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#pragma once

#include <cub/agent/agent_segmented_radix_sort.cuh>
#include <cub/agent/agent_sub_warp_merge_sort.cuh>
#include <cub/block/block_load.cuh>
#include <cub/block/block_merge_sort.cuh>
#include <cub/block/block_radix_rank.cuh>
#include <cub/block/block_scan.cuh>
#include <cub/detail/device_double_buffer.cuh>
#include <cub/detail/temporary_storage.cuh>
#include <cub/device/device_partition.cuh>
#include <cub/thread/thread_sort.cuh>
#include <cub/util_debug.cuh>
#include <cub/util_deprecated.cuh>
#include <cub/util_device.cuh>
#include <cub/util_math.cuh>
#include <cub/util_namespace.cuh>
#include <cub/warp/warp_merge_sort.cuh>

#include <thrust/iterator/counting_iterator.h>
#include <thrust/iterator/reverse_iterator.h>
#include <thrust/system/cuda/detail/core/triple_chevron_launch.h>

#include <nv/target>

#include <type_traits>


CUB_NAMESPACE_BEGIN


/**
 * @brief Fallback kernel, in case there's not enough segments to
 *        take advantage of partitioning.
 *
 * In this case, the sorting method is still selected based on the segment size.
 * If a single warp can sort the segment, the algorithm will use the sub-warp
 * merge sort. Otherwise, the algorithm will use the in-shared-memory version of
 * block radix sort. If data don't fit into shared memory, the algorithm will
 * use in-global-memory radix sort.
 *
 * @param[in] d_keys_in_orig
 *   Input keys buffer
 *
 * @param[out] d_keys_out_orig
 *   Output keys buffer
 *
 * @param[in,out] d_keys_double_buffer
 *   Double keys buffer
 *
 * @param[in] d_values_in_orig
 *   Input values buffer
 *
 * @param[out] d_values_out_orig
 *   Output values buffer
 *
 * @param[in,out] d_values_double_buffer
 *   Double values buffer
 *
 * @param[in] d_begin_offsets
 *   Random-access input iterator to the sequence of beginning offsets of length
 *   @p num_segments, such that `d_begin_offsets[i]` is the first element of the
 *   i-th data segment in `d_keys_*` and `d_values_*`
 *
 * @param[in] d_end_offsets
 *   Random-access input iterator to the sequence of ending offsets of length
 *   @p num_segments, such that `d_end_offsets[i]-1` is the last element of the
 *   i-th data segment in `d_keys_*` and `d_values_*`.
 *   If `d_end_offsets[i]-1 <= d_begin_offsets[i]`, the i-th segment is
 *   considered empty.
 */
template <bool IS_DESCENDING,
          typename ChainedPolicyT,
          typename KeyT,
          typename ValueT,
          typename BeginOffsetIteratorT,
          typename EndOffsetIteratorT,
          typename OffsetT>
__launch_bounds__(ChainedPolicyT::ActivePolicy::LargeSegmentPolicy::BLOCK_THREADS)
  CUB_DETAIL_KERNEL_ATTRIBUTES void DeviceSegmentedSortFallbackKernel(
    const KeyT *d_keys_in_orig,
    KeyT *d_keys_out_orig,
    cub::detail::device_double_buffer<KeyT> d_keys_double_buffer,
    const ValueT *d_values_in_orig,
    ValueT *d_values_out_orig,
    cub::detail::device_double_buffer<ValueT> d_values_double_buffer,
    BeginOffsetIteratorT d_begin_offsets,
    EndOffsetIteratorT d_end_offsets)
{
  using ActivePolicyT = typename ChainedPolicyT::ActivePolicy;
  using LargeSegmentPolicyT = typename ActivePolicyT::LargeSegmentPolicy;
  using MediumPolicyT =
    typename ActivePolicyT::SmallAndMediumSegmentedSortPolicyT::MediumPolicyT;

  const unsigned int segment_id = blockIdx.x;
  OffsetT segment_begin         = d_begin_offsets[segment_id];
  OffsetT segment_end           = d_end_offsets[segment_id];
  OffsetT num_items             = segment_end - segment_begin;

  if (num_items <= 0)
  {
    return;
  }

  using AgentSegmentedRadixSortT =
    cub::AgentSegmentedRadixSort<IS_DESCENDING,
                                 LargeSegmentPolicyT,
                                 KeyT,
                                 ValueT,
                                 OffsetT>;

  using WarpReduceT = cub::WarpReduce<KeyT>;

  using AgentWarpMergeSortT =
    AgentSubWarpSort<IS_DESCENDING, MediumPolicyT, KeyT, ValueT, OffsetT>;

