search for: stopcluster

...e.seed <- substring(Sys.time(), 21, 26)) a <- rnorm(5,0,1) return(a) } maxkk <- 5 cl <- makeCluster(5, type = "SOCK") registerDoSNOW(cl) results=foreach (i = 1:maxkk, .combine = 'rbind') %dopar% testfun() results stopCluster(cl) ################# 2. Suppose I want to use *snow*, according to some reference, I need to use *rsprng* as a generator. Does this generator relay on seed as well? But it seems to me that if I do not use rsprng, it is also fine. ## code without rsprng ## testfun <- function(){ a <- rnor...

Hello, is there any function in the package snow to check for a really running cluster? The function checkCluster only checks the variable cl. And the variable is still available after stopping the cluster! ( a simple solution would be deleting the cluster variable cl in the function stopCluster) > library(snow) > cl <- makeCluster(5) 5 slaves are spawned successfully. 0 failed. > clusterApply(cl, 1:2, get("+"), 3) [[1]] [1] 4 [[2]] [1] 5 > stopCluster(c1) [1] 1 > clusterApply(cl, 1:2, get("+"), 3) Fehler in mpi.probe(source, tag, comm,...

...le, subset=(age <= 28))) } # Do the same thing twice with foreach and doSNOW # it fails!! the error msg was (could not find function "coeftest") cl<-makeCluster(2) registerDoSNOW(cl) foreach(i=1:2) %dopar% { coeftest(lm(length ~ age, data=Mandible, subset=(age <= 28))) } stopCluster(cl) # However if i put require(lmtest) inside the foreach loop, it works again! cl<-makeCluster(2) registerDoSNOW(cl) foreach(i=1:2) %dopar% { require(lmtest) coeftest(lm(length ~ age, data=Mandible, subset=(age <= 28))) } stopCluster(cl) Regards, Julian [[alternative H...

...information in .Random.seed? Thanks & Cheers, Marius Here is the minimal example: require(doSNOW) require(foreach) doForeach <- function(n, seed=1, type="MPI") { ## create cluster object cl <- snow::makeCluster(parallel::detectCores(), type=type) on.exit(snow::stopCluster(cl)) ## shut down cluster and terminate execution environment registerDoSNOW(cl) ## register the cluster object with foreach ## seed if(seed=="L'Ecuyer-CMRG") { if(!exists(".Random.seed")) stop(".Random.seed does not exist - in l'Ecuyer setting&...

...machine "cheaha.ac.uab.edu" "x86_64" [[2]] nodename machine "compute-0-12.local" "x86_64" [[3]] nodename machine "compute-0-13.local" "x86_64" > stopCluster(c1) [1] 1 > q() -------------------------------------- But on running the same script with mpirun i get the following error. *****************************************************************8 [srividya at cheaha ~]$ mpirun -np 3 R -slave R CMD BATCH TestSnow.R /home/srividya/R/library/snow/RMPI...

...s foreach > library(Rmpi) # for default in makeCluster() > cl<- makeCluster(3) # create cluster object with the given number of slaves > registerDoSNOW(cl) # register the cluster object with foreach > x<- foreach(i = 1:3) %dopar% { # simple test > sqrt(i) > } > x > stopCluster(cl) # properly shut down the cluster > > ## ==== minimal example ==== > > ## ==== output ==== > > Sender: LSF System<lsfadmin at a6218> > Subject: Job 921476:<mpirun R --no-save -q -f doSNOW_minimal.R> Done > > Job<mpirun R --no-save -q -f doSNOW_minimal.R...

...Apply(clu, x = 1:2, fun = fun, x1 = 1) ## OK parLapply(cl = clu, X = 1:2, fun = fun, x1 = 1) #OK fun <- function(b, c) (b + c) clusterApply(clu, x = 1:2, fun = fun, c = 1) ## Error clusterApply(cl = clu, x = 1:2, fun = fun, c = 1) ## OK parLapply(cl = clu, X = 1:2, fun = fun, c = 1) ## Error stopCluster(clu) I used "R version 3.4.3 Patched (2018-01-07 r74099". Best regards, Florian

...sqrt(sum((results.lin-hogTest$Y)^2)/length(hogTest$Y)) return(e.test.lin) } } cl<- makeCluster(10, type="SOCK" ) clusterEvalQ(cl,library(e1071)) clusterExport(cl,c("data.X","data.Y","NR","cost1")) RMSEP<-clusterApplyLB(cl,cost1,sv.lin) stopCluster(cl) -- View this message in context: http://old.nabble.com/SVM-Param-Tuning-with-using-SNOW-package-tp26399401p26399401.html Sent from the R help mailing list archive at Nabble.com.

...access y in the global scope. return(z) } np <- detectCores(logical = FALSE) # Two cores of my laptop x <- seq(1, 10, by = 1) y <- 0.5 # Y may be an array in reality. cl <- makeCluster(np) # initiate the cluster r <- parLapply(cl, x, f) # apply f to x for parallel computing stopCluster(cl) The r was a list with 10 empty elements which means f failed to access y. Then I tested f without parallel computing: z <- f(x) print(z) [1] 2.5 4.5 6.5 8.5 10.5 12.5 14.5 16.5 18.5 20.5 The results indicates that we can access y using .GlobalEnv$y in a function without parLapply. Th...

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 cl<-makeCluster(6, type='SOCK') and no R processes are spawned. I was wondering if others have encountered this problem, and any suggestions on solving this would be greatly appreciated. -- Abhijit...

