To elaborate: Tensorflow is clever because it takes your flow graph and cuts it into pieces which it then executes on computational units. Any computational unit will do, really as long as you have a backend for it. This choice makes adaptation to new system much easier.

I believe Caffe and Theano uses the same model, but I didn't study it. There are also some similarity in the model to what OCaml does with the incremental library, though it is not for machine learning.