[R] [R-pkgs] rmongodb 1.1.3 back to CRAN
Dear all, I am pleased to announce that the rmongodb package connecting R with the NoSQL database mongodb is back to CRAN: http://cran.r-project.org/web/packages/rmongodb/index.html This release is a bug fix release to get the package back to CRAN. I have overtaken the package maintenance from Gerald Lindsly and looking forward to extend the great work in this package. Planed new features are: * add high-level functionality to improve usability * enable JSON queries * switch to roxygen (already done and on github) * implement RUnit tests to make the package more stable (work in progress) * update to the newest C driver (including libBSON and libmongoc) * improve documentation, write vignettes (please check github for more details https://github.com/mongosoup/rmongodb/issues) If you have any ideas or bugs please feel free to contact me. Furthermore, please feel free to join me in developing the package: https://github.com/mongosoup/rmongodb Best regards Markus [[alternative HTML version deleted]] ___ R-packages mailing list r-packa...@r-project.org https://stat.ethz.ch/mailman/listinfo/r-packages __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] useR meetup group in Munich, Friday 7th: Web Service Frameworks with R
Dear all, I would like to invite Munich (Germany) area R users for our second meeting: 7th June 2013. The group is aimed to bring together practitioners from industry and academia in order to exchange knowledge and experience in solving data analysis statistical problems by using R. More information about the group at: http://www.meetup.com/munich-useR-group/ Our second meeting will host two talks about Web Service Frameworks with R (shiny and RevolutionDeployR). Meet you in Munich Markus __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Reminder: useR meetup group in Munich, Germany
Dear all, this is a short reminder for the Meetup Munich useR group. Next week Wednesday (16th January 2013) we have our first meeting with two talks about Reporting and Reproducible Research with R and some ideas for an R certification. More information at http://www.meetup.com/munich-useR-group/events/63749502/ Meet you next week Markus On Dec 21, 2012, at 3:28 PM, Markus Schmidberger mschmidber...@freenet.de wrote: Dear all, I would like to invite Munich (Germany) area R users for our first meeting: 16th January 2013. The group is aimed to bring together practitioners (from industry and academia) in order to exchange knowledge and experience in solving data analysis statistical problems by using R. More information about the group at: http://www.meetup.com/munich-useR-group/ 1. Meeting: http://www.meetup.com/munich-useR-group/events/63749502/ Merry Christmas, happy New Year and see you in 2013 Markus __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] useR meetup group in Munich, Germany
Dear all, I would like to invite Munich (Germany) area R users for our first meeting: 16th January 2013. The group is aimed to bring together practitioners (from industry and academia) in order to exchange knowledge and experience in solving data analysis statistical problems by using R. More information about the group at: http://www.meetup.com/munich-useR-group/ 1. Meeting: http://www.meetup.com/munich-useR-group/events/63749502/ Merry Christmas, happy New Year and see you in 2013 Markus __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Running R on a Computer Cluster in the Cloud - cloudnumbers.com
Dear R community,
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--
Dr. rer. nat. Markus Schmidberger
Senior Community Manager
Cloudnumbers.com GmbH
Chausseestraße 6
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Re: [R] MC-Simulation with foreach: Some cores finish early
If you switch directly to the multicore package you can use the mclapply() function. There, check for the parameter mc.preschedule=T / F. You can use this parameter to improve the load balancing. I do not know a parameter to tune foreach with this parameter. Best Markus Am Dienstag, den 12.07.2011, 04:31 -0700 schrieb peter_petersen: Dear R-Users, I run a MC-Simulation using the the packages foreach and doMC on a PowerMac with 24 cores. There are roughly a hundred parametersets and I parallelized the program in a way, that each core computes one of these parametersets completely. The problem ist, that some parametersets take a lot longer to compute than others. After a while there are only a quarter of the cores still computing (their first parameterset), while others are already finished. But some parametersets are still untouched. I have thought about changing my parameterfile in a way, that every combination takes roughly the same time (longer computations are offset with less repetitions), but maybe there is a more elegant solution. Is it somehow possible to wake the finished cores, while there is still work to do? ;-) Sincerly, H. Bumann -- View this message in context: http://r.789695.n4.nabble.com/MC-Simulation-with-foreach-Some-cores-finish-early-tp3661998p3661998.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Munich R Course - Parallel Computing with R
