[Rcpp-devel] Rcpp Parallel and Rcpp Armadillo

[Qiang Kou]

What do you mean by "doesn't work" ? Compiling error or the result is not
right?

I just tried the code, and it seems the code can compile and work.

Best,

KK

On Tue, Dec 9, 2014 at 6:33 AM, Maxime To <maxime.to at outlook.fr> wrote:

> Hi,
>
> I started to work with Rcpp and I have some trouble to adapt some code. I
> copy below the following code:
>
> - I want to write a function named contrib1, that is simplified version
> here, but the idea is that that function makes a large use of the pnorm
> (and qnorm) on marices and I would like to make it faster by applying the
> function using Rcpp parallel.
>
> - Then I started with an example that I tried to adapt
> (http://gallery.rcpp.org/articles/parallel-matrix-transform/
> <http://gallery.rcpp.org/articles/parallel-matrix-transform/>) to build
> the structure Pnorm and the function pPnorm. I also created the function f
> (I wasn't able to use directly the pnorm function as would Sugar allow...)
>
> The example doesn't work. And I don't really understand why. I guess that
> it is a problem of memory allocation... Can anyone help me on that point??
> Moreover, I was able to build a previous version that was working, but once
> I started to iterate on the contrib1 function (I execute an optimization
> algorithm), the RAM memory saturated I wasn't able to figure out why the
> program was not freeing memory after each execution of the function.
>
> I attach the code below. I am a Rcpp novice, so don't hesitate to comment
> on strange things....
> Thanks for your answers!
>
> Maxime
>
> --------------------------------------
>
> #include <RcppArmadillo.h>
> #include <cmath>
> #include <algorithm>
> #include <RcppParallel.h>
>
> using namespace Rcpp;
> using namespace arma;
> using namespace std;
> using namespace RcppParallel;
>
> // [[Rcpp::depends(RcppArmadillo, RcppParallel)]]
>
> inline double f(double x) { return ::Rf_pnorm5(x, 0.0, 1.0, 1, 0); }
>
> struct Pnorm : public Worker
> {
>    // source matrix
>    mat input;
>
>    // destination matrix
>    mat output;
>
>    // initialize with source and destination
>    Pnorm(mat input, mat output)
>       : input(input), output(output) {}
>
>    // take the square root of the range of elements requested
>    void operator()(std::size_t begin, std::size_t end) {
>       std::transform(input.begin() + begin,
>                      input.begin() + end,
>                      output.begin() + begin,
>                      f);
>    }
> };
>
> mat pPnorm(mat x) {
>
>     // allocate the output matrix
>     mat output(x.n_rows, x.n_cols);
>
>     // Pnorm functor (pass input and output matrixes)
>     Pnorm ppnorm(x, output);
>
>     // call parallelFor to do the work
>     parallelFor(0, x.n_elem, ppnorm);
>
>     // return the output matrix
>     mat outmat(output.begin(), output.n_rows, output.n_cols);
>       return outmat;
> }
>
> // [[Rcpp::export]]
> mat contrib1(mat my_matrix) {
>
>         mat pbound2    = pPnorm(my_matrix);
>     return pbound2;
> }
>
>
> ------------------------------------------
> ### Main R code
>
> rm(list=ls(all=TRUE))
>
> library(Rcpp)
> library(RcppGSL)
> library(RcppParallel)
> library(RcppArmadillo)
> setwd('U:/testParallel')
>
> sourceCpp("test.cpp")
>
> asd = matrix(runif(1000), ncol = 100)
> contrib1(asd)
>
>
>
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-- 
Qiang Kou
qkou at umail.iu.edu
School of Informatics and Computing, Indiana University
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