Dirk Eddelbuettel — written Jan 6, 2013 — updated Dec 30, 2016 — source
Sine the 0.10.2 release, Rcpp contains an internal class
which can be used for fine-grained benchmarking. Romain motivated
Timer in a
post to the mailing list
Timer is used to measure the different components of the costs of
random number generation.
A slightly modified version of that example follows below.
We get the following result, each expressing the cost per iteration in nanoseconds, both cumulative (default) and incrementally (by taking differences).
start get/put g/p+rnorm() empty loop 0.000156 1571.057133 3920.082384 3920.085223
get/put g/p+rnorm() empty loop 1571.056977 2349.025251 0.002839
The interesting revelation is that repeatedly calling
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.Tweet