Dear R users, at November 8. 9., 2010, there will be an R course for 'Parallel Computing with R' in Munich at the super computer center. The course is part of the Munich R Course series and gives an introduction to parallel computing with R. Especially the R packages snow, snowfall, multicore, nws and Rmpi will be used. The course is a hands-on tutorial with a lot of different examples. Furthermore, for exercises the super computer HLRB2 (9728 cores) at the LRZ can be used. The course will be held in English. Further information, prices and registration at http://www.statistik.lmu.de/R/inhalte.html#K3eng Please check for other Munich R courses: http://www.statistik.lmu.de/R Best regards Markus Schmidberger -- Dr. rer. nat. Markus Schmidberger Ludwig-Maximilians-Universität München IBE - Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie Lehrstuhl für Biometrie und Bioinformatik Marchioninistr. 15, D-81377 Muenchen URL: http://www.ibe.med.uni-muenchen.de Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Short survey concerning the use of software engineering in the field of High Performance Computing
Already more than 2000 answers. Take the change and help to get a general overview about the use of software engineering. Best Markus -- Dear Colleagues, this is a short survey (21 questions that take about 10 minutes to answer) in context of the research work for my PhD thesis and the Munich Center of Advanced Computing (Project B2). It would be very helpful, if you will take the time to answer my questions concerning the use of software engineering in the field of High Performance Computing. Please note, all questions are mandatory to answer! http://www.q-set.de/q-set.php?sCode=TCSBHMPZAASZ Thank you very much, kind regards Miriam Schmidberger (Dipl. Medien-Inf.) schmi...@in.tum.de Technische Universität München Institut für Informatik Boltzmannstr. 3 85748 Garching Germany Office 01.07.037 Tel: +49 (89) 289-18226 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Short survey concerning the use of software engineering in the field of High Performance Computing
Dear Colleagues, this is a short survey (21 questions that take about 10 minutes to answer) in context of the research work for my PhD thesis and the Munich Center of Advanced Computing (Project B2). It would be very helpful, if you will take the time to answer my questions concerning the use of software engineering in the field of High Performance Computing. Please note, all questions are mandatory to answer! http://www.q-set.de/q-set.php?sCode=TCSBHMPZAASZ Thank you very much, kind regards Miriam Schmidberger (Dipl. Medien-Inf.) schmi...@in.tum.de Technische Universität München Institut für Informatik Boltzmannstr. 3 85748 Garching Germany Office 01.07.037 Tel: +49 (89) 289-18226 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Munich R Course - Parallel Computing with R
Dear R users, at March 15. 16. there will be an R course for 'Parallel Computing with R' in Munich at the super computer center. The course is part of the Munich R Course series and gives an introduction to parallel computing with R. Especially the R packages snow, snowfall, multicore, nws and Rmpi will be used. The course is a hands-on tutorial with a lot of different examples. Furthermore, for exercises the super computer HLRB2 at the LRZ can be used. Currently there are still vacancies. The course will be held in German. Further information at http://www.stat.uni-muenchen.de/R/inhalte.html#K3 Best regards Markus Schmidberger __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] More than doubling performance with snow
Hi, there is a new mailing list for R and HPC: [EMAIL PROTECTED] This is probably a better list for this question. Do not forget, first of all you have to register: https://stat.ethz.ch/mailman/listinfo/r-sig-hpc In this case the communication overhead is the problem. The data / matrix is to big! Have a look to the function snow.time to visualize your communication and calculation time. It is a new function in snow_0.3-4. ( http://www.cs.uiowa.edu/~luke/R/cluster/ ) Best Markus Stefan Evert wrote: I'm sorry but I don't quite understand what not running solve() in this process means. I updated the code and it do show that the result from clusterApply() are identical with the result from lapply(). Could you please explain more about this? The point is that a parallel processing framework like Snow and PVM does not execute the operation in your (interactive) R session, but rather starts separate computing processes that carry out the actual calculation (while your R session is just waiting for the results to become available). These separate processes can either run on different computers in a network, or on your local machine (in order to make use of multiple CPU cores). user system elapsed 0.584 0.144 4.355 user system elapsed 4.777 0.100 4.901 If you take a close look at your timing results, you can see that the total processing time (elapsed) is only slightly shorter with parallelisation (4.35 s) than without (4.9 s). You've probably been looking at user time, i.e. the amount of CPU time your interactive R session consumed. Since with parallel processing, the R session itself doesn't perform the actual calculation (as explained above), it is mostly waiting for results to become available and user time is therefore reduced drastically. In short, when measuring performance improvements from parallelisation, always look at the total elapsed time. So why isn't parallel processing twice as fast as performing the caculation in a single thread? Perhaps the advantage of using both CPU cores was eaten up by the communication overhead. You should also take into account that a lot of other processes (terminals, GUI, daemons, etc.) are running on your computer at the same time, so even with parallel processing you will not have both cores fully available to R. In my experience, there is little benefit in parallelisation as long as you just have two CPU cores on your computer (rather than, say, 8 cores). Hope this clarifies things a bit (and is reasonably accurate, since I don't have much experience with parallelisation), Stefan [ [EMAIL PROTECTED] | http://purl.org/stefan.evert ] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Dipl.