[Rcpp-devel] Rcpp is the best - praise to the praise worthy

[Asis Hallab]

Dear Dirk Eddelbuettel, Romain Francois and contributors,
Dear Rcpp Experts!

It is time to praise you and express my thanks.

I had a very annoying problem generating up to a 300 square matrices
each of sizes up to 500*500 cells. Computing their numeric cell
entries took for ages, even when done using the parallel library with
mclapply and up to 40 cores.
In 2 to 3 % of the cases memory usage skyrocketed to 200GB and zombie
processes were hanging around.
I could never find the cause for that problem, because it only
occurred when my program ran in background (invoked with Rscript),
never when the same data and code was executed in an interactive R
shell (invoked via R).

Anyway, I decided to tackle that particular monster in Rcpp, even
though I haven't used C/C++ in more than a decade and even though time
has been and still is extremely pressing. - I have to hand in my PhD
thesis in a couple of weeks…

It took me only 3 days and a couple of stupid newby emails to this
list, and now, even though I could not get the Rcpp code to be
executed in parallel with OpenMP, I have a running version.
And lo and behold: It is
830 times
faster than the original R code. And still
150 times
faster than the pure R implementation when executed on 10 cores.

A framework like Rcpp is truly excellent, when you can get important
work done in a couple of days without prior knowledge of even the
programming language. Well, mine was very dusty.
And Rcpp is so incredibly efficient, too.

Guys: Thank you very much for providing Rcpp!
I love it and you for having created it.
In the end it simply saved my PhD-ing butt.

Cheers and a nice rest of the weekend!