Using parallel processing in R

multicore
Lately I’ve been running a lot of complex models with huge datasets, which is grinding my computer to a halt for hours. Streamlining code can only go so far, but R is limited because the default session runs on only 1 core. In a time when computers have at least 2 cores, if not more, why not take advantage of that extra computing power? (Heck, even my phone has 2 cores.*)

Luckily, R comes bundled with the “parallel” package, which helps to distribute the workload across multiple cores. It’s a cinch to set up on a local machine:

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