  __shared__ union
  {
    typename AgentSegmentedRadixSortT::TempStorage block_sort;
    typename WarpReduceT::TempStorage warp_reduce;
    typename AgentWarpMergeSortT::TempStorage medium_warp_sort;
  } temp_storage;

  constexpr bool keys_only = std::is_same<ValueT, NullType>::value;
  AgentSegmentedRadixSortT agent(num_items, temp_storage.block_sort);

  constexpr int begin_bit = 0;
  constexpr int end_bit = sizeof(KeyT) * 8;

  constexpr int cacheable_tile_size = LargeSegmentPolicyT::BLOCK_THREADS *
                                      LargeSegmentPolicyT::ITEMS_PER_THREAD;

  d_keys_in_orig += segment_begin;
  d_keys_out_orig += segment_begin;

  if (!keys_only)
  {
    d_values_in_orig += segment_begin;
    d_values_out_orig += segment_begin;
  }

  if (num_items <= MediumPolicyT::ITEMS_PER_TILE)
  {
    // Sort by a single warp
    if (threadIdx.x < MediumPolicyT::WARP_THREADS)
    {
      AgentWarpMergeSortT(temp_storage.medium_warp_sort)
        .ProcessSegment(num_items,
                        d_keys_in_orig,
                        d_keys_out_orig,
                        d_values_in_orig,
                        d_values_out_orig);
    }
  }
  else if (num_items < cacheable_tile_size)
  {
    // Sort by a CTA if data fits into shared memory
    agent.ProcessSinglePass(begin_bit,
                            end_bit,
                            d_keys_in_orig,
                            d_values_in_orig,
                            d_keys_out_orig,
                            d_values_out_orig);
  }
  else
  {
    // Sort by a CTA with multiple reads from global memory
    int current_bit = begin_bit;
    int pass_bits = (cub::min)(int{LargeSegmentPolicyT::RADIX_BITS},
                               (end_bit - current_bit));

    d_keys_double_buffer = cub::detail::device_double_buffer<KeyT>(
      d_keys_double_buffer.current() + segment_begin,
      d_keys_double_buffer.alternate() + segment_begin);

    if (!keys_only)
    {
      d_values_double_buffer = cub::detail::device_double_buffer<ValueT>(
        d_values_double_buffer.current() + segment_begin,
        d_values_double_buffer.alternate() + segment_begin);
    }

    agent.ProcessIterative(current_bit,
                           pass_bits,
                           d_keys_in_orig,
                           d_values_in_orig,
                           d_keys_double_buffer.current(),
                           d_values_double_buffer.current());
    current_bit += pass_bits;

    #pragma unroll 1
    while (current_bit < end_bit)
    {
      pass_bits = (cub::min)(int{LargeSegmentPolicyT::RADIX_BITS},
                             (end_bit - current_bit));

      CTA_SYNC();
      agent.ProcessIterative(current_bit,
                             pass_bits,
                             d_keys_double_buffer.current(),
                             d_values_double_buffer.current(),
                             d_keys_double_buffer.alternate(),
                             d_values_double_buffer.alternate());

      d_keys_double_buffer.swap();
      d_values_double_buffer.swap();
      current_bit += pass_bits;
    }
  }
}


/**
 * @brief Single kernel for moderate size (less than a few thousand items)
 *        segments.
 *
 * This kernel allocates a sub-warp per segment. Therefore, this kernel assigns
 * a single thread block to multiple segments. Segments fall into two
 * categories. An architectural warp usually sorts segments in the medium-size
 * category, while a few threads sort segments in the small-size category. Since
 * segments are partitioned, we know the last thread block index assigned to
 * sort medium-size segments. A particular thread block can check this number to
 * find out which category it was assigned to sort. In both cases, the
 * merge sort is used.
 *
 * @param[in] small_segments
 *   Number of segments that can be sorted by a warp part
 *
 * @param[in] medium_segments
 *   Number of segments that can be sorted by a warp
 *
 * @param[in] medium_blocks
 *   Number of CTAs assigned to process medium segments
 *
 * @param[in] d_small_segments_indices
 *   Small segments mapping of length @p small_segments, such that
 *   `d_small_segments_indices[i]` is the input segment index
 *
 * @param[in] d_medium_segments_indices
 *   Medium segments mapping of length @p medium_segments, such that
 *   `d_medium_segments_indices[i]` is the input segment index
 *
 * @param[in] d_keys_in_orig
 *   Input keys buffer
 *
 * @param[out] d_keys_out_orig
 *   Output keys buffer
 *
 * @param[in] d_values_in_orig
 *   Input values buffer
 *
 * @param[out] d_values_out_orig
 *   Output values buffer
 *
 * @param[in] d_begin_offsets
 *   Random-access input iterator to the sequence of beginning offsets of length
 *   @p num_segments, such that `d_begin_offsets[i]` is the first element of the
 *   <em>i</em><sup>th</sup> data segment in `d_keys_*` and `d_values_*`
 *
 * @param[in] d_end_offsets
 *   Random-access input iterator to the sequence of ending offsets of length
 *   @p num_segments, such that `d_end_offsets[i]-1` is the last element of the
 *   <em>i</em><sup>th</sup> data segment in `d_keys_*` and `d_values_*`. If
 *   `d_end_offsets[i]-1 <= d_begin_offsets[i]`, the <em>i</em><sup>th</sup> is
 *   considered empty.
 */
template <bool IS_DESCENDING,
          typename ChainedPolicyT,
          typename KeyT,
          typename ValueT,
          typename BeginOffsetIteratorT,
          typename EndOffsetIteratorT,
          typename OffsetT>
__launch_bounds__(ChainedPolicyT::ActivePolicy::SmallAndMediumSegmentedSortPolicyT::BLOCK_THREADS)
  CUB_DETAIL_KERNEL_ATTRIBUTES
  void DeviceSegmentedSortKernelSmall(unsigned int small_segments,
                                      unsigned int medium_segments,
                                      unsigned int medium_blocks,
                                      const unsigned int *d_small_segments_indices,
                                      const unsigned int *d_medium_segments_indices,
                                      const KeyT *d_keys_in,
                                      KeyT *d_keys_out,
                                      const ValueT *d_values_in,
                                      ValueT *d_values_out,
                                      BeginOffsetIteratorT d_begin_offsets,
                                      EndOffsetIteratorT d_end_offsets)
{
  const unsigned int tid = threadIdx.x;
  const unsigned int bid = blockIdx.x;

