Just spoke about your use case with a few other folks, and the RPC/Distributed Autograd-based mechanism I described above should work.
Alternately, if you can Torchscript your model (see docs here 4), you may be able to use torch.jit.fork 6 to get this multiprocessing-style parallelism. There are a number of other performance benefits of using Torchscript (such as bypassing the Python Global Interpreter Lock) as well.