As a data scientist or data analyst, you often need to repeat certain computations or series of computations many times. To complete repetitive tasks you could easily use a for loop in R. But if you need a larger number of repetitions or a very complex computation, the for loop could a be time consuming. To overcome slow computation problems, you could use multiple computation cores that are available in any recent computer. You can easily spread your task to multiple computing cores in your computer to simplify complex and repetitive tasks.
Suppose you want to predict airline delay (departure delay) time for each destination, you could do this using simple regression, but for larger data and for each destination, this could be a computational problem and consume huge memory. You can tackle this computational issue by using parallel computing facilities available...