-Tech. Math. Markus Schmidberger Ludwig-Maximilians-Universität München IBE - Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie Marchioninistr. 15, D-81377 Muenchen URL: http://www.ibe.med.uni-muenchen.de Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de Tel: +49 (089) 7095 - 4599 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] rmpi/snow/sge/openmpi help
Hi, there is a new mailing list for R and HPC: [EMAIL PROTECTED] This is probably a better list for your question. Do not forgett, first of all you have to register: https://stat.ethz.ch/mailman/listinfo/r-sig-hpc Did you tried to run openmpi and R without SGE? Like this: orterun -n 1 R --no-save I think openmpi / orterun do not get the correct hostfile. Therefore it starts with a default hostfile and this is only for the local machine! So all nodes are at the same machine. It normally works like this that SGE creates a hostfile and puts the path of the hostfile to a special (environment) variable. Now you have to make sure that the correct hostfile will be used. So SGE should call something like this: ortrun -n 1 --hostfile $PATH_TO_HOSTFILE R --so-save Best Markus jk jk wrote: Forgive the spam. Let me try that e-mail again. I'm trying to get snow working with openmpi and sge. Everything appears to work, except the program only runs on 1 node. If i tell snow to run on 5 nodes, it spawns 5 processes on a single node, 6 nodes = 6 procs on 1 node and so on. I'm at a loss for ideas. Any help would be appreciated. Setup: Rocks Cluster, OpenMPI, R 2.8.0, Snow, Rmpi. Please ask for specifics. Thanks in advance. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Dipl.-Tech. Math. Markus Schmidberger Ludwig-Maximilians-Universität München IBE - Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie Marchioninistr. 15, D-81377 Muenchen URL: http://www.ibe.med.uni-muenchen.de Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de Tel: +49 (089) 7095 - 4599 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Rmpi task-pull
)
}
}
else if (tag == 2) {
# The message contains results. Do something with the results.
# Store them in the data structure
foldNumber - message$foldNumber
rssresult[,foldNumber] - message$result
}
else if (tag == 3) {
# A slave has closed down.
closed_slaves - closed_slaves + 1
}
}
# plot the results
plot(apply(rssresult,1,mean))
mpi.close.Rslaves()
mpi.quit(save=no)
Thanks for your help!!!
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--
Dipl.-Tech. Math. Markus Schmidberger
Ludwig-Maximilians-Universität München
IBE - Institut für medizinische Informationsverarbeitung,
Biometrie und Epidemiologie
Marchioninistr. 15, D-81377 Muenchen
URL: http://www.ibe.med.uni-muenchen.de
Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de
Tel: +49 (089) 7095 - 4599
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[R] SAS - surveyselect in R?
Hello, is there a R function or package containing a similar functionality then the SAS PROC SURVEYSELECT? Thanks Markus __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] torque/psb snow library
Hi Javier, there is a new mailing list for R and HPC: [EMAIL PROTECTED] This is probably a better list for your question. I never tried torque with socket. We use torque and mpi or pvm (and R) and it is working very well. Why do you use socket as communication layer? MPI was especially developed for communication between nodes in a computer cluster. And there you can specify which nodes and the number of processors per node you want use. Therfore I would strongly recommend to use MPI. This will be faster in every condition! Best Markus [EMAIL PROTECTED] wrote: Hello all; I'm trying to execute parallel jobs trough library snow on a cluster built through torque/PSB. I'm succesfully obtaining the cluster with: system(cat $PBS_NODEFILE cluster.txt) mycluster - scan(file=cluster.txt,what=character) cl - makeSOCKcluster(mycluster) The only problem, at the moment, is that if I use processors in nodes other that the one in which I'm running R, the communication is extremely slow. If all processor are in the master computer there not seems ti be any problem. Has anyone got any experience with this and any advice? Perhaps snow() s not adequate for this kind of clusters? Thanks and best regards, Javier __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Dipl.-Tech. Math. Markus Schmidberger Ludwig-Maximilians-Universität München IBE - Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie Marchioninistr. 15, D-81377 Muenchen URL: http://www.ibe.med.uni-muenchen.de Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de Tel: +49 (089) 7095 - 4599 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Problem about spawn nodes with Rmpi
