search for: pnmath

Has anyone successfully compiled pnmath (http://www.stat.uiowa.edu/~luke/R/experimental ) for an intel processor running mac OS 10.5? When I attempt to do so via the R package installer (choosing "Local Source Package" and pointing to the pnmath_0.0-2.tar.gz file), I get the following errors: * Installing *source* package...

...C_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] MASS_7.3-26 loaded via a namespace (and not attached): [1] compiler_3.0.0 fortunes_1.5-0 tools_3.0.0 > I am trying to install pnmath from the commandline (outside R), this is what happens: kjetil@kjetil-HP-Pavilion-dv4-Notebook-PC:~/R/src$ sudo R CMD INSTALL pnmath_0.0-4.tar.gz * installing to library ‘/usr/local/lib/R/site-library’ * installing *source* package ‘pnmath’ ... ** libs gcc -std=gnu99 -I/usr/share/R/include -DNDEBU...

(1) ...need to speed up a monte-carlo sampling...any suggestions about how I can get R to use all 8 cores of a mac pro would be most useful and very appreciated... (2) spent the last few hours trying to get pnmath to compile under os- x 10.5.4... using gcc version 4.2.1 (Apple Inc. build 5553) as downloaded from CRAN, xcode 3.0... ...xcode 3.1 installed over top of above after compilation failure...adverse effect, produced error on "-arch" any suggestion about how to get pnmath to compile...

Hello, The problem I'm working now requires to operate on big matrices. I've noticed that there are some packages that allows to run some commands in parallel. I've tried snow and NetWorkSpaces, without much success (they are far more slower that the normal functions) My problem is very simple, it doesn't require any communication between parallel tasks; only that it divides

I have an "embarrassingly parallel" routine that I need to run 24000^2/2 times (based on some microarray data). All I really need to do is parallelize a nested for-loop. But I haven't found a clear list of what packages/commands I'd need to do this. I've got a dual quad core xeon system running RHEL5, so if I could use hyperthreading to increase the number of (virtual)

...U 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 requires a special build Fork-UNIX only Romp-looks like this hasn?t advanced past the developmental stage Multicore-use on Windows at your own risk R/parallel-seems like the best option if I don?t want to recompile. ? Has anyone ever used R/parallel?? Wha...

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

Dear Sir or Madam, I've been using R for one year and I really appreciate it. I would like to know if a version performing parallel computations on multicore computers and computer clusters exists. Thank you very much. Yours sincerely. Enrico Giorgi _________________________________________________________________ [[alternative HTML version deleted]]

Hello, I've written a package that may use OpenMP to speed up computations. OpenMP is supported in recent Gcc versions by using the -fopenmp flag. The problem is that flag crashed gcc versions that do not support OpenMP. So what is the best way for a package to handle this issue. Has someone a configure script that deals with this ? Thanks, Karl [[alternative HTML version deleted]]

Hello, I compiled R-2.15.2 with linux intel compilers (see below). when I execute some R code on a // 4 proc x 4 cores // server (export MKL_NUM_THREADS = 16) very often I have the situations where only one processor (4 cores) is active instead of 4 (16 cores) ! do you know this fact depends on what ? thank you ! P.S. many functions of R are single-threaded, is there a simple way to make them

Hi everybody! Could somebody help me with the following? I'm trying to run a simple Hello World code in openmp using .C function. The C code i have is: #include <omp.h> #include <stdio.h> #include <R.h> void hello_omp(int *n) { int th_id, nthreads; omp_set_num_threads(*n); #pragma omp parallel private(th_id) { th_id = omp_get_thread_num();

Hello, I am interested in optimizing some of R's vector math functions to utilize the SPE units of the Cell processor (commonly found in the Playstation 3) and I am wondering if anyone has already done any work in that area. I can't find anything using the search page or Google. (Admittedly it is difficult to search for information on a one-letter-named programming language whose

Hello I am fortunate (or in really big trouble) in that the research group I work with will soon be receiving several high end dual quad core machines. We will use the Ubuntu OS on these. We intend to use this cluster for some extensive modeling applications. Our programming guru has demonstrated the ability to link much simpler machines to share CPUs and we purchased the new ones to take

...OS Leopard (10.5.6), latest developer tools installed, gcc/g++/gfortran version 4.4 installed (via http://hpc.sourceforge.net/, after which I updated the gcc & g++ symlinks to link to the 4.4 versions; gfortran used the 4.4 version without updating the symlink). Ultimately I wanted to instalI pnmath, so as per a previous thread ( http://www.nabble.com/Parallel-R-tt18173953.html#a18196319) I built with: LIBS=-lgomp ./configure --with-blas='-framework vecLib' make -j4 The configure runs without a hitch, but make fails, throwing an error seemingly related to qdCocoa: making qdCocoa.d fr...

...OS Leopard (10.5.6), latest developer tools installed, gcc/g++/gfortran version 4.4 installed (via http://hpc.sourceforge.net/, after which I updated the gcc & g++ symlinks to link to the 4.4 versions; gfortran used the 4.4 version without updating the symlink). Ultimately I wanted to instalI pnmath, so as per a previous thread ( http://www.nabble.com/Parallel-R-tt18173953.html#a18196319) I built with: LIBS=-lgomp ./configure --with-blas='-framework vecLib' make -j4 The configure runs without a hitch, but make fails, throwing an error seemingly related to qdCocoa: making qdCocoa.d fr...