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Support for multiple GPUs #134

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thunterdb opened this issue Oct 26, 2017 · 0 comments

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thunterdb commented Oct 26, 2017

TensorFrames should be able to run tasks concurrently on separate GPUs, if they are available. This should be possible with the latest TensorFlow java API:
https://www.tensorflow.org/api_docs/java/reference/org/tensorflow/Session.html#Session(org.tensorflow.Graph, byte[])

Assuming that all the GPUs are available for running tasks, they can be locked onto specific sessions in python by using the following code:

config = tf.ConfigProto()
config.gpu_options.visible_device_list = "0" # Or different values
session = tf.Session(config=config)

thunterdb added the enhancement label

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