I wouldl ike to thank you for your response. The hardest part in the installation is to find a BLAS library to install. If I understand it right once I install BLAS then I only need to change a flag in the ./configure of R installation..
Our system is running opensuse and has intel cores. according to the link here http://cran.r-project.org/doc/manuals/R-admin.html#BLAS I ahve to find a proper BLAS library to installll.. In the explanation for the different alternatives seem that most of those are not implemented any more and other require special configuration :( Are there not any rpm package to do the work nice and "transparently"? B.R Alex ________________________________ From: Rainer M Krug <r.m.k...@gmail.com> Cc: Ernest Adrogué <nfdi...@gmail.com>; "r-help@r-project.org" <r-help@r-project.org> Sent: Tuesday, February 7, 2012 12:08 PM Subject: Re: [R] using mclapply (multi core apply) to do matrix multiplication On 07/02/12 12:02, Alaios wrote: > Thank you very much for your point... > I hope I can find some easy to follow instructions as I do not have root > permission Me neither on pur cluster - but that won't stop you from compiling and installing R in your home directory. By doing this, you have even more control. Cheers and good luck, Rainer for the many cores system and our system administrator want > to have easy instructions to follow. > Thanks a gain. > > ------------------------------------------------------------------------ > *From:* Rainer M Krug <r.m.k...@gmail.com> > *Cc:* Ernest Adrogué <nfdi...@gmail.com>; "r-help@r-project.org" > <r-help@r-project.org> > *Sent:* Tuesday, February 7, 2012 11:44 AM > *Subject:* Re: [R] using mclapply (multi core apply) to do matrix > multiplication > > On 07/02/12 11:31, Alaios wrote: > > I would like to thank you Ernest for your answer. I guess that this > > is gonna be faster as right now R only sees one core. In my work > > there is a system with 64 cores and you can see only one working. If > > I understand it right a [m,n][n,k] matrix multiplication can be split > > into rows (from first matrice) and columns (from the second matrice) > > and then combine all the local results of each cpu together. > > You definitaly can go this way, but I would STRONGLY recommend to search > for "parallel BLAS", check in the R-admin manual the section "Linear > Algebra" which deals with BLAS et al, and e.g. > http://www.r-bloggers.com/compiling-64-bit-r-2-10-1-with-mkl-in-linux/ > > My guess is that a paralelization on the C level in the BLAS et al. > library will be MUCH faster then a paralelization on R level. > > Also, there is a R-sig-hpc mailing list for these kind of questions. > > Cheers, > > Rainer > > > > Would that be too weird for mclapply to handle? > > > > B.R Alex > > > > > > > > ________________________________ From: Ernest > > Adrogué<nfdi...@gmail.com <mailto:nfdi...@gmail.com>> To: > r-help@r-project.org <mailto:r-help@r-project.org> Sent: Tuesday, > > February 7, 2012 11:02 AM Subject: Re: [R] using mclapply (multi core > > apply) to do matrix multiplication > > > > 7-02-2012, 00:29 (-0800); Alaios escriu: > >> Dear all, I am trying to multiply three different matrices and > >> each matrice is of size 16384,16384 the normal %*% multiplciation > >> operator has not finished one day now. As I am running a system > >> with many cores (and it seems that R is using only one of those) I > >> would like to write fast a brief function that converts the typical > >> for loops of a matrix multiplication to a set of lapply sets > >> (mclapply uses the lapply syntax but it applies the work to many > >> cores). > >> > >> If my thinking is correct , in the sense that this will speed up > >> things a lot, I want you to help me covert the first matrix in > >> rows the second in columns and convert those in a format that > >> lapply would like to work with. > > > > If I understand correctly, R uses a specialized library called BLAS > > to do matrix multiplications. I doubt re-implementing the matrix > > multiplication code at R-level would be any faster. What you can try > > is replace BLAS with a multicore version of BLAS although it's not > > easy if you have to compile it yourself. > > > > Also, you may try to re-think the problem you're trying to solve. > > Maybe there's a different approach that is less > > computation-intensive. > > > > > > > > > > ______________________________________________ R-help@r-project.org > <mailto: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. > > > -- > Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation > Biology, UCT), Dipl. Phys. (Germany) > > Centre of Excellence for Invasion Biology > Stellenbosch University > South Africa > > Tel : +33 - (0)9 53 10 27 44 > Cell: +33 - (0)6 85 62 59 98 > Fax : +33 - (0)9 58 10 27 44 > > Fax (D): +49 - (0)3 21 21 25 22 44 > > email: rai...@krugs.de <mailto:rai...@krugs.de> > > Skype: RMkrug > > -- Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology, UCT), Dipl. Phys. (Germany) Centre of Excellence for Invasion Biology Stellenbosch University South Africa Tel : +33 - (0)9 53 10 27 44 Cell: +33 - (0)6 85 62 59 98 Fax : +33 - (0)9 58 10 27 44 Fax (D): +49 - (0)3 21 21 25 22 44 email: rai...@krugs.de Skype: RMkrug [[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.