  using ActivePolicyT = typename ChainedPolicyT::ActivePolicy;
  using SmallAndMediumPolicyT =
    typename ActivePolicyT::SmallAndMediumSegmentedSortPolicyT;
  using MediumPolicyT = typename SmallAndMediumPolicyT::MediumPolicyT;
  using SmallPolicyT  = typename SmallAndMediumPolicyT::SmallPolicyT;

  constexpr int threads_per_medium_segment = MediumPolicyT::WARP_THREADS;
  constexpr int threads_per_small_segment = SmallPolicyT::WARP_THREADS;

  using MediumAgentWarpMergeSortT =
    AgentSubWarpSort<IS_DESCENDING, MediumPolicyT, KeyT, ValueT, OffsetT>;

  using SmallAgentWarpMergeSortT =
    AgentSubWarpSort<IS_DESCENDING, SmallPolicyT, KeyT, ValueT, OffsetT>;

  constexpr auto segments_per_medium_block =
    static_cast<unsigned int>(SmallAndMediumPolicyT::SEGMENTS_PER_MEDIUM_BLOCK);

  constexpr auto segments_per_small_block =
    static_cast<unsigned int>(SmallAndMediumPolicyT::SEGMENTS_PER_SMALL_BLOCK);

  __shared__ union
  {
    typename MediumAgentWarpMergeSortT::TempStorage
      medium_storage[segments_per_medium_block];

    typename SmallAgentWarpMergeSortT::TempStorage
      small_storage[segments_per_small_block];
  } temp_storage;

  if (bid < medium_blocks)
  {
    const unsigned int sid_within_block = tid / threads_per_medium_segment;
    const unsigned int medium_segment_id = bid * segments_per_medium_block +
                                           sid_within_block;

    if (medium_segment_id < medium_segments)
    {
      const unsigned int global_segment_id =
        d_medium_segments_indices[medium_segment_id];

      const OffsetT segment_begin = d_begin_offsets[global_segment_id];
      const OffsetT segment_end   = d_end_offsets[global_segment_id];
      const OffsetT num_items     = segment_end - segment_begin;

      MediumAgentWarpMergeSortT(temp_storage.medium_storage[sid_within_block])
        .ProcessSegment(num_items,
                        d_keys_in + segment_begin,
                        d_keys_out + segment_begin,
                        d_values_in + segment_begin,
                        d_values_out + segment_begin);
    }
  }
  else
  {
    const unsigned int sid_within_block = tid / threads_per_small_segment;
    const unsigned int small_segment_id =
      (bid - medium_blocks) * segments_per_small_block + sid_within_block;

    if (small_segment_id < small_segments)
    {
      const unsigned int global_segment_id =
        d_small_segments_indices[small_segment_id];

      const OffsetT segment_begin = d_begin_offsets[global_segment_id];
      const OffsetT segment_end   = d_end_offsets[global_segment_id];
      const OffsetT num_items     = segment_end - segment_begin;

      SmallAgentWarpMergeSortT(temp_storage.small_storage[sid_within_block])
        .ProcessSegment(num_items,
                        d_keys_in + segment_begin,
                        d_keys_out + segment_begin,
                        d_values_in + segment_begin,
                        d_values_out + segment_begin);
    }
  }
}

/**
 * @brief Single kernel for large size (more than a few thousand items) segments.
 *
 * @param[in] d_keys_in_orig
 *   Input keys buffer
 *
 * @param[out] d_keys_out_orig
 *   Output keys buffer
 *
 * @param[in] d_values_in_orig
 *   Input values buffer
 *
 * @param[out] d_values_out_orig
 *   Output values buffer
 *
 * @param[in] d_begin_offsets
 *   Random-access input iterator to the sequence of beginning offsets of length
 *   @p num_segments, such that `d_begin_offsets[i]` is the first element of the
 *   <em>i</em><sup>th</sup> data segment in `d_keys_*` and `d_values_*`
 *
 * @param[in] d_end_offsets
 *   Random-access input iterator to the sequence of ending offsets of length
 *   @p num_segments, such that `d_end_offsets[i]-1` is the last element of the
 *   <em>i</em><sup>th</sup> data segment in `d_keys_*` and `d_values_*`. If
 *   `d_end_offsets[i]-1 <= d_begin_offsets[i]`, the <em>i</em><sup>th</sup> is
 *   considered empty.
 */
template <bool IS_DESCENDING,
          typename ChainedPolicyT,
          typename KeyT,
          typename ValueT,
          typename BeginOffsetIteratorT,
          typename EndOffsetIteratorT,
          typename OffsetT>
__launch_bounds__(ChainedPolicyT::ActivePolicy::LargeSegmentPolicy::BLOCK_THREADS)
  CUB_DETAIL_KERNEL_ATTRIBUTES void DeviceSegmentedSortKernelLarge(
    const unsigned int *d_segments_indices,
    const KeyT *d_keys_in_orig,
    KeyT *d_keys_out_orig,
    cub::detail::device_double_buffer<KeyT> d_keys_double_buffer,
    const ValueT *d_values_in_orig,
    ValueT *d_values_out_orig,
    cub::detail::device_double_buffer<ValueT> d_values_double_buffer,
    BeginOffsetIteratorT d_begin_offsets,
    EndOffsetIteratorT d_end_offsets)
{
  using ActivePolicyT = typename ChainedPolicyT::ActivePolicy;
  using LargeSegmentPolicyT = typename ActivePolicyT::LargeSegmentPolicy;

