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Question 265 - MLS-C01 discussion

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A company builds computer-vision models that use deep learning for the autonomous vehicle industry. A machine learning (ML) specialist uses an Amazon EC2 instance that has a CPU: GPU ratio of 12:1 to train the models.

The ML specialist examines the instance metric logs and notices that the GPU is idle half of the time The ML specialist must reduce training costs without increasing the duration of the training jobs.

Which solution will meet these requirements?

A.
Switch to an instance type that has only CPUs.
Answers
A.
Switch to an instance type that has only CPUs.
B.
Use a heterogeneous cluster that has two different instances groups.
Answers
B.
Use a heterogeneous cluster that has two different instances groups.
C.
Use memory-optimized EC2 Spot Instances for the training jobs.
Answers
C.
Use memory-optimized EC2 Spot Instances for the training jobs.
D.
Switch to an instance type that has a CPU GPU ratio of 6:1.
Answers
D.
Switch to an instance type that has a CPU GPU ratio of 6:1.
Suggested answer: D

Explanation:

Switching to an instance type that has a CPU: GPU ratio of 6:1 will reduce the training costs by using fewer CPUs and GPUs, while maintaining the same level of performance. The GPU idle time indicates that the CPU is not able to feed the GPU with enough data, so reducing the CPU: GPU ratio will balance the workload and improve the GPU utilization. A lower CPU: GPU ratio also means less overhead for inter-process communication and synchronization between the CPU and GPU processes.References:

Optimizing GPU utilization for AI/ML workloads on Amazon EC2

Analyze CPU vs. GPU Performance for AWS Machine Learning

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asked 16/09/2024
Devon Woods
37 questions
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