Before to be entusiast to move your Neural Network on Ephfany, remember that that a NN is there are partial serial, partial parallel alghoritm, so never forget Amdahl's Law:
http://en.wikipedia.org/wiki/Amdahl's_law. So, to increment layer make worst the efficency (means less parallel calculation and more serial calculation).
To summarize, it is better a unique layer (1-layer is equivalent to N-layer if the 1-layer has enough neurons). Ideally, you should do 1NEURON=1CORE.
I did a NN as "2 INput--> 2layer of 4 neurons-->1OUTput", later I rewrote it as "2 INput--> 1layer of 16 neurons-->1OUTput" in my x86, but because it is totally serial calculation (i mean, no parallelization of that can be parallelized), I don't know what was the best under efficency point of view. In epiphany it will be nice to do the comparison.
My two (euro)cents.