Hi @clyde and @dylanht ,
Currently, the best way to check if the GPU card is the following:
data = graphlab.SFrame('http://s3.amazonaws.com/dato-datasets/mnist/sframe/train')
m = graphlab.neuralnet_classifier.create(data, target='label')
Now in the output, before training progress, if you see:
PROGRESS: Creating neuralnet using cpu
that means the GPU is NOT being used. Otherwise, if you have GPU's they should be listed. If you have multiple GPU's, they should all be leveraged.
Currently, neural nets are the only toolkit accelerated by GPU cards, and fundamentally it's large matrix multiplications that are being offloaded onto the card.
Honestly, this is a bit of a clunky way to check if the GPU is being utilized. I'll make a note to write a utility function to check this.
Hope this helps!