Hi Marce, there is a new mailing list for R and HPC: [EMAIL PROTECTED] This is probably a better list for your question. Probably Rmpi does not find the correct Rmpi implementation. Have you installed a second mpi implementation (lammpi)? How do you have installed Rmpi? Did you compiled it to the mpi libraries? R CMD INSTALL --configure-args=--with-mpi=MPIPATH Rmpi Best Markus Marce wrote: Hi all, now I'm testing R in a virtual cluster, made it with VirtualBox. This one has 3 nodes, running CentOS 5 and OpenMPI 1.2.8, and the principal node (called server) exports the /home to other nodes. I have installed R and OpenMPI in /home, in fact, it seems work OK. Editing the openmpi-default-hostfile and run mpirun -np 3 hostname I can see the hostname of all nodes in my cluster. But my problem comes when I want to spawn several nodes in R. I have installed R 2.6.1 and Rmpi 0.5.5. When I run mpi.spawn.Rslaves(nslaves=3) for example, it only spawn 3 processors in the same node, in fact, the local node. How I can tell to Rmpi that there are 2 o more nodes in the cluster? This problem can be solved passing a hostfile like an argument? Thanks for all [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Dipl.-Tech. Math. Markus Schmidberger Ludwig-Maximilians-Universität München IBE - Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie Marchioninistr. 15, D-81377 Muenchen URL: http://www.ibe.med.uni-muenchen.de Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de Tel: +49 (089) 7095 - 4599 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] R/Parallel
Hi, have a look to Dirks tutorial at the UseR2008. This should be a good starting point: http://www.statistik.uni-dortmund.de/useR-2008/tutorials/eddelbuettel.html Markus Rajasekaramya wrote: Hi there, I am looking for R/parallel package or some other package that would speed up the analysis.I am working on computatioanly intensive data so any suggestions would be really helpful. Kindly let me know if any -- Dipl.-Tech. Math. Markus Schmidberger Ludwig-Maximilians-Universität München IBE - Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie Marchioninistr. 15, D-81377 Muenchen URL: http://www.ibe.med.uni-muenchen.de Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de Tel: +49 (089) 7095 - 4599 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] ParallelR
-BEGIN PGP SIGNED MESSAGE- Hash: SHA1 Hi, mpi is probably the mostly used standard for parallel computing. It was especially developed for message passing. Therefore most packages are based on MPI. Using snow you can choose between socket, mpi, pvm and (in the newest version) nws. I think actually there are no other communication ports. To avoid entering your password you should use ssh-keys! Best Markus Hesen Peng wrote: Hi, I wonder if there are any parallel package which do not rely on mpi or pvm? On Wed, Oct 8, 2008 at 5:09 PM, Markus Schmidberger [EMAIL PROTECTED] wrote: Hi Chi, ParallelR is a commercial software to run R in parallel. It is working very well. We tested it at a small linux cluster. You also can use R and the parallel packages (snow, Rmpi, nws, ...) packages. All Open Source and for free. You probably will have some more work installing the complete system, but the same results. You also can use a batch system with R. We are using Sun Grid Engine! (this should be even possible for parallelR) Best Markus Chi Chan wrote: Anyone using or has access to ParallelR? I was looking at the page and found nothing really useful! http://www.revolution-computing.com/sitegenius/topic.php?id=195 I want to see if I can run R on a cluster of workstation, and use batch systems like Grid Engine or Xgrid: http://gridengine.sunsource.net/ http://ww.apple.com/acg/xgrid/ --Chi __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. - -- Dipl.-Tech. Math. Markus Schmidberger Ludwig-Maximilians-Universität München IBE - Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie Marchioninistr. 15, D-81377 Muenchen URL: http://www.ibe.med.uni-muenchen.de Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de Tel: +49 (089) 7095 - 4599 -BEGIN PGP SIGNATURE- Version: GnuPG v2.0.4-svn0 (GNU/Linux) Comment: Using GnuPG with SUSE - http://enigmail.mozdev.org iD8DBQFI7jNowxqyUctZsggRAqiSAKCz4c3IYw4JRrIMCgVaFDQH/QZqQQCaAsFE 7JzsNIzkdm1A8gLnevHNsTo= =p8Xk -END PGP SIGNATURE- __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Running R under Sun Grid Engine with OpenMPI tight integration
