similar to: Multiple CPU HowTo in Linux?

Dear All I want to store matrix in an array Suppose s<-array(0,4) for(i in 1:4) s[i] <- read_matrix(a,2,2) But the error - number of items to replace is not a multiple of replacement length. Can you suggest me any alternative method for storing a matrix in an array. Thanks In advance. Kind Regards Wesley C Mathew [[alternative HTML version deleted]]

I have a R script that contain these lines for plotting: plot(foo,lwd=2,lty=3,col="red", main=""); plot(bar,lwd=2,lty=3,col="blue"); legend(0.6,0.6,c('Default','Probabilistic'), col=c('red','blue'),lwd=3); But it generate 1 file (Rplot.pdf) with two pages. Each page for 1 plot. Is there a way I can put them together in to one page?

Hi, I want 12 ticks at axis 1 and want to write Jan-Dec on each. something like: axis(1, at=1:12, labels=c('J','F','M','A','M','J','J','A','S','O','N','D')) I could omit default ticks but now how to control ticks. plot(file$time, file$ch4*1000, ylim=c(1500,1700), xaxt='n', xlab= NA,

Hi, I have been working with Program R for my stats class and I keep coming upon the same error, I have read so many sites about inputting data from a text file into R and I'm using the data to do a correspondence analysis. I feel like I have read everything and it is still not explaining why the error message keeps coming up, I have used the exact examples I have seen in articles and the

Hello all, I encountered a problem using the recommended backport method to upgrade R from 2.7.1 to 2.11.1 in a Debian lenny system. r-base cannot install, and I tracked it down to a r-cran-class dependency: # apt-get install r-cran-class Reading package lists... Done Building dependency tree Reading state information... Done Package r-cran-class is not available, but is referred to by

On a Unix machine I ran caret::rfe using the multicore package, and I saved the resulting object using save(lm2, file = "lm2.RData"). [Reproducible example below.] When I try to load("lm2.RData") on my Windows laptop, I get Error in loadNamespace(name) : there is no package called 'multicore' I completely understand the error and I would like to ignore it and

dear r experts---Is there a multicore equivalent of by(), just like mclapply() is the multicore equivalent of lapply()? if not, is there a fast way to convert a data.table into a list based on a column that lapply and mclapply can consume? advice appreciated...as always. regards, /iaw ---- Ivo Welch (ivo.welch at gmail.com)

Hi all, I have R installed on a box, which is running on a machine with 16 core and Redhat - Linux. I am handling huge (size of dataset will be 5 GB) dataset. Lets assume that my data is in the form of structured (multiple) logs. I access the data by using all.files(). Since by default basic version of R utilizes single core, the processing of my analysis code is taking too much time. I got to

Thanks Simon, I will take note of the sensible default for core usage. I?m trying to achieve small scale parallelism, where tasks take 1-5 seconds and make fuller use of consumer hardware. Its not a HPC-worthy computation but even laptops these days come with 4 cores and I don?t see a reason to not make use of it. The goal for the current piece of code I?m working on is to bootstrap many

The attached code produces corrupted pdfs (test2.pdf, test4.pdf and test5.pdf). The resulting pdf depends on how many cores are available on the machine. I don't see why there should be any difference between the pdfs (exept for the timestamp). Doing many operations involving mclapply can increase the size of the resulting pdf by ten times! Thank you for checking this. require(multicore)

Sir, I want to apply mclapply() function for my analysis. So, I have to install multicore package. But I can not install the package. >install.packages("multicore") It gives that package multicore is not available. Can you help me? Regards, Suman Dhara [[alternative HTML version deleted]]

Dear all, I have an R script that uses Rcpp, and I have been trying to parallelize it using mclapply (I tried with the multicore and the parallel library) Sometimes (not always, interestingly), the CPU use for each core drops, usually so that the total over all cores reaches 100%, i.e., as fast as if using just one single core fully. I tried my code directly from within emacs, and also using a

Hello, I spent a lot of a time on a weird bug, and I just managed to narrow it down. In parallel code (here with parallel::mclappy, but I got it doMC/multicore too), if the library(tcltk) is loaded, R hangs when trying to open a DB connection. I got the same behaviour on two different computers, one dual-core, and one 2 xeon quad-core. Here's the code: library(parallel) library(RSQLite)

Thanks Henrik, That clears things up significantly. I did see the warning but failed to include it my initial email. It sounds like an RStudio issue, and it seems like that it?s quite intrinsic to how forks interact with RStudio. Given this code is eventually going to be a part of a package, should I expect it to fail mysteriously in RStudio for my users? Is the best solution here to migrate all

https://gist.github.com/rpietro/6430771 stemDocument function doesn't seem to be working. Tried to look up and a few people have reported the problem, but no solution that I could find. would appreciate any help

Dear R developers, with the inclusion of the package "parallel" in the upcoming release of R, users and package developers are likely to make increasing usage of parallelization features. In part, these features rely on forking the R process. As ?mcfork points out, fork()ing in a GUI process is typically a bad idea. In RKWard, we "only" seem to have problems with signals

On Windows there are a few 'pthreads' implementation, e.g. pthreads-w32 and winpthreads [https://cran.r-project.org/doc/manuals/r-devel/R-exts.html#Using-pthreads]. We're thinking of giving them a try for the matrixStats package, and basic tests indicates it works, but since Windows pthreads are not used by core R (or?) I've got a little bit worried that we will face overwhelming

I'm running r 2. on a mac running 10.6.4 and a dual-core macbook pro. I'm having a funny time with multicore. When I run it with 2 cores, mclapply, R borks with the following error. The process has forked and you cannot use this CoreFoundation functionality safely. You MUST exec(). Break on __THE_PROCESS_HAS_FORKED_AND_YOU_CANNOT_USE_THIS_COREFOUNDATION_FUNCTIONALITY___YOU_MUST_EXEC__()

Is there any reason to expect a problem ? i'm running this script on the cluster down the hall: module load R/2.11.0 R library(multicore) fxx<-function(ll) runif(1) mclapply(1:10,fxx) i get: Error in fork() : Unable to fork. less /proc/cpuinfo yields: processor : 0 vendor_id : GenuineIntel cpu family : 6 model : 15 model name : Intel(R) Xeon(R) CPU

On 03/25/2015 07:48 PM, Simon Urbanek wrote: > On Mar 25, 2015, at 3:46 PM, Valerie Obenchain <vobencha at fredhutch.org> wrote: > >> Hi Simon, >> >> I'm having trouble with nested parallel workers, specifically, forking inside socket connections. >> > > You simply can't by definition - when you fork *all* the workers share the same connection