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Google Professional Machine Learning Engineer Exam - Topic 8 Question 32 Discussion

You are training a deep learning model for semantic image segmentation with reduced training time. While using a Deep Learning VM Image, you receive the following error: The resource 'projects/deeplearning-platforn/zones/europe-west4-c/acceleratorTypes/nvidia-tesla-k80' was not found. What should you do?
A) Ensure that you have GPU quota in the selected region.
B) Ensure that the required GPU is available in the selected region.
C) Ensure that you have preemptible GPU quota in the selected region.
D) Ensure that the selected GPU has enough GPU memory for the workload.

Google Professional Machine Learning Engineer Exam - Topic 8 Question 32 Discussion

Actual exam question for Google's Professional Machine Learning Engineer exam
Question #: 32
Topic #: 8
[All Professional Machine Learning Engineer Questions]

You are training a deep learning model for semantic image segmentation with reduced training time. While using a Deep Learning VM Image, you receive the following error: The resource 'projects/deeplearning-platforn/zones/europe-west4-c/acceleratorTypes/nvidia-tesla-k80' was not found. What should you do?

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Suggested Answer: A

by Yolando at May 06, 2022, 12:40 PM

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Marnie
9 months ago
I thought all GPUs had enough memory for any workload?
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Carman
9 months ago
Preemptible GPU quota? Not sure if that's necessary here.
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Lamonica
9 months ago
Wait, can you really run K80 in that zone? Sounds off.
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Chantell
9 months ago
I think having GPU quota is crucial too.
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Veronika
9 months ago
Definitely check the GPU availability in your region.
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Edison
10 months ago
I don't think it's about GPU memory since the error specifically mentions the resource not being found. So, I lean towards option B.
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Kip
10 months ago
I vaguely recall a practice question where we had to check for preemptible GPUs. Could option C be relevant here too?
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Lashawn
10 months ago
I think I remember that the error might be related to the GPU availability in the region. So, option B could be the right choice.
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Catarina
10 months ago
I'm not entirely sure, but I feel like we discussed something about checking the GPU quota before. Maybe option A is also worth considering?
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Jesusita
10 months ago
Alright, time to put my security knowledge to the test. I think I've got a good handle on the different proxy and inspection methods, so I'll give this my best shot.
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Dean
10 months ago
Okay, let me think this through. We need a storage solution that can handle large volumes of data, has geospatial capabilities, and supports machine learning. I'm leaning towards BigQuery, but I'll need to double-check the pricing and performance details to be sure it's the right choice.
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Cristy
10 months ago
I'm leaning towards option D because none of the other options seem to fit the public key requirement, but I hope I'm not missing something.
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Lauran
10 months ago
I'm pretty confident that Cloud Pub/Sub alone would be sufficient to meet the requirements here. The FIFO guarantee is a core feature of Pub/Sub, so I don't think we need any additional products.
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