similar to: Using multicores in R

Dear all, I have about 50 pages of R codes and ran it in both OS X and Windows. It takes at least haft a day to have the results. The running time is not very different in both Systems. I found that R does not use all cores of CPU by default. Can anybody help me to use all cores of CPU in my programming from the beginning or through programming in both OS X and Windows? Many thanks your

Hi Thomas, Glad to hear the suggestion helped, and that switching to a `data.table` approach reduced the processing time and memory overhead?15 minutes for one of the smaller datasets is certainly better! Sounds like the adjustments you devised, especially keeping the multicore approach for `make_clean_names()` and ensuring that `ID_Key` values remain intact, were the missing components you

Hi Gregg. Just wanted to follow up on the solution you proposed. I had to make some adjustments to get exactly what I wanted, but it works, and takes about 15 minutes on our server configuration: temp <- ??????open_dataset( ????????????sources = input_files, ????????????format = 'csv', ????????????unify_schema = TRUE, ????????????col_types = schema( ????????????"ID_Key"

Hi all, I have R installed on a box, which is running on a machine with 16 core and Redhat - Linux. I am handling huge (size of dataset will be 5 GB) dataset. Lets assume that my data is in the form of structured (multiple) logs. I access the data by using all.files(). Since by default basic version of R utilizes single core, the processing of my analysis code is taking too much time. I got to

How is the server configured to handle memory distribution for individual users. I see it has over 700GB of total system memory, but how much can be assigned it each individual user? AAgain - just curious, and wondering how much memory was assigned to your instance when you were running R. regards, Gregg On Wednesday, December 11th, 2024 at 9:49 AM, Deramus, Thomas Patrick <tderamus at

Hi, We use Icecast 2.4.4 on debian 9 and Centos 7. How can we see if Icecast use multicores? Best regards, Michel -- -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.xiph.org/pipermail/icecast/attachments/20190306/dc2eba1e/attachment.html>

Hi I want to use LLVM to automatically generate multithreaded code for execution on multicore processors. My problem is  code generation for multicores and concurrency primitives. Is there any facilities for code generation? How should I start?  Best Regards. -------------- next part -------------- An HTML attachment was scrubbed... URL:

No es un problema de tm ni de SnowfallC ni de mcapply (por el path utilizas linux, en windows mcapply según el manual no va bien) No defines bien los objetos que pasas. Pasas doc.corpus en lugar de corpus ( o asignas a corpus en lugar de a doc.corpus) . Depura los programas cuando salga un error de objeto, como te pone en el Error que pasas . Temporalmente lo tienes arreglado en

For info, I put a little study I did about the byte code compiler and other speedup approaches (but not multicore) on the Rwiki at http://rwiki.sciviews.org/doku.php?id=tips:rqcasestudy which looks at a specific problem, so may not be relevant to everyone. However, one of my reasons for doing it was to document the "how to" a little. JN > > 2. Have you tried the

Dear all, I would like to ask your help understand the subsequent steps for making my program faster. The following code: Gauslist<-array(data=NA,dim=c(dimx,dimy,dimz)) for (i in c(1:dimz)){ print(sprintf('Creating the %d map',i)); Gauslist[,,i]<-f <- GaussRF(x=x, y=y, model=model, grid=TRUE,param=c(mean,variance,nugget,scale,Whit.alpha)) } creates 100 GaussMaps (each

Creo que lo que quieres hacer necesita esta línea de código justo después de cargar el paquete tm: inmortal = unlist(strsplit(inmortal, " ", fixed = T)) De esta forma, trabajas con palabras, y NO con las frases enteras... Un saludo Isidro Hidalgo Arellano Observatorio Regional de Empleo Consejería de Empleo y Economía http://www.jccm.es > -----Mensaje original----- > De:

It's Redhat Enterprise Linux 9 Specifically: OS Information: NAME="Red Hat Enterprise Linux" VERSION="9.3 (Plow)" ID="rhel" ID_LIKE="fedora" VERSION_ID="9.3" PLATFORM_ID="platform:el9" PRETTY_NAME="Red Hat Enterprise Linux 9.3 (Plow)" ANSI_COLOR="0;31" LOGO="fedora-logo-icon"

Hi all, I am new to this LLVM. I went through the documenation of LLVM but I didn't find any support for Multicore. Is there any such possibility where multicore architecture can be exploited using LLVM. Thanks Vijay -------------- next part -------------- An HTML attachment was scrubbed... URL:

Sir, I want to apply mclapply() function for my analysis. So, I have to install multicore package. But I can not install the package. >install.packages("multicore") It gives that package multicore is not available. Can you help me? Regards, Suman Dhara [[alternative HTML version deleted]]

Hi, I want to parallelize some computations when it's possible on multicore machines. Each computation produces a big objects that I don't want to store if not necessary: in the end only the object that best fits my data have to be returned. In non-parallel mode, a single gloabl object is updated if the current computation gets a better result than the best previously found. My plan

It is so difficult ... Which FE? It need BE support? I didn't get it. 2010/8/4 vijay kumar <vijaygbvv at gmail.com> > Yeah OpenMP support. I read that it has a front end support but not the > back end. So are there any projects or teams looking at this issue. > > On Wed, Aug 4, 2010 at 7:24 AM, Liu <proljc at gmail.com> wrote: > >> Multicore? >> You

Thomas, I'm curious - what OS are you running this on, and how much memory does the computer have?? Let me know if that code worked out as I hoped. regards, gregg On Wednesday, December 11th, 2024 at 6:51 AM, Deramus, Thomas Patrick <tderamus at mgb.org> wrote: > About to try this implementation. > > As a follow-up, this is the exact error: > > Lost warning

Muchas gracias isidro, a la noche reinstalo R y os digo si me ha funcionado. Perdona mi ignorancia de novato pero no he entendido muy bien eso de avisar al desarrollador. Entiendo que es a los de los paquetes, no? un saludo! ruben El 18 de junio de 2014, 13:10, Isidro Hidalgo <ihidalgo@jccm.es> escribió: > Ya he visto que tampoco así funciona. > Sí te puedo decir que me ha dejado

Is there any reason to expect a problem ? i'm running this script on the cluster down the hall: module load R/2.11.0 R library(multicore) fxx<-function(ll) runif(1) mclapply(1:10,fxx) i get: Error in fork() : Unable to fork. less /proc/cpuinfo yields: processor : 0 vendor_id : GenuineIntel cpu family : 6 model : 15 model name : Intel(R) Xeon(R) CPU

Hi R users. Apologies for the lack of concrete examples because the dataset is large, and it being so I believe is the issue. I multiple, very large datasets for which I need to generate 0/1 absence/presence columns Some include over 200M rows, with two columns that need presence/absence columns based on the strings contained within them, as an example, one set has ~29k unique values and the