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cub::DeviceSegmentedReduce Struct Reference

Detailed description

DeviceSegmentedReduce provides device-wide, parallel operations for computing a reduction across multiple sequences of data items residing within device-accessible memory.

reduce_logo.png
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Overview
A reduction (or fold) uses a binary combining operator to compute a single aggregate from a sequence of input elements.
Usage Considerations
  • Dynamic parallelism. DeviceSegmentedReduce methods can be called within kernel code on devices in which CUDA dynamic parallelism is supported.

Static Public Methods

template<typename InputIteratorT , typename OutputIteratorT , typename OffsetIteratorT , typename ReductionOp , typename T >
static CUB_RUNTIME_FUNCTION
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)
 Computes a device-wide segmented reduction using the specified binary reduction_op functor. More...
 
template<typename InputIteratorT , typename OutputIteratorT , typename OffsetIteratorT >
static CUB_RUNTIME_FUNCTION
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)
 Computes a device-wide segmented sum using the addition ('+') operator. More...
 
template<typename InputIteratorT , typename OutputIteratorT , typename OffsetIteratorT >
static CUB_RUNTIME_FUNCTION
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)
 Computes a device-wide segmented minimum using the less-than ('<') operator. More...
 
template<typename InputIteratorT , typename OutputIteratorT , typename OffsetIteratorT >
static CUB_RUNTIME_FUNCTION
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)
 Finds the first device-wide minimum in each segment using the less-than ('<') operator, also returning the in-segment index of that item. More...
 
template<typename InputIteratorT , typename OutputIteratorT , typename OffsetIteratorT >
static CUB_RUNTIME_FUNCTION
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)
 Computes a device-wide segmented maximum using the greater-than ('>') operator. More...
 
template<typename InputIteratorT , typename OutputIteratorT , typename OffsetIteratorT >
static CUB_RUNTIME_FUNCTION
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)
 Finds the first device-wide maximum in each segment using the greater-than ('>') operator, also returning the in-segment index of that item. More...
 

Member Function Documentation

template<typename InputIteratorT , typename OutputIteratorT , typename OffsetIteratorT , typename ReductionOp , typename T >
static CUB_RUNTIME_FUNCTION cudaError_t cub::DeviceSegmentedReduce::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,
initial_value,
cudaStream_t  stream = 0,
bool  debug_synchronous = false 
)
inlinestatic

Computes a device-wide segmented reduction using the specified binary reduction_op functor.

  • Does not support binary reduction operators that are non-commutative.
  • When input a contiguous sequence of segments, a single sequence segment_offsets (of length num_segments+1) can be aliased for both the d_begin_offsets and d_end_offsets parameters (where the latter is specified as segment_offsets+1).
  • When d_temp_storage is NULL, no work is done and the required allocation size is returned in temp_storage_bytes.
Snippet
The code snippet below illustrates a custom min-reduction of a device vector of int data elements.
#include <cub/cub.cuh> // or equivalently <cub/device/device_radix_sort.cuh>
// CustomMin functor
struct CustomMin
{
template <typename T>
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]
Template Parameters
InputIteratorT[inferred] Random-access input iterator type for reading input items (may be a simple pointer type)
OutputIteratorT[inferred] Output iterator type for recording the reduced aggregate (may be a simple pointer type)
OffsetIteratorT[inferred] Random-access input iterator type for reading segment offsets (may be a simple pointer type)
ReductionOp[inferred] Binary reduction functor type having member T operator()(const T &a, const T &b)
T[inferred] Data element type that is convertible to the value type of InputIteratorT
Parameters
[in]d_temp_storageDevice-accessible allocation of temporary storage. When NULL, the required allocation size is written to temp_storage_bytes and no work is done.
[in,out]temp_storage_bytesReference to size in bytes of d_temp_storage allocation
[in]d_inPointer to the input sequence of data items
[out]d_outPointer to the output aggregate
[in]num_segmentsThe number of segments that comprise the sorting data
[in]d_begin_offsetsPointer to the sequence of beginning offsets of length num_segments, such that d_begin_offsets[i] is the first element of the ith data segment in d_keys_* and d_values_*
[in]d_end_offsetsPointer to the sequence of ending offsets of length num_segments, such that d_end_offsets[i]-1 is the last element of the ith data segment in d_keys_* and d_values_*. If d_end_offsets[i]-1 <= d_begin_offsets[i], the ith is considered empty.
[in]reduction_opBinary reduction functor
[in]initial_valueInitial value of the reduction for each segment
[in]stream[optional] CUDA stream to launch kernels within. Default is stream0.
[in]debug_synchronous[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 false.
template<typename InputIteratorT , typename OutputIteratorT , typename OffsetIteratorT >
static CUB_RUNTIME_FUNCTION cudaError_t cub::DeviceSegmentedReduce::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 
)
inlinestatic