  constexpr int small_tile_size = LargeSegmentPolicyT::BLOCK_THREADS *
                                  LargeSegmentPolicyT::ITEMS_PER_THREAD;

  using AgentSegmentedRadixSortT =
    cub::AgentSegmentedRadixSort<IS_DESCENDING,
                                 LargeSegmentPolicyT,
                                 KeyT,
                                 ValueT,
                                 OffsetT>;

  __shared__ typename AgentSegmentedRadixSortT::TempStorage storage;

  const unsigned int bid = blockIdx.x;

  constexpr int begin_bit = 0;
  constexpr int end_bit   = sizeof(KeyT) * 8;

  const unsigned int global_segment_id = d_segments_indices[bid];
  const OffsetT segment_begin          = d_begin_offsets[global_segment_id];
  const OffsetT segment_end            = d_end_offsets[global_segment_id];
  const OffsetT num_items              = segment_end - segment_begin;

  constexpr bool keys_only = std::is_same<ValueT, NullType>::value;
  AgentSegmentedRadixSortT agent(num_items, storage);

  d_keys_in_orig += segment_begin;
  d_keys_out_orig += segment_begin;

  if (!keys_only)
  {
    d_values_in_orig += segment_begin;
    d_values_out_orig += segment_begin;
  }

  if (num_items < small_tile_size)
  {
    // Sort in shared memory if the segment fits into it
    agent.ProcessSinglePass(begin_bit,
                            end_bit,
                            d_keys_in_orig,
                            d_values_in_orig,
                            d_keys_out_orig,
                            d_values_out_orig);
  }
  else
  {
    // Sort reading global memory multiple times
    int current_bit = begin_bit;
    int pass_bits = (cub::min)(int{LargeSegmentPolicyT::RADIX_BITS},
                               (end_bit - current_bit));

    d_keys_double_buffer = cub::detail::device_double_buffer<KeyT>(
      d_keys_double_buffer.current() + segment_begin,
      d_keys_double_buffer.alternate() + segment_begin);

    if (!keys_only)
    {
      d_values_double_buffer = cub::detail::device_double_buffer<ValueT>(
        d_values_double_buffer.current() + segment_begin,
        d_values_double_buffer.alternate() + segment_begin);
    }

    agent.ProcessIterative(current_bit,
                           pass_bits,
                           d_keys_in_orig,
                           d_values_in_orig,
                           d_keys_double_buffer.current(),
                           d_values_double_buffer.current());
    current_bit += pass_bits;

    #pragma unroll 1
    while (current_bit < end_bit)
    {
      pass_bits = (cub::min)(int{LargeSegmentPolicyT::RADIX_BITS},
                             (end_bit - current_bit));

      CTA_SYNC();
      agent.ProcessIterative(current_bit,
                             pass_bits,
                             d_keys_double_buffer.current(),
                             d_values_double_buffer.current(),
                             d_keys_double_buffer.alternate(),
                             d_values_double_buffer.alternate());

      d_keys_double_buffer.swap();
      d_values_double_buffer.swap();
      current_bit += pass_bits;
    }
  }
}

/*
 * Continuation is called after the partitioning stage. It launches kernels
 * to sort large and small segments using the partitioning results. Separation
 * of this stage is required to eliminate device-side synchronization in
 * the CDP mode.
 */
template <typename LargeSegmentPolicyT,
          typename SmallAndMediumPolicyT,
          typename LargeKernelT,
          typename SmallKernelT,
          typename KeyT,
          typename ValueT,
          typename BeginOffsetIteratorT,
          typename EndOffsetIteratorT>
CUB_RUNTIME_FUNCTION cudaError_t
DeviceSegmentedSortContinuation(
    LargeKernelT large_kernel,
    SmallKernelT small_kernel,
    int num_segments,
    KeyT *d_current_keys,
    KeyT *d_final_keys,
    detail::device_double_buffer<KeyT> d_keys_double_buffer,
    ValueT *d_current_values,
    ValueT *d_final_values,
    detail::device_double_buffer<ValueT> d_values_double_buffer,
    BeginOffsetIteratorT d_begin_offsets,
    EndOffsetIteratorT d_end_offsets,
    unsigned int *group_sizes,
    unsigned int *large_and_medium_segments_indices,
    unsigned int *small_segments_indices,
    cudaStream_t stream)
{
  cudaError error = cudaSuccess;

  const unsigned int large_segments = group_sizes[0];

  if (large_segments > 0)
  {
    // One CTA per segment
    const unsigned int blocks_in_grid = large_segments;

