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Question 73 - MLS-C01 discussion

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A Machine Learning Specialist is packaging a custom ResNet model into a Docker container so the company can leverage Amazon SageMaker for training The Specialist is using Amazon EC2 P3 instances to train the model and needs to properly configure the Docker container to leverage the NVIDIA GPUs

What does the Specialist need to do1?

A.
Bundle the NVIDIA drivers with the Docker image
Answers
A.
Bundle the NVIDIA drivers with the Docker image
B.
Build the Docker container to be NVIDIA-Docker compatible
Answers
B.
Build the Docker container to be NVIDIA-Docker compatible
C.
Organize the Docker container's file structure to execute on GPU instances.
Answers
C.
Organize the Docker container's file structure to execute on GPU instances.
D.
Set the GPU flag in the Amazon SageMaker Create TrainingJob request body
Answers
D.
Set the GPU flag in the Amazon SageMaker Create TrainingJob request body
Suggested answer: B

Explanation:

To leverage the NVIDIA GPUs on Amazon EC2 P3 instances, the Machine Learning Specialist needs to build the Docker container to be NVIDIA-Docker compatible. NVIDIA-Docker is a tool that enables GPU-accelerated containers to run on Docker. It automatically configures the container to access the NVIDIA drivers and libraries on the host system. The Specialist does not need to bundle the NVIDIA drivers with the Docker image, as they are already installed on the EC2 P3 instances. The Specialist does not need to organize the Docker container's file structure to execute on GPU instances, as this is not relevant for GPU compatibility. The Specialist does not need to set the GPU flag in the Amazon SageMaker Create TrainingJob request body, as this is only required for using Elastic Inference accelerators, not EC2 P3 instances.References:NVIDIA-Docker,Using GPU-Accelerated Containers,Using Elastic Inference in Amazon SageMaker

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asked 16/09/2024
Erik de Bont
39 questions
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