similar to: Rmpi 0.5-6 : error spawning process

Hello, the package snow is not working on a windows cluster with MPICH2 and Rmpi. There is an error in makeCluster: launch failed: CreateProcess(/usr/bin/env "RPROG="C:\Programme\R\R-2.5.1\bin\R" "OUT=/dev/null" "R_LIBS=" C:/Programme/R/R-2.5.1/library/snow/RMPInode.sh) on 'cl1' failed, error 3 - Das System kann den angegbenen Pfad nicht finden. I

Dear all, I have a large dataset of randomly generated weighed sample for which I wish to compute a kernel density estimate. I have used the "np" package successfully for smaller datasets, however for the larger ones, they take too long when using the cross validation options for bandwidth selection ("cv.ls" or "cv.ml"). Of course, they are much quicker with

Hi I am trying to utilize my dual core processor (and later a High-performance clusters (HPC) ) by using the Rmpi, snow, snowfall, ... packages, but I am struggling at the beginning, i.e. to initialise the "cluster" on my dual core computer. Whenever I try to initialize it (via sfInit(parallel=TRUE, cpus=2) or mpi.spawn.Rslaves(nslaves=2) ), I get an error message: >

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, 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

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

Hi everybody! I have the next code which makes a reduction of the *a *variable in two slaves, using the Rmpi package. library(Rmpi) mpi.spawn.Rslaves(nslaves=2) reduc<-function(){ a<-mpi.comm.rank()+2 mpi.reduce(a,type=2, op="prod") return(paste("a=",a)) } mpi.bcast.Robj2slave(reduc) mpi.remote.exec(reduc()) cat("Product: ")

Hi everybody! I have the next code which makes a reduction of the *a *variable in two slaves, using the Rmpi package. library(Rmpi) mpi.spawn.Rslaves(nslaves=2) reduc<-function(){ a<-mpi.comm.rank()+2 mpi.reduce(a,type=2, op="prod") return(paste("a=",a)) } mpi.bcast.Robj2slave(reduc) mpi.remote.exec(reduc()) cat("Product: ")

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

I have just installed Rmpi on a Suse 9.1 linux cluster with openmpi-1.0.1. I am trying the example included below from the tutorial website. However, I keep getting the following error: > # Load the R MPI package if it is not already loaded. > if (!is.loaded("mpi_initialize")) { + library("Rmpi") + } > > # Spawn as many slaves as possible >

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Dear R list, In the course of learning to work with Rmpi, we are confused about a few points. The following simple program is based on some examples we retrieved from the web. Each slave is writing the same output line multiple times (a multiple equal to the number of slaves). In other words, the write statements are being executed a number of times equal to the number of slaves. I am

Hi All, I'm trying to parallelize some code using Rmpi and I've started with a sample 'hello world' program that's available at http://math.acadiau.ca/ACMMaC/Rmpi/sample.html. The code is as follows; # Load the R MPI package if it is not already loaded. if (!is.loaded("mpi_initialize")) { library("Rmpi") } # Spawn as many slaves as possible

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 =

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

I'm aiming to compare the workings of Rmpi and multicore on a duel processor quad core machine with 64 bit R-2.11.1 Kubuntu 10.4. It's impossible for me to get a small reproducable code segment to show what I mean, but if I show what works for mclapply, I'd hope it's possible to be shown what would be the equivalent way with mpi.apply. The function lr.gbm has variables trees,

Hello, we are doing some computations with MPI and Rmpi. Therefore papply is a very comfortable function. Is it possible to reuse calculated data on slaves? We do some calculation with papply, then we have to do some overall calculation at the master then we want to do some calculation on the slaves with the old results and some new results from the master. We do not want to send all data

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