16

PARALLEL R

Since many R users have very large compu-

tational needs, various tools for some kind

of parallel operation of R have been devised.

This chapter is devoted to parallel R.

Many a novice in parallel processing has, with great anticipation, written

parallel code for some application only to find that the parallel version actu-

ally ran more slowly than the serial one. For reasons to be discussed in this

chapter, this problem is especially acute with R.

Accordingly, understanding the nature of parallel-processing hardware

and software is crucial to success in the parallel world. These issues will be

discussed here in the context of common platforms for parallel R.

We’ll start with a few code examples and then move to general perfor-

mance issues.

16.1 The Mutual Outlinks Problem.................................................

Consider a network graph of some kind, such as web links or links in a social

network. LetAbe theadjacency matrixof the graph, meaning that, say,A[3,8]

is 1 or 0, depending on whether there is a link from node 3 to node 8.

For any two vertices, say any two websites, we might be interested in

mutual outlinks—that is, outbound links that are common to two sites. Sup-

pose that we want to find the mean number of mutual outlinks, averaged