Blame view
tools/cub-1.8.0/cub/device/device_run_length_encode.cuh
14.5 KB
8dcb6dfcb
first commit
|
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 |
/******************************************************************************
* 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::DeviceRunLengthEncode provides device-wide, parallel operations for computing a run-length encoding across a sequence of data items residing within device-accessible memory.
*/
#pragma once
#include <stdio.h>
#include <iterator>
#include "dispatch/dispatch_rle.cuh"
#include "dispatch/dispatch_reduce_by_key.cuh"
#include "../util_namespace.cuh"
/// Optional outer namespace(s)
CUB_NS_PREFIX
/// CUB namespace
namespace cub {
/**
* \brief DeviceRunLengthEncode provides device-wide, parallel operations for demarcating "runs" of same-valued items within a sequence residing within device-accessible memory. 
* \ingroup SingleModule
*
* \par Overview
* A <a href="http://en.wikipedia.org/wiki/Run-length_encoding"><em>run-length encoding</em></a>
* computes a simple compressed representation of a sequence of input elements such that each
* maximal "run" of consecutive same-valued data items is encoded as a single data value along with a
* count of the elements in that run.
*
* \par Usage Considerations
* \cdp_class{DeviceRunLengthEncode}
*
* \par Performance
* \linear_performance{run-length encode}
*
* \par
* The following chart illustrates DeviceRunLengthEncode::RunLengthEncode performance across
* different CUDA architectures for \p int32 items.
* Segments have lengths uniformly sampled from [1,1000].
*
* \image html rle_int32_len_500.png
*
* \par
* \plots_below
*
*/
struct DeviceRunLengthEncode
{
/**
* \brief Computes a run-length encoding of the sequence \p d_in.
*
* \par
* - For the <em>i</em><sup>th</sup> run encountered, the first key of the run and its length are written to
* <tt>d_unique_out[<em>i</em>]</tt> and <tt>d_counts_out[<em>i</em>]</tt>,
* respectively.
* - The total number of runs encountered is written to \p d_num_runs_out.
* - The <tt>==</tt> equality operator is used to determine whether values are equivalent
* - \devicestorage
*
* \par Performance
* The following charts illustrate saturated encode performance across different
* CUDA architectures for \p int32 and \p int64 items, respectively. Segments have
* lengths uniformly sampled from [1,1000].
*
* \image html rle_int32_len_500.png
* \image html rle_int64_len_500.png
*
* \par
* The following charts are similar, but with segment lengths uniformly sampled from [1,10]:
*
* \image html rle_int32_len_5.png
* \image html rle_int64_len_5.png
*
* \par Snippet
* The code snippet below illustrates the run-length encoding of a sequence of \p int values.
* \par
* \code
* #include <cub/cub.cuh> // or equivalently <cub/device/device_run_length_encode.cuh>
*
* // Declare, allocate, and initialize device-accessible pointers for input and output
* int num_items; // e.g., 8
* int *d_in; // e.g., [0, 2, 2, 9, 5, 5, 5, 8]
* int *d_unique_out; // e.g., [ , , , , , , , ]
* int *d_counts_out; // e.g., [ , , , , , , , ]
* int *d_num_runs_out; // e.g., [ ]
* ...
*
* // Determine temporary device storage requirements
* void *d_temp_storage = NULL;
* size_t temp_storage_bytes = 0;
* cub::DeviceRunLengthEncode::Encode(d_temp_storage, temp_storage_bytes, d_in, d_unique_out, d_counts_out, d_num_runs_out, num_items);
*
* // Allocate temporary storage
* cudaMalloc(&d_temp_storage, temp_storage_bytes);
*
* // Run encoding
* cub::DeviceRunLengthEncode::Encode(d_temp_storage, temp_storage_bytes, d_in, d_unique_out, d_counts_out, d_num_runs_out, num_items);
*
* // d_unique_out <-- [0, 2, 9, 5, 8]
* // d_counts_out <-- [1, 2, 1, 3, 1]
* // d_num_runs_out <-- [5]
*
* \endcode
*
* \tparam InputIteratorT <b>[inferred]</b> Random-access input iterator type for reading input items \iterator
* \tparam UniqueOutputIteratorT <b>[inferred]</b> Random-access output iterator type for writing unique output items \iterator
* \tparam LengthsOutputIteratorT <b>[inferred]</b> Random-access output iterator type for writing output counts \iterator
* \tparam NumRunsOutputIteratorT <b>[inferred]</b> Output iterator type for recording the number of runs encountered \iterator
*/
template <
typename InputIteratorT,
typename UniqueOutputIteratorT,
typename LengthsOutputIteratorT,
typename NumRunsOutputIteratorT>
CUB_RUNTIME_FUNCTION __forceinline__
static cudaError_t Encode(
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 keys
UniqueOutputIteratorT d_unique_out, ///< [out] Pointer to the output sequence of unique keys (one key per run)
LengthsOutputIteratorT d_counts_out, ///< [out] Pointer to the output sequence of run-lengths (one count per run)
NumRunsOutputIteratorT d_num_runs_out, ///< [out] Pointer to total number of runs
int num_items, ///< [in] Total number of associated key+value pairs (i.e., the length of \p d_in_keys and \p d_in_values)
cudaStream_t stream = 0, ///< [in] <b>[optional]</b> CUDA stream to launch kernels within. Default is stream<sub>0</sub>.
bool debug_synchronous = false) ///< [in] <b>[optional]</b> Whether or not to synchronize the stream after every kernel launch to check for errors. May cause significant slowdown. Default is \p false.
