OpenMP first steps

OpenMP - Start

Shared memory programming.

OpenMP: Quick reference (3.1, 4.0, 4.5, 5.0), home page, tutorial (LLNL).

Tools

ICC_

Guided parallelization and vectorization (-parallel)
> icpc -c -qopenmp -guide *.cpp 2> gap.txt
gives hints per source line.
Also via make gap_par_report .
do not assume data dependencies in vectorization/parallelization:

pragma directive: #pragma ivdep

See the Parallel Universe Magazine by Intel.

PGI_

do not assume data dependencies in vectorization/parallelization:

compiler option: pgc++ -mp -Mnodepchk *.cpp
pragma directive: #pragma pgi nodepchk

CLANG/LLVM: installation, what's supported

> sudo apt install libomp5 libomp-dev libomp-doc

Change number of threads to 4 (Quick Ref.): > export OMP_NUM_THREADS=4
Preprocessor symbol: _OPENMP

How to OpenMP-parallelize the inner product:

Original code for inner product:

double scalar(const int N, const double x[], const double y[])
{
 double sum = 0.0;
 for (int i=0; i<N; ++i)
 {
    sum += x[i]*y[i];
 }
 return sum;
}

int main()
{
  ...
  double s = scalar(n,a,b);
  ... 
}

OpenMP code for inner product:

double scalar(const unsigned int N, const double x[], const double y[])
{
    double sum = 0.0;
    unsigned int i;
    #pragma omp parallel for private(i) shared(x,y) schedule(static) reduction(+:sum)
    for (i = 0; i < N; ++i) {
        sum += x[i] * y[i];
    }
    return sum;
}


int main(int argc, char **argv)
{
  ...
  {
   double s = scalar(N, x, y);
  }
  ...
}

and compile the code with one of the available compilers

g++ -fopenmp skalar.cpp
icpc -qopenmp skalar.cpp (also possible: icpc -fopenmp skalar.cpp )
pgc++ -mp skalar.cpp
clang++ -fopenmp skalar.cpp