-BEGIN PGP SIGNED MESSAGE- Hash: SHA1 Hi, actually there is no perfect way to use R one multiprocessors. There are two options: * using mpi: This means starting several R sessions and using MPI for the communication between the R sessions. Task distribution, fail over solutions, ... have to be implemented by your self. MPI was developed for multicomputer systems. So it is not very efficient to use it at a multiprocessor machine. But it works! * using multiThreads or openMP: There are packages from Luke Tierney using multi threading or openMP for basic R math functions. http://www.cs.uiowa.edu/~luke/R/experimental/ This are especially for multiprocessors designed math functions. You can achieve nice speedups. But unfortunately this is just working for the basic math functions. Have a look to the useR2008 conference and Dirks Tutorium. There you can find a lot of information! Markus Chi Chan wrote: On Thu, Oct 9, 2008 at 9:02 AM, Dirk Eddelbuettel [EMAIL PROTECTED] wrote: You could have a look at the slides from my UseR! 2008 tutorial [1] on 'high-performance computing with R' which covered Open MPI / Rmpi and includes examples. It may just be that you are expecting something that cannot be done. There is no 'R session on 8 processors'. R is still single-threaded, and neither Open MPI nor the Sun Grid Engine changes that. But what you can do is to start R on a node in your cluster and then use Open MPI to distribute load across the 8 processors. There are examples in my slides. So R uses MPI for task distribution only? That sounds like not very fine grained parallelism. Can I use rsh to start remote R instead of MPI? --Chi Hope this helps, Dirk [1] http://dirk.eddelbuettel.com/presentations.html -- Three out of two people have difficulties with fractions. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. - -- Dipl.-Tech. Math. Markus Schmidberger Ludwig-Maximilians-Universität München IBE - Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie Marchioninistr. 15, D-81377 Muenchen URL: http://www.ibe.med.uni-muenchen.de Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de Tel: +49 (089) 7095 - 4599 -BEGIN PGP SIGNATURE- Version: GnuPG v2.0.4-svn0 (GNU/Linux) Comment: Using GnuPG with SUSE - http://enigmail.mozdev.org iD8DBQFI7jZPwxqyUctZsggRAm9YAJ0VQ3JwzGfYp7ZmwbOJi7HxCTD/rQCglSUP eKJzO3NelDa55vMD3b+lp3o= =5CyM -END PGP SIGNATURE- __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] ParallelR
-BEGIN PGP SIGNED MESSAGE- Hash: SHA1 Hi Chi, ParallelR is a commercial software to run R in parallel. It is working very well. We tested it at a small linux cluster. You also can use R and the parallel packages (snow, Rmpi, nws, ...) packages. All Open Source and for free. You probably will have some more work installing the complete system, but the same results. You also can use a batch system with R. We are using Sun Grid Engine! (this should be even possible for parallelR) Best Markus Chi Chan wrote: Anyone using or has access to ParallelR? I was looking at the page and found nothing really useful! http://www.revolution-computing.com/sitegenius/topic.php?id=195 I want to see if I can run R on a cluster of workstation, and use batch systems like Grid Engine or Xgrid: http://gridengine.sunsource.net/ http://ww.apple.com/acg/xgrid/ --Chi __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -BEGIN PGP SIGNATURE- Version: GnuPG v2.0.4-svn0 (GNU/Linux) Comment: Using GnuPG with SUSE - http://enigmail.mozdev.org iD8DBQFI7SGUwxqyUctZsggRAjInAJ9Cw7cy97nVa57lokaWFx7VJk2iwwCeOuwO KHcLP7HUUMSmfak+oLrQjXU= =fPMX -END PGP SIGNATURE- __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] different results form summarization by loop and sum or rowMeans function
Hi,
I found different results calculating the rowMeans by the function
rowMeans() and a simple for-loop. The differences are very low. But
after this calculation I will start some optimization algorithms (BFGS
or CG) and there I get huge differences (from the small changes in the
beginning or start values, I changed nothing else in the code).
How I can avoid these differences between sum-loops and sum-functions?
Attached a small testcode using data form Bioconductor.
Best
Markus
library(affy)
data(affybatch.example)
mat - exprs(affybatch.example)[1:100,1:3]
mat - exp(1)*mat
mat - asinh(mat)
rowM1- rowMeans(mat)
t=rep(0,100) # Vektor mit 0en
for(i in 1:100){
for(j in 1:3)
t[i] - t[i] + mat[i,j]
}
rowM2 - t/3
m1 - mat - rowM1
m2 - mat -rowM2
print(m1-m2)
sessionInfo()
R version 2.7.1 (2008-06-23)
i386-pc-mingw32
locale:
LC_COLLATE=German_Germany.1252;LC_CTYPE=German_Germany.1252;LC_MONETARY=German_Germany.1252;LC_NUMERIC=C;LC_TIME=German_Germany.1252
attached base packages:
[1] tools stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] affy_1.18.2 preprocessCore_1.2.0 affyio_1.8.0
[4] Biobase_2.0.1
--
Dipl.-Tech. Math. Markus Schmidberger
Ludwig-Maximilians-Universität München
IBE - Institut für medizinische Informationsverarbeitung,
Biometrie und Epidemiologie
Marchioninistr. 15, D-81377 Muenchen
URL: http://ibe.web.med.uni-muenchen.de
Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de
Tel: +49 (089) 7095 - 4599
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] cluster/snow question
Hi Tolga, I am not sure why ls() is showing only args and fun. But x is at the nodes. Try this: clusterEvalQ(cl,x-x+3) [[1]] [1] 4 [[2]] [1] 4 clusterCall(cl,function()x+5) [[1]] [1] 9 [[2]] [1] 9 Best Markus [EMAIL PROTECTED] schrieb: Dear R Users, Apologies for a somewhat basic cluster question. I am trying to come to grips with how variables are instantiated within the environment of each node in a cluster. When I run the following code, I expect to see the variable x in the environment of each node, but fail to do so. What am I doing wrong ? library(snow) noclusters-2 cl - makeCluster(noclusters, type = SOCK) clusterCall(cl,ls) x-1 clusterExport(cl,x) clusterCall(cl,ls) #expect to see x in the environment, but get back the same result as in the call above stopCluster(cl) library(snow) noclusters-2 cl - makeCluster(noclusters, type = SOCK) clusterCall(cl,ls) [[1]] [1] args fun [[2]] [1] args fun x-1 clusterExport(cl,x) clusterCall(cl,ls) #expect to see x in the environment [[1]] [1] args fun [[2]] [1] args fun stopCluster(cl) Thanks in advance, Tolga Generally, this communication is for informational purposes only and it is not intended as an offer or solicitation for the purchase or sale of any financial instrument or as an official confirmation of any transaction. In the event you are receiving the offering materials attached below related to your interest in hedge funds or private equity, this communication may be intended as an offer or solicitation for the purchase or sale of such fund(s). All market prices, data and other information are not warranted as to completeness or accuracy and are subject to change without notice. Any comments or statements made herein do not necessarily reflect those of JPMorgan Chase Co., its subsidiaries and affiliates. This transmission may contain information that is privileged, confidential, legally privileged, and/or exempt from disclosure under applicable law. If you are not the intended recipient, you are hereby notified that any disclosure, copying, distribution, or use of the information contained herein (including any reliance thereon) is STRICTLY PROHIBITED. Although this transmission and any attachments are believed to be free of any virus or other defect that might affect any computer system into which it is received and opened, it is the responsibility of the recipient to ensure that it is virus free and no responsibility is accepted by JPMorgan Chase Co., its subsidiaries and affiliates, as applicable, for any loss or damage arising in any way from its use. If you received this transmission in error, please immediately contact the sender and destroy the material in its entirety, whether in electronic or hard copy format. Thank you. Please refer to http://www.jpmorgan.com/pages/disclosures for disclosures relating to UK legal entities. [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Dipl.-Tech. Math. Markus Schmidberger Ludwig-Maximilians-Universität München IBE - Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie Marchioninistr. 15, D-81377 Muenchen URL: http://ibe.web.med.uni-muenchen.de Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de Tel: +49 (089) 7095 - 4599 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] cluster/snow question
Hi Tolga, in SNOW you have to start a cluster with the command library(snow) cluster - makeCluster(#nodes) The object cluster is a list with an object for each node and each object again is a list with all informations (rank, comm, tags) The size of the cluster is the length of the list. #nodes == length(cluster) E.g. the rank for node one you can get by cluster[[1]]$rank Best Markus [EMAIL PROTECTED] schrieb: Dear R Users, I am attempting to use the snow package for clustering. Is there a way to identfy, in the environment of each node, a rank for that node and also, the total size of the cluster ? By way of analogy, I am looking for the functions in snow equivalent to mpi.comm.rank() and mpi.comm.size() from RMPI, in case that makes things clearer. Thanks in advance, Tolga Generally, this communication is for informational purposes only and it is not intended as an offer or solicitation for the purchase or sale of any financial instrument or as an official confirmation of any transaction. In the event you are receiving the offering materials attached below related to your interest in hedge funds or private equity, this communication may be intended as an offer or solicitation for the purchase or sale of such fund(s). All market prices, data and other information are not warranted as to completeness or accuracy and are subject to change without notice. Any comments or statements made herein do not necessarily reflect those of JPMorgan Chase Co., its subsidiaries and affiliates. This transmission may contain information that is privileged, confidential, legally privileged, and/or exempt from disclosure under applicable law. If you are not the intended recipient, you are hereby notified that any disclosure, copying, distribution, or use of the information contained herein (including any reliance thereon) is STRICTLY PROHIBITED. Although this transmission and any attachments are believed to be free of any virus or other defect that might affect any computer system into which it is received and opened, it is the responsibility of the recipient to ensure that it is virus free and no responsibility is accepted by JPMorgan Chase Co., its subsidiaries and affiliates, as applicable, for any loss or damage arising in any way from its use. If you received this transmission in error, please immediately contact the sender and destroy the material in its entirety, whether in electronic or hard copy format. Thank you. Please refer to http://www.jpmorgan.com/pages/disclosures for disclosures relating to UK legal entities. [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Dipl.-Tech. Math. Markus Schmidberger Ludwig-Maximilians-Universität München IBE - Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie Marchioninistr. 15, D-81377 Muenchen URL: http://ibe.web.med.uni-muenchen.de Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de Tel: +49 (089) 7095 - 4599 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] exit function in R?
try this: stop(Message) warning(Message) Best Markus Federico Abascal schrieb: Hi, This is likely an stupid question, but I cannot find the solution. I am searching for an exit function, to end the execution of an R script if some condition is not filled. Any clue? Thank you in advance! Federico __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Dipl.-Tech. Math. Markus Schmidberger Ludwig-Maximilians-Universität München IBE - Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie Marchioninistr. 15, D-81377 Muenchen URL: http://ibe.web.med.uni-muenchen.de Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de Tel: +49 (089) 7095 - 4599 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] snow, stopping cluster
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, status) : MPI_Error_string: invalid communicator sessionInfo() R version 2.6.0 (2007-10-03) x86_64-unknown-linux-gnu locale: LC_CTYPE=de_DE.UTF-8;LC_NUMERIC=C;LC_TIME=de_DE.UTF-8;LC_COLLATE=de_DE.UTF-8;LC_MONETARY=de_DE.UTF-8;LC_MESSAGES=de_DE.UTF-8;LC_PAPER=de_DE.UTF-8;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=de_DE.UTF-8;LC_IDENTIFICATION=C attached base packages: [1] tools stats graphics grDevices utils datasets methods [8] base other attached packages: [1] affyPara_0.99.2 affy_1.16.0 preprocessCore_1.0.0 [4] affyio_1.6.1 Biobase_1.16.1 Rmpi_0.5-5 [7] snow_0.2-9 loaded via a namespace (and not attached): [1] rcompgen_0.1-15 Best Markus -- Dipl.-Tech. Math. Markus Schmidberger Ludwig-Maximilians-Universität München IBE - Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie Marchioninistr. 15, D-81377 Muenchen URL: http://ibe.web.med.uni-muenchen.de Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de Tel: +49 (089) 7095 - 4599 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Rmpi and C Code, where to get the communicator
Hello,
I try to write parts of my code in C to accelerate the for-loops. But
basic operations I want to do in R (e.g. start cluster). My R code looks
something like this:
library(Rmpi)
mpi.spawn.Rslaves()
mpi.remote.exec()
dyn.load(test.so)
erg - .Call(test, )
mpi.close.Rslaves()
mpi.quit()
And my C function looks something like this:
#include mpi.h
#include R.h
#include Rdefines.h
#include Rinternals.h
SEXP test (SEXP a, ..){
int rank;
comm ??
MPI_Comm_rank (comm, rank);
..
}
For all MPI functions I need the right communicator (MPI_Comm *comm;) to
communicate with the existing slaves. This variable will be generated by
spawning the Rslaves (mpi.spawn.Rslaves). But how to get to this
variable in my C function?
Is the communicator variable somewhere stored in a R variable?
( I use R 2.6.2 and Rmpi 0.5-5)
Thanks
Markus
--
Dipl.-Tech. Math. Markus Schmidberger
Ludwig-Maximilians-Universität München
IBE - Institut für medizinische Informationsverarbeitung,
Biometrie und Epidemiologie
Marchioninistr. 15, D-81377 Muenchen
URL: http://ibe.web.med.uni-muenchen.de
Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de
Tel: +49 (089) 7095 - 4599
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[R] Rmpi and C Code, where to get the communicator
Hello,
I try to write parts of my code in C to accelerate the for-loops. But
basic operations I want to do in R (e.g. start cluster). My R code looks
something like this:
library(Rmpi)
mpi.spawn.Rslaves()
mpi.remote.exec()
dyn.load(test.so)
erg - .Call(test, )
mpi.close.Rslaves()
mpi.quit()
And my C function looks something like this:
#include mpi.h
#include R.h
#include Rdefines.h
#include Rinternals.h
SEXP test (SEXP a, ..){
int rank;
comm ??
MPI_Comm_rank (comm, rank);
..
}
For all MPI functions I need the right communicator (MPI_Comm *comm;) to
communicate with the existing slaves. This variable will be generated by
spawning the Rslaves (mpi.spawn.Rslaves). But how to get to this
variable in my C function?
Is the communicator variable somewhere stored in a R variable?
( I use R 2.6.2 and Rmpi 0.5-5)
Thanks
Markus
--
Dipl.-Tech. Math. Markus Schmidberger
Ludwig-Maximilians-Universität München
IBE - Institut für medizinische Informationsverarbeitung,
Biometrie und Epidemiologie
Marchioninistr. 15, D-81377 Muenchen
URL: http://ibe.web.med.uni-muenchen.de
Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de
Tel: +49 (089) 7095 - 4599
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] Parallel R for dummies (on hpc)
Hi Tim, I think you should have a look at this Rmpi Tutorial http://ace.acadiau.ca/math/ACMMaC/Rmpi/ and to Luke Tierney's webpage: http://www.cs.uiowa.edu/~luke/R/cluster/uiowasnow.html Best, Markus Tim Smith schrieb: Hi, I had access to an hpc cluster, and wanted to parallelize some of my R code. I looked at the snow,nws, rscalapack documentation but was unable to make out how I should submit my job to the hpc, and how I should code a simple program. For example, if I had 10 matrices, and 10 processor how should I write the R (and the hpc submit code) so that I run the calculations (e.g. rowsums) for each matrix in a different processor? Are there any simple examples on how to go about doing this? many thanks! Be a better friend, newshound, and [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Dipl.-Tech. Math. Markus Schmidberger Ludwig-Maximilians-Universität München IBE - Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie Marchioninistr. 15, D-81377 Muenchen URL: http://ibe.web.med.uni-muenchen.de Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de Tel: +49 (089) 7095 - 4599 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] R on a computer cluster
Hi, your required performance is strongly depending on your application. If you talk about a cluster, you should think about several computers. Not only one computer with several processors. If you have several computers. First of all you have to decide for a communication protocol for parallel computing: MPI, PVM, ... Then you have to install this at your computers. I think you should use MPI and one of its implementations: OpenMPI, LamMPI Then there are several R packages for using the communication protocols: Rmpi, snow, Rpvm, ... If you have one computer with severals processors, you can do the same thinks. But then you have only shared memory (bottleneck) and there is not to much improvement in performance. R is not yet implemented for multiple-processors. There is one first, experimental R package using openMP for multi threading: pnmath (http://www.stat.uiowa.edu/~luke/R/experimental/) Some useful links: http://www.stats.uwo.ca/faculty/yu/Rmpi/ http://ace.acadiau.ca/math/ACMMaC/Rmpi/ http://www.open-mpi.org/ http://www.personal.leeds.ac.uk/~bgy1mm/MPITutorial/MPIHome.html Best regards Markus [EMAIL PROTECTED] schrieb: Dear all, I usually run R on my laptop with Windows XP Professional. Now I really want to run R on a computer cluster (4 processors) with Suse Linux Enterprise ver. 10. But I am new with computer cluster. Should I modify my functions in order to use the greater performance and availability than that provided by my laptop? Is there any R manual on parallel computations on multiple-processor? Any suggestion on a basic tutorial on this topic? Thank you. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] snow, MPI, comm
Hello R Users, Hello Luke, in makeMPICluster (library snow) you set a explicit variable comm - 1 Therefore using snow, it is not possible to start two (or more) different MPI Clusters from one R session. Can you put comm and intercomm to the default cluster options? Best regards Markus -- Dipl.-Tech. Math. Markus Schmidberger Ludwig-Maximilians-Universität München IBE - Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie Marchioninistr. 15, D-81377 Muenchen URL: http://ibe.web.med.uni-muenchen.de Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] snow and Rmpi, delayed starting-times at nodes
Hello,
we use R version 2.6.0, Rmpi_0.5-5 and snow_0.2-9 and have a parallel
call like this:
clusterApply(cluster, input.list, function(input, data1, type) {
}, data1, type )
We now have the problem, that the processes at the nodes start delayed.
This means for example, node 4 starts its calculation when node 1 is
finished.(see the attached figure)
Therefore we have a lot of loss in our computation time.
Our messages are not very big:
input.list = list of vectors. Each vector has 10 strings
data1 = one integer
type = one string
What can we do to improve the speed?
Thanks
Markus
--
Dipl.-Tech. Math. Markus Schmidberger
Ludwig-Maximilians-Universität München
IBE - Institut für medizinische Informationsverarbeitung,
Biometrie und Epidemiologie
Marchioninistr. 15, D-81377 Muenchen
URL: http://ibe.web.med.uni-muenchen.de
Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de
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[R] list to Matrix
Hello, I have a list of vectors (all the same length). How to convert the list to a matrix? Each vector should be a column. I tried this: l - list(c(1,2,3),c(1,2,3),c(1,2,3)) mat - matrix( unlist(l), nrow=length(l) ) But I think this is not very efficient. Is there a better solution? Thanks Markus -- Dipl.-Tech. Math. Markus Schmidberger Ludwig-Maximilians-Universität München IBE - Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie Marchioninistr. 15, D-81377 Muenchen URL: http://ibe.web.med.uni-muenchen.de Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
