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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