OpenMP fundamentials

OpenMP is

The presentation can be downloaded here.

• An application programming interface (API) that supports shared-memory programming for C/C++ and Fortran
• Pros:
  • Simple
  • Cross-platform
  • Small overhead
  • Data parallelism support

Usage

Compiler directives:

C/C++

#pragma omp directive [clause, …]

Fortran

!$OMP directive [clause, …]
C$OMP directive [clause, …]
*$OMP directive [clause, …]

Parallel execution

Parallel Regions

Main OpenMP directive

#pragma omp parallel

#pragma omp parallel
{
  printf( "hello world from thread %d of %d\n",
    omp_get_thread_num(),
    omp_get_num_threads() );
}

Параллельное исполнение

• Most of the OpenMP instructions are preprocessor directives
• Main construction is "omp parallel [smth]"

Рис. 7.1.

OpenMP parallel model

• Memory is shared
• Task is divided into the threads
  • Variables can be
    • shared by the threads
    • private, available only for one thread
• Uncareful or wrong variable usage can lead to wrong execution results.

Fork-join model

• Program execution starts from the master thread
• With OpenMP directive master thread creates the additional threads
• After the parallel region is finished all threads are synchronized
• Main thread continues to execute the sequential part

Рис. 7.2.

Основные конструкции OpenMP

• #pragma omp for Each thread gets its own amount of data – data parallelism
• #pragma omp section Each section will be executed in a separate thread – functional parallelism
• #pragma omp single Sequential execution. Only one thread will execute this code

OpenMP sections

#pragma omp sections [ clause [ clause ] ... ] new-line
{
[#pragma omp section new-line ]
structured-block1
[#pragma omp section new-line
structured-block2 ]
}

Functional Parallelism

#pragma omp parallel
#pragma omp sections nowait 
{
  thread1_work();
#pragma omp section
  thread2_work();
#pragma omp section
  thread3_work();
#pragma omp section
  thread4_work(); 
}