Computes a device-wide segmented sum using the addition ('+') operator.

  • Uses 0 as the initial value of the reduction for each segment.
  • When input a contiguous sequence of segments, a single sequence segment_offsets (of length num_segments+1) can be aliased for both the d_begin_offsets and d_end_offsets parameters (where the latter is specified as segment_offsets+1).
  • Does not support + operators that are non-commutative..
  • When d_temp_storage is NULL, no work is done and the required allocation size is returned in temp_storage_bytes.
Snippet
The code snippet below illustrates the sum reduction of a device vector of int data elements.
#include <cub/cub.cuh> // or equivalently <cub/device/device_radix_sort.cuh>
// 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]
Template Parameters
InputIteratorT[inferred] Random-access input iterator type for reading input items (may be a simple pointer type)
OutputIteratorT[inferred] Output iterator type for recording the reduced aggregate (may be a simple pointer type)
OffsetIteratorT[inferred] Random-access input iterator type for reading segment offsets (may be a simple pointer type)
Parameters
[in]d_temp_storageDevice-accessible allocation of temporary storage. When NULL, the required allocation size is written to temp_storage_bytes and no work is done.
[in,out]temp_storage_bytesReference to size in bytes of d_temp_storage allocation
[in]d_inPointer to the input sequence of data items
[out]d_outPointer to the output aggregate
[in]num_segmentsThe number of segments that comprise the sorting data
[in]d_begin_offsetsPointer to the sequence of beginning offsets of length num_segments, such that d_begin_offsets[i] is the first element of the ith data segment in d_keys_* and d_values_*
[in]d_end_offsetsPointer to the sequence of ending offsets of length num_segments, such that d_end_offsets[i]-1 is the last element of the ith data segment in d_keys_* and d_values_*. If d_end_offsets[i]-1 <= d_begin_offsets[i], the ith is considered empty.
[in]stream[optional] CUDA stream to launch kernels within. Default is stream0.
[in]debug_synchronous[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 false.
template<typename InputIteratorT , typename OutputIteratorT , typename OffsetIteratorT >
static CUB_RUNTIME_FUNCTION cudaError_t cub::DeviceSegmentedReduce::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 
)
inlinestatic

Computes a device-wide segmented minimum using the less-than ('<') operator.

