[R] Memory management

[Prof Brian Ripley]

On Tue, 10 Apr 2007, yoooooo wrote:

>
> Hi all, I'm just curious how memory management works in R... I need to run an
> optimization that keeps calling the same function with a large set of
> parameters... so then I start to wonder if it's better if I attach the
> variables first vs passing them in (coz that involves a lot of copying.. )

Your paranethetical comment is wrong: no copying is needed to 'pass in' a 
variable.

> Thus, I do this
> fn3 <- function(x, y, z, a, b, c){ sum(x, y, z, a, b, c) }
> fn4 <- function(){ sum(x, y, z, a, b, c) }
>
> rdn <- rep(1.1, times=1e8)
> r <- proc.time()
> for (i in 1:5)
>  fn3(rdn, rdn, rdn, rdn, rdn, rdn)
> time1 <- proc.time() - r
> print(time1)
>
> lt <- list(x = rdn, y = rdn, z = rdn, a = rdn, b = rdn, c = rdn)
> attach(lt)
> r <- proc.time()
> for (i in 1:5)
>  fn4()
> time2 <- proc.time() - r
> print(time2)
> detach("lt")
>
> The output is
> [1] 25.691  0.003 25.735  0.000  0.000
> [1] 25.822  0.005 25.860  0.000  0.000
>
> Turns out attaching takes longer to run.. which is counter intuitive (unless
> the search to the pos=2 envir takes long time as well) Do you guys know why
> this is the case?

I would not trust timing differences of that nature: they often depend on 
the state of the system, and in particular of the garbage collector.
You should be using system.time() for that reason: it calls the garbage 
collector immediately before timing.

-- 
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 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595