block_histogram.cuh 15.9 KB
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415
/******************************************************************************
 * 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
 * The cub::BlockHistogram class provides [<em>collective</em>](index.html#sec0) methods for constructing block-wide histograms from data samples partitioned across a CUDA thread block.
 */

#pragma once

#include "specializations/block_histogram_sort.cuh"
#include "specializations/block_histogram_atomic.cuh"
#include "../util_ptx.cuh"
#include "../util_arch.cuh"
#include "../util_namespace.cuh"

/// Optional outer namespace(s)
CUB_NS_PREFIX

/// CUB namespace
namespace cub {


/******************************************************************************
 * Algorithmic variants
 ******************************************************************************/

/**
 * \brief BlockHistogramAlgorithm enumerates alternative algorithms for the parallel construction of block-wide histograms.
 */
enum BlockHistogramAlgorithm
{

    /**
     * \par Overview
     * Sorting followed by differentiation.  Execution is comprised of two phases:
     * -# Sort the data using efficient radix sort
     * -# Look for "runs" of same-valued keys by detecting discontinuities; the run-lengths are histogram bin counts.
     *
     * \par Performance Considerations
     * Delivers consistent throughput regardless of sample bin distribution.
     */
    BLOCK_HISTO_SORT,


    /**
     * \par Overview
     * Use atomic addition to update byte counts directly
     *
     * \par Performance Considerations
     * Performance is strongly tied to the hardware implementation of atomic
     * addition, and may be significantly degraded for non uniformly-random
     * input distributions where many concurrent updates are likely to be
     * made to the same bin counter.
     */
    BLOCK_HISTO_ATOMIC,
};



/******************************************************************************
 * Block histogram
 ******************************************************************************/


/**
 * \brief The BlockHistogram class provides [<em>collective</em>](index.html#sec0) methods for constructing block-wide histograms from data samples partitioned across a CUDA thread block. ![](histogram_logo.png)
 * \ingroup BlockModule
 *
 * \tparam T                    The sample type being histogrammed (must be castable to an integer bin identifier)
 * \tparam BLOCK_DIM_X          The thread block length in threads along the X dimension
 * \tparam ITEMS_PER_THREAD     The number of items per thread
 * \tparam BINS                 The number bins within the histogram
 * \tparam ALGORITHM            <b>[optional]</b> cub::BlockHistogramAlgorithm enumerator specifying the underlying algorithm to use (default: cub::BLOCK_HISTO_SORT)
 * \tparam BLOCK_DIM_Y          <b>[optional]</b> The thread block length in threads along the Y dimension (default: 1)
 * \tparam BLOCK_DIM_Z          <b>[optional]</b> The thread block length in threads along the Z dimension (default: 1)
 * \tparam PTX_ARCH             <b>[optional]</b> \ptxversion
 *
 * \par Overview
 * - A <a href="http://en.wikipedia.org/wiki/Histogram"><em>histogram</em></a>
 *   counts the number of observations that fall into each of the disjoint categories (known as <em>bins</em>).
 * - BlockHistogram can be optionally specialized to use different algorithms:
 *   -# <b>cub::BLOCK_HISTO_SORT</b>.  Sorting followed by differentiation. [More...](\ref cub::BlockHistogramAlgorithm)
 *   -# <b>cub::BLOCK_HISTO_ATOMIC</b>.  Use atomic addition to update byte counts directly. [More...](\ref cub::BlockHistogramAlgorithm)
 *
 * \par Performance Considerations
 * - \granularity
 *
 * \par A Simple Example
 * \blockcollective{BlockHistogram}
 * \par
 * The code snippet below illustrates a 256-bin histogram of 512 integer samples that
 * are partitioned across 128 threads where each thread owns 4 samples.
 * \par
 * \code
 * #include <cub/cub.cuh>   // or equivalently <cub/block/block_histogram.cuh>
 *
 * __global__ void ExampleKernel(...)
 * {
 *     // Specialize a 256-bin BlockHistogram type for a 1D block of 128 threads having 4 character samples each
 *     typedef cub::BlockHistogram<unsigned char, 128, 4, 256> BlockHistogram;
 *
 *     // Allocate shared memory for BlockHistogram
 *     __shared__ typename BlockHistogram::TempStorage temp_storage;
 *
 *     // Allocate shared memory for block-wide histogram bin counts
 *     __shared__ unsigned int smem_histogram[256];
 *
 *     // Obtain input samples per thread
 *     unsigned char data[4];
 *     ...
 *
 *     // Compute the block-wide histogram
 *     BlockHistogram(temp_storage).Histogram(data, smem_histogram);
 *
 * \endcode
 *
 * \par Performance and Usage Considerations
 * - The histogram output can be constructed in shared or device-accessible memory
 * - See cub::BlockHistogramAlgorithm for performance details regarding algorithmic alternatives
 *
 */
template <
    typename                T,
    int                     BLOCK_DIM_X,
    int                     ITEMS_PER_THREAD,
    int                     BINS,
    BlockHistogramAlgorithm ALGORITHM           = BLOCK_HISTO_SORT,
    int                     BLOCK_DIM_Y         = 1,
    int                     BLOCK_DIM_Z         = 1,
    int                     PTX_ARCH            = CUB_PTX_ARCH>
class BlockHistogram
{
private:

