similar to: multicore children not quiting

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)

Quick question regarding multicore versions of mapply. Package 'multicore' provides a parallelized version of 'lapply', called 'mclapply'. I haven't found any parallelized versions of 'mapply', however (although one can use the lower level function 'parallel', it becomes harder to control the number of spawned processes etc). Is anyone aware of a

On 4 April 2019 at 17:28, ivo welch wrote: | The following program is whittled down from a much larger program that | always works on Intel, and always works on AMD's threadripper with | lapply but not mclappy. With mclapply on AMD, all processes go into | "suspend" mode and the program then hangs. This bug is replicable on an | AMD Ryzen Threadripper 2950X 16-Core Processor (128GB

On Wed, 17 May 2023 13:55:59 +0000 akshay kulkarni <akshay_e4 at hotmail.com> wrote: > So that means mclapply should run properly, i.e output a try class > object and exit. But it didn't. Can you shed some light on why this > happened? What's your sessionInfo()? Are you using a GUI frontend? mclapply() relies on the fork() system call, which is tricky to get right in a

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)

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__()

Dear all, I am trying to improve my code for many cores. I have started with multicore package and the function mclapply. A multicore version of the lcapply. One problem I have is that when I use this function (you can copy and paste the below) require('multicore') returni <-function(i) {i} system.time(mclapply(seq(1:100000),returni)) I get 4 more versions of rkward.bin running (my

I'm aiming to compare the workings of Rmpi and multicore on a duel processor quad core machine with 64 bit R-2.11.1 Kubuntu 10.4. It's impossible for me to get a small reproducable code segment to show what I mean, but if I show what works for mclapply, I'd hope it's possible to be shown what would be the equivalent way with mpi.apply. The function lr.gbm has variables trees,

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)

The following program is whittled down from a much larger program that always works on Intel, and always works on AMD's threadripper with lapply but not mclappy. With mclapply on AMD, all processes go into "suspend" mode and the program then hangs. This bug is replicable on an AMD Ryzen Threadripper 2950X 16-Core Processor (128GB RAM), running latest ubuntu 18.04. The R version

dear R readers---I thought I would post the following snippet of R code that makes by() like operations easier and faster on multicore machines for R novices and amateurs. I hope it helps some. YMMV. feel free to ignore. PS: I wish R had a POD-like documentation system for end users that are not writing full libraries. because it does not, I did not provide documentation ala '?mc.by'.

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

When I execute mclapply it creates the needed processes, but these processes never begin computing anything, they just wait indefinitely. I recently upgraded to version 2.9.1, which might have caused the problem. -- Med venlig hilsen Rune Schjellerup Philosof Ph.d.-studerende, Statistik, IST, SDU Telefon: 6550 3607 E-mail: rphilosof at health.sdu.dk Adresse: J.B. Winsl?wsvej 9, 5000 Odense

Dear Ivan, REgrets to reply this late... By "holding a lock", you mean a bug in the process right (I am not a computer science guy, excuse my naivete)? THanking you, Yours sincerely, AKSHAY M KULKARNI ________________________________ From: Ivan Krylov <krylov.r00t at gmail.com> Sent: Thursday, May 18, 2023 1:08 PM To: akshay kulkarni <akshay_e4 at

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]]

I have matrices as below: a <- matrix(c(1:10, 11, 12), 3,4) aa <- data.frame(a) b <- matrix(c(10:20, 21), 4,3) bb <- data.frame(b) ... and many more matrices. st = list(aa,bb, ..... ) mclapply(st, FUN, mc.cores=6); #this function apply the function to the elements of the list 'aa', 'bb'...etc FUN = function(st) { Is there a way/function to know the index of

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

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.

Dear Jeff, There was a problem in LYGH and lapply threw an error, but mclapply got stuck in an infinite loop. The doc for mclapply says that mclapply runs under try() with silent = TRUE. So that means mclapply should run properly, i.e output a try class object and exit. But it didn't. Can you shed some light on why this happened? THanking you, Yours sincerely, AKSHAY M

On Tue, Apr 28, 2020 at 9:00 PM Shian Su <su.s at wehi.edu.au> wrote: > > 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