// $Id: simple_ad_openmp.cpp 3757 2015-11-30 12:03:07Z bradbell $
/* --------------------------------------------------------------------------
CppAD: C++ Algorithmic Differentiation: Copyright (C) 2003-15 Bradley M. Bell

CppAD is distributed under multiple licenses. This distribution is under
the terms of the
                    GNU General Public License Version 3.

A copy of this license is included in the COPYING file of this distribution.
Please visit http://www.coin-or.org/CppAD/ for information on other licenses.
-------------------------------------------------------------------------- */

/*
$begin simple_ad_openmp.cpp$$
$spell
	openmp
	CppAD
$$

$section A Simple OpenMP AD: Example and Test$$
$mindex AD$$


$head Purpose$$
This example demonstrates how CppAD can be used in a
OpenMP multi-threading environment.

$head Source Code$$
$code
$verbatim%multi_thread/openmp/simple_ad_openmp.cpp%0%// BEGIN C++%// END C++%1%$$
$$

$end
------------------------------------------------------------------------------
*/
// BEGIN C++
# include <cppad/cppad.hpp>
# include <omp.h>
# define NUMBER_THREADS  4

namespace {
	// structure with problem specific information
	typedef struct {
		// function argument (worker input)
		double          x;
		// This structure would also have return information in it,
		// but this example only returns the ok flag
	} problem_specific;
	// =====================================================================
	// General purpose code you can copy to your application
	// =====================================================================
	using CppAD::thread_alloc;
	// ------------------------------------------------------------------
	// used to inform CppAD when we are in parallel execution mode
	bool in_parallel(void)
	{	return omp_in_parallel() != 0; }
	// ------------------------------------------------------------------
	// used to inform CppAD of the current thread number
	size_t thread_number(void)
	{	return static_cast<size_t>( omp_get_thread_num() ); }
	// ------------------------------------------------------------------
	// structure with information for one thread
	typedef struct {
		// false if an error occurs, true otherwise (worker output)
		bool               ok;
	} thread_one_t;
	// vector with information for all threads
	thread_one_t thread_all_[NUMBER_THREADS];
	// ------------------------------------------------------------------
	// function that calls all the workers
	bool worker(problem_specific* info);
	bool run_all_workers(size_t num_threads, problem_specific* info_all[])
	{	bool ok = true;

		// initialize thread_all_
		int thread_num, int_num_threads = int(num_threads);
		for(thread_num = 0; thread_num < int_num_threads; thread_num++)
		{	// initialize as false to make sure gets called for all threads
			thread_all_[thread_num].ok         = false;
		}

		// turn off dynamic thread adjustment
		omp_set_dynamic(0);

		// set the number of OpenMP threads
		omp_set_num_threads( int_num_threads );

		// setup for using CppAD::AD<double> in parallel
		thread_alloc::parallel_setup(
			num_threads, in_parallel, thread_number
		);
		thread_alloc::hold_memory(true);
		CppAD::parallel_ad<double>();

		// execute worker in parallel
# pragma omp parallel for
	for(thread_num = 0; thread_num < int_num_threads; thread_num++)
		thread_all_[thread_num].ok = worker(info_all[thread_num]);
// end omp parallel for

		// set the number of OpenMP threads to one
		omp_set_num_threads(1);

		// now inform CppAD that there is only one thread
		thread_alloc::parallel_setup(1, CPPAD_NULL, CPPAD_NULL);
		thread_alloc::hold_memory(false);
		CppAD::parallel_ad<double>();

		// check to ok flag returned by during calls to work by other threads
		for(thread_num = 1; thread_num < int_num_threads; thread_num++)
			ok &= thread_all_[thread_num].ok;

		return ok;
	}
	// =====================================================================
	// End of General purpose code
	// =====================================================================
	// function that does the work for one thread
	bool worker(problem_specific* info)
	{	using CppAD::NearEqual;
		using CppAD::AD;
		bool ok = true;

		// CppAD::vector uses the CppAD fast multi-threading allocator
		CppAD::vector< AD<double> > ax(1), ay(1);
		ax[0] = info->x;
		Independent(ax);
		ay[0] = sqrt( ax[0] * ax[0] );
		CppAD::ADFun<double> f(ax, ay);

		// Check function value corresponds to the identity
		double eps = 10. * CppAD::numeric_limits<double>::epsilon();
		ok        &= NearEqual(ay[0], ax[0], eps, eps);

		// Check derivative value corresponds to the identity.
		CppAD::vector<double> d_x(1), d_y(1);
		d_x[0] = 1.;
		d_y    = f.Forward(1, d_x);
		ok    &= NearEqual(d_x[0], 1., eps, eps);

		return ok;
	}
}
bool simple_ad(void)
{	bool ok = true;
	size_t num_threads = NUMBER_THREADS;

	// Check that no memory is in use or avialable at start
	// (using thread_alloc in sequential mode)
	size_t thread_num;
	for(thread_num = 0; thread_num < num_threads; thread_num++)
	{	ok &= thread_alloc::inuse(thread_num) == 0;
		ok &= thread_alloc::available(thread_num) == 0;
	}

	// initialize info_all
	problem_specific *info, *info_all[NUMBER_THREADS];
	for(thread_num = 0; thread_num < num_threads; thread_num++)
	{	// problem specific information
		size_t min_bytes(sizeof(info)), cap_bytes;
		void*  v_ptr = thread_alloc::get_memory(min_bytes, cap_bytes);
		info         = static_cast<problem_specific*>(v_ptr);
		info->x      = double(thread_num) + 1.;
		info_all[thread_num] = info;
	}

	ok &= run_all_workers(num_threads, info_all);

	// go down so that free memory for other threads before memory for master
	thread_num = num_threads;
	while(thread_num--)
	{	// delete problem specific information
		void* v_ptr = static_cast<void*>( info_all[thread_num] );
		thread_alloc::return_memory( v_ptr );
		// check that there is no longer any memory inuse by this thread
		ok &= thread_alloc::inuse(thread_num) == 0;
		// return all memory being held for future use by this thread
		thread_alloc::free_available(thread_num);
	}

	return ok;
}
// END C++
