[Rcpp-devel] Differences between RcppEigen and RcppArmadillo

[Julian Smith]

I agree that RcppEigen is a little bit faster, but ease of use is important
to me, so I feel like RcppArmadillo might win out in my application.

| RcppArmadillo will use the very same LAPACK and BLAS libs your R session
| uses. So MKL, OpenBlas, ... are all options.  Eigen actually has its own
code
| outperforming LAPACK, so it doesn't  as much there.

Why do you think R outperforms RcppArmadillo in this example below? Anyway
to speed this up?

require(RcppArmadillo)
require(inline)

arma.code <- '
  using namespace arma;
  NumericMatrix Xr(Xs);
  int n = Xr.nrow(), k = Xr.ncol();
  mat X(Xr.begin(), n, k, false);
  mat U;
  vec s;
  mat V;
  svd(U, s, V, X);
  return wrap(s);
'
rcppsvd <- cxxfunction(signature(Xs="numeric"),
                        arma.code,
                        plugin="RcppArmadillo")

A<-matrix(rnorm(5000^2), 5000)

> system.time(rcppsvd(A))
    user   system  elapsed
1992.406    4.862 1988.737

> system.time(svd(A))
   user  system elapsed
652.496   2.641 652.614

On Wed, Jun 13, 2012 at 11:43 AM, Dirk Eddelbuettel <edd at debian.org> wrote:

>
> On 13 June 2012 at 10:57, Julian Smith wrote:
> | I've been toying with both RcppArmadillo and RcppEigen the past few days
> and
> | don't know which library to continue using. RcppEigen seems really
> slick, but
> | appears to be lacking some of the decompositions I want and isn't nearly
> as
> | fast to code. RcppArmadillo seems about as fast, easier to code up etc.
> What
> | are some of the advantages/disadvantages of both?
>
> That's pretty close.  I have been a fan of [Rcpp]Armadillo which I find
> easier to get my head around.  Doug, however, moved from [Rcpp]Armadillo to
> [Rcpp]Eigen as it has some things he needs.  Eigen should have a "larger"
> API
> than Armadillo, but I find the code and docs harder to navigate.
>
> And you should find Eigen to be a little faster. Andreas Alfons went as far
> as building 'robustHD' using RcppArmadillo with a drop-in for RcppEigen (in
> package 'sparseLTSEigen'; both package names from memmory and I may have
> mistyped).  He reported a performance gain of around 25% for his problem
> sets.  On the 'fastLm' benchmark, we find the fast Eigen-based
> decompositions
> to be much faster than Armadillo.
>
> | Can you call LAPACK or BLAS from either? Is there a wrapper in RcppEigen
> to
> | call LAPACK functions? Want some other decomposition methods, dont like
> the
> | JacobiSVD method in Eigen.
>
> You need to differentiate between the Eigen and Armadillo docs _for their
> libraries_ and what happens when you access the Rcpp* variant from R.
>
> RcppArmadillo will use the very same LAPACK and BLAS libs your R session
> uses. So MKL, OpenBlas, ... are all options.  Eigen actually has its own
> code
> outperforming LAPACK, so it doesn't  as much there.
>
> Hope this helps,   Dirk (at useR!)
>
> |
> | ----------------------------------------------------------------------
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> | Rcpp-devel at lists.r-forge.r-project.org
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> --
> Dirk Eddelbuettel | edd at debian.org | http://dirk.eddelbuettel.com
>
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