similar to: Question on Rmpi looping

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 >

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

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

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: ")

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,

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I've written a function that uses Rmpi to perform a calculation in parallel. It works fine, but I'm trying to improve efficiency in terms of memory usage and the amount of data being passed back and forth between mater and slaves. Calculations are performed on a symmetrical matrix in order to zero-out some of the cells. In the parallel

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:

I am running R 2.7.0 on a Suse 9.1 linux cluster with a job scheduler dispatching jobs and openmpi-1.0.1. I have tried running one of the examples at http://ace.acadiau.ca/math/ACMMaC/Rmpi/examples.html in Rmpi and they seem to be working, except mpi.close.Rslaves() hangs. The slaves are closed, but the master doesn't finish its script. Below is the example script and the call to R. The job is

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 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 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

Hi, I try use Rmpi package to my compute. In my work I'm using eclipse version 3.6.2 and statEt version 0.10.0 (launch Rterm or RJ). Actually I observed strange behavior, when I try loading Rmpi directly I don't have any problem i.e.: library("Rmpi") mpi.spawn.Rslaves() 8 slaves are spawned successfully. 0 failed. master (rank 0, comm 1) of size 9 is running on: marcin-HP

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 R People: I'm having trouble installing Rmpi on a debian machine. Here is my output: bccd at node000:~$ /bccd/home/bccd bccd at node000:~$ bccd at node000:~$ export RMPI_TYPE=OPENMPI bccd at node000:~$ R CMD INSTALL Rmpi_0.5-9.tar.gz * installing to library '/bccd/home/bccd/R/x86_64-pc-linux-gnu-library/2.15' * installing *source* package 'Rmpi' ... checking for gcc...

Hello, I'm using R on a 10 blade dual quad core Rocks Cluster, and trying to use Rpmi and snow. I basically wondered if at the moment I ought to install Rmpi against another form of mpi (not openmpi) and wondered whether anyone could pass on any experience. I'm mainly worried about (a) the R server taking up 100% cpu time (I think this is a known issue with Rmpi and openmpi) and (b)

Hi I have managed to install MPICH2 and Rmpi on my Windows 7 machine. I can also run the following code > library(Rmpi) > mpi.spawn.Rslaves() 4 slaves are spawned successfully. 0 failed. master (rank 0, comm 1) of size 5 is running on: MyMaster slave1 (rank 1, comm 1) of size 5 is running on: MyMaster slave2 (rank 2, comm 1) of size 5 is running on: MyMaster slave3

Hi I have managed to install MPICH2 and Rmpi on my Windows 7 machine. I can also run the following code > library(Rmpi) > mpi.spawn.Rslaves() 4 slaves are spawned successfully. 0 failed. master (rank 0, comm 1) of size 5 is running on: MyMaster slave1 (rank 1, comm 1) of size 5 is running on: MyMaster slave2 (rank 2, comm 1) of size 5 is running on: MyMaster slave3 (rank 3, comm

R-users, My question is related to earlier posts about benefits of quadcore over dualcore computers; I am trying to setup a cluster of windows xp computers so that eventually I could make use of 10-20 cpu:s, but for learning how to do this, I am playing around with two laptops. I thought that the package snow would come handy in this situation, but to use snow, I would probably need to install