[Rcpp-devel] How much speedup for matrix operations?

[Xavier Robin]

On 11/6/13 6:57 PM, Douglas Bates wrote:
> By default Eigen does not use BLAS, which can be good or bad, 
> depending on the situation.  I notice that the second largest total 
> time is spent in t.default which may mean that you are using an 
> operation like
>
> t(X) %*% X
>
> If so, you can save yourself time by using the crossprod or tcrossprod 
> functions.  For example, the expression above is more cleanly written as
>
> crossprod(X)
>
> or, for t(X) %*% Y,
>
> crossprod(X, Y)
>
> Eigen or Armadillo could help you avoid making unnecessary copied but 
> if your calculation does end up being dominated by matrix 
> multiplications you can't expect to gain much speed relative to R. 
>  You may want to check the type of BLAS you are using.  For Intel 
> processors MKL is generally the fastest (but proprietary) with 
> OpenBLAS in second place.
>
> I see that I am, as often happens, giving you similar advice to Dirk's 
> response.
t(X) %*% Y is indeed a very frequent operation. Thanks for pointing out 
the crossprod function, I was unaware of its existence.


Xavier

>
>
> On Wed, Nov 6, 2013 at 11:35 AM, Xavier Robin <xavier at cbs.dtu.dk 
> <mailto:xavier at cbs.dtu.dk>> wrote:
>
>     Hi,
>
>     I have a pure-R code that spends most of the time performing
>     vector and matrix operations, as shown by the summary of Rprof:
>
>                            self.time self.pct total.time total.pct
>         "%*%"                 903.24    77.67     903.24 77.67
>         "t.default"            76.26     6.56      76.26 6.56
>         "-"                    36.60     3.15      36.60 3.15
>         "+"                    24.44     2.10      24.44 2.10
>         "/"                    24.22     2.08      24.22 2.08
>         "exp"                  20.26     1.74      20.26 1.74
>         "predict.myClass"      17.68     1.52     503.82 43.32
>         "*"                    11.90     1.02      11.90 1.02
>         "t"                     9.38     0.81     811.94 69.82
>         "update.batch"          8.04     0.69     654.68     56.30
>         ...
>
>     So mostly matrix %*% matrix multiplications, transpositions,
>     vector +-/* matrix operations and exponentiations, representing
>     >95% of the computation time.
>     I have very few loops and if/else blocks.
>
>     I want to speed up this code, and I am considering reimplementing
>     it (or part of it) with RcppEigen or RcppArmadillo.
>
>     However, I read that both Eigen and Amarillo use the underlying
>     BLAS, like R.
>     My question is, can I expect any significant speed-up from an Rcpp
>     re-implementation in this case, given it is already mostly matrix
>     algebra (which are supposed to be pretty efficient in R)?
>
>     Thanks,
>     Xavier
>
>     -- 
>     Xavier Robin, PhD
>     Cellular Signal Integration Group (C-SIG) - http://www.lindinglab.org
>     Center for Biological Sequence Analysis (CBS) - http://www.cbs.dtu.dk
>     Department of Systems Biology - Technical University of Denmark (DTU)
>     Anker Engelundsvej, Building 301, DK-2800 Lyngby, DENMARK.
>
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>
>


-- 
Xavier Robin, PhD
Cellular Signal Integration Group (C-SIG) - http://www.lindinglab.org
Center for Biological Sequence Analysis (CBS) - http://www.cbs.dtu.dk
Department of Systems Biology - Technical University of Denmark (DTU)
Anker Engelundsvej, Building 301, DK-2800 Lyngby, DENMARK.

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