Does Python's multiprocessing.Pool support remote subprocesses? [duplicate]

This question already has answers here: Using the multiprocessing module for cluster computing (4 answers) Closed 10 years ago.

I have recently discovered how awesome Pool.map() is for simple multiprocessing tasks, but my local machine only has two processors and I was hoping to take advantage of some remote computing resources.

Can a processing pool be constructed to use remote machines as well as the local machines in a transparent way?

What python code would I need to run on the remote machines, How would I set up the pool on the local (master) machine?

On the documentation page for mul开发者_JS百科tiprocessing, It says Managers are to be used for shared objects, but it's unclear to me how they should be used for a remote Pool. Nothing other than Managers seems make any reference to ports and addresses, so I'm guessing all remote activity happens through this class.

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multiprocessing.Pool seems not designed for distributed processing -- if that's what you want to do, I suggest you check out the execnet package instead. That works over SSH pipes and sends code along to the remote Python interpreter if necessary.