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Exam Professional Machine Learning Engineer topic 1 question 65 discussion

Actual exam question from Google's Professional Machine Learning Engineer
Question #: 65
Topic #: 1
[All Professional Machine Learning Engineer Questions]

While monitoring your model training’s GPU utilization, you discover that you have a native synchronous implementation. The training data is split into multiple files. You want to reduce the execution time of your input pipeline. What should you do?

  • A. Increase the CPU load
  • B. Add caching to the pipeline
  • C. Increase the network bandwidth
  • D. Add parallel interleave to the pipeline
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Suggested Answer: D 🗳️
by Vedjha at Dec. 8, 2022, 11:42 a.m.

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hiromi
Highly Voted 2 years, 1 month ago
Selected Answer: D
It's D https://www.tensorflow.org/guide/data_performance
upvoted 8 times
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PhilipKoku
Most Recent 8 months ago
Selected Answer: D
D) Parallelisation required
upvoted 2 times
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MultiCloudIronMan
10 months, 1 week ago
Selected Answer: D
Multiple files reduce execution time through papalism
upvoted 2 times
...
Werner123
11 months, 1 week ago
Selected Answer: D
"training data split into multiple files", "reduce the execution time of your input pipeline" -> Parallel interleave
upvoted 1 times
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M25
1 year, 8 months ago
Selected Answer: D
Went with D
upvoted 1 times
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OzoneReloaded
2 years, 1 month ago
Selected Answer: D
I think it's D
upvoted 2 times
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Vedjha
2 years, 1 month ago
D for me
upvoted 1 times
...
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C (25%)
B (20%)
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