similar to: Parallel Programming

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, Within a foreach loop with doSNOW, we cant call functions which come from the non-default package. We need to load(require/library) the package once more within the foreach loop. Anyone knows why would happen like this? Is it caused by the snow package and something happened when "snow" parallelize the job? Other than load the package once more with in the foreach loop, is

Is there a way to extract list of words in BioWordVec in R Thank you Tjun Kiat [[alternative HTML version deleted]]

I *think* this might be better posted here: https://bioconductor.org/help/support/ Cheers, Bert On Thu, Feb 1, 2024 at 4:37?PM TJUN KIAT TEO <teotjunk at hotmail.com> wrote: > Is there a way to extract list of words in BioWordVec in R > > Thank you > > Tjun Kiat > > [[alternative HTML version deleted]] > > ______________________________________________

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

Hello group, I am experimenting with parallel processing on my quad core Win 7 32 bit machine. Using these packages for the first time. I can see all my processor running at full performance when I use a smaller dataset require(snow) require(doSNOW) require(foreach) #change the 8 to however many cores\phys processors you have on your machine cl.tmp = makeCluster(rep("localhost",4),

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)

Dear Tomas, thank you very much. I installed r-devel r75201 and tested. The machine with 88 cores has NUMA disabled. It therefore has 2 processor groups with 64 and 24 processors each. require(parallel) detectCores() # [1] 88 This is great! Then I went on to test with a simple 'foreach()' loop. I started with 64 processors (max limit of 1 processor group). I ran with a simple function

Dear expeRts, I struggle with the following problem using snow clusters for parallel computing: I would like to specify l'Ecuyer's random number generator. Base R creates a .Random.seed of length 7, the first value indicating the kind fo random number generator. I would thus like to use the components 2 to 7 as the seed for l'Ecuyer's random number generator. By doing so, I

I am using the package Multicore/Parallel to do importance sampling. I have 5 cores on my computer. And I have let's say 10 000 particles to generate. What I did was to send 5 particles in each time, calling the package parallel. Which means in all I am calling the parallel command 2000 times. What happens is in the end somewhere along the way I end up with the error message error in fork

Dear list, When I run an R CMD check --as-cran on my package (pROC) I get the following note: > Uses the superseded package: ?doSNOW? The fact that it uses the doSNOW package is correct as I have the following example in an .Rd file: > #ifdef windows > if (require(doSNOW)) { > registerDoSNOW(cl <- makeCluster(2, type = "SOCK")) > ci(roc2,

Whas missing the R in the command line: "mpirun -n --hostfile /home/hostfile R --no-save -f rtest.R" Hope this helps mario On 13-Jan-11 22:08, Justin Moriarty wrote: > Hi, > Just wanted to share a working example of doSNOW and foreach for an openMPI cluster. The function eddcmp() is just an example and returns some inocuous warnings. The

I am trying to use the package ode and periodically it will come up with this error message Warning..Internal T (=R1) and H (=R2) are such that in the machine, T + H = T on the next step (H = step size). Solver will continue anyway. And then the program just take very long to run. Is there anyway to get the program to terminate when this warning is issued instead of continuing to run ?

Oh, I completely missed that one. It's very neat as it seems to work both on Windows and Unix. Thanks! Xavier On 10/02/15 10:52, Martyn Plummer wrote: > The CRAN package snow is superseded by the parallel package which is > distributed with R since version 2.14.0. Here are the release notes > > \item There is a new package \pkg{parallel}. > > It incorporates (slightly

This is applicable to either using optim or the differential equation solver or any similar solver Suppose I want to use the differential equation solver and this is my code d<-y[2] vdpol<-function(t,y) { list(c(1, d, 3, 4 ) } stiff<-ode(y=rep(0,4),times=c(0,1),func=dvdpol,parms=1) The thing is I want d to be composed of one of state variables in the

Dear expeRts, This is a similar post as on R-SIG-MAC [I didn't receive an answer there; not sure if it was the right place to post either]. I'm running R version 2.12.1 (Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)) on a MacBook Pro under Mac OS X 10.6.6. The following minimal example runs fine under this setup. However, if I am connected to a server via a VPN client [Cisco

Shouldn't -n be 4 in the bsub command? One master+3 slaves. This was required for snowfall, but I think doSNOW is similar. Hope it helps mario On 16-Dec-10 23:09, Marius Hofert wrote: > Dear expeRts, > > I try to get a minimal example for parallel computing via "foreach" + "doSNOW" to run on a computer cluster (Brutus from

If the code you are running in parallel is complicated, maybe foreach is not sophisticated enough to find all the variables you refer to. Maybe use parallel::clusterExport yourself? But be a aware that passing parameters is much safer than directly accessing globals in parallel processing, so this might just be your warning to not do that anyway. -- Sent from my phone. Please excuse my brevity.

Dear Tomas, thank you for looking into this. Here's the output: # number of logical processors - what detectCores() should return out <- system("wmic cpu get numberoflogicalprocessors", intern=TRUE) [1] "NumberOfLogicalProcessors \r" "22 \r" "22 \r" [4] "20 \r"

Hello all: Please help me with this "can't find object" issue. I'm trying to get leave-one-out predicted values for Beta-binomial regression. It may be the gamlss issue because the code seems to work when %do% is used. I have searched for similar issues, but haven't managed to figure it out. This is on Windows 10 platform. Thanks in advance, Nik #