    #ifdef CUB_DETAIL_DEBUG_ENABLE_LOG
    _CubLog("Invoking "
            "DeviceSegmentedSortKernelLarge<<<%d, %d, 0, %lld>>>()\n",
            static_cast<int>(blocks_in_grid),
            LargeSegmentPolicyT::BLOCK_THREADS,
            (long long)stream);
    #endif

    THRUST_NS_QUALIFIER::cuda_cub::launcher::triple_chevron(
      blocks_in_grid,
      LargeSegmentPolicyT::BLOCK_THREADS,
      0,
      stream)
      .doit(large_kernel,
            large_and_medium_segments_indices,
            d_current_keys,
            d_final_keys,
            d_keys_double_buffer,
            d_current_values,
            d_final_values,
            d_values_double_buffer,
            d_begin_offsets,
            d_end_offsets);

    // Check for failure to launch
    if (CubDebug(error = cudaPeekAtLastError()))
    {
      return error;
    }

    // Sync the stream if specified to flush runtime errors
    error = detail::DebugSyncStream(stream);
    if (CubDebug(error))
    {
      return error;
    }
  }

  const unsigned int small_segments  = group_sizes[1];
  const unsigned int medium_segments =
    static_cast<unsigned int>(num_segments) -
    (large_segments + small_segments);

  const unsigned int small_blocks =
    DivideAndRoundUp(small_segments,
                     SmallAndMediumPolicyT::SEGMENTS_PER_SMALL_BLOCK);

  const unsigned int medium_blocks =
    DivideAndRoundUp(medium_segments,
                     SmallAndMediumPolicyT::SEGMENTS_PER_MEDIUM_BLOCK);

  const unsigned int small_and_medium_blocks_in_grid = small_blocks +
                                                       medium_blocks;

  if (small_and_medium_blocks_in_grid)
  {
    #ifdef CUB_DETAIL_DEBUG_ENABLE_LOG
    _CubLog("Invoking "
            "DeviceSegmentedSortKernelSmall<<<%d, %d, 0, %lld>>>()\n",
            static_cast<int>(small_and_medium_blocks_in_grid),
            SmallAndMediumPolicyT::BLOCK_THREADS,
            (long long)stream);
    #endif

    THRUST_NS_QUALIFIER::cuda_cub::launcher::triple_chevron(
      small_and_medium_blocks_in_grid,
      SmallAndMediumPolicyT::BLOCK_THREADS,
      0,
      stream)
      .doit(small_kernel,
            small_segments,
            medium_segments,
            medium_blocks,
            small_segments_indices,
            large_and_medium_segments_indices + num_segments - medium_segments,
            d_current_keys,
            d_final_keys,
            d_current_values,
            d_final_values,
            d_begin_offsets,
            d_end_offsets);

    // Check for failure to launch
    if (CubDebug(error = cudaPeekAtLastError()))
    {
      return error;
    }

    // Sync the stream if specified to flush runtime errors
    error = detail::DebugSyncStream(stream);
    if (CubDebug(error))
    {
      return error;
    }
  }

  return error;
}

#ifdef CUB_RDC_ENABLED
/*
 * Continuation kernel is used only in the CDP mode. It's used to
 * launch DeviceSegmentedSortContinuation as a separate kernel.
 */
template <typename ChainedPolicyT,
          typename LargeKernelT,
          typename SmallKernelT,
          typename KeyT,
          typename ValueT,
          typename BeginOffsetIteratorT,
          typename EndOffsetIteratorT>
__launch_bounds__(1) CUB_DETAIL_KERNEL_ATTRIBUTES void
DeviceSegmentedSortContinuationKernel(
  LargeKernelT large_kernel,
  SmallKernelT small_kernel,
  int num_segments,
  KeyT *d_current_keys,
  KeyT *d_final_keys,
  detail::device_double_buffer<KeyT> d_keys_double_buffer,
  ValueT *d_current_values,
  ValueT *d_final_values,
  detail::device_double_buffer<ValueT> d_values_double_buffer,
  BeginOffsetIteratorT d_begin_offsets,
  EndOffsetIteratorT d_end_offsets,
  unsigned int *group_sizes,
  unsigned int *large_and_medium_segments_indices,
  unsigned int *small_segments_indices)
{
  using ActivePolicyT = typename ChainedPolicyT::ActivePolicy;
  using LargeSegmentPolicyT = typename ActivePolicyT::LargeSegmentPolicy;
  using SmallAndMediumPolicyT =
    typename ActivePolicyT::SmallAndMediumSegmentedSortPolicyT;

