You can now (already in OpenMP5) use it to write GPU programs. Intels OneAPI uses OpenMP 5.5 to write programs for the Intel PonteVecchio GPUs which are on par

You can now (already in OpenMP5) use it to write GPU programs. Intels OneAPI uses OpenMP 5.5 to write programs for the Intel PonteVecchio GPUs which are on par to the Nvidia A100. https://www.intel.com/content/www/us/en/docs/oneapi/optimization-guide-gpu/2023-0/compiling-and-running-an-openmp-application.html https://www.intel.com/content/www/us/en/docs/oneapi/optimiza... gcc also provides support for NVidia and AMD GPUs https://gcc.gnu.org/wiki/Offloading https://gcc.gnu.org/wiki/Offloading Here is an example how you can use openmp for running a kernel on a nvidia A100: https://people.montefiore.uliege.be/geuzaine/INFO0939/notes/gpu/compileandrun/ https://people.montefiore.uliege.be/geuzaine/INFO0939/notes/... #include <stdlib.h> #include <stdio.h> #include <omp.h> void saxpy(int n, float a, float *x, float *y) { double elapsed = -1.0 \* omp_get_wtime(); // We don't need to map the variable a as scalars are firstprivate by default #pragma omp target teams distribute parallel for map(to:x[0:n]) map(tofrom:y[0:n]) for(int i = 0; i < n; i++) { y[i] = a * x[i] + y[i]; } elapsed += omp_get_wtime(); printf("saxpy done in %6.3lf seconds.\n", elapsed); } int main() { int n = 2000000; float *x = (float*) malloc(n*sizeof(float)); float *y = (float*) malloc(n*sizeof(float)); float alpha = 2.0; #pragma omp parallel for for (int i = 0; i < n; i++) { x[i] = 1; y[i] = i; } saxpy(n, alpha, x, y); free(x); free(y); return 0; }