In this segment, we discuss the push, pull, and push_function, features of IPython that allow finer control over individual namespaces of remote nodes and over the computations that run on them.

In this segment, we discuss the map feature to distribute computations across the available nodes, how to use targets to specify which nodes to use, and how to use blocking to avoid waiting for long computations to finish.

In this segment, we discuss cover importing modules for the remote nodes and how to distribute data (i.e. scatter, gather) to and from these nodes.

IPython provides excellent interactive parallel computing tools. In this segment, we discuss how to set up remote computational engines using ipcluster and how to use special magic commands in IPython to use these remote engines.

Here we show how to run the IPython interpreter on the Wind...

Looking forward to having an 8 core processor in your desktop box? Maybe your server already does? Unfortunately unless your application is designed to use them 7 of those cores are going to be sitting idle. How do you write multi-threaded programs for .NET without the headaches of race conditions an...