The CPU on the nice shiny new server I log in to is really not much faster than that of the ratty old laptop I have in front of me. The server has more memory, and more disk space, but CPU-wise it just has more not faster. For that matter even my laptop has two cores. So if I have some heavy-duty computing task, I'd better find a way to make it use multiple cores in parallel. Some tasks are just plain hard to parallelize (solving ordinary differential equations, for example), but it turns up fairly often that I'm doing something embarrassingly parallel: there's a for loop somewhere that just does the same thing to lots of different pieces of input. If only it were easy to hand each piece to a different core! Well, there are various tools for doing this sort of thing, but most of them apply to scripts or programs that run non-interactively. It turns out that ipython offers tools for interactive parallel computing. I'm going to explain how I use them, by working through a test problem, checking some statistics on a periodicity test (the H test).
The National Geographic 2014 Photo Contest
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