As we saw in this chapter's introduction, one of the limitations of R (and most other programming languages) was that it was created before commodity personal computers had more than one processor or core. As a result, by default, R runs only one process and thus, makes use of one processor/core at a time.
If you have more than one core on your CPU, it means that when you leave your computer alone for a few hours during a long-running computation, your R task is running on one core while the others are idle. Clearly this is not ideal; if your R task took advantage of all the available processing power, you can get massive speed improvements.
Parallel computation (of the type we'll be using) works by starting multiple processes at the same time. The operating system then assigns each of these processes to a particular CPU. When multiple processes run at the same time, the time to completion is only as long as the longest process, as opposed to the time to complete all...