Mira Celine Klein walks us through some of the basics of parallel code execution in R:
In many cases, your code fulfills multiple independent tasks, for example, if you do a simulation with five different parameter sets. The five processes don’t need to communicate with each other, and they don’t need any result from any other process. They could even be run simultaneously on five different computers… or processor cores. This is called parallelization. Modern desktop computers usually have 16 or more processor cores. To find out how many cores you have on your PC, use the function
detectCores(). By default, R uses only one core, but this article tells you how to use multiple cores. If your simulation needs 20 hours to complete with one core, you may get your results within four hours thanks to parallelization!
Read on to see how you can accomplish this, but note that it is operating system-dependent.