/****************************************************************************** * Copyright (c) 2011, Duane Merrill. All rights reserved. * Copyright (c) 2011-2018, NVIDIA CORPORATION. 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. * ******************************************************************************/ /** * \file * cub::DeviceSegmentedReduce provides device-wide, parallel operations for computing a batched reduction across multiple sequences of data items residing within device-accessible memory. */ #pragma once #include #include #include "../iterator/arg_index_input_iterator.cuh" #include "dispatch/dispatch_reduce.cuh" #include "dispatch/dispatch_reduce_by_key.cuh" #include "../util_type.cuh" #include "../util_namespace.cuh" /// Optional outer namespace(s) CUB_NS_PREFIX /// CUB namespace namespace cub { /** * \brief DeviceSegmentedReduce provides device-wide, parallel operations for computing a reduction across multiple sequences of data items residing within device-accessible memory. ![](reduce_logo.png) * \ingroup SegmentedModule * * \par Overview * A reduction (or fold) * uses a binary combining operator to compute a single aggregate from a sequence of input elements. * * \par Usage Considerations * \cdp_class{DeviceSegmentedReduce} * */ struct DeviceSegmentedReduce { /** * \brief Computes a device-wide segmented reduction using the specified binary \p reduction_op functor. * * \par * - Does not support binary reduction operators that are non-commutative. * - When input a contiguous sequence of segments, a single sequence * \p segment_offsets (of length num_segments+1) can be aliased * for both the \p d_begin_offsets and \p d_end_offsets parameters (where * the latter is specified as segment_offsets+1). * - \devicestorage * * \par Snippet * The code snippet below illustrates a custom min-reduction of a device vector of \p int data elements. * \par * \code * #include // or equivalently * * // CustomMin functor * struct CustomMin * { * template * CUB_RUNTIME_FUNCTION __forceinline__ * T operator()(const T &a, const T &b) const { * return (b < a) ? b : a; * } * }; * * // Declare, allocate, and initialize device-accessible pointers for input and output * int num_segments; // e.g., 3 * int *d_offsets; // e.g., [0, 3, 3, 7] * int *d_in; // e.g., [8, 6, 7, 5, 3, 0, 9] * int *d_out; // e.g., [-, -, -] * CustomMin min_op; * int initial_value; // e.g., INT_MAX * ... * * // Determine temporary device storage requirements * void *d_temp_storage = NULL; * size_t temp_storage_bytes = 0; * cub::DeviceSegmentedReduce::Reduce(d_temp_storage, temp_storage_bytes, d_in, d_out, * num_segments, d_offsets, d_offsets + 1, min_op, initial_value); * * // Allocate temporary storage * cudaMalloc(&d_temp_storage, temp_storage_bytes); * * // Run reduction * cub::DeviceSegmentedReduce::Reduce(d_temp_storage, temp_storage_bytes, d_in, d_out, * num_segments, d_offsets, d_offsets + 1, min_op, initial_value); * * // d_out <-- [6, INT_MAX, 0] * * \endcode * * \tparam InputIteratorT [inferred] Random-access input iterator type for reading input items \iterator * \tparam OutputIteratorT [inferred] Output iterator type for recording the reduced aggregate \iterator * \tparam OffsetIteratorT [inferred] Random-access input iterator type for reading segment offsets \iterator * \tparam ReductionOp [inferred] Binary reduction functor type having member T operator()(const T &a, const T &b) * \tparam T [inferred] Data element type that is convertible to the \p value type of \p InputIteratorT */ template < typename InputIteratorT, typename OutputIteratorT, typename OffsetIteratorT, typename ReductionOp, typename T> CUB_RUNTIME_FUNCTION static cudaError_t Reduce( void *d_temp_storage, ///< [in] %Device-accessible allocation of temporary storage. When NULL, the required allocation size is written to \p temp_storage_bytes and no work is done. size_t &temp_storage_bytes, ///< [in,out] Reference to size in bytes of \p d_temp_storage allocation InputIteratorT d_in, ///< [in] Pointer to the input sequence of data items OutputIteratorT d_out, ///< [out] Pointer to the output aggregate int num_segments, ///< [in] The number of segments that comprise the sorting data OffsetIteratorT d_begin_offsets, ///< [in] Pointer to the sequence of beginning offsets of length \p num_segments, such that