  • Uses std::numeric_limits<T>::max() as the initial value of the reduction for each segment.
  • When input a contiguous sequence of segments, a single sequence segment_offsets (of length num_segments+1) can be aliased for both the d_begin_offsets and d_end_offsets parameters (where the latter is specified as segment_offsets+1).
  • Does not support < operators that are non-commutative.
  • When d_temp_storage is NULL, no work is done and the required allocation size is returned in temp_storage_bytes.
Snippet
The code snippet below illustrates the min-reduction of a device vector of int data elements.
#include <cub/cub.cuh> // or equivalently <cub/device/device_radix_sort.cuh>
// 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]
Template Parameters
InputIteratorT[inferred] Random-access input iterator type for reading input items (may be a simple pointer type)
OutputIteratorT[inferred] Output iterator type for recording the reduced aggregate (may be a simple pointer type)
OffsetIteratorT[inferred] Random-access input iterator type for reading segment offsets (may be a simple pointer type)
Parameters
[in]d_temp_storageDevice-accessible allocation of temporary storage. When NULL, the required allocation size is written to temp_storage_bytes and no work is done.
[in,out]temp_storage_bytesReference to size in bytes of d_temp_storage allocation
[in]d_inPointer to the input sequence of data items
[out]d_outPointer to the output aggregate
[in]num_segmentsThe number of segments that comprise the sorting data
[in]d_begin_offsetsPointer to the sequence of beginning offsets of length num_segments, such that d_begin_offsets[i] is the first element of the ith data segment in d_keys_* and d_values_*
[in]d_end_offsetsPointer to the sequence of ending offsets of length num_segments, such that d_end_offsets[i]-1 is the last element of the ith data segment in d_keys_* and d_values_*. If d_end_offsets[i]-1 <= d_begin_offsets[i], the ith is considered empty.
[in]stream[optional] CUDA stream to launch kernels within. Default is stream0.
[in]debug_synchronous[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 false.
template<typename InputIteratorT , typename OutputIteratorT , typename OffsetIteratorT >
static CUB_RUNTIME_FUNCTION cudaError_t cub::DeviceSegmentedReduce::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 
)
inlinestatic

Finds the first device-wide minimum in each segment using the less-than ('<') operator, also returning the in-segment index of that item.

  • The output value type of d_out is cub::KeyValuePair <int, T> (assuming the value type of d_in is T)
    • The minimum of the ith 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<T>::max()} tuple is produced for zero-length inputs
  • When input a contiguous sequence of segments, a single sequence segment_offsets (of length num_segments+1) can be aliased for both the d_begin_offsets and d_end_offsets parameters (where the latter is specified as segment_offsets+1).
  • Does not support < operators that are non-commutative.
  • When d_temp_storage is NULL, no work is done and the required allocation size is returned in temp_storage_bytes.
Snippet
The code snippet below illustrates the argmin-reduction of a device vector of int data elements.
#include <cub/cub.cuh> // or equivalently <cub/device/device_radix_sort.cuh>
// 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<int, int> *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}]
Template Parameters
InputIteratorT[inferred] Random-access input iterator type for reading input items (of some type T) (may be a simple pointer type)
OutputIteratorT[inferred] Output iterator type for recording the reduced aggregate (having value type KeyValuePair<int, T>) (may be a simple pointer type)
OffsetIteratorT[inferred] Random-access input iterator type for reading segment offsets (may be a simple pointer type)
Parameters
[in]d_temp_storageDevice-accessible allocation of temporary storage. When NULL, the required allocation size is written to temp_storage_bytes and no work is done.
[in,out]temp_storage_bytesReference to size in bytes of d_temp_storage allocation
[in]d_inPointer to the input sequence of data items
[out]d_outPointer to the output aggregate
[in]num_segmentsThe number of segments that comprise the sorting data
[in]d_begin_offsetsPointer to the sequence of beginning offsets of length num_segments, such that d_begin_offsets[i] is the first element of the ith data segment in d_keys_* and d_values_*
[in]d_end_offsetsPointer to the sequence of ending offsets of length num_segments, such that d_end_offsets[i]-1 is the last element of the ith data segment in d_keys_* and d_values_*. If d_end_offsets[i]-1 <= d_begin_offsets[i], the ith is considered empty.
[in]stream[optional] CUDA stream to launch kernels within. Default is stream0.
[in]debug_synchronous[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 false.
template<typename InputIteratorT , typename OutputIteratorT , typename OffsetIteratorT >
static CUB_RUNTIME_FUNCTION cudaError_t cub::DeviceSegmentedReduce::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 
)
inlinestatic

Computes a device-wide segmented maximum using the greater-than ('>') operator.

