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- //---------------------------------------------------------------------------//
- // Copyright (c) 2016 Jakub Szuppe <j.szuppe@gmail.com>
- //
- // 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_DETAIL_REDUCE_ON_CPU_HPP
- #define BOOST_COMPUTE_ALGORITHM_DETAIL_REDUCE_ON_CPU_HPP
- #include <algorithm>
- #include <boost/compute/buffer.hpp>
- #include <boost/compute/command_queue.hpp>
- #include <boost/compute/detail/meta_kernel.hpp>
- #include <boost/compute/detail/iterator_range_size.hpp>
- #include <boost/compute/detail/parameter_cache.hpp>
- #include <boost/compute/iterator/buffer_iterator.hpp>
- #include <boost/compute/type_traits/result_of.hpp>
- #include <boost/compute/algorithm/detail/serial_reduce.hpp>
- namespace boost {
- namespace compute {
- namespace detail {
- template<class InputIterator, class OutputIterator, class BinaryFunction>
- inline void reduce_on_cpu(InputIterator first,
- InputIterator last,
- OutputIterator result,
- BinaryFunction function,
- command_queue &queue)
- {
- typedef typename
- std::iterator_traits<InputIterator>::value_type T;
- typedef typename
- ::boost::compute::result_of<BinaryFunction(T, T)>::type result_type;
- const device &device = queue.get_device();
- const uint_ compute_units = queue.get_device().compute_units();
- boost::shared_ptr<parameter_cache> parameters =
- detail::parameter_cache::get_global_cache(device);
- std::string cache_key =
- "__boost_reduce_cpu_" + boost::lexical_cast<std::string>(sizeof(T));
- // for inputs smaller than serial_reduce_threshold
- // serial_reduce algorithm is used
- uint_ serial_reduce_threshold =
- parameters->get(cache_key, "serial_reduce_threshold", 16384 * sizeof(T));
- serial_reduce_threshold =
- (std::max)(serial_reduce_threshold, uint_(compute_units));
- const context &context = queue.get_context();
- size_t count = detail::iterator_range_size(first, last);
- if(count == 0){
- return;
- }
- else if(count < serial_reduce_threshold) {
- return serial_reduce(first, last, result, function, queue);
- }
- meta_kernel k("reduce_on_cpu");
- buffer output(context, sizeof(result_type) * compute_units);
- size_t count_arg = k.add_arg<uint_>("count");
- size_t output_arg =
- k.add_arg<result_type *>(memory_object::global_memory, "output");
- k <<
- "uint block = " <<
- "(uint)ceil(((float)count)/get_global_size(0));\n" <<
- "uint index = get_global_id(0) * block;\n" <<
- "uint end = min(count, index + block);\n" <<
- k.decl<result_type>("result") << " = " << first[k.var<uint_>("index")] << ";\n" <<
- "index++;\n" <<
- "while(index < end){\n" <<
- "result = " << function(k.var<T>("result"),
- first[k.var<uint_>("index")]) << ";\n" <<
- "index++;\n" <<
- "}\n" <<
- "output[get_global_id(0)] = result;\n";
- size_t global_work_size = compute_units;
- kernel kernel = k.compile(context);
- // reduction to global_work_size elements
- kernel.set_arg(count_arg, static_cast<uint_>(count));
- kernel.set_arg(output_arg, output);
- queue.enqueue_1d_range_kernel(kernel, 0, global_work_size, 0);
- // final reduction
- reduce_on_cpu(
- make_buffer_iterator<result_type>(output),
- make_buffer_iterator<result_type>(output, global_work_size),
- result,
- function,
- queue
- );
- }
- } // end detail namespace
- } // end compute namespace
- } // end boost namespace
- #endif // BOOST_COMPUTE_ALGORITHM_DETAIL_REDUCE_ON_CPU_HPP
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