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HP Exam HPE2-N69 Topic 3 Question 33 Discussion

Actual exam question for HP's HPE2-N69 exam
Question #: 33
Topic #: 3
[All HPE2-N69 Questions]

A company has recently expanded its ml engineering resources from 5 CPUs 1012 GPUs.

What challenge is likely to continue to stand in the way of accelerating deep learning (DU training?

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Suggested Answer: B

The complexity of adjusting model code to distribute the training process across multiple GPUs. Deep learning (DL) training requires a large amount of computing power and can be accelerated by using multiple GPUs. However, this requires adjusting the model code to distribute the training process across the GPUs, which can be a complex and time-consuming process. Thus, the complexity of adjusting the model code is likely to continue to be a challenge in accelerating DL training.


Contribute your Thoughts:

Graciela
3 months ago
Yeah, B makes sense. More GPUs need proper coding.
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Katie
3 months ago
Possible, but more likely they'd struggle with the code adjustments.
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Mozelle
3 months ago
Could it be A, a lack of understanding of the DL model architecture?
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Margurite
3 months ago
I concur. Distributing across GPUs is not straightforward.
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Katie
3 months ago
I would say B, adjusting model code for multiple GPUs. It's highly technical.
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Graciela
4 months ago
This question seems tricky, what do you think is the main challenge for this company?
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