Google Cloud Professional Machine Learning Engineer — Question 119
You are building a TensorFlow model for a financial institution that predicts the impact of consumer spending on inflation globally. Due to the size and nature of the data, your model is long-running across all types of hardware, and you have built frequent checkpointing into the training process. Your organization has asked you to minimize cost. What hardware should you choose?
Answer options
- A. A Vertex AI Workbench user-managed notebooks instance running on an n1-standard-16 with 4 NVIDIA P100 GPUs
- B. A Vertex AI Workbench user-managed notebooks instance running on an n1-standard-16 with an NVIDIA P100 GPU
- C. A Vertex AI Workbench user-managed notebooks instance running on an n1-standard-16 with a non-preemptible v3-8 TPU
- D. A Vertex AI Workbench user-managed notebooks instance running on an n1-standard-16 with a preemptible v3-8 TPU
Correct answer: D
Explanation
The correct answer is D, as preemptible TPUs are typically more cost-effective than other hardware options, making them suitable for minimizing costs during model training. Options A and B involve NVIDIA GPUs, which are generally more expensive, and option C uses a non-preemptible TPU, which also incurs higher costs without the flexibility of preemptible resources.