/home/runner/work/cccl/cccl/cub/cub/thread/thread_search.cuh

File members: /home/runner/work/cccl/cccl/cub/cub/thread/thread_search.cuh

/******************************************************************************
 * 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
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 * 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;
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 * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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#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/util_namespace.cuh>
#include <cub/util_type.cuh>

#include <iterator>

#include <nv/target>

CUB_NAMESPACE_BEGIN

template <typename AIteratorT, typename BIteratorT, typename OffsetT, typename CoordinateT>
_CCCL_HOST_DEVICE _CCCL_FORCEINLINE void MergePathSearch(
  OffsetT diagonal, AIteratorT a, BIteratorT b, OffsetT a_len, OffsetT b_len, CoordinateT& path_coordinate)
{
  using T = cub::detail::value_t<AIteratorT>;

  OffsetT split_min = CUB_MAX(diagonal - b_len, 0);
  OffsetT split_max = CUB_MIN(diagonal, a_len);

  while (split_min < split_max)
  {
    OffsetT split_pivot = (split_min + split_max) >> 1;
    if (a[split_pivot] <= b[diagonal - split_pivot - 1])
    {
      // Move candidate split range up A, down B
      split_min = split_pivot + 1;
    }
    else
    {
      // Move candidate split range up B, down A
      split_max = split_pivot;
    }
  }

  path_coordinate.x = CUB_MIN(split_min, a_len);
  path_coordinate.y = diagonal - split_min;
}

template <typename InputIteratorT, typename OffsetT, typename T>
_CCCL_DEVICE _CCCL_FORCEINLINE OffsetT LowerBound(InputIteratorT input, OffsetT num_items, T val)
{
  OffsetT retval = 0;
  while (num_items > 0)
  {
    OffsetT half = num_items >> 1;
    if (input[retval + half] < val)
    {
      retval    = retval + (half + 1);
      num_items = num_items - (half + 1);
    }
    else
    {
      num_items = half;
    }
  }

  return retval;
}

template <typename InputIteratorT, typename OffsetT, typename T>
_CCCL_DEVICE _CCCL_FORCEINLINE OffsetT UpperBound(InputIteratorT input, OffsetT num_items, T val)
{
  OffsetT retval = 0;
  while (num_items > 0)
  {
    OffsetT half = num_items >> 1;
    if (val < input[retval + half])
    {
      num_items = half;
    }
    else
    {
      retval    = retval + (half + 1);
      num_items = num_items - (half + 1);
    }
  }

  return retval;
}

#if defined(__CUDA_FP16_TYPES_EXIST__)

template <typename InputIteratorT, typename OffsetT>
_CCCL_DEVICE _CCCL_FORCEINLINE OffsetT UpperBound(InputIteratorT input, OffsetT num_items, __half val)
{
  OffsetT retval = 0;
  while (num_items > 0)
  {
    OffsetT half = num_items >> 1;

    bool lt;
    NV_IF_TARGET(NV_PROVIDES_SM_53,
                 (lt = __hlt(val, input[retval + half]);),
                 (lt = __half2float(val) < __half2float(input[retval + half]);));

    if (lt)
    {
      num_items = half;
    }
    else
    {
      retval    = retval + (half + 1);
      num_items = num_items - (half + 1);
    }
  }

  return retval;
}
#endif // __CUDA_FP16_TYPES_EXIST__

CUB_NAMESPACE_END