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Question 203 - Professional Data Engineer discussion
You are working on a niche product in the image recognition domain. Your team has developed a model that is dominated by custom C++ TensorFlow ops your team has implemented. These ops are used inside your main training loop and are performing bulky matrix multiplications. It currently takes up to several days to train a model. You want to decrease this time significantly and keep the cost low by using an accelerator on Google Cloud. What should you do?
A.
Use Cloud TPUs without any additional adjustment to your code.
B.
Use Cloud TPUs after implementing GPU kernel support for your customs ops.
C.
Use Cloud GPUs after implementing GPU kernel support for your customs ops.
D.
Stay on CPUs, and increase the size of the cluster you're training your model on.
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