/****************************************************************************** * Copyright (c) 2010-2011, Duane Merrill. All rights reserved. * Copyright (c) 2011-2018, NVIDIA CORPORATION. All rights reserved. * Modifications Copyright (c) 2017-2020, Advanced Micro Devices, Inc. All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are met: * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of the NVIDIA CORPORATION nor the * names of its contributors may be used to endorse or promote products * derived from this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE * DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY * DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * ******************************************************************************/ #ifndef HIPCUB_ROCPRIM_DEVICE_DEVICE_SEGMENTED_REDUCE_HPP_ #define HIPCUB_ROCPRIM_DEVICE_DEVICE_SEGMENTED_REDUCE_HPP_ #include #include #include "../config.hpp" #include "../thread/thread_operators.cuh" #include "../iterator/arg_index_input_iterator.cuh" #include BEGIN_HIPCUB_NAMESPACE struct DeviceSegmentedReduce { template< typename InputIteratorT, typename OutputIteratorT, typename OffsetIteratorT, typename ReductionOp, typename T > HIPCUB_RUNTIME_FUNCTION static cudaError_t Reduce(void * d_temp_storage, size_t& temp_storage_bytes, InputIteratorT d_in, OutputIteratorT d_out, int num_segments, OffsetIteratorT d_begin_offsets, OffsetIteratorT d_end_offsets, ReductionOp reduction_op, T initial_value, cudaStream_t stream = 0, bool debug_synchronous = false) { return (cudaError_t)::rocprim::segmented_reduce( d_temp_storage, temp_storage_bytes, d_in, d_out, num_segments, d_begin_offsets, d_end_offsets, ::cub::detail::convert_result_type(reduction_op), initial_value, stream, debug_synchronous ); } template< typename InputIteratorT, typename OutputIteratorT, typename OffsetIteratorT > HIPCUB_RUNTIME_FUNCTION static cudaError_t Sum(void * d_temp_storage, size_t& temp_storage_bytes, InputIteratorT d_in, OutputIteratorT d_out, int num_segments, OffsetIteratorT d_begin_offsets, OffsetIteratorT d_end_offsets, cudaStream_t stream = 0, bool debug_synchronous = false) { using input_type = typename std::iterator_traits::value_type; return Reduce( d_temp_storage, temp_storage_bytes, d_in, d_out, num_segments, d_begin_offsets, d_end_offsets, ::cub::Sum(), input_type(), stream, debug_synchronous ); } template< typename InputIteratorT, typename OutputIteratorT, typename OffsetIteratorT > HIPCUB_RUNTIME_FUNCTION static cudaError_t Min(void * d_temp_storage, size_t& temp_storage_bytes, InputIteratorT d_in, OutputIteratorT d_out, int num_segments, OffsetIteratorT d_begin_offsets, OffsetIteratorT d_end_offsets, cudaStream_t stream = 0, bool debug_synchronous = false) { using input_type = typename std::iterator_traits::value_type; return Reduce( d_temp_storage, temp_storage_bytes, d_in, d_out, num_segments, d_begin_offsets, d_end_offsets, ::cub::Min(), std::numeric_limits::max(), stream, debug_synchronous ); } template< typename InputIteratorT, typename OutputIteratorT, typename OffsetIteratorT > HIPCUB_RUNTIME_FUNCTION static cudaError_t ArgMin(void * d_temp_storage, size_t& temp_storage_bytes, InputIteratorT d_in, OutputIteratorT d_out, int num_segments, OffsetIteratorT d_begin_offsets, OffsetIteratorT d_end_offsets, cudaStream_t stream = 0, bool debug_synchronous = false) { using OffsetT = int; using T = typename std::iterator_traits::value_type; using O = typename std::iterator_traits::value_type; using OutputTupleT = typename std::conditional< std::is_same::value, KeyValuePair, O >::type; using OutputValueT = typename OutputTupleT::Value; using IteratorT = ArgIndexInputIterator; IteratorT d_indexed_in(d_in); const OutputTupleT init(1, std::numeric_limits::max()); return Reduce( d_temp_storage, temp_storage_bytes, d_indexed_in, d_out, num_segments, d_begin_offsets, d_end_offsets, ::cub::ArgMin(), init, stream, debug_synchronous ); } template< typename InputIteratorT, typename OutputIteratorT, typename OffsetIteratorT > HIPCUB_RUNTIME_FUNCTION static cudaError_t Max(void * d_temp_storage, size_t& temp_storage_bytes, InputIteratorT d_in, OutputIteratorT d_out, int num_segments, OffsetIteratorT d_begin_offsets, OffsetIteratorT d_end_offsets, cudaStream_t stream = 0, bool debug_synchronous = false) { using input_type = typename std::iterator_traits::value_type; return Reduce( d_temp_storage, temp_storage_bytes, d_in, d_out, num_segments, d_begin_offsets, d_end_offsets, ::cub::Max(), std::numeric_limits::lowest(), stream, debug_synchronous ); } template< typename InputIteratorT, typename OutputIteratorT, typename OffsetIteratorT > HIPCUB_RUNTIME_FUNCTION static cudaError_t ArgMax(void * d_temp_storage, size_t& temp_storage_bytes, InputIteratorT d_in, OutputIteratorT d_out, int num_segments, OffsetIteratorT d_begin_offsets, OffsetIteratorT d_end_offsets, cudaStream_t stream = 0, bool debug_synchronous = false) { using OffsetT = int; using T = typename std::iterator_traits::value_type; using O = typename std::iterator_traits::value_type; using OutputTupleT = typename std::conditional< std::is_same::value, KeyValuePair, O >::type; using OutputValueT = typename OutputTupleT::Value; using IteratorT = ArgIndexInputIterator; IteratorT d_indexed_in(d_in); const OutputTupleT init(1, std::numeric_limits::lowest()); return Reduce( d_temp_storage, temp_storage_bytes, d_indexed_in, d_out, num_segments, d_begin_offsets, d_end_offsets, ::cub::ArgMax(), init, stream, debug_synchronous ); } }; END_HIPCUB_NAMESPACE #endif // HIPCUB_ROCPRIM_DEVICE_DEVICE_SEGMENTED_REDUCE_HPP_