Sine the 0.10.2 release, Rcpp contains an internal class Timer which can be used for fine-grained benchmarking. Romain motivated Timer in a post to the mailing * list where Timer is used to measure the different components of the costs of random number generation.

A slightly modified version of that example follows below.

#include <Rcpp.h>
#include <Rcpp/Benchmark/Timer.h>

using namespace Rcpp;

// [[Rcpp::export]]
NumericVector useTimer() {
    int n = 1000000;

    // start the timer
    Timer timer;
    for(int i=0; i<n; i++) {
        GetRNGstate();
        PutRNGstate();
    }
    timer.step("get/put") ;

    for(int i=0; i<n; i++) {
        GetRNGstate();
        rnorm(10, 0.0, 1.0);
        PutRNGstate();
    }
    timer.step("g/p+rnorm()");

    for(int i=0; i<n; i++) {
        // empty loop
    }
    timer.step( "empty loop" ) ;

    NumericVector res(timer);
    for (int i=0; i<res.size(); i++) {
        res[i] = res[i] / n;
    }
    return res;
}

We get the following result, each expressing the cost per iteration in nanoseconds:

useTimer()


    get/put g/p+rnorm()  empty loop 
  1.634e+03   2.573e+03   2.620e-04 

The interesting revelation is that repeatedly calling GetRNGstate() and PutRNGstate() can amount to about 60% of the cost of RNG draws. Luckily, we usually only have to call these helper functions once per subroutine called from R (rather than repeatedly as shown here) so this is not really a permanent cost to bear when running simulations with R.

It also show the usefulness of a fine-grained timer at the code level.