  // In case of CDP:
  // 1. each CTA has a different main stream
  // 2. all streams are non-blocking
  // 3. child grid always completes before the parent grid
  // 4. streams can be used only from the CTA in which they were created
  // 5. streams created on the host cannot be used on the device
  //
  // Due to (4, 5), we can't pass the user-provided stream in the continuation.
  // Due to (1, 2, 3) it's safe to pass the main stream.
  cudaError_t error =
    DeviceSegmentedSortContinuation<LargeSegmentPolicyT, SmallAndMediumPolicyT>(
      large_kernel,
      small_kernel,
      num_segments,
      d_current_keys,
      d_final_keys,
      d_keys_double_buffer,
      d_current_values,
      d_final_values,
      d_values_double_buffer,
      d_begin_offsets,
      d_end_offsets,
      group_sizes,
      large_and_medium_segments_indices,
      small_segments_indices,
      0); // always launching on the main stream (see motivation above)

  CubDebug(error);
}
#endif // CUB_RDC_ENABLED

template <typename KeyT,
          typename ValueT>
struct DeviceSegmentedSortPolicy
{
  using DominantT =
    cub::detail::conditional_t<(sizeof(ValueT) > sizeof(KeyT)), ValueT, KeyT>;

  constexpr static int KEYS_ONLY = std::is_same<ValueT, cub::NullType>::value;

  //----------------------------------------------------------------------------
  // Architecture-specific tuning policies
  //----------------------------------------------------------------------------

  struct Policy350 : ChainedPolicy<350, Policy350, Policy350>
  {
    constexpr static int BLOCK_THREADS = 128;
    constexpr static int RADIX_BITS = sizeof(KeyT) > 1 ? 6 : 4;
    constexpr static int PARTITIONING_THRESHOLD = 300;

    using LargeSegmentPolicy =
      AgentRadixSortDownsweepPolicy<BLOCK_THREADS,
                                    9,
                                    DominantT,
                                    BLOCK_LOAD_WARP_TRANSPOSE,
                                    LOAD_DEFAULT,
                                    RADIX_RANK_MATCH,
                                    BLOCK_SCAN_WARP_SCANS,
                                    RADIX_BITS>;

    constexpr static int ITEMS_PER_SMALL_THREAD =
      Nominal4BItemsToItems<DominantT>(5);

    constexpr static int ITEMS_PER_MEDIUM_THREAD =
      Nominal4BItemsToItems<DominantT>(5);

    using SmallAndMediumSegmentedSortPolicyT =
      AgentSmallAndMediumSegmentedSortPolicy<

        BLOCK_THREADS,

        // Small policy
        cub::AgentSubWarpMergeSortPolicy<4,
                                         ITEMS_PER_SMALL_THREAD,
                                         WarpLoadAlgorithm::WARP_LOAD_DIRECT,
                                         CacheLoadModifier::LOAD_DEFAULT>,

        // Medium policy
        cub::AgentSubWarpMergeSortPolicy<32,
                                         ITEMS_PER_MEDIUM_THREAD,
                                         WarpLoadAlgorithm::WARP_LOAD_DIRECT,
                                         CacheLoadModifier::LOAD_DEFAULT>>;
  };

  struct Policy500 : ChainedPolicy<500, Policy500, Policy350>
  {
    constexpr static int BLOCK_THREADS = 256;
    constexpr static int RADIX_BITS = sizeof(KeyT) > 1 ? 6 : 4;
    constexpr static int PARTITIONING_THRESHOLD = 300;

    using LargeSegmentPolicy =
      AgentRadixSortDownsweepPolicy<BLOCK_THREADS,
                                    16,
                                    DominantT,
                                    BLOCK_LOAD_DIRECT,
                                    LOAD_DEFAULT,
                                    RADIX_RANK_MEMOIZE,
                                    BLOCK_SCAN_RAKING_MEMOIZE,
                                    RADIX_BITS>;

    constexpr static int ITEMS_PER_SMALL_THREAD =
      Nominal4BItemsToItems<DominantT>(7);

    constexpr static int ITEMS_PER_MEDIUM_THREAD =
      Nominal4BItemsToItems<DominantT>(7);

    using SmallAndMediumSegmentedSortPolicyT =
      AgentSmallAndMediumSegmentedSortPolicy<

        BLOCK_THREADS,

        // Small policy
        cub::AgentSubWarpMergeSortPolicy<4, // Threads per segment
                                         ITEMS_PER_SMALL_THREAD,
                                         WarpLoadAlgorithm::WARP_LOAD_DIRECT,
                                         CacheLoadModifier::LOAD_DEFAULT>,

        // Medium policy
        cub::AgentSubWarpMergeSortPolicy<32, // Threads per segment
                                         ITEMS_PER_MEDIUM_THREAD,
                                         WarpLoadAlgorithm::WARP_LOAD_DIRECT,
                                         CacheLoadModifier::LOAD_DEFAULT>>;
  };

  struct Policy600 : ChainedPolicy<600, Policy600, Policy500>
  {
    constexpr static int BLOCK_THREADS = 256;
    constexpr static int RADIX_BITS = sizeof(KeyT) > 1 ? 6 : 4;
    constexpr static int PARTITIONING_THRESHOLD = 500;

    using LargeSegmentPolicy =
      AgentRadixSortDownsweepPolicy<BLOCK_THREADS,
                                    19,
                                    DominantT,
                                    BLOCK_LOAD_TRANSPOSE,
                                    LOAD_DEFAULT,
                                    RADIX_RANK_MATCH,
                                    BLOCK_SCAN_WARP_SCANS,
                                    RADIX_BITS>;

    constexpr static int ITEMS_PER_SMALL_THREAD =
      Nominal4BItemsToItems<DominantT>(9);

    constexpr static int ITEMS_PER_MEDIUM_THREAD =
      Nominal4BItemsToItems<DominantT>(9);

    using SmallAndMediumSegmentedSortPolicyT =
      AgentSmallAndMediumSegmentedSortPolicy<

