I already have intel basekit installed, and eclipse for C / C ++: (eclipse-inst-jre-linux64.tar.gz), but I can't find a way to run a simple example using openmp. In the terminal I compile my example with:
icpx -fiopenmp -fopenmp-targets = spir64 random_openmp.cpp
but I can't do the same using eclipse. Please find the example code below:
# include <iostream>
# include <iomanip>
# include <cmath>
# include <ctime>
# include <omp.h>
using namespace std;
int main ( );
void monte_carlo ( int n, int &seed );
double random_value ( int &seed );
void timestamp ( );
/******************************************************************************/
int main ( void )
/******************************************************************************/
/*
Purpose:
MAIN is the main program for RANDOM_OPENMP.
Discussion:
This program simply explores one issue in the generation of random
numbers in a parallel program. If the random number generator uses
an integer seed to determine the next entry, then it is not easy for
a parallel program to reproduce the same exact sequence.
But what is worse is that it might not be clear how the separate
OpenMP threads should handle the SEED value - as a shared or private
variable? It seems clear that each thread should have a private
seed that is initialized to a distinct value at the beginning of
the computation.
Licensing:
This code is distributed under the GNU LGPL license.
Modified:
03 September 2012
Author:
John Burkardt
*/
{
int n;
int seed;
timestamp ( );
cout << "\n";
cout << "RANDOM_OPENMP\n";
cout << " C++ version\n";
cout << " An OpenMP program using random numbers.\n";
cout << " The random numbers depend on a seed.\n";
cout << " We need to insure that each OpenMP thread\n";
cout << " starts with a different seed.\n";
cout << "\n";
cout << " Number of processors available = " << omp_get_num_procs ( ) << "\n";
cout << " Number of threads = " << omp_get_max_threads ( ) << "\n";
n = 100;
seed = 123456789;
monte_carlo ( n, seed );
/*
Terminate.
*/
cout << "\n";
cout << "RANDOM_OPENMP\n";
cout << " Normal end of execution.\n";
cout << "\n";
timestamp ( );
return 0;
}
/******************************************************************************/
void monte_carlo ( int n, int &seed )
/******************************************************************************/
/*
Purpose:
MONTE_CARLO carries out a Monte Carlo calculation with random values.
Licensing:
This code is distributed under the GNU LGPL license.
Modified:
03 September 2012
Author:
John Burkardt
Parameter:
Input, int N, the number of values to generate.
Input, int &SEED, a seed for the random number generator.
*/
{
int i;
int my_id;
int *my_id_vec;
int my_seed;
int *my_seed_vec;
double *x;
x = new double[n];
my_id_vec = new int[n];
my_seed_vec = new int[n];
# pragma omp master
{
cout << "\n";
cout << " Thread Seed I X(I)\n";
cout << "\n";
}
# pragma omp parallel private ( i, my_id, my_seed ) shared ( my_id_vec, my_seed_vec, n, x )
{
my_id = omp_get_thread_num ( );
my_seed = seed + my_id;
cout << " " << setw(6) << my_id
<< " " << setw(12) << my_seed << "\n";
# pragma omp for
for ( i = 0; i < n; i++ )
{
my_id_vec[i] = my_id;
x[i] = random_value ( my_seed );
my_seed_vec[i] = my_seed;
// cout << " " << setw(6) << my_id
// << " " << setw(12) << my_seed
// << " " << setw(6) << i
// << " " << setw(14) << x[i] << "\n";
}
}
//
// C++ OpenMP IO from multiple processors comes out chaotically.
// For this reason only, we'll save the data from the loop and
// print it in the sequential section!
//
for ( i = 0; i < n; i++ )
{
cout << " " << setw(6) << my_id_vec[i]
<< " " << setw(12) << my_seed_vec[i]
<< " " << setw(6) << i
<< " " << setw(14) << x[i] << "\n";
}
delete [] my_id_vec;
delete [] my_seed_vec;
delete [] x;
return;
}
/******************************************************************************/
double random_value ( int &seed )
/******************************************************************************/
/*
Purpose:
RANDOM_VALUE generates a random value R.
Discussion:
This is not a good random number generator. It is a SIMPLE one.
It illustrates a model which works by accepting an integer seed value
as input, performing some simple operation on the seed, and then
producing a "random" real value using some simple transformation.
Licensing:
This code is distributed under the GNU LGPL license.
Modified:
03 September 2012
Author:
John Burkardt
Parameters:
Input/output, int &SEED, a seed for the random
number generator.
Output, double RANDOM_VALUE, the random value.
*/
{
double r;
seed = ( seed % 65536 );
seed = ( ( 3125 * seed ) % 65536 );
r = ( double ) ( seed ) / 65536.0;
return r;
}
//****************************************************************************80
void timestamp ( )
//****************************************************************************80
//
// Purpose:
//
// TIMESTAMP prints the current YMDHMS date as a time stamp.
//
// Example:
//
// 31 May 2001 09:45:54 AM
//
// Modified:
//
// 24 September 2003
//
// Author:
//
// John Burkardt
//
// Parameters:
//
// None
//
{
# define TIME_SIZE 40
static char time_buffer[TIME_SIZE];
const struct tm *tm;
time_t now;
now = time ( NULL );
tm = localtime ( &now );
strftime ( time_buffer, TIME_SIZE, "%d %B %Y %I:%M:%S %p", tm );
cout << time_buffer << "\n";
return;
# undef TIME_SIZE
}
