239 lines
		
	
	
		
			7.6 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
			
		
		
	
	
			239 lines
		
	
	
		
			7.6 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
| //---------------------------------------------------------------------------//
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| // Copyright (c) 2014 Roshan <thisisroshansmail@gmail.com>
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| //
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| // Distributed under the Boost Software License, Version 1.0
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| // See accompanying file LICENSE_1_0.txt or copy at
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| // http://www.boost.org/LICENSE_1_0.txt
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| //
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| // See http://boostorg.github.com/compute for more information.
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| //---------------------------------------------------------------------------//
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| 
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| #ifndef BOOST_COMPUTE_RANDOM_LINEAR_CONGRUENTIAL_ENGINE_HPP
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| #define BOOST_COMPUTE_RANDOM_LINEAR_CONGRUENTIAL_ENGINE_HPP
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| 
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| #include <algorithm>
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| 
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| #include <boost/compute/types.hpp>
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| #include <boost/compute/buffer.hpp>
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| #include <boost/compute/kernel.hpp>
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| #include <boost/compute/context.hpp>
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| #include <boost/compute/program.hpp>
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| #include <boost/compute/command_queue.hpp>
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| #include <boost/compute/algorithm/transform.hpp>
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| #include <boost/compute/container/vector.hpp>
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| #include <boost/compute/detail/iterator_range_size.hpp>
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| #include <boost/compute/iterator/discard_iterator.hpp>
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| #include <boost/compute/utility/program_cache.hpp>
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| 
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| namespace boost {
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| namespace compute {
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| 
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| ///
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| /// \class linear_congruential_engine
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| /// \brief 'Quick and Dirty' linear congruential engine
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| ///
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| /// Quick and dirty linear congruential engine to generate low quality
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| /// random numbers very quickly. For uses in which good quality of random
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| /// numbers is required(Monte-Carlo Simulations), use other engines like
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| /// Mersenne Twister instead.
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| ///
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| template<class T = uint_>
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| class linear_congruential_engine
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| {
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| public:
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|     typedef T result_type;
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|     static const T default_seed = 1;
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|     static const T a = 1099087573;
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|     static const size_t threads = 1024;
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| 
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|     /// Creates a new linear_congruential_engine and seeds it with \p value.
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|     explicit linear_congruential_engine(command_queue &queue,
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|                                         result_type value = default_seed)
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|         : m_context(queue.get_context()),
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|           m_multiplicands(m_context, threads * sizeof(result_type))
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|     {
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|         // setup program
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|         load_program();
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| 
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|         // seed state
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|         seed(value, queue);
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| 
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|         // generate multiplicands
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|         generate_multiplicands(queue);
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|     }
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| 
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|     /// Creates a new linear_congruential_engine object as a copy of \p other.
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|     linear_congruential_engine(const linear_congruential_engine<T> &other)
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|         : m_context(other.m_context),
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|           m_program(other.m_program),
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|           m_seed(other.m_seed),
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|           m_multiplicands(other.m_multiplicands)
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|     {
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|     }
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| 
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|     /// Copies \p other to \c *this.
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|     linear_congruential_engine<T>&
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|     operator=(const linear_congruential_engine<T> &other)
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|     {
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|         if(this != &other){
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|             m_context = other.m_context;
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|             m_program = other.m_program;
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|             m_seed = other.m_seed;
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|             m_multiplicands = other.m_multiplicands;
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|         }
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| 
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|         return *this;
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|     }
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| 
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|     /// Destroys the linear_congruential_engine object.
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|     ~linear_congruential_engine()
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|     {
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|     }
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| 
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|     /// Seeds the random number generator with \p value.
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|     ///
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|     /// \param value seed value for the random-number generator
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|     /// \param queue command queue to perform the operation
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|     ///
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|     /// If no seed value is provided, \c default_seed is used.
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|     void seed(result_type value, command_queue &queue)
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|     {
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|         (void) queue;
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| 
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|         m_seed = value;
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|     }
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| 
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|     /// \overload
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|     void seed(command_queue &queue)
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|     {
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|         seed(default_seed, queue);
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|     }
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| 
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|     /// Generates random numbers and stores them to the range [\p first, \p last).
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|     template<class OutputIterator>
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|     void generate(OutputIterator first, OutputIterator last, command_queue &queue)
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|     {
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|         size_t size = detail::iterator_range_size(first, last);
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| 
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|         kernel fill_kernel(m_program, "fill");