d_begin_offsets[i] is the first element of the i^th data segment in d_keys_* and d_values_* OffsetIteratorT d_end_offsets, ///< [in] Pointer to the sequence of ending offsets of length \p num_segments, such that d_end_offsets[i]-1 is the last element of the i^th data segment in d_keys_* and d_values_*. If d_end_offsets[i]-1 <= d_begin_offsets[i], the i^th is considered empty. ReductionOp reduction_op, ///< [in] Binary reduction functor T initial_value, ///< [in] Initial value of the reduction for each segment cudaStream_t stream = 0, ///< [in] [optional] CUDA stream to launch kernels within. Default is stream₀. bool debug_synchronous = false) ///< [in] [optional] Whether or not to synchronize the stream after every kernel launch to check for errors. Also causes launch configurations to be printed to the console. Default is \p false. { // Signed integer type for global offsets typedef int OffsetT; return DispatchSegmentedReduce::Dispatch( d_temp_storage, temp_storage_bytes, d_in, d_out, num_segments, d_begin_offsets, d_end_offsets, reduction_op, initial_value, stream, debug_synchronous); } /** * \brief Computes a device-wide segmented sum using the addition ('+') operator. * * \par * - Uses \p 0 as the initial value of the reduction for each segment. * - When input a contiguous sequence of segments, a single sequence * \p segment_offsets (of length num_segments+1) can be aliased * for both the \p d_begin_offsets and \p d_end_offsets parameters (where * the latter is specified as segment_offsets+1). * - Does not support \p + operators that are non-commutative.. * - \devicestorage * * \par Snippet * The code snippet below illustrates the sum reduction of a device vector of \p int data elements. * \par * \code * #include // or equivalently * * // Declare, allocate, and initialize device-accessible pointers for input and output * int num_segments; // e.g., 3 * int *d_offsets; // e.g., [0, 3, 3, 7] * int *d_in; // e.g., [8, 6, 7, 5, 3, 0, 9] * int *d_out; // e.g., [-, -, -] * ... * * // Determine temporary device storage requirements * void *d_temp_storage = NULL; * size_t temp_storage_bytes = 0; * cub::DeviceSegmentedReduce::Sum(d_temp_storage, temp_storage_bytes, d_in, d_out, * num_segments, d_offsets, d_offsets + 1); * * // Allocate temporary storage * cudaMalloc(&d_temp_storage, temp_storage_bytes); * * // Run sum-reduction * cub::DeviceSegmentedReduce::Sum(d_temp_storage, temp_storage_bytes, d_in, d_out, * num_segments, d_offsets, d_offsets + 1); * * // d_out <-- [21, 0, 17] * * \endcode * * \tparam InputIteratorT [inferred] Random-access input iterator type for reading input items \iterator * \tparam OutputIteratorT [inferred] Output iterator type for recording the reduced aggregate \iterator * \tparam OffsetIteratorT [inferred] Random-access input iterator type for reading segment offsets \iterator */ template < typename InputIteratorT, typename OutputIteratorT, typename OffsetIteratorT> CUB_RUNTIME_FUNCTION static cudaError_t Sum( void *d_temp_storage, ///< [in] %Device-accessible allocation of temporary storage. When NULL, the required allocation size is written to \p temp_storage_bytes and no work is done. size_t &temp_storage_bytes, ///< [in,out] Reference to size in bytes of \p d_temp_storage allocation InputIteratorT d_in, ///< [in] Pointer to the input sequence of data items OutputIteratorT d_out, ///< [out] Pointer to the output aggregate int num_segments, ///< [in] The number of segments that comprise the sorting data OffsetIteratorT d_begin_offsets, ///< [in] Pointer to the sequence of beginning offsets of length \p num_segments, such that d_begin_offsets[i] is the first element of the i^th data segment in d_keys_* and d_values_* OffsetIteratorT d_end_offsets, ///< [in] Pointer to the sequence of ending offsets of length \p num_segments, such that d_end_offsets[i]-1 is the last element of the i^th data segment in d_keys_* and d_values_*. If d_end_offsets[i]-1 <= d_begin_offsets[i], the i^th is considered empty. cudaStream_t stream = 0, ///< [in] [optional] CUDA stream to launch kernels within. Default is stream₀. bool debug_synchronous = false) ///< [in] [optional] Whether or not to synchronize the stream after every kernel launch to check for errors. Also causes launch configurations to be printed to the console. Default is \p false. { // Signed