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

[Xavier Robin]

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.