view release on metacpan or  search on metacpan

xgboost/cub/cub/block/block_histogram.cuh  view on Meta::CPAN

 */

#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,