integer type for global offsets typedef int OffsetT; // The output value type typedef typename If<(Equals::value_type, void>::VALUE), // OutputT = (if output iterator's value type is void) ? typename std::iterator_traits::value_type, // ... then the input iterator's value type, typename std::iterator_traits::value_type>::Type OutputT; // ... else the output iterator's value type return DispatchSegmentedReduce::Dispatch( d_temp_storage, temp_storage_bytes, d_in, d_out, num_segments, d_begin_offsets, d_end_offsets, cub::Sum(), OutputT(), // zero-initialize stream, debug_synchronous); } /** * \brief Computes a device-wide segmented minimum using the less-than ('<') operator. * * \par * - Uses std::numeric_limits::max() as the initial value of the reduction for each segment. * - When input a contiguous sequence of segments, a single sequence * \p segment_offsets (of length num_segments+1) can be aliased * for both the \p d_begin_offsets and \p d_end_offsets parameters (where * the latter is specified as segment_offsets+1). * - Does not support \p < operators that are non-commutative. * - \devicestorage * * \par Snippet * The code snippet below illustrates the min-reduction of a device vector of \p int data elements. * \par * \code * #include // or equivalently * * // Declare, allocate, and initialize device-accessible pointers for input and output * int num_segments; // e.g., 3 * int *d_offsets; // e.g., [0, 3, 3, 7] * int *d_in; // e.g., [8, 6, 7, 5, 3, 0, 9] * int *d_out; // e.g., [-, -, -] * ... * * // Determine temporary device storage requirements * void *d_temp_storage = NULL; * size_t temp_storage_bytes = 0; * cub::DeviceSegmentedReduce::Min(d_temp_storage, temp_storage_bytes, d_in, d_out, * num_segments, d_offsets, d_offsets + 1); * * // Allocate temporary storage * cudaMalloc(&d_temp_storage, temp_storage_bytes); * * // Run min-reduction * cub::DeviceSegmentedReduce::Min(d_temp_storage, temp_storage_bytes, d_in, d_out, * num_segments, d_offsets, d_offsets + 1); * * // d_out <-- [6, INT_MAX, 0] * * \endcode * * \tparam InputIteratorT [inferred] Random-access input iterator type for reading input items \iterator * \tparam OutputIteratorT [inferred] Output iterator type for recording the reduced aggregate \iterator * \tparam OffsetIteratorT [inferred] Random-access input iterator type for reading segment offsets \iterator */ template < typename InputIteratorT, typename OutputIteratorT, typename OffsetIteratorT> CUB_RUNTIME_FUNCTION static cudaError_t Min( void *d_temp_storage, ///< [in] %Device-accessible allocation of temporary storage. When NULL, the required allocation size is written to \p temp_storage_bytes and no work is done. size_t &temp_storage_bytes, ///< [in,out] Reference to size in bytes of \p d_temp_storage allocation InputIteratorT d_in, ///< [in] Pointer to the input sequence of data items OutputIteratorT d_out, ///< [out] Pointer to the output aggregate int num_segments, ///< [in] The number of segments that comprise the sorting data OffsetIteratorT d_begin_offsets, ///< [in] Pointer to the sequence of beginning offsets of length \p num_segments, such that d_begin_offsets[i] is the first element of the i^th data segment in d_keys_* and d_values_* OffsetIteratorT d_end_offsets, ///< [in] Pointer to the sequence of ending offsets of length \p num_segments, such that d_end_offsets[i]-1 is the last element of the i^th data segment in d_keys_* and d_values_*. If d_end_offsets[i]-1 <= d_begin_offsets[i], the i^th is considered empty. cudaStream_t stream = 0, ///< [in] [optional] CUDA stream to launch kernels within. Default is stream₀. bool debug_synchronous = false) ///< [in] [optional] Whether or not to synchronize the stream after every kernel launch to check for errors. Also causes launch configurations to be printed to the console. Default is \p false. { // Signed integer type for global offsets typedef int OffsetT; // The input value type typedef typename std::iterator_traits::value_type InputT; return DispatchSegmentedReduce::Dispatch( d_temp_storage, temp_storage_bytes, d_in, d_out, num_segments, d_begin_offsets, d_end_offsets, cub::Min(), Traits::Max(), // replace with std::numeric_limits::max() when C++11 support is more prevalent stream, debug_synchronous); } /** * \brief Finds the first device-wide minimum in each segment using