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NVIDIA AI Infrastructure Sample Questions:

1. After successfully installing the NVIDIA Container Toolkit and configuring the Docker runtime, you attempt to run a container that requires GPU access. However, the container fails to start with an error indicating that no GPUs are detected. You've verified that 'nvidia-smi' works on the host. Which of the following could be potential causes for this issue? (Select all that apply)

A) The NVIDIA drivers are not compatible with the kernel version running on the host.
B) The '-gpus all' flag was not included when running the 'docker run' command.
C) The NVIDIA Container Toolkit package is corrupted and needs to be reinstalled.
D) The Docker daemon was not restarted after configuring the NVIDIA runtime.
E) The container image itself is missing the necessary CUDA libraries.

2. You're optimizing an AMD EPYC server with 4 NVIDIAAIOO GPUs for a large language model training workload. You observe that the GPUs are consistently underutilized (50-60% utilization) while the CPUs are nearly maxed out. Which of the following is the MOST likely bottleneck?

A) The storage system (SSD/NVMe) is too slow, leading to data starvation.
B) Insufficient CPU cores to prepare and feed data to the GPUs.
C) The NCCL (NVIDIA Collective Communications Library) is not properly configured for inter-GPU communication.
D) The PCle interconnect between the CPUs and GPUs is saturated.
E) The system RAM is too small, causing excessive swapping.

3. Which of the following statements regarding the benefits of using a BlueField DPU for network offload are TRUE? (Select TWO)

A) Simplified network configuration compared to traditional NICs.
B) Reduced CPU utilization on the host server for network-related tasks.
C) Elimination of the need for a dedicated network interface card (NIC).
D) Automatic compatibility with all existing network protocols without requiring software updates.
E) Increased network throughput due to hardware acceleration.

4. Consider an AMD EPYC-based server with 8 NVIDIAAIOO GPUs connected via PCle Gen4. You're running a distributed training job using Horovod. You've noticed that communication between GPUs is a bottleneck. Which of the following NCCL configuration options would be MOST beneficial in this scenario? (Assume all options are syntactically correct for NCCL).

A) NCCL SOCKET IF-NAME=eth0
B) NCCL NET PLUGIN=none
C) NCCL P2P DISABLE-0
D) NCCL IB HCA=mlx5 0
E) NCCL IB DISABLE-1

5. You are troubleshooting a network performance issue in your NCP-AII environment. After running 'ibstat' on a host, you see the following output for one of the InfiniBand ports:

What does the 'LMC: 0' indicate, and what are the implications for network performance?

A) LMC: 0 indicates that the link is down and not functioning correctly.
B) LMC : 0 is the default and expected value; it has no impact on performance.
C) LMC : 0 indicates that the Subnet Manager is not running correctly.
D) LMC: 0 indicates that Link Aggregation (LAG) is not enabled on this port, meaning only a single link is being used for communication.
E) LMC : 0 indicates the port is operating at the lowest possible speed.

Solutions: