dotnet / dotnet/machinelearning
Passing input from GPU
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area-TensorFlow
Priority:3
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Description
I am working in a pipeline architecture where all intermediary data resides in the GPU. I am interested in passing data already in the GPU into a DL network with the output still residing in the GPU to be passed to the next element in a pipeline. Essentially I would like to pass a cuda array into the network, get an output and convert back into a cuda array. I’d like to do this without having to perform CPU/GPU copies. Is this possible at the moment?
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