the less-than ('<') operator, also returning the in-segment index of that item. * * \par * - The output value type of \p d_out is cub::KeyValuePair (assuming the value type of \p d_in is \p T) * - The minimum of the i^th segment is written to d_out[i].value and its offset in that segment is written to d_out[i].key. * - The {1, std::numeric_limits::max()} tuple is produced for zero-length inputs * - When input a contiguous sequence of segments, a single sequence * \p segment_offsets (of length num_segments+1) can be aliased * for both the \p d_begin_offsets and \p d_end_offsets parameters (where * the latter is specified as segment_offsets+1). * - Does not support \p < operators that are non-commutative. * - \devicestorage * * \par Snippet * The code snippet below illustrates the argmin-reduction of a device vector of \p int data elements. * \par * \code * #include // or equivalently * * // Declare, allocate, and initialize device-accessible pointers for input and output * int num_segments; // e.g., 3 * int *d_offsets; // e.g., [0, 3, 3, 7] * int *d_in; // e.g., [8, 6, 7, 5, 3, 0, 9] * KeyValuePair *d_out; // e.g., [{-,-}, {-,-}, {-,-}] * ... * * // Determine temporary device storage requirements * void *d_temp_storage = NULL; * size_t temp_storage_bytes = 0; * cub::DeviceSegmentedReduce::ArgMin(d_temp_storage, temp_storage_bytes, d_in, d_out, * num_segments, d_offsets, d_offsets + 1); * * // Allocate temporary storage * cudaMalloc(&d_temp_storage, temp_storage_bytes); * * // Run argmin-reduction * cub::DeviceSegmentedReduce::ArgMin(d_temp_storage, temp_storage_bytes, d_in, d_out, * num_segments, d_offsets, d_offsets + 1); * * // d_out <-- [{1,6}, {1,INT_MAX}, {2,0}] * * \endcode * * \tparam InputIteratorT [inferred] Random-access input iterator type for reading input items (of some type \p T) \iterator * \tparam OutputIteratorT [inferred] Output iterator type for recording the reduced aggregate (having value type KeyValuePair) \iterator * \tparam OffsetIteratorT [inferred] Random-access input iterator type for reading segment offsets \iterator */ template < typename InputIteratorT, typename OutputIteratorT, typename OffsetIteratorT> CUB_RUNTIME_FUNCTION static cudaError_t ArgMin( void *d_temp_storage, ///< [in] %Device-accessible allocation of temporary storage. When NULL, the required allocation size is written to \p temp_storage_bytes and no work is done. size_t &temp_storage_bytes, ///< [in,out] Reference to size in bytes of \p d_temp_storage allocation InputIteratorT d_in, ///< [in] Pointer to the input sequence of data items OutputIteratorT d_out, ///< [out] Pointer to the output aggregate int num_segments, ///< [in] The number of segments that comprise the sorting data OffsetIteratorT d_begin_offsets, ///< [in] Pointer to the sequence of beginning offsets of length \p num_segments, such that d_begin_offsets[i] is the first element of the i^th data segment in d_keys_* and d_values_* OffsetIteratorT d_end_offsets, ///< [in] Pointer to the sequence of ending offsets of length \p num_segments, such that d_end_offsets[i]-1 is the last element of the i^th data segment in d_keys_* and d_values_*. If d_end_offsets[i]-1 <= d_begin_offsets[i], the i^th is considered empty. cudaStream_t stream = 0, ///< [in] [optional] CUDA stream to launch kernels within. Default is stream₀. bool debug_synchronous = false) ///< [in] [optional] Whether or not to synchronize the stream after every kernel launch to check for errors. Also causes launch configurations to be printed to the console. Default is \p false. { // Signed integer type for global offsets typedef int OffsetT; // The input type typedef typename std::iterator_traits::value_type InputValueT; // The output tuple type typedef typename If<(Equals::value_type, void>::VALUE), // OutputT = (if output iterator's value type is void) ? KeyValuePair, // ... then the key value pair OffsetT + InputValueT typename std::iterator_traits::value_type>::Type OutputTupleT; // ... else the output iterator's value type // The output value type typedef typename OutputTupleT::Value OutputValueT; // Wrapped input iterator to produce index-value tuples typedef ArgIndexInputIterator ArgIndexInputIteratorT; ArgIndexInputIteratorT d_indexed_in(d_in); // Initial value OutputTupleT initial_value(1, Traits::Max()); // replace with