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NVIDIA AI Infrastructure Sample Questions:
1. You are developing a distributed deep learning application that uses multiple GPUs across several Docker containers running on different physical servers. How do you ensure that each container can access and utilize the GPUs on its respective host?
A) Use Docker Swarm and specify GPU resource constraints in the 'docker-compose.yml' file to allocate GPUs to each service.
B) Ensure the NVIDIA Container Toolkit is installed and configured on each host machine, and use a container orchestration platform like Kubernetes to manage the deployment and GPU assignment.
C) Install the same version of NVIDIA drivers on all host machines and configure a network file system (NFS) to share the CUDA libraries between the containers.
D) Manually configure each container to use the 'CUDA VISIBLE DEVICES' environment variable to specify the GPUs it should use on its respective host.
E) Create a custom Docker network and configure each container to use the network's gateway as the default GPU device.
2. Consider a scenario where you are running a CUDA application on an NVIDIA GPU. The application compiles successfully but crashes during runtime with a *CUDA ERROR ILLEGAL ADDRESS* error. You've carefully reviewed your code and can't find any obvious out- of-bounds memory accesses. What advanced debugging techniques could help you pinpoint the source of this error?
A) Use 'cuda-memcheck' to detect memory access errors at runtime.
B) Employ the CUDA Debugger (cuda-gdb) to step through the code and inspect variable values and memory contents.
C) Reduce the block size used in CUDA kernels to decrease the likelihood of shared memory conflicts.
D) Utilize NVIDIA Nsight Systems to profile the application and identify memory allocation patterns.
E) Enable ECC (Error Correction Code) memory on the GPU to detect and correct memory errors.
3. You're managing a cluster of servers with BlueField-2 DPUs. One server is experiencing intermittent network connectivity issues. You suspect a problem with the DPU's firmware. Which of the following is the MOST reliable method to determine the CURRENT firmware version of the BlueField-2 DPIJ?
A) Run 'ethtool -i on a network interface associated with the DPIJ.
B) Use the 'mst status' command to query the device status and firmware version.
C) Examine the '/proc/driver/mlx4_core/versiorf file.
D) Check the system logs for firmware-related messages during boot.
E) Query the DPIJ's BMC (Baseboard Management Controller) via IPMI or Redfish.
4. Consider a scenario where you are using NCCL (NVIDIA Collective Communications Library) for multi-GPU training across multiple servers connected via NVLink switches. Which NCCL environment variable would you use to specify the network interface to be used for communication?
A) NCCL COMM ID
B) NCCL NET INTERFACE
C) NCCL 1B HCA
D) NCCL SOCKET IFNAME
E) NCCL PORT
5. You are deploying a multi-tenant A1 infrastructure with strict isolation requirements. Which network technology would be most suitable for creating isolated virtual networks for each tenant?
A) VLANs (Virtual LANs)
B) VXLAN (Virtual Extensible LAN)
C) GRE (Generic Routing Encapsulation)
D) IPsec
E) QinQ (802. lad)
Solutions:
Question # 1 Answer: B | Question # 2 Answer: A,B,D | Question # 3 Answer: B | Question # 4 Answer: E | Question # 5 Answer: B |