Thanks Uwe but, actually, I did so.
Since “filetorun.exe” looks in the current folder for
“input.txt”, I tried moving all needed files to a newly created
temporary folder “tmp.id” (say, tmp.1) and running the executable.
This works fine by doing it directly from the windows command line but not by
doing it from R, since using:
#
System(“C:/Users/…/currentworkdirectory/temp.1/filetorun.exe”)
#
Causes “filetorun.exe” to look for “input.txt” in
“C:/Users/…/currentworkdirectory”. So there’s no point
on moving files to a folder, it seems that input file must be situated in the
current R work directory. Does anybody know how to avoid this behaviour?
I hope I’ve explained that clearly,
Xavier Portell Canal, PhD candidate.
Department of Agri-food Engineering,
Universitat Politècnica de Catalunya
-----Uwe Ligges <lig...@statistik.tu-dortmund.de> ha escrit: -----
Per a: Xavier Portell/UPC <xavier.port...@upc.edu>
De: Uwe Ligges <lig...@statistik.tu-dortmund.de>
Data: 05/08/2012 07:46PM
a/c: r-help@r-project.org
Assumpte: Re: [R] Parallel runs of an external executable with snow in local
On 03.08.2012 19:21, Xavier Portell/UPC wrote:
> Hi everyone,
>
> I'm aiming to run an external executable (say filetorun.EXE) in parallel. The
> external executable collect needed data from a file, say "input.txt" and, in
> turn,generates several output files, say "output.txt". I need to generate
> "input.txt", run the executable and keep "input.txt" and "output.txt". I'm
> using Windows 7, R version 2.15.1 (2012-06-22) on RStudio and platform:
> i386.pc.mingw32/i386 (32-bit).
>
> My first attempt was a R code which, by using
> System("filetorun.EXE", intern = F, ignore.stdout = F,
> ignore.stderr = F, wait = T, input = NULL,
> show.output.on.console = T, minimized = F, invisible = T))
> , ran the executable and kept required files to a conveniently named folder.
> After that I changed my previous R script so I could use the function
> lapply().This script apparently worked fine.
>
> Finally, I tried to parallelize the problem by using snow and parLapply().
> The resulting script looks like this:
>
> ## Not run
> #
> library(snow)cl <- makeCluster(3, type = "SOCK")
> clusterExport(cl,list('param.esp','copy.files','for12.template','program.executor'))
> parLapply(cl,a.list,a.function))stopCluster(cl)
> #
> ##End not run
>
> Although it runs, the parallelized version is messing up the input parameters
> to pass to the executable (see table below, where parameters P1 and P2 are
> considered. ".s" comes from the serial code and ".p" from the parallelized
> one):
> s r P1.s P2.s P1.p P2.p
> 1 1 1 1.0 3.00 2.0 3.00
> 2 2 1 1.5 3.00 2.0 3.75
> 3 3 1 2.0 3.00 2.0 3.00
> 4 4 1 1.0 3.75 1.5 3.00
> 5 5 1 1.5 3.75 1.5 3.00
> 6 6 1 2.0 3.75 2.0 3.75
>
> My first thought to avoid the described behaviour was creating a temporary
> file, say "tmp.id" with id being an identification run number, and copying
> "filetorun.EXE" and "Input.txt" to "tmp.id". However, while doing so, I
> realised that although running the correct "filetorun.EXE" copy (i.e., the
> one in "tmp.id") R looks for "input.txt" in the work directory.
Not sure about the real setup, but you can actually specify the path,
not only filenames.
Uwe Ligges
>
>
> I've been looking thoroughly for a solution but I got nothing.
>
> Thanks for any help in advance,
>
>
> Xavier Portell Canal
>
> PhD candidate
> Department of Agri-food engineering,
> Universitat Politècnica de Catalunya
>
> ______________________________________________
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>
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