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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#ifndef BOOST_COMPUTE_RANDOM_LINEAR_CONGRUENTIAL_ENGINE_HPP
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#define BOOST_COMPUTE_RANDOM_LINEAR_CONGRUENTIAL_ENGINE_HPP
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#include <algorithm>
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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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namespace boost {
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namespace compute {
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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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    /// 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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        // seed state
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        seed(value, queue);
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        // generate multiplicands
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        generate_multiplicands(queue);
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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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    /// 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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        return *this;
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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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    /// 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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        m_seed = value;
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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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    /// 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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        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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        size_t offset = 0;
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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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            offset += count;
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            if(offset >= size){
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                break;
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            }
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            update_seed(queue);
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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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        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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    /// 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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    /// 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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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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        queue.enqueue_task(multiplicand_kernel);
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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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    /// \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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        std::string cache_key =
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            std::string("__boost_linear_congruential_engine_") + type_name<T>();
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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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            "__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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        m_program = cache->get_or_build(cache_key, std::string(), source, m_context);
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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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} // end compute namespace
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} // end boost namespace
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#endif // BOOST_COMPUTE_RANDOM_LINEAR_CONGRUENTIAL_ENGINE_HPP
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