[R] Ubuntu vs. Windows
p.dalgaard at biostat.ku.dk
Tue Apr 22 23:03:36 CEST 2008
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.
> R-help at r-project.org mailing list
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
O__ ---- Peter Dalgaard Øster 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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