std::numeric_limits::max() when C++11 support is more prevalent return DispatchSegmentedReduce::Dispatch( d_temp_storage, temp_storage_bytes, d_indexed_in, d_out, num_segments, d_begin_offsets, d_end_offsets, cub::ArgMin(), initial_value, stream, debug_synchronous); } /** * \brief Computes a device-wide segmented maximum using the greater-than ('>') operator. * * \par * - Uses std::numeric_limits::lowest() as the initial value of the reduction. * - When input a contiguous sequence of segments, a single sequence * \p segment_offsets (of length num_segments+1) can be aliased * for both the \p d_begin_offsets and \p d_end_offsets parameters (where * the latter is specified as segment_offsets+1). * - Does not support \p > operators that are non-commutative. * - \devicestorage * * \par Snippet * The code snippet below illustrates the max-reduction of a device vector of \p int data elements. * \par * \code * #include // or equivalently * * // Declare, allocate, and initialize device-accessible pointers for input and output * int num_segments; // e.g., 3 * int *d_offsets; // e.g., [0, 3, 3, 7] * int *d_in; // e.g., [8, 6, 7, 5, 3, 0, 9] * int *d_out; // e.g., [-, -, -] * ... * * // Determine temporary device storage requirements * void *d_temp_storage = NULL; * size_t temp_storage_bytes = 0; * cub::DeviceSegmentedReduce::Max(d_temp_storage, temp_storage_bytes, d_in, d_out, * num_segments, d_offsets, d_offsets + 1); * * // Allocate temporary storage * cudaMalloc(&d_temp_storage, temp_storage_bytes); * * // Run max-reduction * cub::DeviceSegmentedReduce::Max(d_temp_storage, temp_storage_bytes, d_in, d_out, * num_segments, d_offsets, d_offsets + 1); * * // d_out <-- [8, INT_MIN, 9] * * \endcode * * \tparam InputIteratorT [inferred] Random-access input iterator type for reading input items \iterator * \tparam OutputIteratorT [inferred] Output iterator type for recording the reduced aggregate \iterator * \tparam OffsetIteratorT [inferred] Random-access input iterator type for reading segment offsets \iterator */ template < typename InputIteratorT, typename OutputIteratorT, typename OffsetIteratorT> CUB_RUNTIME_FUNCTION static cudaError_t Max( void *d_temp_storage, ///< [in] %Device-accessible allocation of temporary storage. When NULL, the required allocation size is written to \p temp_storage_bytes and no work is done. size_t &temp_storage_bytes, ///< [in,out] Reference to size in bytes of \p d_temp_storage allocation InputIteratorT d_in, ///< [in] Pointer to the input sequence of data items OutputIteratorT d_out, ///< [out] Pointer to the output aggregate int num_segments, ///< [in] The number of segments that comprise the sorting data OffsetIteratorT d_begin_offsets, ///< [in] Pointer to the sequence of beginning offsets of length \p num_segments, such that d_begin_offsets[i] is the first element of the i^th data segment in d_keys_* and d_values_* OffsetIteratorT d_end_offsets, ///< [in] Pointer to the sequence of ending offsets of length \p num_segments, such that d_end_offsets[i]-1 is the last element of the i^th data segment in d_keys_* and d_values_*. If d_end_offsets[i]-1 <= d_begin_offsets[i], the i^th is considered empty. cudaStream_t stream = 0, ///< [in] [optional] CUDA stream to launch kernels within. Default is stream₀. bool debug_synchronous = false) ///< [in] [optional] Whether or not to synchronize the stream after every kernel launch to check for errors. Also causes launch configurations to be printed to the console. Default is \p false. { // Signed integer type for global offsets typedef int OffsetT; // The input value type typedef typename std::iterator_traits::value_type InputT; return DispatchSegmentedReduce::Dispatch( d_temp_storage, temp_storage_bytes, d_in, d_out, num_segments, d_begin_offsets, d_end_offsets, cub::Max(), Traits::Lowest(), // replace with std::numeric_limits::lowest() when C++11 support is more prevalent stream, debug_synchronous); } /** * \brief Finds the first device-wide maximum in each segment using the greater-than ('>') operator, also returning the in-segment index of that item * * \par * - The output value type of \p d_out is cub::KeyValuePair (assuming the value type of \p d_in is \p T) * - The maximum of the i^th segment is written to d_out[i].value and its offset in that segment is written to d_out[i].key. * - The {1, std::numeric_limits::lowest()} tuple is produced for zero-length inputs * - When input a contiguous sequence of segments, a single sequence * \p segment_offsets (of length num_segments+1) can be aliased * for both the \p d_begin_offsets and \p d_end_offsets parameters (where * the latter is specified as segment_offsets+1). * - Does not support \p > operators that are non-commutative. * - \devicestorage * * \par Snippet * The code snippet below illustrates the argmax-reduction of a device vector of \p int data elements. * \par * \code * #include // or equivalently * * // Declare, allocate, and initialize device-accessible pointers for input and output * int num_segments; // e.g., 3 * int *d_offsets; // e.g., [0, 3, 3, 7] * int *d_in; // e.g., [8, 6, 7, 5, 3, 0, 9] * KeyValuePair *d_out; // e.g., [{-,-}, {-,-}, {-,-}] * ... * * // Determine temporary device storage requirements * void *d_temp_storage = NULL; * size_t temp_storage_bytes = 0; * cub::DeviceSegmentedReduce::ArgMax(d_temp_storage, temp_storage_bytes, d_in, d_out, * num_segments, d_offsets, d_offsets + 1); * * // Allocate temporary storage * cudaMalloc(&d_temp_storage, temp_storage_bytes); * * // Run argmax-reduction * cub::DeviceSegmentedReduce::ArgMax(d_temp_storage, temp_storage_bytes, d_in, d_out, * num_segments, d_offsets, d_offsets + 1); * * // d_out <-- [{0,8}, {1,INT_MIN}, {3,9}] * * \endcode * * \tparam InputIteratorT [inferred] Random-access input iterator type for reading input items (of some type \p T) \iterator * \tparam OutputIteratorT [inferred] Output iterator type for recording the reduced aggregate (having value type KeyValuePair) \iterator * \tparam OffsetIteratorT [inferred] Random-access input iterator type for reading segment offsets \iterator */ template < typename InputIteratorT, typename OutputIteratorT, typename OffsetIteratorT> CUB_RUNTIME_FUNCTION static cudaError_t ArgMax( void *d_temp_storage, ///< [in] %Device-accessible allocation of temporary storage. When NULL, the required allocation size is written to \p temp_storage_bytes and no work is done. size_t &temp_storage_bytes, ///< [in,out] Reference to size in bytes of \p d_temp_storage allocation InputIteratorT d_in, ///< [in] Pointer to the input sequence of data items OutputIteratorT d_out, ///< [out] Pointer to the output aggregate int num_segments, ///< [in] The number of segments that comprise the sorting data OffsetIteratorT d_begin_offsets, ///< [in] Pointer to the sequence of beginning offsets of length \p num_segments, such that d_begin_offsets[i] is the first element of the i^th data segment in d_keys_* and d_values_* OffsetIteratorT d_end_offsets, ///< [in] Pointer to the sequence of ending offsets of length \p num_segments, such that d_end_offsets[i]-1 is the last element of the i^th data segment in d_keys_* and d_values_*. If d_end_offsets[i]-1 <= d_begin_offsets[i], the i^th is considered empty. cudaStream_t stream = 0, ///< [in] [optional] CUDA stream to launch kernels within. Default is stream₀. bool debug_synchronous = false) ///< [in] [optional] Whether or not to synchronize the stream after every kernel launch to check for errors. Also causes launch configurations to be printed to the console. Default is \p false. { // Signed integer type for global offsets typedef int OffsetT; // The input type typedef typename std::iterator_traits::value_type InputValueT; // The output tuple type typedef typename If<(Equals::value_type, void>::VALUE), // OutputT = (if output iterator's value type is void) ? KeyValuePair, // ... then the key value pair OffsetT + InputValueT typename std::iterator_traits::value_type>::Type OutputTupleT; // ... else the output iterator's value type // The output value type typedef typename OutputTupleT::Value OutputValueT; // Wrapped input iterator to produce index-value tuples typedef ArgIndexInputIterator ArgIndexInputIteratorT; ArgIndexInputIteratorT d_indexed_in(d_in); // Initial value OutputTupleT initial_value(1, Traits::Lowest()); // replace with std::numeric_limits::lowest() when C++11 support is more prevalent return DispatchSegmentedReduce::Dispatch( d_temp_storage, temp_storage_bytes, d_indexed_in, d_out, num_segments, d_begin_offsets, d_end_offsets, cub::ArgMax(), initial_value, stream, debug_synchronous); } }; } // CUB namespace CUB_NS_POSTFIX // Optional outer namespace(s)