similar to: Parallel computing with snow

Hi, The following function use to work, but now it doesn't giving the error "> CallSnow(, 100) Using snow package, asking for 2 nodes 2 slaves are spawned successfully. 0 failed. Error in checkForRemoteErrors(val) : 2 nodes produced errors; first error: no applicable method for 'lapply' applied to an object of class "list" ". Where this is the

Hi I try parallelising some code using the snow package and the following lines: cl <- makeSOCKcluster(8) pfunc <- function (x) (if(x <= (-th)) 1 else 0) ###correlation coefficient clusterExport(cl,c("pfunc","th")) cor.c.f <- parApply(cl,tms,c(1,2),FUN=pfunc) The parApply results in the error message: > cor.c.f <- parApply(cl,tms,c(1,2),FUN=pfunc) Error

Hello All, I can run the "lower level" functions OK, but many of the higher level (eg. parSApply) functions are generating errors. When running the example (from the snow help docs) for parApply on MacOSX 10.5.5, I get the following error: cl <- makeSOCKcluster(c("localhost","localhost")) sum(parApply(cl, matrix(1:100,10), 1, sum)) Error in

Hi Greg, I don't know if this is related to your problem, but I get the same error (on both ubuntu and fedora linux, R 2.9) and just found a very curious behaviour - snowfall apply functions don't like the variable name "c". E.g.: c<-1 sfLapply(1:10, exp) issues the same error you had posted, while subsequent rm("c") sfLapply(1:10, exp) runs fine. Rainer

From: Rock <zimilo@code-trick.com> --- fs/btrfs/backref.c | 10 ++-- fs/btrfs/qgroup.c | 16 +++--- fs/btrfs/send.c | 2 +- fs/btrfs/ulist.c | 154 +++++++++++++++++++++++++++++++++++++--------------- fs/btrfs/ulist.h | 45 ++++++++++++--- 5 files changed, 161 insertions(+), 66 deletions(-) diff --git a/fs/btrfs/backref.c b/fs/btrfs/backref.c index ff6475f..a5bebc8

(Posted also to debian-user) In my office network I have access to a debian powerpc server and 2 freebsd 6 servers (actually one of them is my notebook). Experienced user of the statistical software R, I have now a go at parallel computation via (r-)pvm and snow under R to enhance the performance of a heavy duty statistical problem involving many iteration on the calculation of models. I moved

I'm using /parApply/() function in "snow" package for parallel computing (boostrapping repeating calculation), as the follows: MyBoostrapping <- function( i ){ ..... } cl <- makeCluster( ncluster, type = "SOCK") i.circle <- as.matrix( 1:128, , 1) parApply( cl, i.circle, 1, FUN = MyBoostrapping) It works. However, I want to set more than one arguments to

Dear R gurus, I have a very embarrassingly parallelizable job that I am trying to speed up with snow on our local cluster. Basically, I am doing ~50,000 t.test for a series of micro-array experiments, one gene at a time. Thus, I can easily spread the load across multiple processors and nodes. So, I have a master list object that tells me what rows to pick up for each genes to do the t.test from

I've started to use the parallel package and it works very well speeding things up. Thank you for making this easy to do. Should I have expected that parCapply would return a vector when parApply returns a matrix? library(parallel) x <- matrix(rnorm(8), nc = 2) apply(x, 2, function(y) y) [,1] [,2] [1,] -0.9649685 0.91339851 [2,] -1.4313140 0.13457671 [3,] 1.0499248

Hi, Here are the issues I found: Typos ----- (a) Found: It a parallel version of ?evalq?, "is" missing. (b) Found: 'parLapplyLB', 'parSapplyLB' are load-balancing versions, intended for use when applying ?FUN? to 'parLapplyLB' has no 'FUN' arg (more on this below). (c) Found: 'clusterApply' calls 'fun' on the first

invoking parLapply without a cluster fails to find a previously registered cluster > library(parallel) > setDefaultCluster(makePSOCKcluster(2)) > parLapply(X=1:2, fun=function(...) {}) Error in cut.default(i, breaks) : invalid number of intervals This is because in parLapply length(cl) is determined before defaultCluster(cl) is called. By inspection, this appears to be true of

R Help - I'm trying to run a correlation matrix with a covariate of "age" and will at some point will also want to covary other variables concurrently. I'm using the "psych" package and have tried other methods such as writing a loop to extract semi-partial correlations, but it does not seem to be working. How can I accomplish this? library(psych) > set.cor(y =

Dear R yet again! I finally got the Rmpi package to install! Yay!. However, when I go into R to use it, there is an error with the dyn.load file. This should be simple (allegedly). Please help. Thanks, Sincerely, Erin mailto: hodgess at gator.uhd.edu /home/faculty/hodgess/R-2.6.0/bin [hodgess at gator bin]$ ./R CMD INSTALL Rmpi_0.5-4.tar.gz

Dear all, I have used the Rmpi package many times before however this time I've installed it as I always do with openMPI tar.gz file direct from the website. I'm installing on my ubuntu 8.10. Linux 2.6.27-11-generic #1 SMP Thu Jan 29 19:28:32 UTC 2009 x86_64 GNU/Linux All i get is: > library(Rmpi) Segmentation fault :~$ Which dumps me back into the shell, and doens't give me much

CentOS Errata and Security Advisory 2009:0134 https://rhn.redhat.com/errata/RHSA-2008-0134.html The following updated files have been uploaded and are currently syncing to the mirrors: s390: updates/s390/RPMS/expect-5.38.0-92.8.c3.s390.rpm updates/s390/RPMS/expect-devel-5.38.0-92.8.c3.s390.rpm updates/s390/RPMS/expectk-5.38.0-92.8.c3.s390.rpm updates/s390/RPMS/itcl-3.2-92.8.c3.s390.rpm

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CentOS Errata and Security Advisory CESA-2008:0134 tcltk security update for CentOS 3 x86_64: https://rhn.redhat.com/errata/RHSA-2008-0134.html The following updated file has been uploaded and is currently syncing to the mirrors: x86_64: updates/x86_64/RPMS/expect-5.38.0-92.8.x86_64.rpm updates/x86_64/RPMS/expect-devel-5.38.0-92.8.x86_64.rpm updates/x86_64/RPMS/itcl-3.2-92.8.x86_64.rpm

CentOS Errata and Security Advisory CESA-2008:0134 tcltk security update for CentOS 3 i386: https://rhn.redhat.com/errata/RHSA-2008-0134.html The following updated file has been uploaded and is currently syncing to the mirrors: i386: updates/i386/RPMS/expect-5.38.0-92.8.i386.rpm updates/i386/RPMS/expect-devel-5.38.0-92.8.i386.rpm updates/i386/RPMS/itcl-3.2-92.8.i386.rpm

Hi, I am using R to fit statistical models to data were the observations are means of the original data. R is used to calculate the mean before fitting the model. My problem is: When R calculates the means using tapply, the class of the means differs from the class of the original data, which gives me trouble when I want to use the original data to calculate model predictions. Here is a simple

CentOS Errata and Security Advisory 2009:0134 https://rhn.redhat.com/errata/RHSA-2008-0134.html The following updated files have been uploaded and are currently syncing to the mirrors: ia64: updates/ia64/RPMS/expect-5.38.0-92.8.c3.ia64.rpm updates/ia64/RPMS/expect-devel-5.38.0-92.8.c3.ia64.rpm updates/ia64/RPMS/expectk-5.38.0-92.8.c3.ia64.rpm updates/ia64/RPMS/itcl-3.2-92.8.c3.ia64.rpm