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NVIDIA AI Infrastructure Sample Questions:

1. You encounter a situation where a container running with GPU support is experiencing significant performance degradation compared to running the same application directly on the host. You have already verified that the NVIDIA drivers are correctly installed and the NVIDIA Container Toolkit is properly configured. Which of the following could be contributing factors to this performance difference?
(Select all that apply)

A) The container is using a significantly older version of the CUDA runtime compared to the host.
B) The '-ipc=host' flag is not used when running the container, causing inter-process communication overhead.
C) CPU pinning or NIJMA affinity is not properly configured for the container, leading to inefficient memory access.
D) The kernel version within the container is significantly different from the host kernel, leading to driver compatibility issues.
E) Insufficient bandwidth between CPU and GPU

2. You are setting up a virtualized environment (using VMware vSphere) to run GPU-accelerated workloads. You have multiple physical GPUs in your server and want to assign specific GPUs to different virtual machines (VMs) for dedicated access. Which vSphere technology would BEST support this?

A) VMware High Availability (HA)
B) VMware vMotion
C) VMware DirectPath I/O (Passthrough)
D) VMware vGPU
E) VMware DRS (Distributed Resource Scheduler)

3. 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?

A) High bandwidth
B) Large MTU
C) Low cost
D) High packet loss rate
E) Low latency

4. You are using MIG (Multi-lnstance GPU) on an NVIDIAAI 00 GPU within a Kubernetes cluster. You want to configure a pod to use a specific MIG instance. How do you define the GPU resource request in the pod's YAML definition?

A) Using the annotation 'nvidia.com/gpu.product' and the value of the particular GPU device you desire.
B) Specify the full GPU ID (e.g., 'nvidia.com/gpu: 1') in the resource request.
C) Specify the MIG device profile name (e.g., 'nvidia.com/mig-l g.7gb: 1 in the resource request.
D) Use a custom resource definition (CRD) to define MIG instances and reference it in the resource request.
E) Use a generic resource request like 'nvidia.com/gpu: 0.125' to allocate a portion of the GPIJ.

5. You've installed a DGX A100 server During the initial hardware validation, you observe that one of the GPUs is consistently reporting lower performance compared to the others. Which troubleshooting steps should you take, in the CORRECT order, to diagnose the problem?

A) 1. Update the GPU driver. 2. Run GPU diagnostics. 3. Check GPU temperature. 4. Reseat the GPIJ.
B) 1. Check GPU temperature. 2. Reseat the GPU. 3. Run GPU diagnostics. 4. Update the GPU driver.
C) 1. Reseat the GPU. 2. Check GPU temperature. 3. Update the GPU driver. 4. Run GPU diagnostics.
D) 1. Run GPU diagnostics. 2. Reseat the GPIJ. 3. Check GPU temperature. 4. Update the GPU driver.
E) 1. Check the power supply connections. 2. Check GPU temperature. 3. Reseat the GPIJ. 4. Run GPU diagnostics.

Solutions: