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Using IPython for Parallel Computing (April 2014)


Abstract: IPython provides tools for interactive computing -- code introspection, completion, and environments such as an interactive shell and web-based notebook. In addition to these environments, IPython provides a suite of tools for interactive parallel computing on multicore machines or clusters. We will cover some of the API and architecture for IPython.parallel, using some example use cases. It will all be presented in IPython notebooks, so you can follow along if you like.


Min finished his PhD at UC Berkeley in computational plasma physics in May, 2013. He has been a contributor to IPython since 2006, when the first implementation of IPython's parallel computing capabilities was his undergraduate thesis at Santa Clara University. He now works full time on IPython at UC Berkeley, funded by the Alfred P. Sloan Foundation. He is also the maintainer of pyzmq, the Python bindings of the ZeroMQ messaging library


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