  • Uses std::numeric_limits<T>::lowest() as the initial value of the reduction.
  • When input a contiguous sequence of segments, a single sequence segment_offsets (of length num_segments+1) can be aliased for both the d_begin_offsets and d_end_offsets parameters (where the latter is specified as segment_offsets+1).
  • Does not support > operators that are non-commutative.
  • When d_temp_storage is NULL, no work is done and the required allocation size is returned in temp_storage_bytes.
Snippet
The code snippet below illustrates the max-reduction of a device vector of int data elements.
#include <cub/cub.cuh> // or equivalently <cub/device/device_radix_sort.cuh>
// 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]
Template Parameters
InputIteratorT[inferred] Random-access input iterator type for reading input items (may be a simple pointer type)
OutputIteratorT[inferred] Output iterator type for recording the reduced aggregate (may be a simple pointer type)
OffsetIteratorT[inferred] Random-access input iterator type for reading segment offsets (may be a simple pointer type)
Parameters
[in]d_temp_storageDevice-accessible allocation of temporary storage. When NULL, the required allocation size is written to temp_storage_bytes and no work is done.
[in,out]temp_storage_bytesReference to size in bytes of d_temp_storage allocation
[in]d_inPointer to the input sequence of data items
[out]d_outPointer to the output aggregate
[in]num_segmentsThe number of segments that comprise the sorting data
[in]d_begin_offsetsPointer to the sequence of beginning offsets of length num_segments, such that d_begin_offsets[i] is the first element of the ith data segment in d_keys_* and d_values_*
[in]d_end_offsetsPointer to the sequence of ending offsets of length num_segments, such that d_end_offsets[i]-1 is the last element of the ith data segment in d_keys_* and d_values_*. If d_end_offsets[i]-1 <= d_begin_offsets[i], the ith is considered empty.
[in]stream[optional] CUDA stream to launch kernels within. Default is stream0.
[in]debug_synchronous[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 false.
template<typename InputIteratorT , typename OutputIteratorT , typename OffsetIteratorT >
static CUB_RUNTIME_FUNCTION cudaError_t cub::DeviceSegmentedReduce::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 
)
inlinestatic

Finds the first device-wide maximum in each segment using the greater-than ('>') operator, also returning the in-segment index of that item.

  • The output value type of d_out is cub::KeyValuePair <int, T> (assuming the value type of d_in is T)
    • The maximum of the ith 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<T>::lowest()} tuple is produced for zero-length inputs
  • When input a contiguous sequence of segments, a single sequence segment_offsets (of length num_segments+1) can be aliased for both the d_begin_offsets and d_end_offsets parameters (where the latter is specified as segment_offsets+1).
  • Does not support > operators that are non-commutative.
  • When d_temp_storage is NULL, no work is done and the required allocation size is returned in temp_storage_bytes.
Snippet
The code snippet below illustrates the argmax-reduction of a device vector of int data elements.
#include <cub/cub.cuh> // or equivalently <cub/device/device_reduce.cuh>
// 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<int, int> *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}]
Template Parameters
InputIteratorT[inferred] Random-access input iterator type for reading input items (of some type T) (may be a simple pointer type)
OutputIteratorT[inferred] Output iterator type for recording the reduced aggregate (having value type KeyValuePair<int, T>) (may be a simple pointer type)
OffsetIteratorT[inferred] Random-access input iterator type for reading segment offsets (may be a simple pointer type)
Parameters
[in]d_temp_storageDevice-accessible allocation of temporary storage. When NULL, the required allocation size is written to temp_storage_bytes and no work is done.
[in,out]temp_storage_bytesReference to size in bytes of d_temp_storage allocation
[in]d_inPointer to the input sequence of data items
[out]d_outPointer to the output aggregate
[in]num_segmentsThe number of segments that comprise the sorting data
[in]d_begin_offsetsPointer to the sequence of beginning offsets of length num_segments, such that d_begin_offsets[i] is the first element of the ith data segment in d_keys_* and d_values_*
[in]d_end_offsetsPointer to the sequence of ending offsets of length num_segments, such that d_end_offsets[i]-1 is the last element of the ith data segment in d_keys_* and d_values_*. If d_end_offsets[i]-1 <= d_begin_offsets[i], the ith is considered empty.
[in]stream[optional] CUDA stream to launch kernels within. Default is stream0.
[in]debug_synchronous[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 false.

The documentation for this struct was generated from the following file: