search for: papply

Hello, we are doing some computations with MPI and Rmpi. Therefore papply is a very comfortable function. Is it possible to reuse calculated data on slaves? We do some calculation with papply, then we have to do some overall calculation at the master then we want to do some calculation on the slaves with the old results and some new results from the master. We do not...

...The obvious approach is to use multiple R processes which talk to each other via some message passing library. Fortunately, R has a plethora of such packages. My question is, which is the best choice for this sort of use? From reading their API docs, here are my brief thoughts on each so far: - papply: Not suitable, no bi-directional communication. Slave process return values when the papply() call completes, that's it. - biopara: Not suitable, simple one-way master/slave communication only, just like papply. - snow: Not directly suitable, the supported communication is intended...

Dear List, the advent of multicore machines in the consumer segment makes me wonder whether it would, at least in principle, be possible to divide a computational task into more slave R processes running on the different cores of the same processor, more or less in the way package SNOW would do on a cluster. I am thinking of simple 'embarassingly parallel' problems, just like inverting

Hello R-helpers. I've tried to recreate a parallel version of tapply() and table() using a combination of the parallel functions mclapply() and pvec() and papply(), but haven't been successful. In the end, I'm trying to get a cross tab of two vectors. I currently (can) use tapply(..., sum) and table(), and even xtabs() and ftable(), but with tens of millions of words and tens of thousands of files to loop over, it take a long time, like days. Does...

Hello and thanks in advance for your time. I've created a simulation on my cluster which uses a custom package developed by me for different functions and also the snow package. Right now I'm using LAM to communicate between nodes and am currently only testing my code on 3 nodes for simplicity, though I plan on expanding to 16 later. My problem is this error: "Error in

...ct","compositions","cyclones","hapassoc","haplo.score","haplo.stats","hapsim","httpRequest", "labdsv","kza","LMGene","Malmig","magic","negenes","oz","papply","spe","wavethresh","waveslim","tdthap") failPackages3 <- c("rcom","Rlsf") #put the 3 sets of rejects together failPackages <- union(failPackages1,union(failPackages2,failPackages3)) #list of all currently installed packages...

...nel when running R on amd64 with > 1 CPU http://finzi.psych.upenn.edu/R/Rhelp02a/archive/35109.html A couple of questions: 1. Is this still the case with the newer dual-core opterons (e.g., the 275 et al., families) running Linux (kernel 2.6)? 2. How does this affect using Rmpi (and snow, papply, et al.) on multi-server clusters with > 1 CPU? If I understand correctly, and if the situation is what Andy described, if we use a SMP kernel we will suffer a within-node penalty in one of the Rmpi processes. Is this correct? Thanks, R. -- Ram??n D??az-Uriarte Bioinformatics Unit Centro...

Hi, I have few high-level questions about the Snow and Rmpi packages . I understand that Snow uses Rmpi as one of possible transport layers, yet my questions about user experience, not technical details: 1. Does Snow install and work well in Windows? 2. Interruptibility. I understand that currently it is impossible to interrupt a running top-level command in Snow ( Ctl-c or the likes), the

Hello, which possibilities are available in R for simultaneous or parallel computing? I only could find biopara (http://cran.r-project.org/src/contrib/Descriptions/biopara.html) Are there other possibilities? Are there special groups working on simultaneous computing with R? Thanks Markus -- Dipl.-Tech. Math. Markus Schmidberger Ludwig-Maximilians-Universit?t M?nchen IBE - Institut f?r

Dear R-dev, I would like to accelerate my R computation by using parallel OpenMP compilers (e.g from Pathscale) on a 2-processor AMD server and I would like to know whether R is a tread safe library. The main kernel of the OpenMP parallelization is a C SEXP function that performs the computational routine in parallel with: ******************* SEXP example(SEXP list, SEXP expr, SEXP rho) {

Hello, I have a question that I was wondering if anyone had a fairly straightforward answer to: what is the quickest and easiest way to take advantage of the extra cores / processors that are now commonplace on modern machines? And how do I do that in Windows? I realise that this is a complex question that is not answered easily, so let me refine it some more. The type of scripts that I'm

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Dear All, The institute I work for is organizing an internal workshop for High Performance Computing (HPC). I am planning to attend it and talk a bit about fluid dynamics, but there is also quite a lot of interest devoted to data post-processing and management of huge data sets. A lot of people are interested in image processing/pattern recognition and statistic applied to geography/ecology, but I