Hello,

I am looking for a way to do fast matrix operations (multiplication, Inversion) for
large matrices (n=8000) in R. I know R is not that fast in linear algebra than
other software. 
So I wanted to write some code in C++ and incorporate this code in R. I have used the
package RcppArmadillo, because a lot of people write that it is really fast in
doing matrix algebra. So I have run a short example. See the code below.
I was wondering that I got almost the same CPU time for the matrix algebra in my
example. I expect that using C++ Code in R is faster than using the standard
matrix operations in R. 

Is there a way to do matrix algebra in R faster as the standard command (e.g. %*%) using
the Rcpp or RcppArmadillo packages? I would be happy about any idea or advice.
Thanks in advance


 > library(Rcpp)
> library(RcppArmadillo)
> library(inline)
> library(RcppEigen)
> library(devtools)
> 
> # Generation of the matrix
> n=2000
> A<-matrix(rnorm(n^2,0,1), n,n)
> 
> # Code in R 
> system.time(
+     D<-A%*%A%*%A+A)
   user  system elapsed 
  12.29    0.01   12.33 
> 
> # Code using RcppArmadillo
> src <-
+     '
+ arma::mat X = Rcpp::as<arma::mat>(X_);
+ arma::mat ans = X * X * X + X;
+ return(wrap(ans));
+ '
> mprod6_inline_RcppArma <- cxxfunction(signature(X_="numeric"),
+                                       body = src, plugin="RcppArmadillo")
> 
> system.time(
+     C<-mprod6_inline_RcppArma(X=A))
   user  system elapsed 
  12.30    0.08   12.40 

 		 	   		  
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