- So in essence, an OpenMP program is nothing more than a
multi-threaded program that you have seen
when we discussed pthreads
- Just like in pthreads, there are 2 different kinds
of variables:
- Shared variables
where a single copy of the variable exists
and all threads access that single copy
- Private variables where a copy exists for each thread and each thread accesses its own copy of that variable.
- Shared variables
where a single copy of the variable exists
and all threads access that single copy
- How to tell which variables are shared/private
- Variables
without any directives
that are
defined OUTSIDE the scope of a parallel region
but are visible
inside the scope
of a parallel region are
by default SHARED
- Variables without any directives that are defined INSIDE the scope of a parallel region are NON-SHARED (only possible is languages with scoping rules - C/C++)
- Variables
without any directives
that are
defined OUTSIDE the scope of a parallel region
but are visible
inside the scope
of a parallel region are
by default SHARED
- C/C++ example of SHARED variable:
-
Example Program:
(Shared variable in OpenMP) ---
click here
- Compile with: g++ -fopenmp openMP02a.C
- Run with: export OMP_NUM_THREADS=8; a.out (make sure you run on compute.mathcs.emory.edu - an 8-way multi-processor)
You should see the value for N at the end is not always 1009, it could be less. You have seen this phenomenon before in threaded programs when multiple-threads update a shared variable concurrently... The same things is happening here.
#include <omp.h> int main(int argc, char *argv[]) { int N; // Variable defined OUTSIDE parallel region.... // It is therefore SHARED N = 0; #pragma omp parallel { int i; for ( i = 0; i < 10000; i++ ) N = N + 1; cout << "N = " << N << endl; } }
-
Example Program:
(Shared variable in OpenMP) ---
click here
- C/C++ example of NON-SHARED (private) variable:
-
Example Program:
(Shared variable in OpenMP) ---
click here
- Compile with: g++ -fopenmp openMP02b.C
- Run with: export OMP_NUM_THREADS=8; a.out (make sure you run on compute.mathcs.emory.edu - an 8-way multi-processor)
#include <omp.h> int main(int argc, char *argv[]) { #pragma omp parallel { int N = 0; // Variable defined INSIDE parallel region.... // It is therefore NON-SHARED int i; for ( i = 0; i < 10000; i++ ) N = N + 1; cout << "N = " << N << endl; } // ERROR if you try to do this: // cout << "N = " << N << endl; // because N is not defined in the outer scope !!! } -
Example Program:
(Shared variable in OpenMP) ---
click here