{
typedef int OffsetT; // Signed integer type for global offsets
typedef NullType* FlagIterator; // FlagT iterator type (not used)
typedef NullType SelectOp; // Selection op (not used)
typedef Equality EqualityOp; // Default == operator
typedef cub::Sum ReductionOp; // Value reduction operator
// The lengths output value type
typedef typename If<(Equals<typename std::iterator_traits<LengthsOutputIteratorT>::value_type, void>::VALUE), // LengthT = (if output iterator's value type is void) ?
OffsetT, // ... then the OffsetT type,
typename std::iterator_traits<LengthsOutputIteratorT>::value_type>::Type LengthT; // ... else the output iterator's value type
// Generator type for providing 1s values for run-length reduction
typedef ConstantInputIterator<LengthT, OffsetT> LengthsInputIteratorT;
return DispatchReduceByKey<InputIteratorT, UniqueOutputIteratorT, LengthsInputIteratorT, LengthsOutputIteratorT, NumRunsOutputIteratorT, EqualityOp, ReductionOp, OffsetT>::Dispatch(
d_temp_storage,
temp_storage_bytes,
d_in,
d_unique_out,
LengthsInputIteratorT((LengthT) 1),
d_counts_out,
d_num_runs_out,
EqualityOp(),
ReductionOp(),
num_items,
stream,
debug_synchronous);
}
/**
* \brief Enumerates the starting offsets and lengths of all non-trivial runs (of length > 1) of same-valued keys in the sequence \p d_in.
*
* \par
* - For the <em>i</em><sup>th</sup> non-trivial run, the run's starting offset
* and its length are written to <tt>d_offsets_out[<em>i</em>]</tt> and
* <tt>d_lengths_out[<em>i</em>]</tt>, respectively.
* - The total number of runs encountered is written to \p d_num_runs_out.
* - The <tt>==</tt> equality operator is used to determine whether values are equivalent
* - \devicestorage
*
* \par Performance
*
* \par Snippet
* The code snippet below illustrates the identification of non-trivial runs within a sequence of \p int values.
* \par
* \code
* #include <cub/cub.cuh> // or equivalently <cub/device/device_run_length_encode.cuh>
*
* // Declare, allocate, and initialize device-accessible pointers for input and output
* int num_items; // e.g., 8
* int *d_in; // e.g., [0, 2, 2, 9, 5, 5, 5, 8]
* int *d_offsets_out; // e.g., [ , , , , , , , ]
* int *d_lengths_out; // e.g., [ , , , , , , , ]
* int *d_num_runs_out; // e.g., [ ]
* ...
*
* // Determine temporary device storage requirements
* void *d_temp_storage = NULL;
* size_t temp_storage_bytes = 0;
* cub::DeviceRunLengthEncode::NonTrivialRuns(d_temp_storage, temp_storage_bytes, d_in, d_offsets_out, d_lengths_out, d_num_runs_out, num_items);
*
* // Allocate temporary storage
* cudaMalloc(&d_temp_storage, temp_storage_bytes);
*
* // Run encoding
* cub::DeviceRunLengthEncode::NonTrivialRuns(d_temp_storage, temp_storage_bytes, d_in, d_offsets_out, d_lengths_out, d_num_runs_out, num_items);
*
* // d_offsets_out <-- [1, 4]
* // d_lengths_out <-- [2, 3]
* // d_num_runs_out <-- [2]
*
* \endcode
*
* \tparam InputIteratorT <b>[inferred]</b> Random-access input iterator type for reading input items \iterator
* \tparam OffsetsOutputIteratorT <b>[inferred]</b> Random-access output iterator type for writing run-offset values \iterator
* \tparam LengthsOutputIteratorT <b>[inferred]</b> Random-access output iterator type for writing run-length values \iterator
* \tparam NumRunsOutputIteratorT <b>[inferred]</b> Output iterator type for recording the number of runs encountered \iterator
*/
template <
typename InputIteratorT,
typename OffsetsOutputIteratorT,
typename LengthsOutputIteratorT,
typename NumRunsOutputIteratorT>
CUB_RUNTIME_FUNCTION __forceinline__
static cudaError_t NonTrivialRuns(
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 input sequence of data items
OffsetsOutputIteratorT d_offsets_out, ///< [out] Pointer to output sequence of run-offsets (one offset per non-trivial run)
LengthsOutputIteratorT d_lengths_out, ///< [out] Pointer to output sequence of run-lengths (one count per non-trivial run)
NumRunsOutputIteratorT d_num_runs_out, ///< [out] Pointer to total number of runs (i.e., length of \p d_offsets_out)
int num_items, ///< [in] Total number of associated key+value pairs (i.e., the length of \p d_in_keys and \p d_in_values)
cudaStream_t stream = 0, ///< [in] <b>[optional]</b> CUDA stream to launch kernels within. Default is stream<sub>0</sub>.
bool debug_synchronous = false) ///< [in] <b>[optional]</b> Whether or not to synchronize the stream after every kernel launch to check for errors. May cause significant slowdown. Default is \p false.
{
typedef int OffsetT; // Signed integer type for global offsets
typedef Equality EqualityOp; // Default == operator
return DeviceRleDispatch<InputIteratorT, OffsetsOutputIteratorT, LengthsOutputIteratorT, NumRunsOutputIteratorT, EqualityOp, OffsetT>::Dispatch(
d_temp_storage,
temp_storage_bytes,
d_in,
d_offsets_out,
d_lengths_out,
d_num_runs_out,
EqualityOp(),
num_items,
stream,
debug_synchronous);
}
};
} // CUB namespace
CUB_NS_POSTFIX // Optional outer namespace(s)
|