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NVIDIA AI Infrastructure Sample Questions (Q163-Q168):
NEW QUESTION # 163
During NVLink Switch configuration, you encounter issues where certain GPUs are not being recognized by the system. Which of the following troubleshooting steps are most likely to resolve this problem?
Answer: B,D,E
Explanation:
Explanation:Physical connection issues (A), BIOS configuration (B), and firmware incompatibility (C) are the most common causes of GPUs not being recognized. Reinstalling the operating system is a drastic measure that is unlikely to solve the problem. Checking the Power supply may also required to ensure the complete system have enough capacity and stability.
NEW QUESTION # 164
You are configuring a network bridge on a Linux host that will connect multiple physical network interfaces to a virtual machine. You need to ensure that the virtual machine receives an IP address via DHCP. Which of the following is the correct command sequence to create the bridge interface 'br0', add physical interfaces 'eth0' and 'eth1' to it, and bring up the bridge interface? Assume the required packages are installed. Consider using 'ip' command.
Answer: A
Explanation:
Option D is the correct sequence using the Sip' command. First, create the bridge ' bro'. Then, add the physical interfaces 'eth0 and "eth1' as slaves to the bridge. Next, bring up the physical interfaces. After that, bring up the bridge interface . Finally, use "dhclient bro to obtain an IP address for the bridge via DHCP. Option C is the old way, using 'brctr and 'ifconfig', which are deprecated. The others lack the crucial step of bringing up the bridge after attaching the physical interfaces and before running 'dhclient'.
NEW QUESTION # 165
You've deployed a GPU-accelerated application in Kubernetes using the NVIDIA device plugin. However, your pods are failing to start with an error indicating that they cannot find the NVIDIA libraries. Which of the following could be potential causes of this issue? (Multiple Answers)
Answer: A,C,D,E
Explanation:
If pods cannot find NVIDIA libraries, it could be because the drivers are missing on the host, the container runtime is not configured to use the NVIDIA runtime, the NVIDIA device plugin is misconfigured preventing GPU discovery and allocation, or the application container image does not include the NVIDIA libraries. E is likely incorrect, if the GPU's compute capability is insufficient then the app would likely start, but throw an error when trying to use the GPU.
NEW QUESTION # 166
You are designing a large-scale AI training cluster spanning multiple racks. The networking topology necessitates both short-reach (within rack) and long-reach (inter-rack) connections. Which combination of cable types and transceivers is MOST cost-effective and suitable for this scenario, assuming a mix of 200GbE and 400GbE links?
Answer: B
Explanation:
DAC cables are cost-effective and suitable for short-reach, high-bandwidth connections within a rack. For inter-rack connections, SR4 transceivers with multimode fiber (for shorter inter-rack links) and LR4 transceivers with single-mode fiber (for longer inter-rack links) provide a good balance of cost and performance. AOCs are generally more expensive than DACs. ER4 is overkill for many inter-rack scenarios and is more expensive than LR4.
NEW QUESTION # 167
You're troubleshooting a DGX-I server exhibiting performance degradation during a large-scale distributed training job. 'nvidia-smu shows all GPUs are detected, but one GPU consistently reports significantly lower utilization than the others. Attempts to reschedule orkloads to that GPU frequently result in CUDA errors. Which of the following is the MOST likely cause and the BEST initial roubleshooting step?
Answer: B
Explanation:
While all options are possibilities, the consistently lower utilization and CUDA errors point strongly to a hardware fault. Running nvidia-smi -i -q' provides detailed telemetry data, including temperature, power limits, and ECC error counts, which are crucial for diagnosing GPU hardware issues.
NEW QUESTION # 168
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