similar to: exit function in R?

A new version of the 'snow' package for parallel computing in R is available at http://www.stat.uiowa.edu/~luke/R/cluster/snow_0.3-3.tar.gz This substantially revises the way in which worker processes are started to allow snow to be used on Windows and Mac/Windows/Linux combinations. I have successfully used the SOCK version on a standalone Windows machine and combinations of

Hello, I try to write parts of my code in C to accelerate the for-loops. But basic operations I want to do in R (e.g. start cluster). My R code looks something like this: library(Rmpi) mpi.spawn.Rslaves() mpi.remote.exec(....) dyn.load("test.so") erg <- .Call("test", ....) .... mpi.close.Rslaves() mpi.quit() And my C function looks something like this: #include

Hello, I have this kind of dataframe and have to plot it. data <- data.frame(sw= c(1,2,3,4,5,6,7,8,9,10,11,12,15), zehn = c(33.44,20.67,18.20,18.19,17.89,19.65,20.05,19.87,20.55,22.53,NA,NA,NA), zwanzig = c(61.42,NA,26.60,23.28,NA,24.90,24.47,24.53,26.41,28.26,NA,29.80,35.49), fuenfzig =

When I execute mclapply it creates the needed processes, but these processes never begin computing anything, they just wait indefinitely. I recently upgraded to version 2.9.1, which might have caused the problem. -- Med venlig hilsen Rune Schjellerup Philosof Ph.d.-studerende, Statistik, IST, SDU Telefon: 6550 3607 E-mail: rphilosof at health.sdu.dk Adresse: J.B. Winsl?wsvej 9, 5000 Odense

Hi, I had access to an hpc cluster, and wanted to parallelize some of my R code. I looked at the snow,nws, rscalapack documentation but was unable to make out how I should submit my job to the hpc, and how I should code a simple program. For example, if I had 10 matrices, and 10 processor how should I write the R (and the hpc submit code) so that I run the calculations (e.g. rowsums) for each

Hello all; I'm trying to execute parallel jobs trough library snow on a cluster built through torque/PSB. I'm succesfully obtaining the cluster with: >system("cat $PBS_NODEFILE > cluster.txt") >mycluster <- scan(file="cluster.txt",what="character") >cl <- makeSOCKcluster(mycluster) The only problem, at the moment, is that if I use

Hi all, now I'm testing R in a "virtual cluster", made it with VirtualBox. This one has 3 nodes, running CentOS 5 and OpenMPI 1.2.8, and the principal node (called "server") exports the /home to other nodes. I have installed R and OpenMPI in /home, in fact, it seems work OK. Editing the openmpi-default-hostfile and run "mpirun -np 3 hostname" I can see the

Dear R Users, I am attempting to use the snow package for clustering. Is there a way to identfy, in the environment of each node, a rank for that node and also, the total size of the cluster ? By way of analogy, I am looking for the functions in snow equivalent to mpi.comm.rank() and mpi.comm.size() from RMPI, in case that makes things clearer. Thanks in advance, Tolga Generally, this

Anyone using or has access to ParallelR? I was looking at the page and found nothing really useful! http://www.revolution-computing.com/sitegenius/topic.php?id=195 I want to see if I can run R on a cluster of workstation, and use batch systems like Grid Engine or Xgrid: http://gridengine.sunsource.net/ http://ww.apple.com/acg/xgrid/ --Chi

Hello, which possibilities are available in R for simultaneous or parallel computing? I only could find biopara (http://cran.r-project.org/src/contrib/Descriptions/biopara.html) Are there other possibilities? Are there special groups working on simultaneous computing with R? Thanks Markus -- Dipl.-Tech. Math. Markus Schmidberger Ludwig-Maximilians-Universit?t M?nchen IBE - Institut f?r

Has anybody tried to use Rmpi with the OpenMPI library instead of LAM/MPI? LAM appears to be somewhat hardcoded in the Rmpi setup. Before I start to experiment with changing this, has anybody else tried Rmpi with non-LAM MPI implementations? Dirk -- Hell, there are no rules here - we're trying to accomplish something. -- Thomas A. Edison

Hi, I'm testing the efficiency of the Rmpi package regarding parallelization using a cluster. I've found and tried the task pull programming method, but even if it is described as the best method, it seems to cause deadlock, anyone could help me in using this method? here is the code I've found and tried: # Initialize MPI library("Rmpi") # Notice we just say "give us

Dear all, I have a problem that may be someone of you can help. I am a newbie and do not find how to do it in manuals. I have two arrays, for example: ar1 <- array(data=c(1:16),dim=c(4,4)) ar2 <- array(data=c(1:16),dim=c(4,4)) colnames(ar1)<-c("A","B","D","E") colnames(ar2)<-c("C","A","E","B") > ar1

Dear members of the list, it is likely a stupid question but I cannot find the information neither in R manuals nor in google. I am generating a plot (from hclust results) but I cannot see properly the labels because the default font size is too large. How can I change it? Thanks! Federico

Hello, assume I have an "unstructured" text line from a connection. Unfortunately, it is in string format: R> x [1] "\talpha0\t-0.638\t0.4043\t0.4043\t-2.215\t-0.5765\t-0.137\t501\t2000" How can I extract the data included in this string object "x" in order to get the elements for the parameter vector called "alpha0", i.e. -0.638 0.4043 0.0467

Hello, I want to use expresso for preprocessing the hgu133a-spikein data from affycompII. But there is an error: > library(affy) > path <- "z:/Microarray/hgu133a-spikein/rawdata" > celFile <- list.celfiles(path=path,full.names=TRUE); > affyBatch <- ReadAffy(filenames=celFile[1:6]); > eset1 <-

Hello, I try to write an extension in C, to get a faster functions. Therefore I have to add an element (vector) to a vector. The command in R is very simple: x = c(x,a) But in C I have the problem to reallocate my vector for getting more space. Everything I tried, I get a "Segmentation fault". So, how can I combine two vectors in C and give the result back to R (return(x))? Thanks

Hi R users: Is there a function to obtain the correlation within groups from this very simple lme model? > modeloMx1 Linear mixed-effects model fit by REML Data: barrag Log-restricted-likelihood: -70.92739 Fixed: fza_tension ~ 1 (Intercept) 90.86667 Random effects: Formula: ~1 | molde (Intercept) Residual StdDev: 2.610052 2.412176 Number of Observations: 30 Number

Hi, I am using a cluster with LAM 7.1.3/MPI 2 and R 2.6.0. Rmpi version 0.5-5 is working very well. Now I have tested "Rmpi 0.5-6". During spawning the Rslaves I get an error: MPI_Error_string: error spawning process > sessionInfo() R version 2.6.0 (2007-10-03) x86_64-unknown-linux-gnu locale:

Hello, is there any function in the package snow to check for a really running cluster? The function checkCluster only checks the variable cl. And the variable is still available after stopping the cluster! ( a simple solution would be deleting the cluster variable cl in the function stopCluster) > library(snow) > cl <- makeCluster(5) 5 slaves are spawned successfully. 0