Re: [R] No speed effect by using RcppArmadillo compared to R in matrix operations

2013-10-26 Thread Dirk Eddelbuettel
Andreas Recktenwald mx.uni-saarland.de> writes: > another option if you're using Linux AND an Intel processor would be > linking R against Intel MKL (Math Kernel Library). Under Linux you can You do not have to "link" R against MKL. One simply builds and links R against _any_ BLAS implementa

Re: [R] No speed effect by using RcppArmadillo compared to R in matrix operations

2013-10-26 Thread Andreas Recktenwald
Hi, another option if you're using Linux AND an Intel processor would be linking R against Intel MKL (Math Kernel Library). Under Linux you can get a (free) non-commercial licence for it. Here I'm using an Intel(R) Core(TM) i5-3210M CPU @ 2.50GHz laptop processor with R 3.0.2 build with i

Re: [R] No speed effect by using RcppArmadillo compared to R in matrix operations

2013-10-26 Thread Jeff Newmiller
I think you don't have accurate information about the speed of R in performing linear algebra computations. It relies on standard numerical libraries for that work, so it is as fast as those libraries are (you are unlikely to beat even an unoptimized version of those libraries with your ad hoc c

[R] No speed effect by using RcppArmadillo compared to R in matrix operations

2013-10-26 Thread Timo Schmid
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,