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198 lines
8.0 KiB
198 lines
8.0 KiB
11 years ago
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/*
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* Copyright 2008-2012 NVIDIA Corporation
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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/*! \file transform_reduce.h
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* \brief Fused transform / reduction
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*/
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#pragma once
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#include <thrust/detail/config.h>
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#include <thrust/detail/execution_policy.h>
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namespace thrust
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{
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/*! \addtogroup reductions
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* \{
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* \addtogroup transformed_reductions Transformed Reductions
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* \ingroup reductions
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* \{
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*/
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/*! \p transform_reduce fuses the \p transform and \p reduce operations.
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* \p transform_reduce is equivalent to performing a transformation defined by
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* \p unary_op into a temporary sequence and then performing \p reduce on the
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* transformed sequence. In most cases, fusing these two operations together is
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* more efficient, since fewer memory reads and writes are required.
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*
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* \p transform_reduce performs a reduction on the transformation of the
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* sequence <tt>[first, last)</tt> according to \p unary_op. Specifically,
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* \p unary_op is applied to each element of the sequence and then the result
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* is reduced to a single value with \p binary_op using the initial value
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* \p init. Note that the transformation \p unary_op is not applied to
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* the initial value \p init. The order of reduction is not specified,
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* so \p binary_op must be both commutative and associative.
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*
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* The algorithm's execution is parallelized as determined by \p exec.
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*
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* \param exec The execution policy to use for parallelization.
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* \param first The beginning of the sequence.
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* \param last The end of the sequence.
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* \param unary_op The function to apply to each element of the input sequence.
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* \param init The result is initialized to this value.
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* \param binary_op The reduction operation.
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* \return The result of the transformed reduction.
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*
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* \tparam DerivedPolicy The name of the derived execution policy.
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* \tparam InputIterator is a model of <a href="http://www.sgi.com/tech/stl/InputIterator.html">Input Iterator</a>,
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* and \p InputIterator's \c value_type is convertible to \p UnaryFunction's \c argument_type.
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* \tparam UnaryFunction is a model of <a href="http://www.sgi.com/tech/stl/UnaryFunction.html">Unary Function</a>,
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* and \p UnaryFunction's \c result_type is convertible to \c OutputType.
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* \tparam OutputType is a model of <a href="http://www.sgi.com/tech/stl/Assignable.html">Assignable</a>,
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* and is convertible to \p BinaryFunction's \c first_argument_type and \c second_argument_type.
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* \tparam BinaryFunction is a model of <a href="http://www.sgi.com/tech/stl/BinaryFunction.html">Binary Function</a>,
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* and \p BinaryFunction's \c result_type is convertible to \p OutputType.
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*
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* The following code snippet demonstrates how to use \p transform_reduce
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* to compute the maximum value of the absolute value of the elements
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* of a range using the \p thrust::host execution policy for parallelization:
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*
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* \code
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* #include <thrust/transform_reduce.h>
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* #include <thrust/functional.h>
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* #include <thrust/execution_policy.h>
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*
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* template<typename T>
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* struct absolute_value : public unary_function<T,T>
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* {
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* __host__ __device__ T operator()(const T &x) const
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* {
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* return x < T(0) ? -x : x;
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* }
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* };
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*
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* ...
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*
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* int data[6] = {-1, 0, -2, -2, 1, -3};
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* int result = thrust::transform_reduce(thrust::host,
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* data, data + 6,
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* absolute_value<int>(),
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* 0,
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* thrust::maximum<int>());
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* // result == 3
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* \endcode
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*
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* \see \c transform
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* \see \c reduce
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*/
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template<typename DerivedPolicy,
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typename InputIterator,
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typename UnaryFunction,
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typename OutputType,
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typename BinaryFunction>
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OutputType transform_reduce(const thrust::detail::execution_policy_base<DerivedPolicy> &exec,
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InputIterator first,
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InputIterator last,
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UnaryFunction unary_op,
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OutputType init,
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BinaryFunction binary_op);
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/*! \p transform_reduce fuses the \p transform and \p reduce operations.
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* \p transform_reduce is equivalent to performing a transformation defined by
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* \p unary_op into a temporary sequence and then performing \p reduce on the
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* transformed sequence. In most cases, fusing these two operations together is
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* more efficient, since fewer memory reads and writes are required.
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|
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*
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* \p transform_reduce performs a reduction on the transformation of the
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* sequence <tt>[first, last)</tt> according to \p unary_op. Specifically,
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* \p unary_op is applied to each element of the sequence and then the result
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* is reduced to a single value with \p binary_op using the initial value
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* \p init. Note that the transformation \p unary_op is not applied to
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* the initial value \p init. The order of reduction is not specified,
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* so \p binary_op must be both commutative and associative.
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*
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* \param first The beginning of the sequence.
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* \param last The end of the sequence.
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* \param unary_op The function to apply to each element of the input sequence.
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* \param init The result is initialized to this value.
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* \param binary_op The reduction operation.
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* \return The result of the transformed reduction.
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*
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* \tparam InputIterator is a model of <a href="http://www.sgi.com/tech/stl/InputIterator.html">Input Iterator</a>,
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* and \p InputIterator's \c value_type is convertible to \p UnaryFunction's \c argument_type.
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* \tparam UnaryFunction is a model of <a href="http://www.sgi.com/tech/stl/UnaryFunction.html">Unary Function</a>,
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* and \p UnaryFunction's \c result_type is convertible to \c OutputType.
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* \tparam OutputType is a model of <a href="http://www.sgi.com/tech/stl/Assignable.html">Assignable</a>,
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* and is convertible to \p BinaryFunction's \c first_argument_type and \c second_argument_type.
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* \tparam BinaryFunction is a model of <a href="http://www.sgi.com/tech/stl/BinaryFunction.html">Binary Function</a>,
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* and \p BinaryFunction's \c result_type is convertible to \p OutputType.
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*
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* The following code snippet demonstrates how to use \p transform_reduce
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* to compute the maximum value of the absolute value of the elements
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* of a range.
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*
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* \code
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* #include <thrust/transform_reduce.h>
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* #include <thrust/functional.h>
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*
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* template<typename T>
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* struct absolute_value : public unary_function<T,T>
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* {
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* __host__ __device__ T operator()(const T &x) const
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* {
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* return x < T(0) ? -x : x;
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* }
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* };
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*
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* ...
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*
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* int data[6] = {-1, 0, -2, -2, 1, -3};
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* int result = thrust::transform_reduce(data, data + 6,
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* absolute_value<int>(),
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* 0,
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* thrust::maximum<int>());
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* // result == 3
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* \endcode
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*
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* \see \c transform
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* \see \c reduce
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*/
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template<typename InputIterator,
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typename UnaryFunction,
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typename OutputType,
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typename BinaryFunction>
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OutputType transform_reduce(InputIterator first,
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InputIterator last,
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UnaryFunction unary_op,
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OutputType init,
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BinaryFunction binary_op);
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/*! \} // end transformed_reductions
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* \} // end reductions
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*/
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} // end namespace thrust
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#include <thrust/detail/transform_reduce.inl>
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