        BLOCK_THREADS,

        // Small policy
        cub::AgentSubWarpMergeSortPolicy<4, // Threads per segment
                                         ITEMS_PER_SMALL_THREAD,
                                         WarpLoadAlgorithm::WARP_LOAD_DIRECT,
                                         CacheLoadModifier::LOAD_DEFAULT>,

        // Medium policy
        cub::AgentSubWarpMergeSortPolicy<32, // Threads per segment
                                         ITEMS_PER_MEDIUM_THREAD,
                                         WarpLoadAlgorithm::WARP_LOAD_DIRECT,
                                         CacheLoadModifier::LOAD_DEFAULT>>;
  };

  struct Policy610 : ChainedPolicy<610, Policy610, Policy600>
  {
    constexpr static int BLOCK_THREADS = 256;
    constexpr static int RADIX_BITS = sizeof(KeyT) > 1 ? 6 : 4;
    constexpr static int PARTITIONING_THRESHOLD = 500;

    using LargeSegmentPolicy =
      AgentRadixSortDownsweepPolicy<BLOCK_THREADS,
                                    19,
                                    DominantT,
                                    BLOCK_LOAD_DIRECT,
                                    LOAD_DEFAULT,
                                    RADIX_RANK_MEMOIZE,
                                    BLOCK_SCAN_WARP_SCANS,
                                    RADIX_BITS>;

    constexpr static int ITEMS_PER_SMALL_THREAD =
      Nominal4BItemsToItems<DominantT>(9);

    constexpr static int ITEMS_PER_MEDIUM_THREAD =
      Nominal4BItemsToItems<DominantT>(9);

    using SmallAndMediumSegmentedSortPolicyT =
      AgentSmallAndMediumSegmentedSortPolicy<

        BLOCK_THREADS,

        // Small policy
        cub::AgentSubWarpMergeSortPolicy<4, // Threads per segment
                                         ITEMS_PER_SMALL_THREAD,
                                         WarpLoadAlgorithm::WARP_LOAD_DIRECT,
                                         CacheLoadModifier::LOAD_DEFAULT>,

        // Medium policy
        cub::AgentSubWarpMergeSortPolicy<32, // Threads per segment
                                         ITEMS_PER_MEDIUM_THREAD,
                                         WarpLoadAlgorithm::WARP_LOAD_DIRECT,
                                         CacheLoadModifier::LOAD_DEFAULT>>;
  };

  struct Policy620 : ChainedPolicy<620, Policy620, Policy610>
  {
    constexpr static int BLOCK_THREADS = 256;
    constexpr static int RADIX_BITS = sizeof(KeyT) > 1 ? 5 : 4;
    constexpr static int PARTITIONING_THRESHOLD = 500;

    using LargeSegmentPolicy =
      AgentRadixSortDownsweepPolicy<BLOCK_THREADS,
                                    16,
                                    DominantT,
                                    BLOCK_LOAD_TRANSPOSE,
                                    LOAD_DEFAULT,
                                    RADIX_RANK_MEMOIZE,
                                    BLOCK_SCAN_RAKING_MEMOIZE,
                                    RADIX_BITS>;

    constexpr static int ITEMS_PER_SMALL_THREAD =
      Nominal4BItemsToItems<DominantT>(9);

    constexpr static int ITEMS_PER_MEDIUM_THREAD =
      Nominal4BItemsToItems<DominantT>(9);

    using SmallAndMediumSegmentedSortPolicyT =
      AgentSmallAndMediumSegmentedSortPolicy<

        BLOCK_THREADS,

        // Small policy
        cub::AgentSubWarpMergeSortPolicy<4, // Threads per segment
                                         ITEMS_PER_SMALL_THREAD,
                                         WarpLoadAlgorithm::WARP_LOAD_DIRECT,
                                         CacheLoadModifier::LOAD_DEFAULT>,

        // Medium policy
        cub::AgentSubWarpMergeSortPolicy<32, // Threads per segment
                                         ITEMS_PER_MEDIUM_THREAD,
                                         WarpLoadAlgorithm::WARP_LOAD_DIRECT,
                                         CacheLoadModifier::LOAD_DEFAULT>>;
  };

  struct Policy700 : ChainedPolicy<700, Policy700, Policy620>
  {
    constexpr static int BLOCK_THREADS = 256;
    constexpr static int RADIX_BITS = sizeof(KeyT) > 1 ? 6 : 4;
    constexpr static int PARTITIONING_THRESHOLD = 500;

    using LargeSegmentPolicy =
      AgentRadixSortDownsweepPolicy<BLOCK_THREADS,
                                    19,
                                    DominantT,
                                    BLOCK_LOAD_DIRECT,
                                    LOAD_DEFAULT,
                                    RADIX_RANK_MEMOIZE,
                                    BLOCK_SCAN_WARP_SCANS,
                                    RADIX_BITS>;

    constexpr static int ITEMS_PER_SMALL_THREAD =
      Nominal4BItemsToItems<DominantT>(7);

    constexpr static int ITEMS_PER_MEDIUM_THREAD =
      Nominal4BItemsToItems<DominantT>(KEYS_ONLY ? 11 : 7);

    using SmallAndMediumSegmentedSortPolicyT =
      AgentSmallAndMediumSegmentedSortPolicy<

