[R] Computation time differences between Linux and Windows

[ripley@stats.ox.ac.uk]

On 2 Dec 2002, Mpiktas wrote:

> Today I came accros a very interesting thing. I was asked how much time

Really?  You have a real application for repeatedly multiplying random
matrices and nothing else?

> it takes for R to calculate the product of two large matrices. So I
> generated two 2000x2000 matrices of random normal numbers and measured
> the time with function system.time
>
> m1 <- matrix(rnorm(2000*2000),2000)
> m2 <- matrix(rnorm(2000*2000),2000)
> system.time(m3 <- m1%*%m2)
>
> and it produced
>
> 46.47  0.36 47.68  0.00  0.00
>
> on Debian GNU/Linux Woody, R 1.6.1 computer. The same three lines on the
> same computer but under Windows 2000 and R 1.5.1 I got
>
> 550.23   0.40 552.97     NA     NA
>
> So to calculate the product of two matrices it takes approximately 10
> times more on Windows than on Linux.
>
> Is this a bug or a feature?

Most likely your own misunderstanding.  Your Debian installation will be
using an optimized BLAS (probably the only pre-compiled distribution that
does by default), and I don't suppose that you used an optimized BLAS for
Windows (although they are available on CRAN for the common chips).

It is bad practice to compare the current version of R on one system with
an obselete one on another, as well as to compare ones with different
degrees of tuning.

> The same operation in Matlab 5.3 on Windows 2000 took approximately 300
> seconds and in Octave 2.0.16.92 (i386-pc-linux-gnu) on Linux about 550
> seconds. I tried to keep minimum processes running during the
> computations.
>
> I suspect the answer to this is different memory management accros
> different programs and platforms. Am I right?

Not at this size of matrix.

BLAS makes a big difference to simple computations, but little to real
problems done in R.  Simple `benchmarks' can be seriously misleading. In
fact, for this one R was actually slowed down for users without a fast
BLAS to allow the speed-up using ATLAS (the default on Debian).

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595