similar to: Set the number of threads using openmp with .Fortran?

I got this to work on Linux but it is not working on Windows. *My understanding is that this should also work on windows, is that correct?* If so, what should I do? differently? To get it to work on Linux, I modified my R script as follows: #' OpenMP Hello World #' #' @param nthreads The number of threads that you want to use #' @example #' hello(nthreads=2) #' @export

I was able to make some progress by using this <https://github.com/bert9bert/ParallelForest/blob/master/src/Makevars> as a reference. Now: *This is my makevars:* ##### Compiler flags ##### PKG_FCFLAGS = $(SHLIB_OPENMP_FFLAGS) PKG_LIBS = $(SHLIB_OPENMP_CFLAGS) ##### Phony target for R's build system to invoke ##### all: $(SHLIB) ##### Clean target ##### clean: rm -f *.o *.mod

Dear R experts, recently I started developing a Rcpp package "OpenMPTest". Within that package I want to use OpenMP, as in the following code example: // header file #include <omp.h> using namespace Rcpp ; RcppExport SEXP testOpenMP( SEXP nThreads ) ; // cpp file SEXP testOpenMP( SEXP nThreads ) { BEGIN_RCPP NumericVector numberThreads = NumericVector( nThreads );

Hi, I created a R library that uses a Fortran module. Everything works like a charm on linux. Now I'm trying to make it work on Windows. I cloned my git repository <https://github.com/ignacio82/MyPi> on a windows computer, and when I press the build and reload button on Rstudio I get these errors: ==> Rcmd.exe INSTALL --no-multiarch --with-keep.source MyPi * installing to library

On Fri, Apr 18, 2014 at 11:13 AM, Dmitry Vyukov <dvyukov at google.com> wrote: > Hi, > > This is long thread, so I will combine several comments into single email. > > > >> - 8-bit per-thread counters, dumping into central counters on overflow. > >The overflow will happen very quickly with 8bit counter. > > Yes, but it reduces contention by 256x (a thread

On Fri, Apr 18, 2014 at 11:44 AM, Dmitry Vyukov <dvyukov at google.com> wrote: > On Fri, Apr 18, 2014 at 11:32 AM, Dmitry Vyukov <dvyukov at google.com>wrote: > >> On Fri, Apr 18, 2014 at 11:13 AM, Dmitry Vyukov <dvyukov at google.com>wrote: >> >>> Hi, >>> >>> This is long thread, so I will combine several comments into single

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();

On Apr 17, 2014, at 2:04 PM, Chandler Carruth <chandlerc at google.com> wrote: > On Thu, Apr 17, 2014 at 1:27 PM, Justin Bogner <mail at justinbogner.com> wrote: > Chandler Carruth <chandlerc at google.com> writes: > > if (thread-ID != main's thread-ID && shard_count < std::min(MAX, NUMBER_OF_CORES)) { > > shard_count = std::min(MAX,

Dears, I am writing a code in Fortran using OpenMP directives. When compiling the code in gfortran 4.4 does not occur any problem. When compiling the code in gfortran 4.6, an error message appears. In other compilers the error does not occur. A small example. ## Code in Fortran        subroutine hello()        implicit none        integer :: nthreads, tid        integer ::

¡Buenas tardes! Antes de nada, dar las gracias por permitirme participar en esta lista. Soy un usuario recién llegado a R de la mano del análisis geoespacial. Soy un arqueólogo que se ha topado con un package para R creado por un arqueólogo para la ejecución de procesos para a creación de rutas de menor coste cuyo nombre es leastcostpath y que se encuentra en el repositorio de GitHub. Contiene

Dear R-SIG-Debian, I am using R version 3.1.2 with rstudio-server 0.98.113 on debian build 3.2.0-4-amd64 #1 SMP Debian 3.2.68-1+deb7u1 x86_64 GNU/Linux. I often use the %dopar% operator in from the foreach package to run code in parallel. However, the only other use on the box seemingly installed a few items and suddenly %dopar% will use far more than the number of cores I am specifying and

You should be able to set PKG_FCFLAGS="-fno-stack-protector" when compiling to ensure that the stack protector is not used. (Trying that out on a Windows VM, with a simple `R CMD build` + `R CMD INSTALL`, compilation of your package succeeded but linking failed saying the DLL 'Fpi' was not found; I imagine that's a separate issue.) As an aside, be sure to check out what

Hi, I am using LLVM 3.6.1 to test the following code: #include <omp.h> #include <stdio.h> #include <stdlib.h> int main() { int tid, nthreads; #pragma omp parallel sections private(nthreads, tid) { #pragma omp section { tid = omp_get_thread_num(); printf("Hello, tid = %d\n ", tid); } #pragma omp section { tid = omp_get_thread_num();

Hi all, i want to replace a bunch of Apple Xserves with Xraids and HFS+ (brr) by Sun x4200 with SAS-Jbods and ZFS. The application will be the Helios UB+ fileserver suite. I installed the latest Solaris 10 on a x4200 with 8gig of ram and two Sun SAS controllers, attached two sas-jbods with 8 SATA-HDDs each und created a zfs pool as a raid 10 by doing something like the following: [i]zpool create

I am trying to parallelize part of a C function that is called from R (via .C) using OpenMP's "parallel for" pragma. I get mixed results: some runs finish with no problem, but some lead to R crashing after issuing a long error message involving memory violations. I found this post, which describes how a .Call() function can be made to avoid crashing R by raising the stack limit:

Dear All, What is the preferred way for Package A, to initialize a cluster, and load Package B on all nodes? I am writing a package that parallelizes some functions through the use of a cluster if useRs are on a Windows machine (using parLapply and family). I also make use of another package in some of my code, so it is necessary to load the required packages on each slave once the cluster is

Hi, I experience surprisingly large timing differences for the multiplication of matrices of the same dimension. An example is given below. How can this be explained? I posted the question on Stackoverflow: https://stackoverflow.com/questions/58886111/r-why-is-matrix-product-slower-when-matrix-has-very-small-values Somebody could reproduce the behavior but I did not get any useful explanations

Can you send the IR you are using? Volkan On Thu, Oct 8, 2015 at 6:28 AM Erdem Derebaşoğlu < erdemderebasoglu at hotmail.com> wrote: > Thanks. I enabled my pass. I have one resolved issue though: > MachineMemOperand::getAddrSpace() always returns zero. How can I use it to > distinguish private memory accesses? > > Erdem > > ------------------------------ > From:

Dear all, I found a strange thing with the snow package. This will work: y = matrix(1:4, 2) cl = makeCluster(rep('localhost', 8), type='SOCK') parMM(cl, y, y) This will not: y = matrix(1:4, 2) ncore = system('nproc') parMM(cl, y, y) Error in cut.default(i, breaks) : invalid number of intervals I also tried: cl = makeCluster(rep('localhost', ncore),

Hi I've built a dll using Fortran code and can call it by either R or Fortran. Calling by the former gives me the wrong answer and the later gives the correct answer. >From what I've read, it looks like I should use the subroutines DBLEPR, INTPR and REALPR to print to the R console rather than using Fortran standard I/O and that if I use the command R CMD SHLIB source.f that these