What does the Specialist need to do?
Bundle the NVIDIA drivers with the Docker image.
Build the Docker container to be NVIDIA-Docker compatible.
Organize the Docker container’s file structure to execute on GPU instances.
Set the GPU flag in the Amazon SageMaker CreateTrainingJob request body.
Explanations:
Bundling NVIDIA drivers with the Docker image is unnecessary because the NVIDIA drivers should be installed on the host system (EC2 instance) and not included in the Docker image itself. Docker images should utilize the drivers available on the host for GPU access.
Building the Docker container to be NVIDIA-Docker compatible is essential for leveraging NVIDIA GPUs. This means using thenvidiaruntime, which allows the container to access GPU resources directly. It ensures that the container can utilize the GPU effectively during training.
Organizing the Docker container’s file structure to execute on GPU instances does not directly impact GPU utilization. The primary requirement is to ensure that the container is built with the appropriate runtime configurations to access the GPUs, not the file structure itself.
Setting the GPU flag in the Amazon SageMaker CreateTrainingJob request body is not sufficient on its own. While this is part of the configuration for training jobs, it does not address the requirement to ensure that the Docker container itself is configured to leverage the NVIDIA GPUs correctly. The container must be built to utilize the GPU resources effectively.