Implementing parallel computation in R
Avoiding loops in R is a kind of good general principle (if you are not sure about that, take a look at this, a bit old but always great) post by Revolution Analytics at http://blog.revolutionanalytics.com/2010/11/loops-in-r.html.
The main reason why these kind of statements should be avoided is that R tends to handle your loops really slowly and, therefore, inefficiently.
Nevertheless, sometimes, these loops are really the only way to apply a given function or operation to your set of data. When dealing with these cases, and every time you are interested in improving your code efficiency, implementing parallel computation can give an important boost to your code.
The basic idea behind parallel computation is quite easy and described in the following points:
- Take the full job; you need to, for instance, calculate the square root of one thousand numbers in a vector
- Split it into smaller chunks of vector, n
- Send each chunk to one of the n workers that you...