.....$ con :Classes 'sockconn', 'connection' atomic [1:1] 3 .. .. ..- attr(*, "conn_id")=<externalptr> ..$ host: chr "localhost" ..$ rank: int 1 ..- attr(*, "class")= chr "SOCKnode" $ :List of 3 .... Then I stop it with > stopCluster(.PBcluster) > .PBcluster [[1]] $con Error in summary.connection(x) : invalid connection > str(.PBcluster) List of 4 $ :List of 3 ..$ con :Classes 'sockconn', 'connection' atomic [1:1] 3 .. .. ..- attr(*, "conn_id")=<externalptr> ..$ host: chr "lo...

...l, x, 2, function(y) y) [,1] [,2] [1,] -0.9649685 0.91339851 [2,] -1.4313140 0.13457671 [3,] 1.0499248 1.58967879 [4,] -1.8974411 0.03639876 parCapply(cl, x, function(y) y) [1] -0.96496852 -1.43131396 1.04992479 -1.89744113 0.91339851 0.13457671 [7] 1.58967879 0.03639876 stopCluster(cl) > sessionInfo() R version 2.15.0 beta (2012-03-15 r58760) Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 attached base packages: [1] parallel stats graphics grDevices utils datasets methods [8] base...

...)) c <- as.data.frame(replicate(1000, rnorm(20))) d <- as.data.frame(replicate(1000, rnorm(20))) abcd <- list(a, b, c, d) cl <- makeCluster(4) results <- parLapply(cl,    X = abcd,    FUN = function(i) {      clhs(x = i, size = round(nrow(i) / 5), iter = 2000, simple = FALSE)    }, ) stopCluster(cl) ****************************************** Before running the last line, R is throwing an error: "Error in length(x) : 'x' is missing". Any ideas what I am doing wrong and how to improve? Many thanks! Best, Chega [[alternative HTML version deleted]]

...nction(n) pastK(n, x, k)) pred = sapply(pastList, function(v) mfv(v)[1]) ratio = sum(pred==x, na.rm=T)/(length(pred) - sum(is.na(pred))) } testK = function() { k = seq(3, 25, 2) r = parSapply(cl, k, function(i) predR(x, i)) # r = sapply(k, function(i) predR(x, i)) } r = testK() stopCluster(cl) Here is the error: Error in checkForRemoteErrors(val) : 8 nodes produced errors; first error: could not find function "predR" Best regards, Kaiyin ZHONG ------------------------------ FMB, Erasmus MC k.zhong@erasmusmc.nl kindlychung@gmail.com [[alternative HTML version delete...

...;wrb") writeBin(rep(0.0,10),con) close(con) library(simplemmap) library(parallel) cl <- makeCluster(1) x <- mmap(filePath, "double") ## Turn gctorture on clusterEvalQ(cl, gctorture()) clusterExport(cl, "x") ## x is an 0-length vector on the worker clusterEvalQ(cl, x) stopCluster(cl) ``` you can find more info on the problem if you manually build a connection between two R processes and export the ALTREP object. See output below ``` > con <- socketConnection(port = 1234,server = FALSE) > gctorture() > x <- unserialize(con) Warning message: In unserialize(con...

...registerDoSNOW(cl <- makeCluster(2, type = "SOCK")) > ci(roc2, method="bootstrap", parallel=TRUE) > \dontrun{ci(roc2, method="bootstrap", parallel=TRUE)} > \dontshow{ci(roc2, method="bootstrap", parallel=TRUE, boot.n=20)} > stopCluster(cl) > } > #endif > #ifdef unix > if (require(doMC)) { > registerDoMC(2) > \dontrun{ci(roc2, method="bootstrap", parallel=TRUE)} > \dontshow{ci(roc2, method="bootstrap", parallel=TRUE, boot.n=20)} > } > #endif The "superseded" par...

...us library(doSNOW) library(Rmpi) library(rlecuyer) library(foreach) cl <- makeCluster(mpi.universe.size(), type ="MPI") tmp <- clusterSetupRNG(cl, seed=rep(1,6)) registerDoSNOW(cl) counter <- 0 res <- foreach(k = 1:1000) %do% { counter <- counter + 1 } tmp <- stopCluster(cl) unlist(res)

...<- function(base.dir) { this.host <- as.character(system("hostname", intern=T)) this.rnd <- sample(1:1e6, 1) test.file <- paste(sep="", base.dir, this.host, "_", this.rnd) file.create(test.file) } # end my.test() clusterCall(cl, my.test, base.dir) stopCluster(cl) # End code For example, the files "moab_65835" and "escalante_65835" are created. Regards, Scott Waichler Pacific Northwest National Laboratory scott.waichler at pnl.gov

...ery time. The following code segment shows what I am trying to do: for (j in loopstart:loopend) { call.m=list( step1=T, dat=x.m[,c(1:7, j)] # x.m is data from a csv file read into a table ) clusterApplyLB(cluster,c(10:100),test.each.term,call=call.m) } stopCluster(cluster) The problem that I am having is that sometimes it will run for 50 iterations of this loop then crash. Sometimes 15 iterations, sometimes 2. When the crash happens, I receive the following error message every time: Error in checkForRemoteErrors(val) : one node produced an error: c...

...r All, Is the following expected behaviour? set.seed(1) library(parallel) cl = makeCluster(5) clusterSetRNGStream(cl, iseed = NULL) parSapply(cl, 1:5, function(i) sample(1:10, 1)) # 7 4 2 10 10 clusterSetRNGStream(cl, iseed = NULL) # 7 4 2 10 10 parSapply(cl, 1:5, function(i) sample(1:10, 1)) stopCluster(cl) The documentation could be read either way, e.g. * iseed: An integer to be supplied to set.seed, or NULL not to set reproducible seeds. >From Details .... optionally setting the seed of the streams by set.seed(iseed) (otherwise they are set from the current seed of the master process: a...