1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
|
/******************************************************************************
* 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
* Thread utilities for sequential reduction over statically-sized array types
*/
#pragma once
#include <cub/config.cuh>
#if defined(_CCCL_IMPLICIT_SYSTEM_HEADER_GCC)
# pragma GCC system_header
#elif defined(_CCCL_IMPLICIT_SYSTEM_HEADER_CLANG)
# pragma clang system_header
#elif defined(_CCCL_IMPLICIT_SYSTEM_HEADER_MSVC)
# pragma system_header
#endif // no system header
#include <cub/detail/type_traits.cuh>
#include <cub/thread/thread_operators.cuh>
CUB_NAMESPACE_BEGIN
/// Internal namespace (to prevent ADL mishaps between static functions when mixing different CUB installations)
namespace internal {
/**
* @brief Sequential reduction over statically-sized array types
*
* @param[in] input
* Input array
*
* @param[in] reduction_op
* Binary reduction operator
*
* @param[in] prefix
* Prefix to seed reduction with
*/
template <int LENGTH,
typename T,
typename ReductionOp,
typename PrefixT,
typename AccumT = detail::accumulator_t<ReductionOp, PrefixT, T>>
__device__ __forceinline__ AccumT
ThreadReduce(T *input, ReductionOp reduction_op, PrefixT prefix, Int2Type<LENGTH> /*length*/)
{
AccumT retval = prefix;
#pragma unroll
for (int i = 0; i < LENGTH; ++i)
retval = reduction_op(retval, input[i]);
return retval;
}
/**
* @brief Perform a sequential reduction over @p LENGTH elements of the @p input array,
* seeded with the specified @p prefix. The aggregate is returned.
*
* @tparam LENGTH
* LengthT of input array
*
* @tparam T
* <b>[inferred]</b> The data type to be reduced.
*
* @tparam ReductionOp
* <b>[inferred]</b> Binary reduction operator type having member
* <tt>T operator()(const T &a, const T &b)</tt>
*
* @param[in] input
* Input array
*
* @param[in] reduction_op
* Binary reduction operator
*
* @param[in] prefix
* Prefix to seed reduction with
*/
template <int LENGTH,
typename T,
typename ReductionOp,
typename PrefixT,
typename AccumT = detail::accumulator_t<ReductionOp, PrefixT, T>>
__device__ __forceinline__ AccumT ThreadReduce(T *input, ReductionOp reduction_op, PrefixT prefix)
{
return ThreadReduce(input, reduction_op, prefix, Int2Type<LENGTH>());
}
/**
* @brief Perform a sequential reduction over @p LENGTH elements of the @p input array.
* The aggregate is returned.
*
* @tparam LENGTH
* LengthT of input array
*
* @tparam T
* <b>[inferred]</b> The data type to be reduced.
*
* @tparam ReductionOp
* <b>[inferred]</b> Binary reduction operator type having member
* <tt>T operator()(const T &a, const T &b)</tt>
*
* @param[in] input
* Input array
*
* @param[in] reduction_op
* Binary reduction operator
*/
template <int LENGTH, typename T, typename ReductionOp>
__device__ __forceinline__ T ThreadReduce(T *input, ReductionOp reduction_op)
{
T prefix = input[0];
return ThreadReduce<LENGTH - 1>(input + 1, reduction_op, prefix);
}
/**
* @brief Perform a sequential reduction over the statically-sized @p input array,
* seeded with the specified @p prefix. The aggregate is returned.
*
* @tparam LENGTH
* <b>[inferred]</b> LengthT of @p input array
*
* @tparam T
* <b>[inferred]</b> The data type to be reduced.
*
* @tparam ReductionOp
* <b>[inferred]</b> Binary reduction operator type having member
* <tt>T operator()(const T &a, const T &b)</tt>
*
* @param[in] input
* Input array
*
* @param[in] reduction_op
* Binary reduction operator
*
* @param[in] prefix
* Prefix to seed reduction with
*/
template <int LENGTH,
typename T,
typename ReductionOp,
typename PrefixT,
typename AccumT = detail::accumulator_t<ReductionOp, PrefixT, T>>
__device__ __forceinline__ AccumT ThreadReduce(T (&input)[LENGTH],
ReductionOp reduction_op,
PrefixT prefix)
{
return ThreadReduce(input, reduction_op, prefix, Int2Type<LENGTH>());
}
/**
* @brief Serial reduction with the specified operator
*
* @tparam LENGTH
* <b>[inferred]</b> LengthT of @p input array
*
* @tparam T
* <b>[inferred]</b> The data type to be reduced.
*
* @tparam ReductionOp
* <b>[inferred]</b> Binary reduction operator type having member
* <tt>T operator()(const T &a, const T &b)</tt>
*
* @param[in] input
* Input array
*
* @param[in] reduction_op
* Binary reduction operator
*/
template <int LENGTH, typename T, typename ReductionOp>
__device__ __forceinline__ T ThreadReduce(T (&input)[LENGTH], ReductionOp reduction_op)
{
return ThreadReduce<LENGTH>((T*) input, reduction_op);
}
} // internal namespace
CUB_NAMESPACE_END
|
