similar to: SNOW: Simple Parallel Computing in R

Dear Friends, I'm trying to learn to use parallel computation using snow & rpvm Now, I have two boxes: 1) Pentium 4, pvm 3.4.5, R 2.2.0 with FreeBSD 5.4 (box uffbsd); 2) PowerPC, pvm 3.4.5, R 2.1.1 with Debian Linux latest stable (box powerpclinux); I'm using the instructions in (found in snow.pdf) http://www.stat.uiowa. edu/~luke/R/cluster/cluster.html. Now ** from the box

I see about 7 different R packages for multi-process parallel programming. Which do you think is the best, most complete, and most robust to pick for general purpose Erlang-style message-passing programming in R, and why? First here's my use case, and then my analysis so far. I often have code whose basic organization looks something like this: 1. Fetch step: For each date, gather up or

At office, using the internal LAN at my disposal, I'm having a go at parallel computing - to begin with - with pvm, rpvm & snow. The two boxes are as follows Remote machine uffbsd: CPU: Intel(R) Pentium(R) 4 CPU 2.00GHz (1994.13-MHz 686-class CPU) Origin = "GenuineIntel" Id = 0xf24 Stepping = 4 real memory = 260046848 (248 MB) This machine NbBSD: CPU: Mobile Intel(R)

Hi, does anybody know how to use the dual processors in the machines of a cluster? I am using R with rpvm and snow packages. I usually start pvm daemon and add host machines first, and then run R to start my computing work. But I find that only one processor in each machine is used in this way and the other one always stays idle. Is there any simple way to tell pvm to use the two processors at

Caveat: I've only played with this a couple of years ago... I believe you can just add each host _twice_ (or as many times as the number of CPUs at that host) to get both CPUs to work. Andy From: Paul Y. Peng > > Hi, > > does anybody know how to use the dual processors in the > machines of a cluster? I am using R with rpvm and snow > packages. I usually start pvm

Hi folks, is it possible to read more things about R behavior in multiprocessor / multihost environment ? Is there any distributed computation project associated to it ? Laurent

Hi All - I'm running a faily long script that uses rpvm & snowFT to spawn off multiple processes with the 'clusterApplyFT' function. Specifically, what happens is that the head node generates a number of seed clusters that are then spawned off to the pvm cluster (in this case, nodes on a 4 dual-core machine) using clusterApplyFT to apply a function to each seed cluster that

I tried ot build rpvm in my own makefile. But runs into some linker errors like e.g. undefined reference to `_R_alloc' My enviornment looks like this: CYGWIN pvm 3.4 compiled under cygwin myself R installed from the rw2001.exe setup file. I guess that the R under rw2001.exe was build with some other compiler? I then tried to compile R myself under CYGWIN but runs into the following

Hi all, I'm trying to get the snow package with mpi working on my linux ubuntu 10.04 machine. When I tried to install it (see below) it already had problems with the dependencies. R version 2.14.0 (2011-10-31) Copyright (C) 2011 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: x86_64-pc-linux-gnu (64-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You

Hello R enthusiasts, I am working with a Fedora Core 6 OS and R 2.5. I have just finished loading PVM on my test cluster and this is working properly. Also, rpvm has been loaded in R. However, when I try to load my test program, I receive this error: Loading required package: rpvm Error in dyn.load(x, as.logical(local), as.logical(now)) ; unable to load shared library

I've trying to fix the check error in rpvm package. Right now on my Mac, I use darwinport to install PVM and I can get rpvm to pass the check using 'R -arch x86_64 CMD check'. However the default 'R CMD check' uses i386 which fails since PVM is built for x86_64 only. So is there a way to ensure proper architecture is used that matches that of the external library like PVM?

All, We are researching approaches to parallel R with the end goal of running R in a distributed manner on a Linux cluster. We expect of course to do some work decomposing our problems to be task-parallel or data-parallel, but wouldn't mind getting an initial boost working with "embarrassingly parallel" code sections and one of the approaches below. Incidentally our environment

Dear R Users, Is there a version of rpvm available for windows ? I have recently had some problems with snow using SOCKS and was considering PVM as an alternative. Thanks in advance, Tolga Generally, this communication is for informational purposes only and it is not intended as an offer or solicitation for the purchase or sale of any financial instrument or as an official confirmation of

Is the rmpi package (or rpvm) needed to exploit multiple cores on a single unix box using the snow package. The documentation of the package does not provide info about setting up a single machine with multiple cores. Also, if how effective is it to run a bayesian simulation on parallel (or distributed) processors using the snow package. Thanks, Saeed

Greetings all. I am trying to run some stuff using the SNOW library on RH EL3 intel x86_64 and I am running into this error: Error in unserialize(node$con) : error reading from connection I am using sockets (not preferred but I can't seem to get rpvm or Rmpi either one to work on x86_64 for different reasons) and it seems to work well when the jobs are small, but it seems that they are

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

When trying to create (a very simple) cluster using makeSOCKcluster or makeCluster I get the following error message: > library(snow) > cl <- makeSOCKcluster("localhost") Fatal error: kann Datei '~/R/i686-suse-linux-gnu-library/2.8/snow/RSOCKnode.R' nicht ?ffnen: Datei oder Verzeichnis nicht gefunden (translation: could not open file [...]: File or directory not

Thanks to Luke Tierney, Agustin Lobo, Stephen Eglen, A.J. Rossini, Simon Wood and Timothy H. Keitt for responding to my question about poor man's parallel processing. Much of the substantive material was cc'ed to r-help already, but my take is as follows. 1) Currently, there is nothing "simple" for solving my problem. 2) I thought that Timothy Keitt's description of the use

Hey my R buddies, I installed the "snow" and "rpvm" package on my Lenovo Thinkpad T400 today. The experiment below gave me a surprise. The time consumed by serial processing was several times larger than that taken by parallel processing. I'm very curious how this happened. Thank you very much. > library(snow) > > cc <- makePVMcluster(2) > > temp <-

Dear R-devel, Inspired by Michael Li's talk at JSM, I decided to try rpvm and snow on our two linux boxes. It only took me a couple of hours of screwing around to get it working (sooner if I had RTFM). Our setup is: 2 dual PIII-866 Xeons, one with 2GB RDRAM, the other with 1.28GB RDRAM. The first machine is acting as the NIS/NFS server. both /usr and /home are exported to the second