[Rcpp-devel] Differences between RcppEigen and RcppArmadillo

[Julian Smith]

Doesn't svd in R by default compute D, U and V?

http://stat.ethz.ch/R-manual/R-patched/library/base/html/svd.html

On Wed, Jun 13, 2012 at 4:07 PM, Douglas Bates <bates at stat.wisc.edu> wrote:

> On Wed, Jun 13, 2012 at 5:16 PM, Dirk Eddelbuettel <edd at debian.org> wrote:
> >
> > On 13 June 2012 at 15:05, Julian Smith wrote:
> > | 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.
> >
> > Yup, that my personal view too.
> >
> > | | 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?
> >
> > That is odd. "I guess it shouldn't." I shall take another look -- as I
> > understand it both should go to the same underlying Lapack routine.  I
> may
> > have to consult with Conrad on this.
> >
> > Thanks for posting a full and reproducible example!
> >
> > Dirk
> >
> > | 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);
> > | '
>
> Because the arma code is evaluating the singular vectors (U and V) as
> well as the singular values (S) whereas the R code is only evaluating
> the singular values.  There is considerably more effort required to
> evaluate the singular vectors in addition to the singular values.
>
> > | 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!)
> > |
> > |     |
> > |     |
> ----------------------------------------------------------------------
> > |     | _______________________________________________
> > |     | Rcpp-devel mailing list
> > |     | Rcpp-devel at lists.r-forge.r-project.org
> > |     |
> https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel
> > |     --
> > |     Dirk Eddelbuettel | edd at debian.org | http://dirk.eddelbuettel.com
> > |
> > |
> >
> > --
> > Dirk Eddelbuettel | edd at debian.org | http://dirk.eddelbuettel.com
> > _______________________________________________
> > Rcpp-devel mailing list
> > Rcpp-devel at lists.r-forge.r-project.org
> > https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.r-forge.r-project.org/pipermail/rcpp-devel/attachments/20120613/9801bf54/attachment-0001.html>