similar to: Snow Parallel R: makeCluster with more nodes than available

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 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),

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

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

Dear list, i have some problems using the snow package to create a SOCK cluster. The errors just occour irregularly but it seems to me that they occour when I try to create more than one cluster on the same machine via different R instances started via submitting LSF jobs to a cluster. Does anyone have an idea how to solve this or where to start digging for solutions? The error messages

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

Dear All, I am learning parallel in R and start with the package "snow". I did a test about running time and the parallel version is much slower than the regulat code. My laptop is X200s with dual core intel L9400 cpu. Should I make more clusters than 2? Or how to improve the performance? # install.packages("snow") library(snow) cl <- makeCluster(2) t1 <- proc.time() a

Hello, I am trying to do model autocalibration using the snow and rgenoud packages. The function I want to run in task-parallel fashion across multiple machines is one that pre- and post-processes data and runs an external model code. My problem is that external file I/O is happening only in the master node and not in the slaves. I have followed Jasjeet Sekhon's suggestion to test the

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 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),

Hello, After getting help to solve part of my problem and some delay on my part, I am posting a more refined version to see if someone can help me further. I am trying to autocalibrate a model in my subject area using the snow and rgenoud packages. I want to use the key function "fn" that is called by genoud() to finalize input, run the model executable, and compute the objective

Hi Everybody, I know that R has snow package which can be used for Parallel Computing. However, every time I try making a cluster, the only type of cluster I'm able to make is the "SOCK" (that too because I disabled the firewalls). For the rest (i.e. MPI, NWS, and PVM), I get error every time I try making one. I get the following errors

(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

hello, I'm using R 1.8.1 with the lastest snow package on FreeBSD 4.9. However, when I try to using socket clusters, it's very unstable. Sometimes it dies half way when I run parSapply(), sometimes it dies when cluster connection is idle. I create a socket cluster by following cmd cl = makeCluster("foo", type = "SOCK", outfile="/tmp/rafanlog");

Hello, Is the first time I am using SNOW package and I am trying to tune the cost parameter for a linear SVM, where the cost (variable cost1) takes 10 values between 0.5 and 30. I have a large dataset and a pc which is not very powerful, so I need to tune the parameters using both CPUs of the pc. Somehow I cannot manage to do it. It seems that both CPUs are fitting the model for the same values

Hi everyone, I'm aiming to run an external executable (say filetorun.EXE) in parallel. The external executable collect needed data from a file, say "input.txt" and, in turn,generates several output files, say "output.txt". I need to generate "input.txt", run the executable and keep "input.txt" and "output.txt". I'm using Windows 7, R

I am running R.And I want to make parallel computations. When using the snow package under R-2.13.1patched or the parallel package under R 2.14.0dev, R isn't able to create a cluster. When typing: cl <- makeCluster(4) R doesn't respond. It doesn't crash either. specs: OS: 32 bit, Windows XP Prof, SP3. Processor: Intel Core i3 cpu, quad core. My colleague works on exactly the

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

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

There are a few points I found unclear or unmentioned in the snow documentation (mostly I looked at the cluster.html web page). I thought I'd mention them here. What is the start up environment for the children? -------------------------------------------------- My best guess at the answer is in parentheses Do they inherit shell variables? (no) Do they inherit variables set in R or other