openmp

I am learning OPENMP and wrote the following code to solve nqueens problem. //Full Code: https://github.com/Shafaet/Codes/blob/master/OPENMP/Parallel%20N- Queen%20problem.cpp int n; int call(int col,int rowmask,int dia1,int dia2) { if(col==n) { return 1; } int row,ans=0; for(row=0;row<n;row++) { if(!(rowmask & (1<<row)) & !(dia1 & (1<<(row+col))) & !(dia2 & (1<<((row+n-1)-col)))) { ans+=call(col+1,rowmask|1<<row,dia1|(1<<(row+col)), dia2|(1<<((row+n-1)-col))); } } return ans; } double parallel() { double st=omp_get_wtime(); int ans=0; int i; int rowmask=0,dia1=0,dia2=0; #pragma omp parallel

In my C++ program, I'd like to run its executable sometimes with and sometimes without using OpenMP (i.e. multi-threading or single-threading). I am considering any of the following two cases how my code is using OpenMP: (1) Assume that my code is only having #include <omp.h> and OpenMP directives. (2) Same as (1) and my code further calls OpenMP functions like omp_get_thread_num() . In order not to have different code for different running, is it the only way using some self-defined precompiler variable to guard where OpenMP appears in my code ? Thanks and regards! Steve Hi the easiest way to

I've got some code that can run with (or without) OpenMP - it depends on how the user sets up the makefile. If they want to run with OpenMP, then they just add -fopenmp to CFLAGS and CXXFLAGS . I'm trying to determine what preprocessor macro I can use to tell when -fopenmp is in effect. The omp.h header does not look very interesting: $ cat /usr/lib/gcc/x86_64-linux-gnu/4.8/include/omp.h | grep define #define OMP_H 1 #define _LIBGOMP_OMP_LOCK_DEFINED 1 # define __GOMP_NOTHROW throw () # define __GOMP_NOTHROW __attribute__((__nothrow__)) And I can't get the preprocessor to offer up anything

I very rarely use fortran, however I have been tasked with taking legacy code rewriting it to run in parallel. I'm using gfortran for my compiler choice. I found some excellent resources at https://computing.llnl.gov/tutorials/openMP/ as well as a few others. My problem is this, before I add any OpenMP directives, if I simply compile the legacy program: gfortran Example1.F90 -o Example1 everything works, but turning on the openmp compiler option even without adding directives: gfortran -openmp Example1.F90 -o Example1 ends up with a Segmentation fault when I run the legacy program. Using

I was given some code to paralellize using OpenMP and, among the various function calls, I noticed this for loop takes some good guilt on the computation time. double U[n][n]; double L[n][n]; double Aprime[n][n]; for(i=0; i<n; i++) { for(j=0; j<n; j++) { if (j <= i) { double s; s=0; for(k=0; k<j; k++) { s += L[j][k] * U[k][i]; } U[j][i] = Aprime[j][i] - s; } else if (j >= i) { double s; s=0; for(k=0; k<i; k++) { s += L[j][k] * U[k][i]; } L[j][i] = (Aprime[j][i] - s) / U[i][i]; } } However, after trying to parallelize it and applying some semaphores here and there (with no luck), I came to the

I have a question about the Microsoft PPL library, and parallel programming in general. I am using FFTW to perform a large set (100,000) of 64 x 64 x 64 FFTs and inverse FFTs. In my current implementation, I use a parallel for loop and allocate the storage arrays within the loop. I have noticed that my CPU usage only tops out at about 60-70% in these cases. (Note this is still better utilization than the built in threaded FFTs provided by FFTW which I have tested). Since I am using fftw_malloc, is it possible that excessive locking is occurring which is preventing full usage? In light of this,

I'm only asking this to try to understand what I've spent 24 hours trying to fix. My system: Ubuntu 12.04.2, Matlab R2011a, both of them 64-bit, Intel Xeon processor based on Nehalem. The problem is simply, Matlab allows OpenMP based programs to utilize all CPU cores with hyper-threading enabled but does not allow the same for TBB. When running TBB, I can launch only 4 threads, even when I change the maxNumCompThreads to 8. While with OpenMP I can use all the threads I want. Without Hyper-threading, both TBB and OpenMP utilize all 4 cores of course. I understand Hyper-threading and that its

Sitting here with a simple rails 3 app in which I have a simple Gallery model and each gallery has many images. The image model is extended with paperclip and with the following options has_attached_file :local, :styles => { :large => "800x800>", :medium => "300x300>", :thumb => "100x100#", :small => "60x60#" } In my galleries_controller I have the following action that is implemented in order to work with the jQuery-File-Upload plugin. thereby the json response. def add_image gallery = Gallery.find params[:id] image = gallery.images.new({:local => params[:local]}) if image.save render :json =