MLS-C01 Practice Question: Machine Learning Implementation and Operations
A data scientist is using SageMaker to train a deep learning model. The training script uses TensorFlow and runs on a single p3.2xlarge instance. The scientist wants to reduce training time by using multiple GPUs. What should the scientist do?
⚠ Common exam trap
Test-takers frequently assume increasing instance count or switching frameworks automatically enables multi-GPU training, but AWS tests the understanding that distributed training requires explicit code changes (e.g., Horovod or DDP) and that a single p3.2xlarge instance has only one GPU, so multi-GPU training requires a different instance type or multiple instances.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Modify the training script to use Horovod for distributed training.
Horovod is a distributed deep learning framework that integrates with TensorFlow to enable multi-GPU training across multiple instances. By modifying the training script to use Horovod's `hvd.DistributedOptimizer` and broadcasting initial variables, the data scientist can leverage multiple GPUs on a single p3.2xlarge instance (which has 1 GPU) or scale to multiple instances, directly reducing training time through data parallelism.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the instance count to 4 without changing the script.
Why it's wrong here
Without distributed training support, multiple instances will not utilize all GPUs.
- ✓
Modify the training script to use Horovod for distributed training.
Why this is correct
Horovod enables multi-GPU and multi-instance distributed training.
- ✗
Switch to PyTorch framework.
Why it's wrong here
The framework change does not automatically enable distributed training.
- ✗
Use SageMaker Managed Spot Training.
Why it's wrong here
Spot Training does not provide additional GPUs.
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