firmware, and remote console access.
NEW QUESTION # 47
You have installed the NVIDIA Container Toolkit and are attempting to run a container with GPU support. However, the 'docker run' command fails with an error indicating that the NVIDIA runtime is not found. You have already verified that the NVIDIA Container Toolkit is installed, and the Docker daemon has been restarted. What is the most likely cause of this error?
Answer: D
Explanation:
The most likely cause is an issue with the S/etc/docker/daemon.json' file (A). This file configures Docker's runtime settings, including specifying the NVIDIA runtime. If the file is missing or has incorrect entries, Docker will not be able to find the NVIDIA runtime. While driver incompatibility (B) can cause issues, it typically manifests as runtime errors within the container, not a failure to find the runtime itself. 'nvidia- container-runtime' might be a required package depending on the installation method. A missing GPU is unlikely since the Toolkit would likely fail to install, although this is also an error that can prevent the NVIDIA runtime from being started.
NEW QUESTION # 48
You are configuring a switch port connected to a host in an NCP-AII environment. The host is running RoCEv2. To optimize performance and prevent packet loss, which flow control mechanism should you enable on the switch port?
Answer: B
Explanation:
Priority Flow Control (PFC), also known as 802.1Qbb, is the appropriate flow control mechanism for RoCEv2. RoCEv2 is a lossless Ethernet protocol, and PFC allows you to enable flow control on specific traffic classes, preventing packet loss in congested situations. By enabling PFC specifically for the traffic class carrying RoCEv2 traffic, you ensure that high-priority A1 training data is delivered reliably without being affected by congestion on other parts of the network.
NEW QUESTION # 49
You are designing a network for a distributed training job utilizing multiple GPUs across multiple nodes. Which network characteristic is MOST critical for minimizing training time?
Answer: A,C,E
Explanation:
Distributed training involves frequent data exchange between GPUs. High bandwidth is necessary to move large datasets quickly. Low latency reduces the round-trip time for communication. Large MTIJ (Maximum Transmission Unit) can reduce overhead by transmitting larger packets. High packet loss is detrimental to performance. Low cost should not be prioritized over performance in a distributed training environment.
NEW QUESTION # 50
An infrastructure engineer in an AI factory has successfully replaced a power supply unit on an NVIDIA DGX H100. After installation, both the IN and OUT LEDs on the new power supply illuminate solid green.
Which NVSM CLI command should the engineer use to quickly verify the overall system status and ensure it is operating as expected?
Answer: C
Explanation:
The NVIDIA System Management (NVSM) tool is the definitive CLI utility for monitoring the health of DGX platforms. While replacing a PSU (Power Supply Unit) is a common maintenance task, verifying that the new component is correctly integrated into the system's health model is mandatory. While nvsm show power would provide specific data regarding wattage and voltage for the PSU, the most comprehensive way to ensure the replacement hasn't caused secondary issues or that the system hasn't remained in a "Degraded" state is to run nvsm show health. This command performs a global check across all subsystems: GPUs, NVLink switches, storage, fans, and power. If the PSU replacement was successful and the system is back to full redundancy, nvsm show health will return a "Healthy" status. In an AI factory setting, where DGX H100 nodes pull significant power, ensuring that all 6 PSUs (in an N+N or N+1 configuration) are not only physically green but logically acknowledged by the Baseboard Management Controller (BMC) is critical for preventing unexpected shutdowns during high-load training iterations.
NEW QUESTION # 51
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