asyncoro version 2.7 has been released. This version improves support for distributed computing with remote coroutines. 'discoro.py' can now be invoked with number of CPUs to run instances of discoro_server so that compute intensive coroutines can run (one per CPU, for example). These coroutines and the client can communicate using message passing. See 'discoro_client.py' for an example on how to use this module.
Note that it is up to the client to schedule jobs for effective use of CPUs on remote nodes. dispy project is easier to use if jobs need to be scheduled, especially if many nodes are used for distributed computing. However, with dispy the client and remote computations can not communicate (except for computations sending intermediate results to the client).
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