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Hi, this post is about foreach operators, the compiler package and the last update of doMC that includes support for the compiler functionality. I am using a home-made %dopar%-like operator that adds some custom expression to be executed before the foreach loop expression itself (see sample code below). It used to work perfectly with doMC 1.2.1, but with the introduction of the compi...

Thank you very much Steve. Your suggestion works perfectly -- at least with doSEQ, doMC and doMPI. Bests, Renaud On 28/06/2011 15:35, Stephen Weston wrote: > I think that the result of the concatenation should be a call object, > rather than an expression object. How about something along the > lines of: > > '%dopar2%'<- function(obj, ex) { > ex<...

Hi all, Sometimes I'll find myself "ctrl-c"-ing like a madman to kill some code that's parallelized via foreach/doMC when I realized that I just set my cpu off to do something boneheaded, and it will keep doing that thing for a while. In these situations, since I interrupted its normal execution, foreach/doMC doesn't "clean up" after itself by killing the processes that were spawned. Furthermore, I...

Hello, I am trying to run a small example with foreach, but I am having some problems. Here is the code: *library(doMC) registerDoMC() zappa = list() frank = list() foreach (i = 1:4) %dopar% { zappa[[i]] = kmeans (iris[-5],4) frank[[i]] = warnings() }* The code runs without error. However the zappa and frank will be empty lists. If I use regular *for *instead, the list will be filled up with kmeans and warning...

Dear all, I am currently working on a package which involves some simulation where no current simulation run depends on a previous simulation run. That is why I decided to parallelize the computation using the doMC package (which exists only for unix-like OS). I can create a package without any R CMD check and R CMD build errors on my computers (Ubuntu Linux 32bit & 64 bit). The problem that I have is: I would like to make the package platform-independent. In this case, this should not be difficult. A s...

REvolution Computing has just released three new packages for R to CRAN (under the open-source Apache 2.0 license): foreach, iterators, and doMC. Together, they provide a simple, scalable parallel computing framework for R that lets you take advantage of your multicore or multiprocessor workstation to program loops that run faster than traditional loops in R. The three packages build on each other to implement a new loop construct for R --...

REvolution Computing has just released three new packages for R to CRAN (under the open-source Apache 2.0 license): foreach, iterators, and doMC. Together, they provide a simple, scalable parallel computing framework for R that lets you take advantage of your multicore or multiprocessor workstation to program loops that run faster than traditional loops in R. The three packages build on each other to implement a new loop construct for R --...

Hi, in R 2.12.1, R CMD check hangs when building a vignette that uses a foreach loop with the doMC parallel backend. This does not happen in R 2.13.1, nor if I use doSEQ instead of doMC. All versions of multicore, doMC and foreach are the same on both my R installations. Has anybody encountered a similar issue? Thank you. Renaud ### UNIVERSITY OF CAPE TOWN This e-mail is subject to the...

...m this <http://stackoverflow.com/questions/14553357/parallelizing-on-a-supercomputer-and-then-combining-the-parallel-results-r> previous post, as well as one particularly helpful and patient XSEDE guy. I'm only using one node (for the meantime), but each of its 32 cores. I'm using doMC instead of snow, because the guy at the supercomputer is in the process of getting Rmpi running. For now, 32 cores should be (more than) adequate for me. My script is of the sort: |define a bunch of functions load the data call libraries require(doMC) require(plyr) registerDoMC(32) main.functio...

Dear all, I am converting a large process to a parallel backhend using doMC and foreach. Basically, I havea long list of input graph files and each of them calls soem basic igraph package functions. I am parallelizing the run, in order to save time. All works fine, and each %dopar% call ends with a vector of results that at the end got fed into a data frame and saved...

some hints for the search engines. I just did install.packages("foreach") install.packages("doMC") library(doMC) registerDoMC() library(foreach) > foreach(i = 1:3) %dopar% sqrt(i) 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_...

