ecency-mobile/ios/Pods/boost-for-react-native/boost/compute/algorithm/accumulate.hpp

185 lines
6.1 KiB
C++

//---------------------------------------------------------------------------//
// Copyright (c) 2013 Kyle Lutz <kyle.r.lutz@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_ACCUMULATE_HPP
#define BOOST_COMPUTE_ALGORITHM_ACCUMULATE_HPP
#include <boost/preprocessor/seq/for_each.hpp>
#include <boost/compute/system.hpp>
#include <boost/compute/functional.hpp>
#include <boost/compute/command_queue.hpp>
#include <boost/compute/algorithm/reduce.hpp>
#include <boost/compute/algorithm/detail/serial_accumulate.hpp>
#include <boost/compute/container/array.hpp>
#include <boost/compute/container/vector.hpp>
#include <boost/compute/detail/iterator_range_size.hpp>
namespace boost {
namespace compute {
namespace detail {
template<class InputIterator, class T, class BinaryFunction>
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<T, 1> 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<class T, class F>
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<type>) \
{ \
return init == type(0); \
} \
inline bool can_accumulate_with_reduce(type init, multiplies<type>) \
{ \
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<class T>
inline bool can_accumulate_with_reduce(T init, min<T>)
{
return init == (std::numeric_limits<T>::max)();
}
template<class T>
inline bool can_accumulate_with_reduce(T init, max<T>)
{
return init == (std::numeric_limits<T>::min)();
}
#undef BOOST_COMPUTE_DETAIL_DECLARE_CAN_ACCUMULATE_WITH_REDUCE
template<class InputIterator, class T, class BinaryFunction>
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<int> function).
///
/// Note that because floating-point addition is not associative, calling
/// \c accumulate() with \c plus<float> 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<int>
/// accumulate(vec.begin(), vec.end(), 0, plus<int>()); // fast
/// reduce(vec.begin(), vec.end(), &result, plus<int>()); // fast
///
/// // with vec = boost::compute::vector<float>
/// accumulate(vec.begin(), vec.end(), 0, plus<float>()); // slow
/// reduce(vec.begin(), vec.end(), &result, plus<float>()); // fast
/// \endcode
///
/// \see reduce()
template<class InputIterator, class T, class BinaryFunction>
inline T accumulate(InputIterator first,
InputIterator last,
T init,
BinaryFunction function,
command_queue &queue = system::default_queue())
{
return detail::dispatch_accumulate(first, last, init, function, queue);
}
/// \overload
template<class InputIterator, class T>
inline T accumulate(InputIterator first,
InputIterator last,
T init,
command_queue &queue = system::default_queue())
{
typedef typename std::iterator_traits<InputIterator>::value_type IT;
return detail::dispatch_accumulate(first, last, init, plus<IT>(), queue);
}
} // end compute namespace
} // end boost namespace
#endif // BOOST_COMPUTE_ALGORITHM_ACCUMULATE_HPP