There are much more active projects that do the same thing as this.

- IPython parallel (https://ipyparallel.readthedocs.io/en/latest/ ) is pretty much the same idea but under active development, supports both local processes, small clusters, cloud computng, an HPC environments (SGE style supercomputing schedulers).

- Joblib is a great tool for common embarrassingly parallel problems - run on many cores with a one liner (https://pythonhosted.org/joblib/index.html)

- Dask provides a graph-based approach to lasily building up task graphs and finding an optimal way to run them in parallel (http://dask.pydata.org/)