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dear R experts--- I am experimenting with multicore processing, so far with pretty disappointing results. Here is my simple example: A <- 100000 randvalues <- abs(rnorm(A)) minfn <- function( x, i ) { log(abs(x))+x^3+i/A+randvalues[i] } ?## an arbitrary function ARGV <- commandArgs(trailingOnly=TRUE) if (ARGV[1] == "do-onecore") { ?library(foreach) ?discard <-

When I install Windows Server 2003 Standard Edition on Xen, I didn''t configure multicore (vcpus = 1, cpus not set). Now I''d like to fully utilize multicore, but whatever I set, windows task manager can not see more than 1 cpu. Do I have to reinstall the OS with vcpus and cpus being set properly? Since the image file is licensed, is there any way I configure windows to show multi

Hi, I want to parallelize some computations when it's possible on multicore machines. Each computation produces a big objects that I don't want to store if not necessary: in the end only the object that best fits my data have to be returned. In non-parallel mode, a single gloabl object is updated if the current computation gets a better result than the best previously found. My plan

Hello, I am new to R and have created an application using R 2.10, with a graphical UI using TclTk 8.5, running on windows 7, quad core machine. The intention of the application is to launch calculations and display results on a graphical dashboard. I've reached a roadblock, and I need to confirm that the following CANNOT be done. I've been trying to find a mechanism for doing the

My long-promised Rdsm package is now on CRAN. Some of you may recall that I made a prototype available on my own Web page last July. This is the official version, much evolved since I released the prototype. The CRAN description states: Provides a threads-like programming environment for R, usable both on a multicore machine and across a network of multiple machines. The package

How would I rewrite my code so that I can implement the use of multicore on an Rstudio server to run regsubsets using the "exhaustive" method? The data has 1200 variables and 9000 obs so the code has been shortened here: model<-regsubsets(price~x + y + z + a + b + ...., data=sample, nvmax=500, method=c("exhaustive")) Our server is a quad core 7.5 gb ram, is that

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]]

Hi everyone, Thanks for the help in advance. I just want to know if there is absolutely any way of using multicore if my loop can't run in parallel as each iteration depends on the previous iteration. I have Windows R 2.9.2 and REvolution R Enterprise 2.0 for Windows 64 bit. I also have if necessary R on Ubuntu. 8gb of ram and a core 2 duo processor but I could use a quad core as well. Many

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

It is so difficult ... Which FE? It need BE support? I didn't get it. 2010/8/4 vijay kumar <vijaygbvv at gmail.com> > Yeah OpenMP support. I read that it has a front end support but not the > back end. So are there any projects or teams looking at this issue. > > On Wed, Aug 4, 2010 at 7:24 AM, Liu <proljc at gmail.com> wrote: > >> Multicore? >> You

Hi all, I am new to this LLVM. I went through the documenation of LLVM but I didn't find any support for Multicore. Is there any such possibility where multicore architecture can be exploited using LLVM. Thanks Vijay -------------- next part -------------- An HTML attachment was scrubbed... URL:

Hi, When testing syslinux on Hygon Dhyana processor, there are some information as follows: boot: cpuidtest.c32 Vendor = Unknown Vendor ... boot: ifcpu.c32 debug multicore multicore : 1 cores on this system After adding support for Hygon Dhyana processor, the info- rmation is correct: boot: cpuidtest.c32 Vendor = Hygon ... boot: ifcpu.c32 debug multicore multicore : 64 cores on this

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

On Aug 3, 2010, at 8:48 PM, Liu wrote: > It is so difficult ... > Which FE? It need BE support? I didn't get it. > > 2010/8/4 vijay kumar <vijaygbvv at gmail.com> > Yeah OpenMP support. I read that it has a front end support but not the back end. So are there any projects or teams looking at this issue. > > On Wed, Aug 4, 2010 at 7:24 AM, Liu <proljc at

Hello All, In general when we use Rprof for performance evaluation on Multicore systems the output provides the time on the basis of the "user" time and the sampling time is equal to the the user time as reported by system.time. This does not seem right behavior when R is linked to BLAS/Lapack or other libraries which are optimized for parallel or multicore architectures as

Hello All, In general when we use Rprof for performance evaluation on Multicore systems the output provides the time on the basis of the "user" time and the sampling time is equal to the the user time as reported by system.time. This does not seem right behavior when R is linked to BLAS/Lapack or other libraries which are optimized for parallel or multicore architectures as

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

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)

This is a 'rather than re-invent the wheel' post. Has anyone out there re-written combn so that it can be parallelized - with multicore, snow, or otherwise? I have a job that requires large numbers of combinations, and rather than get all of the index values, then crank it through mclapply, I was wondering if there was a way to just do this natively within a function. Just curious.

Multicore? You want OpenMP support? 2010/8/3 vijay kumar <vijaygbvv at gmail.com> > Hi all, > I am new to this LLVM. I went through the documenation of LLVM but > I didn't find any support for Multicore. Is there any such possibility where > multicore architecture can be exploited using LLVM. > > > > Thanks > Vijay > >