MLA-C01 · Question #72
An ML engineer is using Amazon SageMaker to train a deep learning model that requires distributed training. After some training attempts, the ML engineer observes that the instances are not performing
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Question
An ML engineer is using Amazon SageMaker to train a deep learning model that requires distributed training. After some training attempts, the ML engineer observes that the instances are not performing as expected. The ML engineer identifies communication overhead between the training instances. What should the ML engineer do to MINIMIZE the communication overhead between the instances?
Options
- APlace the instances in the same VPC subnet. Store the data in a different AWS Region from
- BPlace the instances in the same VPC subnet but in different Availability Zones. Store the data in a
- CPlace the instances in the same VPC subnet. Store the data in the same AWS Region and
- DPlace the instances in the same VPC subnet. Store the data in the same AWS Region but in a
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