similar to: foreach + snowfall for multicore situations

Hi, in R 2.12.1, R CMD check hangs when building a vignette that uses a foreach loop with the doMC parallel backend. This does not happen in R 2.13.1, nor if I use doSEQ instead of doMC. All versions of multicore, doMC and foreach are the same on both my R installations. Has anybody encountered a similar issue? Thank you. Renaud ### UNIVERSITY OF CAPE TOWN This e-mail is subject to the

Dear all, I am trying to execute the simple example in snowfall http://cran.r-project.org/web/packages/snowfall/vignettes/snowfall.pdf ... require(snow) require(snowfall) sfInit( parallel=TRUE, cpus=2 ) sfLapply( 1:10, exp ) sfStop() I have installed the snow and snowfall packages in R on a machine with windows xp, however, after running the "sfInit( parallel=TRUE, cpus=2 )" line I

Greetings, I am trying to use Reference Class methods in Snowfall, using R 2.12.1 on Ubuntu Natty. Using then directly seems to work (stanza 2 below), but using them indirectly does not (stanza 3 below). I get an "attempt to apply non-function" error. In addition to exporting the instance of the object I created to the Snowfall slaves, I also made several attempts to export the

Hi, I would like to get suggestion about parallel computing package on a multicore windows workstation. I tried doSMP, but it crashes R a lot. I am wondering if "snow" and "snowfall" can be used on a single workstation (i,e, not cluster). At suggestion would be appreciated, Best, Richard [[alternative HTML version deleted]]

Dear All, I have a question of how to export S4 class specification to clusters/workers in parallel computing. The package I used is snowfall. The problem is reproducible as follows. Any hint is greatly appreciated. Edwin Sun === begin =========== library(snowfall) sfInit(parallel = TRUE, cpus = 2) setClass("catt", representation(aa = "numeric")) setClass("dogg",

Dear users, I want to set up R to use one R-script directory and one R-library (directory for packages) for many end-users. I try to do this by using one network-share. This works fine as long as we don't use the snowfall package with parallel=TRUE (sfInit(parallel=TRUE, cpus=4, type="SOCK")). When running R with default settings (local library and local script directory)

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Dear expeRts, I'm currently trying to get data from a PostgreSQL database _in parallel_. I tried two methods: * passing the DBI Connection object to the cluster nodes * connecting the the DB on each node (1) The execution of the first method looks like this: > result = sfClusterApplyLB(input, fun, dbiCon) and produces an "expired PostgreSQLConnection" error. (Of course the

Dear Ola, I cannot say anything about Windows 7, as we do not have any Win7 machines here in our institute and I even do not know someone who have Win7 on a private machine. I will try to find a machine with this OS and test it. Anybody having experiences with Win7 yet? Greetings Jo > -------- Original Message -------- > Subject: [R] snowfall on Win7 > Date: Tue, 15 Dec 2009 11:25:37

Hi all, Sometimes I'll find myself "ctrl-c"-ing like a madman to kill some code that's parallelized via foreach/doMC when I realized that I just set my cpu off to do something boneheaded, and it will keep doing that thing for a while. In these situations, since I interrupted its normal execution, foreach/doMC doesn't "clean up" after itself by killing the

Guys, Is anyone using snowfall? It seems that the last version is broken. sfinit contains test code: data("config", package = "snowfall") configM <- as.matrix(t(config)) config <- as.list(configM) names(config) <- dimnames(configM)[[2]] .sfOption$SERVER <<- as.character(config[["SERVER"]]) .sfOption$PORT <<-

Hello all, I am re-posting my previous question with a simpler, more transparent, commented code. I have been ramming my head against this problem, and I wondered if anyone could lend a hand. I want to make parallel a bootstrap of a linear mixed model on my 8-core mac. Below is the process that I want to make parallel (namely, the boot.out<-boot(dat.res,boot.fun, R = nboot) command).

Dear R users, we have a problem when building R packages which depend on platform specific packages. The following example will illustrate our problem: For parallel computing (in our own package) we want to use the multicore package. Since multicore is not available for Windows we subtitute it by the snowfall package. Currently we create two packages with different "Depends" argument

Hello, Just wondering why I am unable to run this in parallel. A dput of my dataset is attached at the end. Please use to create my data object. I want to run this function in parallel (not sure if this is an efficient implementation): #Function to calculate the time to maturity for the option require(fCalendar,quietly=TRUE) #Trying to calculate the trading days

I experienced the following problem with R 1.3.0 which is probably a bug. The program hangs-up if 1.) a coordinate of segments is outside the ploting region and 2.) the option log="x" is used. ## ## works fine ## plot(1,1, xlim=c(0.5, 2), ylim=c(0.5, 2)) segments(0.5 , 1.2, 1, 0.6) segments(0.25, 1.2, 1, 0.6) segments(1 , 1.2, 1, 0.6) ## ## hang-up ## plot(1,1, xlim=c(0.5, 2),

Hello, I am trying to run a small example with foreach, but I am having some problems. Here is the code: *library(doMC) registerDoMC() zappa = list() frank = list() foreach (i = 1:4) %dopar% { zappa[[i]] = kmeans (iris[-5],4) frank[[i]] = warnings() }* The code runs without error. However the zappa and frank will be empty lists. If I use regular *for *instead, the list will be filled up

People of R(th), I have been ramming my head against this problem, and I wondered if anyone could lend a hand. I want to parallelize a bootstrap of a linear model on my 8-core mac. Below is the process that I want to parallelize (namely, the m2.ph.rlm.boot<-boot(m2.ph,m2.ph.fun, R = nboot) command). This is an extension of the bootstrapping linear models example in Venables and Ripley to

Dear all, I know this topic has already been covered in other posts (at least the for loop Vs apply family of function), but I am looking for fresh / up-to-date opinion and feedback on those 3 methods to run unavoidable loops in R. I realise that it may be too general question for many, so any feedback appreciated. 1. apply Vs for loop >> Seems apply is (was?) supposed to be faster than

Hello, I have a fairly complex hierarchical model that I using rjags to fit. Short test runs verify that it works and everything appears to be setup correctly. Now that I want to collect a larger sample from the posterior (5,000 or more). This looks like it will take several days to run on my hardware (Intel core i7, 16GB RAM) I read in the rjags documentation that there is an option for

Dear R-listers, I have been using Snowfall (version 1.84) for parallel computing on a quad-PC running Windows 7 for a month or so without much problem. I started having problems runnnig R with Snowfall over our network when a new Novell client was installed for Windows 7. I experinenced network mapping problem with this new client. Our network colleague provided a fix which worked but a little