search for: makeclusters

Hi all, I can't get the functionality of the package parallel to work. Specifically, makeCluster() hangs when I run it. I first noticed the problem when trying to run Rstan with multiple cores and the traced it back to the core package parallel. The following results in R hanging after the call to makeCluster. library(parallel) # Calculate the number of cores no_cores <-

Dear Henrik, thank you, for the quick reply. Bizarrely enough, the problem vanished when I woke the computer from sleep (I had previously replicated the problem after several restarts of both R and the MacOS). I will follow-up if I can again replicate the problem. Florian On 2/10/18 4:39 PM, Henrik Bengtsson wrote: > A few quick comments: > > * You mention R --vanilla, but make sure

Good day, I'm trying the example cl <- makeCluster(2, type = "SOCK") from the makeCluster documentation and the R command prompt never returns. I am using a 32-bit Windows 10 computer. The problem doesn't happen on another 64-bit Windows 10 computer but does happen on another 32-bit Windows 7 computer. Can anyone reproduce it? Are there any other options that can be passed to

A few quick comments: * You mention R --vanilla, but make sure to try with parallel::makeCluster(), so that you don't happen to pick up snow::makeCluster() if 'snow' is attached and ahead of parallel on the search() path. * Try creating a single background worker, i.e. parallel::makeCluster(1L). * Try with cl <- future::makeClusterPSOCK(1L, verbose = TRUE), which gives the same

Dear list, I just realized that one of the examples given in the help page to the function makeCluster of the library(snow) has a small syntax error : ## to get started library(snow) ?makeCluster .. will open a halp page containing the command towards the end of the examples : cl <- makeCluster(c(rep(list(macOptions), 2), rep(list(lnxOptions), 2), rep(list(winOptions),

...s(mpi)), they don't seem to exist in the repository any longer. Can anyone please help me with this. Also, where can I find them and how do I install the PVM, MPI, and NWS packages? Any help would be greatly appreciated . Steve -- View this message in context: http://n4.nabble.com/Help-with-makeClusters-for-Snow-tp977592p977592.html Sent from the R help mailing list archive at Nabble.com.

Hello, I was using snow to parallel-process some code in R-2.10 (32-bit windows. ). The code is as follows: require(foreach) require(doSNOW) cl <- makeCluster(6, type='SOCK') registerDoSNOW(cl) bl2 <- foreach(i=icount(length(unqmrno))) %dopar% { (some code here) } stopCluster(cl) When I run the same code in Windows R-2.11 (either 32-bit or 64-bit), R hangs at

Hi Dario, On 2018-06-14 14:00, Dario Strbenac wrote: > Good day, > > I'm trying the example cl <- makeCluster(2, type = "SOCK") Why use the 'snow' package and not 'parallel'? > from the makeCluster documentation and the R command prompt never > returns. I am using a 32-bit Windows 10 computer. The problem doesn't > happen on another

The command which hangs: I'm hoping there is a simple explanation, but I searched on-line and nothing jumped out. > cl <- makeCluster(type="SOCK",c("localhost"),manual=TRUE) Manually start worker on localhost with C:/PROGRA~1/R/R-214~1.2/bin/Rscript.exe "C:/Program Files/R/R-2.14.2/library/snow/RSOCKnode.R" MASTER=localhost PORT=11944 OUT=/dev/null

(Bcc: CRAN) This is a proposal helping CRAN and alike as well as individual developers to avoid stray R processes being left behind that might be produced when an example or a package test fails to set up a parallel::makeCluster(). ISSUE If a package test sets up a PSOCK cluster and then the master process dies for one reason or the other, the PSOCK worker processes will remain running for 30

The problem causing the stray worker processes when the master fails to open a server socket to listen to connections from workers is not related to timeout in socketConnection(), because socketConnection() will fail right away. It is caused by a bug in checking the setup timeout (PR 17391). Fixed in 76275. Best Tomas On 3/18/19 2:23 AM, Henrik Bengtsson wrote: > (Bcc: CRAN) > >

Hi all, I would like to know what would happen if using snow I create a cluster of size 50, for example using makeCluster(50,type='SOCK') on a machine with 2 Cores and run a function. Does snow run 25 and 25 functions on each of my 2 "real" processors or it just run 50 functions in one processor ? Thanks.

I'm trying to suppress the output of: makeCluster(detectCores()) and haven't had luck. So far, I've tried invisible, sink, and capture.output. Any ideas are appreciated. Thanks. -- View this message in context: http://r.789695.n4.nabble.com/suppress-output-of-makeCluster-tp4632904.html Sent from the R help mailing list archive at Nabble.com.

I know this is not a revolution support forum, but as anyone noticed the following? I have a foreach loop to generate random samples. If I run the exact code below in normal r (2.14.1) it works as expected, but if I run it from revolution 4.2.0 each loop returns the same numbers. The only way I can get revolution to give different numbers is using 1 instead of 8 in registerDoSNOW(makeCluster(8,

Hi, all-- I've been working on a doParallel package to provide a foreach parallel backend for the new parallel package, but I am having trouble building the vignette. On my system, if I use the following minimal vignette (call it buggyVignette.Rnw): \documentclass[a4paper]{article} \title{Sweave Example 1} \author{Rich Calaway} \begin{document} \maketitle In this example

Dear All, I have three classes of questions about generating random numbers with different packages (windows xp 32bit R). . 1. Suppose I would like to use package *foreach*, can I use current Sys.time as a seed? Although I can get the time up to1e-6 second precesion, the code below dose not work well on a local machine with two cores. ################# library(foreach) library(snow)

I have a network of four machines set up. I'm having trouble spawning my slaves on these machines. All the examples I have found so far use makeCluster with type="MPI", and I guess I'm missing some kind of cluster configuration in my environment variables because all my clusters are formed on the machine where my initial session is running. Can anyone refer me to a link that

Dear R help, I am trying to set up a cluster for parallel computing on a machine running 64-bit windows XP, using the doSNOW package on R 2.14.1. However, the command makeCluster() consistently makes the computer hang. No R processes are started, no CPU consumed, R just becomes unresponsive. ESC still terminates the command, but I cannot start the cluster. There seems to be quite a lot of posts

Dear all, I found a strange thing with the snow package. This will work: y = matrix(1:4, 2) cl = makeCluster(rep('localhost', 8), type='SOCK') parMM(cl, y, y) This will not: y = matrix(1:4, 2) ncore = system('nproc') parMM(cl, y, y) Error in cut.default(i, breaks) : invalid number of intervals I also tried: cl = makeCluster(rep('localhost', ncore),

I am trying to do parallel programming and I tried this library(doSNOW) library(foreach) testfunc<-function(x){ x<-x+1 x } noc<-2 cl <- makeCluster(do.call(rbind,rep(list("localhost"),noc)), type = "SOCK") registerDoSNOW(cl) clusterExport(cl=cl,c("testfunc.r")) testl<-foreach(pp=1:2) %dopar% { testfunc(pp) } And this works but if I try to