    /******************************************************************************
     * Constants and type definitions
     ******************************************************************************/

    /// Constants
    enum
    {
        /// The thread block size in threads
        BLOCK_THREADS = BLOCK_DIM_X * BLOCK_DIM_Y * BLOCK_DIM_Z,
    };

    /**
     * Ensure the template parameterization meets the requirements of the
     * targeted device architecture.  BLOCK_HISTO_ATOMIC can only be used
     * on version SM120 or later.  Otherwise BLOCK_HISTO_SORT is used
     * regardless.
     */
    static const BlockHistogramAlgorithm SAFE_ALGORITHM =
        ((ALGORITHM == BLOCK_HISTO_ATOMIC) && (PTX_ARCH < 120)) ?
            BLOCK_HISTO_SORT :
            ALGORITHM;

    /// Internal specialization.
    typedef typename If<(SAFE_ALGORITHM == BLOCK_HISTO_SORT),
        BlockHistogramSort<T, BLOCK_DIM_X, ITEMS_PER_THREAD, BINS, BLOCK_DIM_Y, BLOCK_DIM_Z, PTX_ARCH>,
        BlockHistogramAtomic<BINS> >::Type InternalBlockHistogram;

    /// Shared memory storage layout type for BlockHistogram
    typedef typename InternalBlockHistogram::TempStorage _TempStorage;


    /******************************************************************************
     * Thread fields
     ******************************************************************************/

    /// Shared storage reference
    _TempStorage &temp_storage;

    /// Linear thread-id
    unsigned int linear_tid;


    /******************************************************************************
     * Utility methods
     ******************************************************************************/

    /// Internal storage allocator
    __device__ __forceinline__ _TempStorage& PrivateStorage()
    {
        __shared__ _TempStorage private_storage;
        return private_storage;
    }


public:

    /// \smemstorage{BlockHistogram}
    struct TempStorage : Uninitialized<_TempStorage> {};


    /******************************************************************//**
     * \name Collective constructors
     *********************************************************************/
    //@{

    /**
     * \brief Collective constructor using a private static allocation of shared memory as temporary storage.
     */
    __device__ __forceinline__ BlockHistogram()
    :
        temp_storage(PrivateStorage()),
        linear_tid(RowMajorTid(BLOCK_DIM_X, BLOCK_DIM_Y, BLOCK_DIM_Z))
    {}


    /**
     * \brief Collective constructor using the specified memory allocation as temporary storage.
     */
    __device__ __forceinline__ BlockHistogram(
        TempStorage &temp_storage)             ///< [in] Reference to memory allocation having layout type TempStorage
    :
        temp_storage(temp_storage.Alias()),
        linear_tid(RowMajorTid(BLOCK_DIM_X, BLOCK_DIM_Y, BLOCK_DIM_Z))
    {}


    //@}  end member group
    /******************************************************************//**
     * \name Histogram operations
     *********************************************************************/
    //@{


    /**
     * \brief Initialize the shared histogram counters to zero.
     *
     * \par Snippet
     * The code snippet below illustrates a the initialization and update of a
     * histogram of 512 integer samples that are partitioned across 128 threads
     * where each thread owns 4 samples.
     * \par
     * \code
     * #include <cub/cub.cuh>   // or equivalently <cub/block/block_histogram.cuh>
     *
     * __global__ void ExampleKernel(...)
     * {
     *     // Specialize a 256-bin BlockHistogram type for a 1D block of 128 threads having 4 character samples each
     *     typedef cub::BlockHistogram<unsigned char, 128, 4, 256> BlockHistogram;
     *
     *     // Allocate shared memory for BlockHistogram
     *     __shared__ typename BlockHistogram::TempStorage temp_storage;
     *
     *     // Allocate shared memory for block-wide histogram bin counts
     *     __shared__ unsigned int smem_histogram[256];
     *
     *     // Obtain input samples per thread
     *     unsigned char thread_samples[4];
     *     ...
     *
     *     // Initialize the block-wide histogram
     *     BlockHistogram(temp_storage).InitHistogram(smem_histogram);
     *
     *     // Update the block-wide histogram
     *     BlockHistogram(temp_storage).Composite(thread_samples, smem_histogram);
     *
     * \endcode
     *
     * \tparam CounterT              <b>[inferred]</b> Histogram counter type
     */
    template <typename CounterT     >
    __device__ __forceinline__ void InitHistogram(CounterT      histogram[BINS])
    {
        // Initialize histogram bin counts to zeros
        int histo_offset = 0;

