similar to: snow package on multi core unix box

Hi, I installed the snow package on a unix box that has multiple cores. To be able to exploit the multiple cores (on one pc) do I still need to install the rmpi package (or rpvm). Another question, if i run a bayesian simulation on the multiple core after setting them up correctly (using snow), would you think there will be a noticeable speedup gain. Thanks, Saeed --- linux centos 4 dual core

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

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

The package `snow' (Simple Network of Workstations), originally announced in early form about a year ago on this list, is now available from CRAN. Snow implements a simple mechanism for using a workstation cluster for ``embarrassingly parallel'' computations in R. The interface, which is based in part on the Python CoW (Cluster of Workstations; http://www.scipy.org/) package, is

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

Rmpi is not currently available on CRAN, and I don't think it has been for a few months. It is available at http://www.stats.uwo.ca/faculty/yu/Rmpi/ Does anyone know its current status? A few months ago I corresponded with the author, who noted some build problems (specifically on Debian) were the hang up, and seemed to be working on it. I wasn't able to get it to work then (on a

Hello, I have a question that I was wondering if anyone had a fairly straightforward answer to: what is the quickest and easiest way to take advantage of the extra cores / processors that are now commonplace on modern machines? And how do I do that in Windows? I realise that this is a complex question that is not answered easily, so let me refine it some more. The type of scripts that I'm

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

> x <- train[,c( 2:18, 20:21, 24, 27:31)] > y <- train$out > > svm.pr <- svm(x, y, probability = TRUE, method="C-classification", kernel="radial", cost=bestc, gamma=bestg, cross=10) > > pred <- predict(svm.pr, valid[,c( 2:18, 20:21, 24, 27:31)], decision.values = TRUE, probability = TRUE) > attr(pred, "decision.values")[1:4,]

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

Hi, I have few high-level questions about the Snow and Rmpi packages . I understand that Snow uses Rmpi as one of possible transport layers, yet my questions about user experience, not technical details: 1. Does Snow install and work well in Windows? 2. Interruptibility. I understand that currently it is impossible to interrupt a running top-level command in Snow ( Ctl-c or the likes), the

Dear R-users, I am trying to make Snow and Rmpi working on an heterogenous cluster of linux computers. The master computer is built on a 64 bit architecture whereas all nodes are built on a 32 bit architecture. LAM/MPI was installed successfully on all machine. LAM boots correctly on the master computer and it recognizes all nodes defined in the lamhosts file. However, when starting R,

The proper use of SPRNG is a little unclear to me in each of these packages, even more so when I put them all together. My immediate question: in snow I did clusterSetupSRNG. If a later want to (re) set the system to a known seed, how do I do it? That is, I want each distributed process to recreate exactly the same random numbers that it did before; I assume SPRNG assures the streams are

Thanks to Saeed Abu Nimeh. I used pkg_add to install R package on 4.4BSD. My directory now has the following: BUILDDIR Makefrag.cc_lo config.log m4 tests Makeconf Makefrag.cxx config.status po tools Makefile R-2.6.1 doc roots Makefile.bak R-2.6.1.tar.gz etc share Makefrag.cc SVN-REVISION libtool

Hi, I need to understand when is it best to use /rmpi/ and when is it best to use /snow/ for parallel programming in R? I understand snow can be used for a group of non-clustered work stations also. But I wish to understand from the point of view of using both on clusters for a problem which has few chunks of straightforward data-parallelism interleaved with some communication. Since both are

Dear R-user, I am trying to use the function 'parLapply' from the 'snow' package which is supposed to work the same wys as 'lapply' but for a parallelized cluster of computers. The function I am trying to call in parallel is 'dudi.pca' (from the 'ade4' package) which performs principal component analyses. When I call this function on a list of

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

Parallel programming with snowFT Our package snowFT is now available at CRAN. It is an extention of the package snow, which adds fault tolerance (in the sense of recomputing computational units when hardware/network failures occur on compute nodes) and a tighter notion of reproducibility for computations running on clusters. It additionally provides tools for flexible management of cluster size

Parallel programming with snowFT Our package snowFT is now available at CRAN. It is an extention of the package snow, which adds fault tolerance (in the sense of recomputing computational units when hardware/network failures occur on compute nodes) and a tighter notion of reproducibility for computations running on clusters. It additionally provides tools for flexible management of cluster size

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