Re: [R] Ubuntu vs. Windows

From: Peter Dalgaard <p.dalgaard_at_biostat.ku.dk>
Date: Tue, 22 Apr 2008 23:03:36 +0200

Doran, Harold wrote:
> Dear List:
>
> I am very much a unix neophyte, but recently had a Ubuntu box installed
> in my office. I commonly use Windows XP with 3 GB RAM on my machine and
> the Ubuntu machine is exactly the same as my windows box (e.g.,
> processor and RAM) as far as I can tell.
>
> Now, I recently had to run a very large lmer analysis using my windows
> machine, but was unable to due to memory limitations, even after
> increasing all the memory limits in R (which I think is a 2gig max
> according to the FAQ for windows). So, to make this computationally
> feasible, I had to sample from my very big data set and then run the
> analysis. Even still, it would take something on the order of 45 mins to
> 1 hr to get parameter estimates. (BTW, SAS Proc nlmixed was even worse
> and kept giving execution errors until the data set was very small and
> then it ran for a long time)
>
> However, I just ran the same analysis on the Ubuntu machine with the
> full, complete data set, which is very big and lmer gave me back
> parameter estimates in less than 5 minutes.
>
> Because I have so little experience with Ubuntu, I am quite pleased and
> would like to understand this a bit better. Does this occur because R is
> a bit friendlier with unix somehow? Or, is this occuring because unix
> somehow has more efficient methods for memory allocation?
>
Probably partly the latter and not the former (we try to make the most of what the OS offers in either case), but a more important difference is that we can run in 64 bit address space on non-Windows platforms (assuming that you run a 64 bit Ubuntu).

Even with 64 bit Windows we do not have the 64 bit toolchain in place to build R except as a 32 bit program. Creating such a toolchain is beyond our reach, and although progress is being made, it is painfully slow (http://sourceforge.net/projects/mingw-w64/). Every now and then, the prospect of using commercial tools comes up, but they are not "plug-compatible" and using them would leave end users without the possibility of building packages with C code, unless they go out and buy the same toolchain.

> I wish I knew enough to even ask the right questions. So, I welcome any
> enlightenment members may add.
>
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>

-- 
   O__  ---- Peter Dalgaard             ุster Farimagsgade 5, Entr.B
  c/ /'_ --- Dept. of Biostatistics     PO Box 2099, 1014 Cph. K
 (*) \(*) -- University of Copenhagen   Denmark      Ph:  (+45) 35327918
~~~~~~~~~~ - (p.dalgaard_at_biostat.ku.dk)              FAX: (+45) 35327907

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Received on Tue 22 Apr 2008 - 21:20:58 GMT

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