Hi,
Does that prevent the model from converging.
I would not expect any learning to give the same results for such different hardwares.
Keep in mind that adding two float numbers can give you different answers depending on the hardware (and both will be correct with respect to the standard).
Nothing makes the answer on one machine more correct than the other, they both are.
Now if that prevent the model from converging, I would first try different random seeds on the original machine to make sure that the model is actually stable and converges all the time, not just for that one random seed.