Answer-first summary for fast verification
Answer: A Deep Learning VM with an n1-standard-2 machine and 1 GPU with all libraries pre-installed.
The correct answer is C: 'A Deep Learning VM with an n1-standard-2 machine and 1 GPU with all libraries pre-installed.' This is because the task involves training a convolutional neural network (CNN), which benefits significantly from GPU acceleration rather than just using CPUs. Moreover, since the objective is to speed up model training without the need for manual device placement or complex setup, choosing a pre-configured Deep Learning VM with GPUs and all necessary libraries already installed is the most efficient and user-friendly option. Options A and B, while potentially powerful, would require manual setup of dependencies, and option D does not include GPUs, which are crucial for CNN tasks.
Author: LeetQuiz Editorial Team
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Your team is developing a convolutional neural network (CNN) architecture from scratch to address a specific problem domain. Initial trials on your current on-premises CPU-only infrastructure were promising, but the model's convergence is notably slow. To expedite the training process and shorten the time-to-market, your team is considering leveraging Google Cloud's powerful hardware offerings. Given that your code base lacks manual device placement and is not wrapped in an Estimator model-level abstraction, which Google Cloud environment should you select to train your model for optimal performance?
A
A VM on Compute Engine and 1 TPU with all dependencies installed manually.
B
A VM on Compute Engine and 8 GPUs with all dependencies installed manually.
C
A Deep Learning VM with an n1-standard-2 machine and 1 GPU with all libraries pre-installed.
D
A Deep Learning VM with more powerful CPU e2-highcpu-16 machines with all libraries pre-installed.
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