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NVIDIA AI Infrastructure Sample Questions (Q286-Q291):
NEW QUESTION # 286
You are planning the network infrastructure for a DGX SuperPOD. You need to ensure that the network fabric can handle the high bandwidth and low latency requirements of A1 training workloads. Which network technology is the RECOMMENDED choice for interconnecting the DGX nodes within the SuperPOD, and why?
Answer: A
Explanation:
InfiniBand is the recommended network technology for DGX SuperPODs due to its high bandwidth, low latency, and support for RDMA (Remote Direct Memory Access). RDMA allows GPIJs to directly access each other's memory without involving the CPU, significantly reducing latency and improving performance for distributed A1 training workloads. Ethernet, even at higher speeds, generally doesn't offer the same level of performance and RDMA capabilities as InfiniBand.
NEW QUESTION # 287
You are observing high latency in your GPU-accelerated inference service deployed on Kubernetes. You suspect that GPU resource contention might be the cause. What steps can you take to diagnose and mitigate this issue within the Kubernetes environment? (Multiple Answers)
Answer: A,C,D
Explanation:
Monitoring GPU utilization helps identify resource contention. Resource quotas prevent one namespace from consuming excessive GPU resources. MIG allows partitioning GPUs for workload isolation. Increasing replicas (option D) might help, but it doesn't address the underlying contention issue. Restarting the cluster is not a solution for ongoing contention.
NEW QUESTION # 288
An InfiniBand fabric is experiencing intermittent packet loss between two high-performance compute nodes. You suspect a faulty cable or connector. Besides physically inspecting the cables, what software-based tools or techniques can you employ to diagnose potential link errors contributing to this packet loss?
Answer: D
Explanation:
All of the mentioned options are valid techniques for diagnosing link errors. 'ibdiagnet' performs a thorough fabric analysis. Monitoring switch port counters reveals link-level errors. 'iperf/ibperf identifies packet loss, which can be correlated with switch error counters. A comprehensive approach combining these methods is most effective.
NEW QUESTION # 289
A user reports that their CUDA application is running slower than expected after an NVIDIA driver update. You suspect a driver compatibility issue. How can you revert to a previous NVIDIA driver version on an Ubuntu system, assuming you have the older driver package 'nvidia-driver-470 470.82.00-0ubuntu1_amd64.deb'?
Answer: C
Explanation:
The safest and most reliable approach is to first remove the current NVIDIA driver using 'sudo apt purge nvidia- to avoid conflicts. Then, install the .deb' package using 'sudo dpkg -i' and resolve any potential dependency issues with 'sudo apt -fix-broken install'. 'nvidia-smi' cannot downgrade drivers. Editing "/etc/apt/sources.list' can be risky and lead to system instability. Directly installing with 'dpkg -i' without purging the old driver can cause conflicts. If you installed with .run' before, then you must uninstall using that method first.
NEW QUESTION # 290
Which of the following commands correctly configures the NGC CLI to use a specific API key stored in an environment variable named 'NGC API KEY'?
Answer: B
Explanation:
The 'ngc config set' command uses '-apikey' to specify the API key directly. The correct syntax is 'ngc config set - to ensure the environment variable is properly expanded and passed as a string.
NEW QUESTION # 291
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