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//---------------------------------------------------------------------------// // Copyright (c) 2013 Kyle Lutz // // Distributed under the Boost Software License, Version 1.0 // See accompanying file LICENSE_1_0.txt or copy at // http://www.boost.org/LICENSE_1_0.txt // // See http://boostorg.github.com/compute for more information. //---------------------------------------------------------------------------// #ifndef BOOST_COMPUTE_ALGORITHM_ACCUMULATE_HPP #define BOOST_COMPUTE_ALGORITHM_ACCUMULATE_HPP #include #include #include #include #include #include #include #include #include #include #include namespace boost { namespace compute { namespace detail { // Space complexity O(1) template inline T generic_accumulate(InputIterator first, InputIterator last, T init, BinaryFunction function, command_queue &queue) { const context &context = queue.get_context(); size_t size = iterator_range_size(first, last); if(size == 0){ return init; } // accumulate on device array device_result(context); detail::serial_accumulate( first, last, device_result.begin(), init, function, queue ); // copy result to host T result; ::boost::compute::copy_n(device_result.begin(), 1, &result, queue); return result; } // returns true if we can use reduce() instead of accumulate() when // accumulate() this is true when the function is commutative (such as // addition of integers) and the initial value is the identity value // for the operation (zero for addition, one for multiplication). template inline bool can_accumulate_with_reduce(T init, F function) { (void) init; (void) function; return false; } /// \internal_ #define BOOST_COMPUTE_DETAIL_DECLARE_CAN_ACCUMULATE_WITH_REDUCE(r, data, type) \ inline bool can_accumulate_with_reduce(type init, plus) \ { \ return init == type(0); \ } \ inline bool can_accumulate_with_reduce(type init, multiplies) \ { \ return init == type(1); \ } BOOST_PP_SEQ_FOR_EACH( BOOST_COMPUTE_DETAIL_DECLARE_CAN_ACCUMULATE_WITH_REDUCE, _, (char_)(uchar_)(short_)(ushort_)(int_)(uint_)(long_)(ulong_) ) template inline bool can_accumulate_with_reduce(T init, min) { return init == (std::numeric_limits::max)(); } template inline bool can_accumulate_with_reduce(T init, max) { return init == (std::numeric_limits::min)(); } #undef BOOST_COMPUTE_DETAIL_DECLARE_CAN_ACCUMULATE_WITH_REDUCE template inline T dispatch_accumulate(InputIterator first, InputIterator last, T init, BinaryFunction function, command_queue &queue) { size_t size = iterator_range_size(first, last); if(size == 0){ return init; } if(can_accumulate_with_reduce(init, function)){ T result; reduce(first, last, &result, function, queue); return result; } else { return generic_accumulate(first, last, init, function, queue); } } } // end detail namespace /// Returns the result of applying \p function to the elements in the /// range [\p first, \p last) and \p init. /// /// If no function is specified, \c plus will be used. /// /// \param first first element in the input range /// \param last last element in the input range /// \param init initial value /// \param function binary reduction function /// \param queue command queue to perform the operation /// /// \return the accumulated result value /// /// In specific situations the call to \c accumulate() can be automatically /// optimized to a call to the more efficient \c reduce() algorithm. This /// occurs when the binary reduction function is recognized as associative /// (such as the \c plus function). /// /// Note that because floating-point addition is not associative, calling /// \c accumulate() with \c plus results in a less efficient serial /// reduction algorithm being executed. If a slight loss in precision is /// acceptable, the more efficient parallel \c reduce() algorithm should be /// used instead. /// /// For example: /// \code /// // with vec = boost::compute::vector /// accumulate(vec.begin(), vec.end(), 0, plus()); // fast /// reduce(vec.begin(), vec.end(), &result, plus()); // fast /// /// // with vec = boost::compute::vector /// accumulate(vec.begin(), vec.end(), 0, plus()); // slow /// reduce(vec.begin(), vec.end(), &result, plus()); // fast /// \endcode /// /// Space complexity: \Omega(1)
/// Space complexity when optimized to \c reduce(): \Omega(n) /// /// \see reduce() template inline T accumulate(InputIterator first, InputIterator last, T init, BinaryFunction function, command_queue &queue = system::default_queue()) { BOOST_STATIC_ASSERT(is_device_iterator::value); return detail::dispatch_accumulate(first, last, init, function, queue); } /// \overload template inline T accumulate(InputIterator first, InputIterator last, T init, command_queue &queue = system::default_queue()) { BOOST_STATIC_ASSERT(is_device_iterator::value); typedef typename std::iterator_traits::value_type IT; return detail::dispatch_accumulate(first, last, init, plus(), queue); } } // end compute namespace } // end boost namespace #endif // BOOST_COMPUTE_ALGORITHM_ACCUMULATE_HPP