I ran out of memory running my network on a single GPU(12 GB memory). My network is a ConvLSTM with n timesteps, and at each timestep, I pass a single image, for now.
At each timestep, all the network weights will be same but the feature maps generated would lead to large memory usage.
Should I execute each timestep in a different GPU, or should I split the network into multiple layers/components and execute all the timesteps of that component on a single GPU.
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