How can I use the function 'Predict' in deep learning toolbox with full GPU capacity
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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?
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Srivardhan Gadila
2021-5-22
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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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