[R-sig-hpc] To run bugsparallel

[Paul Johnson]

I didn't want you to think we are ignoring you.  I don't know the
answer because I use Linux, not Windows, and you do outline a very
complicated toolchain.  I can ask some questions that may help you
think through this.

1. You have success with MPI programs in R?  Except for winbugs, I
mean. Right?  You can run the examples that circulate with programs
like Rmpi or snowFT?

2. You have success running just ONE thread with winbugs from R?  (no
parallelism). Right?

3. When you run winbugs from R, are you able to get it to run multiple
chains at once (without invoking MPI)?

4. what is "bugsparallel" software?  Do we have any reason to believe
it is good?

I doubt that testing all of this on a one processor system is useful.
In my experience, mpich will notice that and refuse to do anything at
all.

On Linux, Winbugs works horribly for me.  There is an alternative
implementation of BUGS called jags that runs on Linux.  I believe that
if you really want to get something that works in an understandable
way, you might consider going in that direction.  I'm sorry nobody
stepped up to answer your question, but you have to admit that you
have created a very complicated problem and there aren't many Windows
users who have tried it. Especially on one processor systems.

pj

On Thu, Mar 4, 2010 at 7:07 PM, Debabrata Midya
<Debabrata.Midya at services.nsw.gov.au> wrote:
> Hi,
>
> Thanks in advance.
>
> I have posted this one on 25 Feb 2010 and so far I have not received
> any answer. That is why, I am posting it once again. I may be excused
> for this.
>
> I have come across bugsparallel software to run WinBUGS in parallel.
>
> I need your assistance to solve this problem. The computer hangs while
> running at bugs.fit <- bugsParallel(…….)
>
> I have described below how I have tried.
>
> 1. I am running on Windows XP and I have tested on a Pentium® D CPU
> 2.80GHz, 1.50 GB of RAM and it has a single processor (for a test run
> only).
>
>
> 2. Installed: MPICH2 requires Microsoft .Net 2.0 .NET Framework Version
> 2.0 Redistributable Package (
> http://www.microsoft.com/downloads/details.aspx?familyid=AEA55F2F-07B5-4A8C-8A44-B4E1B196D5C0&displaylang=en
> )(NETCFSetupv2.msi)
>
> 3. Installed: Visual C++ 2005 SP1 Redistributable Package (x86) (
> http://www.microsoft.com/downloads/details.aspx?FamilyID=200b2fd9-ae1a-4a14-984d-389c36f85647&DisplayLang=en
> ). (vcredist_x86.exe)
>
> 3. Installed: MPICH2 for Windows (mpich2-1.2.1-win-ia32.msi )
>
> 4.      I have installed R-2.10.1 and Rmpi 0.5-9. I have tested the
> following code and it works.
>
> library(Rmpi)
> mpi.spawn.Rslaves(nslaves=3)
> mpi.parReplicate(20, mean(rnorm(1000)))
> mpi.close.Rslaves()
>
> 5. I have installed rlecuyer (0.3-1), coda (0.13-4) and lattice.
>
> 6. I have installed WinBUGS 1.4
>
> 7.      But the machine hangs on bugs.fit <- bugsParallel(…….) whenever
> I run bugsparallel code. That means the program runs up to
> mpi.setup.rngstream() # initializes parallel random number generation
>
> model.name = "FXaExample1" # root name of modeling files
> workDir = "M:/Rmpi/bugsparallel/bugsParallel/FXaExample1" # change to
> match the path to the directory containing FXaExample1.R and
> FXaExample1.txt
> toolsDir = "M:/Rmpi/bugsparallel/bugsParallel/bugsTools" # change to
> match your setup
> bugsDir = paste("M:/WinBUGS14/",sep="")
> nSlaves = 4
>
> library(Rmpi)
> library(rlecuyer)
> library(coda)
> library(lattice)
> source(paste(toolsDir,"/bgillespie.utilities.R",sep="")) # These are a
> few of my favorite things
> source(paste(toolsDir,"/bugsParallel-1.0.R",sep=""))
> source(paste(toolsDir,"/bugs.tools.R",sep="")) # A few BUGS-specific
> utilities
>
> set.seed("10271998") # not required but forces consistent results
> setwd(workDir)
> ###################################################################
> # Data management
>
> xdata = read.csv("fxa.data.avg.csv")
>
> # create WinBUGS data set
> bugsdata = list(
>            nobs = nrow(xdata),
>            cobs = xdata$cavg,
>            FXa = xdata$fxa.inh.avg)
>
> # create initial estimates
> bugsinit = function() list(
>            Emax = runif(1,40,100),
>            logEC50 = rnorm(1,log(100),0.4),
>            gamma = 10*rbeta(1,0.25,5),
>            sigma = exp(rnorm(1,log(5),0.2)))
>
> # specify what variables to monitor
> parameters = c("Emax","EC50","gamma","sigma","FXaPred")
>
> # specify the variables for which you want history and density plots
> parameters.to.plot = c("deviance","Emax","EC50","gamma","sigma")
>
> ################################################################################################
> # run WinBUGS
>
> n.chains = nSlaves
> n.iter = 600
> n.burnin = 100
> n.thin = 5
>
> mpi.spawn.Rslaves(nslaves = nSlaves) # launches multiple R slave
> processes on available processors
> mpi.setup.rngstream() # initializes parallel random number generation
>
> if(.Platform$OS.type == "windows"){
>            bugs.fit <- bugsParallel(data=bugsdata,inits=bugsinit,
>
> parameters.to.save=parameters,model.file=paste(getwd(),"/",model.name,".txt",sep=""),
>
> n.chains=n.chains,n.iter=n.iter,n.thin=n.thin,n.burnin=n.burnin,refresh=10,clearWD=T,
>                        bugs.directory = bugsDir)
> }else if(.Platform$OS.type == "unix"){
> #          wineBin = "/Applications/Darwine/Wine.bundle/Contents/bin"
>            wineBin = "/usr/local/MacPorts/bin"
>            bugs.fit <- bugsParallel(data=bugsdata,inits=bugsinit,
>
> parameters.to.save=parameters,model.file=paste(getwd(),"/",model.name,".txt",sep=""),
>
> n.chains=n.chains,n.iter=n.iter,n.thin=n.thin,n.burnin=n.burnin,refresh=10,clearWD=T,
>                        bugs.directory = bugsDir, useWINE=T,
> WINE=paste(wineBin,"/wine",sep=""),
>                        newWINE=T,
> WINEPATH=paste(wineBin,"/winepath",sep=""))
> }
>
> It runs up to mpi.setup.rngstream() but hangs on at
>
> bugs.fit <- bugsParallel(…….)
>
> Once again, thank you very much for the time you have given.
>
> I am looking forward for your reply.
>
> Regards,
>
>
> Deb
>
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-- 
Paul E. Johnson
Professor, Political Science
1541 Lilac Lane, Room 504
University of Kansas