Parallelizing processing with pmap

The easiest way to parallelize data is to take a loop that you already have and handle each item in it in a thread.

This is essentially what pmap does. If you replace a call to map with pmap, it takes each call to the function's argument and executes it in a thread pool. pmap is not completely lazy, but it's not completely strict either. Instead, it stays just ahead of the output consumed. So, if the output is never used, it won't be fully realized.

For this recipe, we'll calculate the Mandelbrot set. Each point in the output takes enough time that this is a good candidate to parallelize. We can just swap map for pmap and immediately see a speedup.

How to do it…

The Mandelbrot set can be found by feeding a point into a function and then feeding the results of this back into the function. The point will either settle on a value or it will take off. The Mandelbrot set contains the points that don't settle that is, points whose values explode after repeatedly...