openmp

问题 I am trying to speed up a sparse matrix-vector product using open mp, the code is as follows: void zAx(double * z, double * data, long * colind, long * row_ptr, double * x, int M){ long i, j, ckey; int chunk = 1000; //int * counts[8]={0}; #pragma omp parallel num_threads(8) { #pragma omp for private(ckey,j,i) schedule(static,chunk) for (i=0; i<M; i++ ){ z[i]=0; for (ckey=row_ptr[i]; ckey<row_ptr[i+1]; ckey++) { j = colind[ckey]; z[i] += data[ckey]*x[j]; } } } } Now, this code runs fine, and

问题 From what I understand, #pragma omp parallel and its variations basically execute the following block in a number of concurrent threads, which corresponds to the number of CPUs. When having nested parallelizations - parallel for within parallel for, parallel function within parallel function etc. - what happens on the inner parallelization? I'm new to OpenMP, and the case I have in mind is probably rather trivial - multiplying a vector with a matrix. This is done in two nested for loops.

问题 $ gcc 12.c -fopenmp 12.c:9:9: fatal error: 'omp.h' file not found #include<omp.h> ^ 1 error generated. While compiling openMP programs I get the above error. I am using OS X Yosemite. I first tried by installing native gcc compiler by typing gcc in terminal and later downloaded Xcode too still I got the same error. Then I downloaded gcc through: $ brew install gcc Still I'm getting the same error. I did try changing the compiler path too still it shows: $ which gcc /usr/bin/gcc So how do I

问题 OpenMP has its own support for atomic access, however, there are at least two reasons for preferring C++11 atomics: they are significantly more flexible and they are part of the standard. On the other hand, OpenMP is more powerful than the C++11 thread library. The standard specifies the atomic operations library and the thread support library in two distinct chapters. This makes me to believe that the components for atomic access are kind of orthogonal to the thread library used. Can I

问题 I have an OpenMP code that looks like the following while(counter < MAX) { #pragma omp parallel reduction(+:counter) { // do monte carlo stuff // if a certain condition is met, counter is incremented } } Hence, the idea is that the parallel section gets executed by the available threads as long as the counter is below a certain value. Depending on the scenario (I am doing MC stuff here, so it is random), the computations might take long than others, so that there is an imbalance between the

问题 I have an OpenMP code that looks like the following while(counter < MAX) { #pragma omp parallel reduction(+:counter) { // do monte carlo stuff // if a certain condition is met, counter is incremented } } Hence, the idea is that the parallel section gets executed by the available threads as long as the counter is below a certain value. Depending on the scenario (I am doing MC stuff here, so it is random), the computations might take long than others, so that there is an imbalance between the

问题 I got tons of warning from openBLAS like OpenBLAS Warning : Detect OpenMP Loop and this application may hang. Please rebuild the library with USE_OPENMP=1 option. OpenBLAS Warning : Detect OpenMP Loop and this application may hang. Please rebuild the library with USE_OPENMP=1 option. OpenBLAS Warning : Detect OpenMP Loop and this application may hang. Please rebuild the library with USE_OPENMP=1 option. OpenBLAS Warning : Detect OpenMP Loop and this application may hang. Please rebuild the

问题 I got tons of warning from openBLAS like OpenBLAS Warning : Detect OpenMP Loop and this application may hang. Please rebuild the library with USE_OPENMP=1 option. OpenBLAS Warning : Detect OpenMP Loop and this application may hang. Please rebuild the library with USE_OPENMP=1 option. OpenBLAS Warning : Detect OpenMP Loop and this application may hang. Please rebuild the library with USE_OPENMP=1 option. OpenBLAS Warning : Detect OpenMP Loop and this application may hang. Please rebuild the

问题 Here I present a simple fortran code using OpenMP that calculate a summation of arrays multiple times. My computers has 6 cores with 12 threads and memory space of 16G. There are two versions of this code. The first version has only 1 file test.f90 and the summation is implemented in this file. The code is presented as follows program main implicit none integer*8 :: begin, end, rate integer i, j, k, ii, jj, kk, cnt real*8,allocatable,dimension(:,:,:)::theta, e allocate(theta(2000,50,5))

问题 I am trying to parallelize a simple mandelbrot c program, yet I get this error that has to do with not including acc routine information. Also, I am not sure whether I should be copying data in and out of the parallel section. PS I am relatively new to parallel programming, so any advice with learning it would be appreciated. (Warning when compiled) PGC-S-0155-Procedures called in a compute region must have acc routine information: fwrite (mandelbrot.c: 88) PGC-S-0155-Accelerator region