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|         fill_kernel.set_arg(1, m_multiplicands);
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|         fill_kernel.set_arg(2, first.get_buffer());
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| 
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|         size_t offset = 0;
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| 
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|         for(;;){
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|             size_t count = 0;
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|             if(size > threads){
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|                 count = (std::min)(static_cast<size_t>(threads), size - offset);
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|             }
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|             else {
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|                 count = size;
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|             }
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|             fill_kernel.set_arg(0, static_cast<const uint_>(m_seed));
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|             fill_kernel.set_arg(3, static_cast<const uint_>(offset));
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|             queue.enqueue_1d_range_kernel(fill_kernel, 0, count, 0);
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| 
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|             offset += count;
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| 
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|             if(offset >= size){
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|                 break;
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|             }
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| 
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|             update_seed(queue);
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|         }
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|     }
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| 
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|     /// \internal_
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|     void generate(discard_iterator first, discard_iterator last, command_queue &queue)
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|     {
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|         (void) queue;
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| 
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|         size_t size = detail::iterator_range_size(first, last);
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|         uint_ max_mult =
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|             detail::read_single_value<T>(m_multiplicands, threads-1, queue);
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|         while(size >= threads) {
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|             m_seed *= max_mult;
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|             size -= threads;
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|         }
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|         m_seed *=
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|             detail::read_single_value<T>(m_multiplicands, size-1, queue);
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|     }
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| 
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|     /// Generates random numbers, transforms them with \p op, and then stores
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|     /// them to the range [\p first, \p last).
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|     template<class OutputIterator, class Function>
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|     void generate(OutputIterator first, OutputIterator last, Function op, command_queue &queue)
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|     {
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|         vector<T> tmp(std::distance(first, last), queue.get_context());
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|         generate(tmp.begin(), tmp.end(), queue);
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|         transform(tmp.begin(), tmp.end(), first, op, queue);
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|     }
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| 
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|     /// Generates \p z random numbers and discards them.
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|     void discard(size_t z, command_queue &queue)
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|     {
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|         generate(discard_iterator(0), discard_iterator(z), queue);
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|     }
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| 
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| private:
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|     /// \internal_
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|     /// Generates the multiplicands for each thread
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|     void generate_multiplicands(command_queue &queue)
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|     {
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|         kernel multiplicand_kernel =
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|             m_program.create_kernel("multiplicand");
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|         multiplicand_kernel.set_arg(0, m_multiplicands);
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| 
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|         queue.enqueue_task(multiplicand_kernel);
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|     }
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| 
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|     /// \internal_
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|     void update_seed(command_queue &queue)
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|     {
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|         m_seed *=
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|             detail::read_single_value<T>(m_multiplicands, threads-1, queue);
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|     }
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| 
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|     /// \internal_
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|     void load_program()
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|     {
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|         boost::shared_ptr<program_cache> cache =
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|             program_cache::get_global_cache(m_context);
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| 
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|         std::string cache_key =
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|             std::string("__boost_linear_congruential_engine_") + type_name<T>();
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| 
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|         const char source[] =
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|             "__kernel void multiplicand(__global uint *multiplicands)\n"
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|             "{\n"
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|             "    uint a = 1099087573;\n"
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|             "    multiplicands[0] = a;\n"
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|             "    for(uint i = 1; i < 1024; i++){\n"
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|             "        multiplicands[i] = a * multiplicands[i-1];\n"
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|             "    }\n"
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|             "}\n"
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| 
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|             "__kernel void fill(const uint seed,\n"
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|             "                   __global uint *multiplicands,\n"
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|             "                   __global uint *result,"
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|             "                   const uint offset)\n"
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|             "{\n"
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|             "    const uint i = get_global_id(0);\n"
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|             "    result[offset+i] = seed * multiplicands[i];\n"
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|             "}\n";
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| 
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|         m_program = cache->get_or_build(cache_key, std::string(), source, m_context);
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|     }
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| 
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| private:
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|     context m_context;
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|     program m_program;
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|     T m_seed;
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|     buffer m_multiplicands;
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| };
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| 
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| } // end compute namespace
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| } // end boost namespace
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| 
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| #endif // BOOST_COMPUTE_RANDOM_LINEAR_CONGRUENTIAL_ENGINE_HPP
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