[R] How does R compares for speed?

[Liaw, Andy]

> From: Prof Brian D Ripley [mailto:ripley at stats.ox.ac.uk]
> 
> On Wed, 12 Jun 2002, Philippe Grosjean wrote:
> > Hi,
> >
> > For those who are interested, I have update my R benchmark 
> (to version
> > 1.5.0) and also to Splus 6. They are available at:
> > http://www.sciviews.org/other/benchmark.htm. A comparison 
> is made between
> > Matlab (5.3 & 6), R 1.5.0, Splus 6 rel 2, O-Matrix 5.1, 
> Octave 2.1.31,
> > Scilab 2.6, Rlab 2.1 and OX 3.00 under Windows 2000 pro.
> >
> > Overall, R is not the fastest package, but it is one of the 
> fastest... and
> > comparison with Splus is interesting! Please, note that the 
> benchmark tests
> > only a few function, and also gives no information about 
> the "richness" or
> > "usability" of the various software tested. At least, it is 
> interesting to
> > note that R is becoming more and more performant with versions: the
> > benchmark applied to previous versions of R identified some lacks in
> > performance, particularly in the sort() function, which now 
> belong to the
> > past. Congratulation for all who contributed (and still 
> contribute) to make
> > R one of the best statistical and "number crunching" system!!!
> 
> I couldn't find any details of how you actually programmed 
> the systems.
> For one example, there are many ways to do linear regression in R, and
> most of them give a lot more output than matrix languages.  I suspect
> R and S-PLUS are slow on test I-E because they do more.

The scripts for the benchmark are actually on that web site.  The regression
part is coded as:

  a <- Rnorm(700*700); dim(a) <- c(700,700)
  b <- 1:700
  timing <- system.time({
    qra <- qr(a, tol = 1e-7);
    c <- qr.coef(qra, b)
    #Rem: a little faster than c <- lsfit(a, b, inter=F)$coefficients
  })[3]

For the timing on cross product, though, it's coded as crossprod(a, a), but
in R 1.5.0, crossprod(a) would have cut the time quite a bit.  On my PIII
laptop (IBM Thinkpad T22) with R-1.5.0 linked against ATLAS:

> a <- matrix(rnorm(550*550), 550,550)
> system.time(crossprod(a,a))
[1] 0.67 0.00 0.69   NA   NA
> system.time(crossprod(a))
[1] 0.32 0.00 0.47   NA   NA
> system.time(crossprod(a,a))
[1] 0.53 0.02 0.55   NA   NA
> system.time(crossprod(a))
[1] 0.32 0.00 0.33   NA   NA
> system.time(crossprod(a,a))
[1] 0.53 0.00 0.53   NA   NA
> system.time(crossprod(a))
[1] 0.30 0.00 0.33   NA   NA
> system.time(crossprod(a,a))
[1] 0.53 0.00 0.53   NA   NA
> system.time(crossprod(a))
[1] 0.32 0.00 0.32   NA   NA

Cheers,
Andy
 
> 
> -- 
> 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
> 
> 
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