Elementwise matrix multiplication: R versus Rcpp (How to speed this code up?)

Question

I am new to C++ programming (using Rcpp for seamless integration into R), and I would appreciate some advice on how to speed up some calcu

Answer 1

For starters, I'd write the Armadillo version (interface) as

#include 
// [[Rcpp::depends(RcppArmadillo)]]

using namespace Rcpp;
using namespace arma;

// [[Rcpp::export]]
arama::mat A_matvecprod_elwise(const arma::mat & X, const arma::vec & y){
  int k = X.n_cols ;
  arma::mat Y = repmat(y, 1, k) ;  // 
  arma::mat out = X % Y;  
  return out;
}

as you're doing an additional conversion in and out (though the wrap() gets added by the glue code). The const & is notional (as you learned via your last question, a SEXP is a pointer object that is lightweight to copy) but better style.

You didn't show your benchmark results so I can't comment on the effect of matrix size etc pp. I suspect you might get better answers on rcpp-devel than here. Your pick.

Edit: If you really want something cheap and fast, I would just do this:

// [[Rcpp::export]]
mat cheapHadamard(mat X, vec y) {
    // should row dim of X versus length of Y here
    for (unsigned int i=0; i

which allocates no new memory and will hence be faster, and probably be competitive with R.

Test output:

R> cheapHadamard(testmat, testvec)
     [,1] [,2] [,3]
[1,]    1    4    7
[2,]    4   10   16
[3,]    9   18   27
R>