        #pragma unroll
        for(; histo_offset + BLOCK_THREADS <= BINS; histo_offset += BLOCK_THREADS)
        {
            histogram[histo_offset + linear_tid] = 0;
        }
        // Finish up with guarded initialization if necessary
        if ((BINS % BLOCK_THREADS != 0) && (histo_offset + linear_tid < BINS))
        {
            histogram[histo_offset + linear_tid] = 0;
        }
    }


    /**
     * \brief Constructs a block-wide histogram in shared/device-accessible memory.  Each thread contributes an array of input elements.
     *
     * \par
     * - \granularity
     * - \smemreuse
     *
     * \par Snippet
     * The code snippet below illustrates a 256-bin histogram of 512 integer samples that
     * are partitioned across 128 threads where each thread owns 4 samples.
     * \par
     * \code
     * #include <cub/cub.cuh>   // or equivalently <cub/block/block_histogram.cuh>
     *
     * __global__ void ExampleKernel(...)
     * {
     *     // Specialize a 256-bin BlockHistogram type for a 1D block of 128 threads having 4 character samples each
     *     typedef cub::BlockHistogram<unsigned char, 128, 4, 256> BlockHistogram;
     *
     *     // Allocate shared memory for BlockHistogram
     *     __shared__ typename BlockHistogram::TempStorage temp_storage;
     *
     *     // Allocate shared memory for block-wide histogram bin counts
     *     __shared__ unsigned int smem_histogram[256];
     *
     *     // Obtain input samples per thread
     *     unsigned char thread_samples[4];
     *     ...
     *
     *     // Compute the block-wide histogram
     *     BlockHistogram(temp_storage).Histogram(thread_samples, smem_histogram);
     *
     * \endcode
     *
     * \tparam CounterT              <b>[inferred]</b> Histogram counter type
     */
    template <
        typename            CounterT     >
    __device__ __forceinline__ void Histogram(
        T                   (&items)[ITEMS_PER_THREAD],     ///< [in] Calling thread's input values to histogram
        CounterT             histogram[BINS])                ///< [out] Reference to shared/device-accessible memory histogram
    {
        // Initialize histogram bin counts to zeros
        InitHistogram(histogram);

        CTA_SYNC();

        // Composite the histogram
        InternalBlockHistogram(temp_storage).Composite(items, histogram);
    }



    /**
     * \brief Updates an existing block-wide histogram in shared/device-accessible memory.  Each thread composites an array of input elements.
     *
     * \par
     * - \granularity
     * - \smemreuse
     *
     * \par Snippet
     * The code snippet below illustrates a the initialization and update of a
     * histogram of 512 integer samples that are partitioned across 128 threads
     * where each thread owns 4 samples.
     * \par
     * \code
     * #include <cub/cub.cuh>   // or equivalently <cub/block/block_histogram.cuh>
     *
     * __global__ void ExampleKernel(...)
     * {
     *     // Specialize a 256-bin BlockHistogram type for a 1D block of 128 threads having 4 character samples each
     *     typedef cub::BlockHistogram<unsigned char, 128, 4, 256> BlockHistogram;
     *
     *     // Allocate shared memory for BlockHistogram
     *     __shared__ typename BlockHistogram::TempStorage temp_storage;
     *
     *     // Allocate shared memory for block-wide histogram bin counts
     *     __shared__ unsigned int smem_histogram[256];
     *
     *     // Obtain input samples per thread
     *     unsigned char thread_samples[4];
     *     ...
     *
     *     // Initialize the block-wide histogram
     *     BlockHistogram(temp_storage).InitHistogram(smem_histogram);
     *
     *     // Update the block-wide histogram
     *     BlockHistogram(temp_storage).Composite(thread_samples, smem_histogram);
     *
     * \endcode
     *
     * \tparam CounterT              <b>[inferred]</b> Histogram counter type
     */
    template <
        typename            CounterT     >
    __device__ __forceinline__ void Composite(
        T                   (&items)[ITEMS_PER_THREAD],     ///< [in] Calling thread's input values to histogram
        CounterT             histogram[BINS])                 ///< [out] Reference to shared/device-accessible memory histogram
    {
        InternalBlockHistogram(temp_storage).Composite(items, histogram);
    }

};

}               // CUB namespace
CUB_NS_POSTFIX  // Optional outer namespace(s)