search for: dosmp

Hello, I'd like to use package 'doSMP'. But I can only found source codes in the CRAN. I tried to build source code using 'r CMD build doSMP' in the source directory, the following error is shown: ERROR: dependencies 'foreach', 'iterators', 'revoIPC' are not available for pack age 'doSMP'...

Hi list, I was testing out the "doSMP" package from REvolutionR in my regular R2.11.0 installation and I got the following error message.? Well, one obvious thing is that R2.11.0 was built using "i386-pc-mingw32" which is different from what revoIPC used.? I could just use REvolutionR, but all my R peripherals were set u...

Hello dear list, I just noticed that: Package ‘doSMP’ was removed from the CRAN repository. http://cran.r-project.org/web/packages/doSMP/index.html Does any one know the reason for this? Is this a technical or a legal (e.g: license) issue? Thanks, Tal ----------------Contact Details:------------------------------------------------------- Contac...

Hello, I am having trouple installing doSMP and revoIPC from: https://r-forge.r-project.org/R/?group_id=950 My Linux system: Linux 2.6.35-25-generic #44-Ubuntu SMP Fri Jan 21 17:40:44 UTC 2011 x86_64 GNU/Linux Ubuntu 10.10 \n \l I get this reply: costas at ELEPHANT:~/Downloads$ sudo R CMD INSTALL revoIPC_1.0-3.tar.gz * installing to lib...

Some might have noticed that REvolution Computing released the doSMP package to the general public about a month and a half ago, which allows multiple cores to be accessed for parallel computation in R. Some of our physical habitat calculations were taking an extraordinary amount of time to complete and required over-weekend runs, which prompted our interest in...

...ols=ncol(t) nRows=nrow(t) tTA = matrix(nrow=nRows,ncol=nCols) require(TTR) system.time( for (i in 1:nCols) { x = t[,i] xROC = ROC(x) tTA[,i]=xROC } ) user system elapsed 123.24 0.07 123.47 # PARALLEL CODE nCols=ncol(t) nRows=nrow(t) tTA = matrix(nrow=nRows,ncol=nCols) require(doSMP) workers <- startWorkers(4) # My computer has 4 cores registerDoSMP(workers) system.time( foreach (i=1:nCols) %dopar%{ x = t[,i] xROC = ROC(x) tTA[,i]=xROC } ) # stop workers stopWorkers(workers) It is taking ages! Thanks, S

Hi, I would like to get suggestion about parallel computing package on a multicore windows workstation. I tried doSMP, but it crashes R a lot. I am wondering if "snow" and "snowfall" can be used on a single workstation (i,e, not cluster). At suggestion would be appreciated, Best, Richard [[alternative HTML version deleted]]

...e to use the 'foreach' package with a foreach loop. However, whenever I call a function from an enabled package outside of MASS, I get an error message that a number of the functions aren't recognized (even though the functions should be defined). For example: library(foreach) library(doSMP) library(survival) # Create the simplest test data set test1 <- list(time=c(4,3,1,1,2,2,3), status=c(1,1,1,0,1,1,0), x=c(0,2,1,1,1,0,0), sex=c(0,0,0,0,1,1,1)) # Fit a stratified model coxph(Surv(time, status) ~ x + strata(sex), test1) w <- startWorke...

foreach (or virtually anything you might use for concurrent programming) only really makes sense if the work the "clients" are doing is substantial enough to overwhelm the communication overhead. And there are many ways to accomplish the same task more or less efficiently (for example, doing blocks of tasks in chunks rather than passing each one as an individual job). But more to the

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

...on multiple time and save every list entry into a specific arrays "x" and "y"; stop time system.time(for(j in 1:n.run) { z = check(j) x[,, j] <- z$sme y[,, j] <- z$test }) #### trying to do the same with a foreach loop - does not work!! require(doSMP) workers <- startWorkers(2) # My computer has 2 cores registerDoSMP(workers) notcreative = array(NA,dim=c(4,n.vpn,n.l?ufe)) tempList = list(matrix(NA,4,n.vpn),matrix(NA,4,n.vpn)) system.time(notcreative <- foreach(j=1:n.run) %dopar% { tempList=check(j) x[,,j] = tempList$sme...

?I want to take advantage of my multicore CPU to speed up a loop in a simulation program.? I didn?t write the code, but the iterations appear independent to me, at least in the sense that the results of one loop do not depend on previous ones.? Right now I?m relegated to a Windows box that runs Windows 7.? These appear to be the options: ? Pnmath-appears to parallelize non-BLAS routine but

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

Dear users, The company where I work is considering getting a license for Revolution Enterprise - Windows 64-bit. I'll appreciate for those familiar with the product if can share your experiences with it? In particular, how does it compare to the "free" version of R 64-bit? Thanks in advance. Regards, Lars. [[alternative HTML version deleted]]

...now available for the webinar "Portfolio design, optimization and stability analysis" presented by Diethelm W?rtz of the Rmetrics Association: http://bit.ly/dG4fI0 A question on StackOverflow provides some great suggestions for managing memory usage in an R session: http://bit.ly/glgGSq doSMP, an open-source package from Revolution Analytics to support parallel processing in R on Windows, is now available on CRAN: http://bit.ly/e0DzkZ Other non-R-related stories in the past 2 months included a cartoon about factor analysis (http://bit.ly/hJ4J6X), computers impersonating humans on Jeopa...

I write about R every weekday at the Revolutions blog: http://blog.revolutionanalytics.com and every month I post a summary of articles from the previous month of particular interest to readers of r-help. In case you missed them, here are some articles related to R from the month of March: The doSMP package, which enables parallel processing for R on multiprocessor machine, is now available on CRAN: http://bit.ly/gTS7BJ The Offensive Politics blog provided R code used to make a map of precinct returns in the Chicago mayoral election: http://bit.ly/fon0BJ A connector to integrate R output int...

...on inside-R.org describing "What is R?". http://bit.ly/aSeES1 examined the performance benefits of linking R to multithreaded math libraries like Atlas or (in the case of Revolution R) the Intel MKL libraries. Nathan VanHoudnos follows up (http://bit.ly/csGLBh) with his experiences using doSMP on an 8-core machine. http://bit.ly/b5ot3F linked to slides and a replay the joint webinar from Revolution, Jaspersoft and OpenBI, "Supercharging business analytics with R". http://bit.ly/b85lFf took a look at the use of R for political science, and how it was used to predict the outcom...

I am trying to create a frequency distribution and I am a bit confused. Here are the commands I have entered: > data <- read.csv(file="40609_sortedfinal.csv",head=TRUE,sep=",") > NumberOfActionsByStatus = data$STATUS > NumberOfActionsByUser = data$ETS_LOGIN > NumberOfBidOffer = data$BID_OFFER > NumberOfActionsByUser.freq = table(NumberOfActionsByUser) >