similar to: R on a computer cluster

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

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

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, The problem I'm working now requires to operate on big matrices. I've noticed that there are some packages that allows to run some commands in parallel. I've tried snow and NetWorkSpaces, without much success (they are far more slower that the normal functions) My problem is very simple, it doesn't require any communication between parallel tasks; only that it divides

I have an "embarrassingly parallel" routine that I need to run 24000^2/2 times (based on some microarray data). All I really need to do is parallelize a nested for-loop. But I haven't found a clear list of what packages/commands I'd need to do this. I've got a dual quad core xeon system running RHEL5, so if I could use hyperthreading to increase the number of (virtual)

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

I'm invoking R from withing a shell script like this R --no-save --no-restore --gui=none > `hostname` 2>&1 <<BYE # various commands here BYE I would like to regain control from the invoking terminal at some point. I tried source(stdin()) but got a syntax error, presumably stdin is the little shell here snippet (the part between <<BYE and BYE). Is there some way to

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 all, I would like to call TLNise ("Two-Level Normal indipendent sampling estimation") software within R. This software estimates a hierarchical model and it can be download from Philip Everson's website at "http://www.swarthmore.edu/NatSci/peverso1/TLNise/tlnise.htm". The TLNise software consists of: 1) a Fortran source code (tlnisemv1.f) and 2) a Splus code

Can anybody, please, explain me how many parameter are estimated using randomLCA? For examples, model "dentistry.lca2random" estimate 1 scale (or variance, b_j) parameter and 2 position parameters (a_cj)? Doesn't it? Do I need at least 4 diagnostic tests for such a model? What happens if I specify options blocksize and byclass? How many diagnostic tests (or rater) I need?

Dear R Gurus: Is there a problem with Rmpi on x86 with SUSE 10.1, please? I've tried everything and it still won't load. Has anyone else dealt with this please? Thanks, Edna Bell

Dear Sir or Madam, I've been using R for one year and I really appreciate it. I would like to know if a version performing parallel computations on multicore computers and computer clusters exists. Thank you very much. Yours sincerely. Enrico Giorgi _________________________________________________________________ [[alternative HTML version deleted]]

Hello I am fortunate (or in really big trouble) in that the research group I work with will soon be receiving several high end dual quad core machines. We will use the Ubuntu OS on these. We intend to use this cluster for some extensive modeling applications. Our programming guru has demonstrated the ability to link much simpler machines to share CPUs and we purchased the new ones to take

Hola! This is 64bit Lubuntu 13.04, with R-3.0.0 installed from deb http://ppa.launchpad.net/marutter/rrutter/ubuntu raring main via synaptic. gcc --version gcc (Ubuntu/Linaro 4.7.3-1ubuntu1) 4.7.3 > sessionInfo() R version 3.0.0 (2013-04-03) Platform: x86_64-pc-linux-gnu (64-bit) locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8

Has anyone successfully compiled pnmath (http://www.stat.uiowa.edu/~luke/R/experimental ) for an intel processor running mac OS 10.5? When I attempt to do so via the R package installer (choosing "Local Source Package" and pointing to the pnmath_0.0-2.tar.gz file), I get the following errors: * Installing *source* package 'pnmath' ... ** libs ** arch - i386 gcc -arch i386

(1) ...need to speed up a monte-carlo sampling...any suggestions about how I can get R to use all 8 cores of a mac pro would be most useful and very appreciated... (2) spent the last few hours trying to get pnmath to compile under os- x 10.5.4... using gcc version 4.2.1 (Apple Inc. build 5553) as downloaded from CRAN, xcode 3.0... ...xcode 3.1 installed over top of above after

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

On a 2.4.17 (MontaVista 2.1) kernel using ext3, I recently starting seeing the error EXT3-fs error (device ide1(22,1)) in start_transaction: Readonly filesystem EXT3-fs error (device ide1(22,1)) in ext3_delete_inode: Readonly filesystem on a file system within 10-20 seconds after remounting it r/o. Apparemtly a write is being deferred past the remount point and then runs into problems when it is

Can anyone comment on whether or not it is possible to successfully disable the journal of an ext3 root file system prior to reboot? My application is to try and make sure there is no journal prior to installing and rebooting into a system which does not support ext3. I know that as long as the root is cleanly remounted r/o with no journal updates pending, this will be compatible. I'm

After several trial and error attempts, I managed to install the Rmpi package without error on my Linux machine, running Fedora 5. I installed lam-7.1.2, lam-devel-7.1.2 and R-2.4.1, R-devel-2.4.1 The Package Rmpi_5.0-3.tar.gz, I installed once from within R and once from the command line to make sure, I link the right libraries: R CMD INSTALL Rmpi_5.0-3.tar.gz