[R] (performance) time in Windows vs Linux

[Uwe Ligges]

Yes, under 64-bit it is sometimes slower and it highly depends on the 
problem and the compiler you have. Note also that nobody managed to get 
a 64-bit Windows R binary compiled with gcc so far.
Remember, 10 years ago there was the SUN Ultra Sparc III and above 
architecture, and gcc was known to produce extremely inefficient 64-bit 
binaries for that platform. Things got somewhat better in the meantime.

With the tests I used 32-bit R compiled with gcc was roughly 10% slower 
on Windows than under Linux - but as I said, it depends on the problem. 
Trying loops versus matrix operations is a way to specify a two very 
different problems, for example.

Uwe Ligges





Cézar Freitas wrote:
> Hi, all.
> 
> I began to migrate my R codes from Windows to Linux and surprised me
> with an old question. I simplified the problem and made a little test to compare times at same
> computer and the Linux time is worse (not so little) than Windows time:
> 28 vs 53 seconds.
> 
> I make an example (below) to facilitate all to see the difference.
> I also build from source (it's my first time) a version of R to compare with the distributed (compiled) R version. The times are similar to the other Linux version.
> 
> I supposed R on Linux should be faster (32 and 64 bit) than windows version. Is this difference because 64 bit R version is slower than 32 bits one? I started the machine in both sittuations and checked free memory.
> 
> Tecnichal details:
> Machine: Intel Core 2 Duo DDR2 4 Gb RAM
> Windows version: XP Professional - 32 bits
> R version: 2.9* binaries
> Linux version: Ubuntu 8* (Hardy) - 64 bits
> R version: 2.9* binaries and 2.9* compiled from source
> 
> Thanks to all,
> Cezar Freitas
> 
>  #code
>  N = 50000
>  n = 15000
>  
>  #makes data
>  dad = as.data.frame(cbind(sample(N,N,replace=FALSE), rpois(N,30)))
>  names(dad) = c("id","age")
>  
>  aux = as.data.frame(cbind(sample(N,n,replace=FALSE), round(runif(n),4)))
>  names(aux) = c("id","score")
>  
>  #calculates time
>  set.seed(790) #to be equal to everyone
>  system.time({
>    dad$score = 0
>    subdad = subset(dad, id%in%aux$id)
>    for(k in 1:(dim(subdad)[1])){
>      temp = aux$score[aux$id==subdad$id[k]]
>      if(length(temp)) subdad$score[k] = temp
>    }
>  })
>  
>  #windows time
>  #   user  system elapsed
>  #  27.81    0.00   27.82
>  
>  #linux usual compilation time
>  #   user  system elapsed
>  # 52.635   0.016  52.748
>  
>  #linux (my compilation) time
>  #   user  system elapsed
>  # 52.567   0.016  52.588
>  #==============END OF CODE
> 
> 
> 
> 
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