MLS-C01 Question 328
Single answerA data science team is training a machine learning model on AWS using a large dataset stored in Amazon S3. The training process involves GPU-intensive operations and will run continuously for several hours. The team is cost-conscious but also needs high performance for faster model training. Which instance type should they choose to balance cost and performance?
- A
p3.2xlarge
- B
t2.micro
- C
c5.large
- D
m5.xlarge
Show answer and explanation
Correct answer: A
Explanation
GPU-intensive machine learning model training requires instances with GPU capabilities to achieve high performance. The p3 instance family is specifically designed for such workloads, offering Nvidia GPUs for efficient deep learning and machine learning training. Among the options provided, p3.2xlarge is the most appropriate choice that balances cost and performance for this scenario.
- A. Correct.
p3.2xlarge is a GPU-optimized instance type designed for high-performance machine learning tasks. It is suitable for GPU-intensive operations and offers a good balance between cost and performance for such workloads.
- B. Incorrect.
t2.micro is a general-purpose instance with very limited CPU and memory resources. It is not suitable for GPU-intensive operations and would result in extremely poor performance for machine learning training.
- C. Incorrect.
c5.large is a compute-optimized instance type, but it does not have GPU capabilities. While it might offer good performance for CPU-bound tasks, it is not appropriate for GPU-intensive machine learning training.
- D. Incorrect.
m5.xlarge is a general-purpose instance type that provides a balance of compute, memory, and network resources. However, it does not support GPU operations, making it unsuitable for GPU-intensive machine learning tasks.