Dear R users, I am using R right now for a simulation of a model that needs a lot of memory. Therefore I use the *bigmemory* package and - to make it faster - the *doMC* package. See my code posted on http://pastebin.com/dFRGdNrG Now, if I use the foreach loop with the addon %do% (for sequential run) I have no problems at all - only here and there some singularities in regressor matrices which should be ok. BUT if I run the loop on multiple cores I get very often...

Hi I'm processing sequencing data trying to collapsing the locations of each unique sequence and write the results to a file (as storing that in a table will require 10GB mem at least) so I wrote a function that, given a sequence id, provide the needed line to be stored library(doMC) # load library registerDoMC(12) # assign the Number of CPU fileConn<-file(paste(fq_file,"_SeqID.txt",sep=""),open = "at") # open connection writeLines(paste("ReadID","Freq","Seq","LOC_UG","Nb_UG_Seq",sep="\t&...

...g(abs(x))+x^3+i/A+randvalues[i] } ?## an arbitrary function ARGV <- commandArgs(trailingOnly=TRUE) if (ARGV[1] == "do-onecore") { ?library(foreach) ?discard <- foreach(i = 1:A) %do% uniroot( minfn, c(1e-20,9e20), i ) } else if (ARGV[1] == "do-multicore") { ?library(doMC) ?registerDoMC() ?cat("You have", getDoParWorkers(), "cores\n") ?discard <- foreach(i = 1:A) %dopar% uniroot( minfn, c(1e-20,9e20), i ) } else if (ARGV[1] == "plain") ?for (i in 1:A) discard <- uniroot( minfn, c(1e-20,9e20), i ) else cat("sorry, but...

Hi, all, I have a really big matrix that I want to run k-means on. I tried: >data <- read.big.memory('mydata.csv',type='double',backingfile='mydata.bin',descriptorfile='mydata.desc') I'm using doMC to register multicore. >library(doMC) >registerDoMC(cores=8) >ans<-bigkmeans(data,k) In system monitor, it seems only one thread running R. Is there anything I did wrong? Thanks in advance for any suggestions. Best, Lishu [[alternative HTML version deleted]]

...> 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" part is more confusing to me, though. The doSNOW package seems to...

There may be several parts to the problem: 1. Winbind on Samba 3.4.x seems unable to allocate idmap entries (UID/SID or GID/SID) , whether or not the backend is LDAP or TDB. Winbind on Samba 3.0.x is able to create idmap allocation mappings with an LDAP backend. The two problems with Samba 3.0.x are as follows - "getent" would stop showing trusted users once the cache period

hi all am a newbie to xen. was wondering if there is a way to share memory between domains. i need to be able to write to a shared memory from one domain and allow other domain(s) to read from it. for example domA is always the writer and domB or domC are always readers. to be able to do that does hypervisor provide anything like "shmget" for domA and "shmat" for domB and domC?:) i''m just reading up grant tables etc where some frames are shared between domains. would grant tables mechanism allow me to do abo...

...doesn't require a cluster. Jay <<example code omitted>> Not only is the sequential foreach much slower than the simple for-loop (as least in this particular instance), but I am not quite sure how to make foreach run parallel. Where would I get this parallel backend? I looked at doMC and doRedis, but these do not run on Windows, as far as I understand. And doSNOW is something to use when you have a cluster, while I have a simple dual-core PC. It is not really clear for how to make parallel computing work. Please, help. Regards, Sergey -- John W. Emerson (Jay) Associate Prof...

...values are not getting into the Valuation.R script then #A = MCPVMPA = 0 and B = MCMKMPA = 0 So VarX = NaN Then it does something like: if (VarZ>VarX) VarY = 0 else VarY = VarX-VarZ #This line generates the error I have all the libraries installed: library(foreach) library(doMC) registerDoMC() It's not the installation because all the example code with %dopar% I've tested work fine. So can you help me please to make my code work? Any ideas? -- L.E. Marcos Larios Sata Rosa [[alternative HTML version deleted]]