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How can I use the function 'Predict' in deep learning toolbox with full GPU capacity

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Huhufly
Huhufly on 19 May 2021
Commented: Huhufly on 25 May 2021
I'm currently learning to use the deep learning toolbox to train a U-net for image regression tasks. When I was trying to use the 'predict' function with a minibatch size of 512 to generate some output, I found that the GPU memory usage was fluctuating periodically from 3.3/11GB to 9/11GB. I am pretty new to the matlab so I am wondering what is the cause of the phenomenon and how can I maximize the GPU useage so as to further accelerate the computation. Could anyone give me a little hint or suggestions?

Accepted Answer

Srivardhan Gadila
Srivardhan Gadila on 22 May 2021
As per my knowledge, the fluctuation in the memory usage is due to the different computational and memory requirement across the layers of the U-Net network i.e., based on the layer properties there may be more number of computations involved for a layer when compared to another layer within the same network.

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