        BLOCK_THREADS,

        // Small policy
        cub::AgentSubWarpMergeSortPolicy<(KEYS_ONLY ? 4 : 8), // Threads per segment
                                         ITEMS_PER_SMALL_THREAD,
                                         WarpLoadAlgorithm::WARP_LOAD_DIRECT,
                                         CacheLoadModifier::LOAD_DEFAULT>,

        // Medium policy
        cub::AgentSubWarpMergeSortPolicy<32, // Threads per segment
                                         ITEMS_PER_MEDIUM_THREAD,
                                         WarpLoadAlgorithm::WARP_LOAD_DIRECT,
                                         CacheLoadModifier::LOAD_DEFAULT>>;
  };

  struct Policy800 : ChainedPolicy<800, Policy800, Policy700>
  {
    constexpr static int BLOCK_THREADS = 256;
    constexpr static int PARTITIONING_THRESHOLD = 500;

    using LargeSegmentPolicy =
      cub::AgentRadixSortDownsweepPolicy<BLOCK_THREADS,
                                         23,
                                         DominantT,
                                         cub::BLOCK_LOAD_TRANSPOSE,
                                         cub::LOAD_DEFAULT,
                                         cub::RADIX_RANK_MEMOIZE,
                                         cub::BLOCK_SCAN_WARP_SCANS,
                                         (sizeof(KeyT) > 1) ? 6 : 4>;

    constexpr static int ITEMS_PER_SMALL_THREAD =
      Nominal4BItemsToItems<DominantT>(9);

    constexpr static int ITEMS_PER_MEDIUM_THREAD =
      Nominal4BItemsToItems<DominantT>(KEYS_ONLY ? 7 : 11);

    using SmallAndMediumSegmentedSortPolicyT =
      AgentSmallAndMediumSegmentedSortPolicy<

        BLOCK_THREADS,

        // Small policy
        cub::AgentSubWarpMergeSortPolicy<(KEYS_ONLY ? 4 : 2), // Threads per segment
                                         ITEMS_PER_SMALL_THREAD,
                                         WarpLoadAlgorithm::WARP_LOAD_TRANSPOSE,
                                         CacheLoadModifier::LOAD_DEFAULT>,

        // Medium policy
        cub::AgentSubWarpMergeSortPolicy<32, // Threads per segment
                                         ITEMS_PER_MEDIUM_THREAD,
                                         WarpLoadAlgorithm::WARP_LOAD_TRANSPOSE,
                                         CacheLoadModifier::LOAD_DEFAULT>>;
  };

  struct Policy860 : ChainedPolicy<860, Policy860, Policy800>
  {
    constexpr static int BLOCK_THREADS = 256;
    constexpr static int PARTITIONING_THRESHOLD = 500;

    using LargeSegmentPolicy =
      cub::AgentRadixSortDownsweepPolicy<BLOCK_THREADS,
                                         23,
                                         DominantT,
                                         cub::BLOCK_LOAD_TRANSPOSE,
                                         cub::LOAD_DEFAULT,
                                         cub::RADIX_RANK_MEMOIZE,
                                         cub::BLOCK_SCAN_WARP_SCANS,
                                         (sizeof(KeyT) > 1) ? 6 : 4>;

    constexpr static bool LARGE_ITEMS = sizeof(DominantT) > 4;

    constexpr static int ITEMS_PER_SMALL_THREAD =
      Nominal4BItemsToItems<DominantT>(LARGE_ITEMS ? 7 : 9);

    constexpr static int ITEMS_PER_MEDIUM_THREAD =
      Nominal4BItemsToItems<DominantT>(LARGE_ITEMS ? 9 : 7);

    using SmallAndMediumSegmentedSortPolicyT =
      AgentSmallAndMediumSegmentedSortPolicy<

        BLOCK_THREADS,

        // Small policy
        cub::AgentSubWarpMergeSortPolicy<(LARGE_ITEMS ? 8 : 2), // Threads per segment
                                         ITEMS_PER_SMALL_THREAD,
                                         WarpLoadAlgorithm::WARP_LOAD_TRANSPOSE,
                                         CacheLoadModifier::LOAD_LDG>,

        // Medium policy
        cub::AgentSubWarpMergeSortPolicy<16, // Threads per segment
                                         ITEMS_PER_MEDIUM_THREAD,
                                         WarpLoadAlgorithm::WARP_LOAD_TRANSPOSE,
                                         CacheLoadModifier::LOAD_LDG>>;
  };

  /// MaxPolicy
  using MaxPolicy = Policy860;
};

template <bool IS_DESCENDING,
          typename KeyT,
          typename ValueT,
          typename OffsetT,
          typename BeginOffsetIteratorT,
          typename EndOffsetIteratorT,
          typename SelectedPolicy = DeviceSegmentedSortPolicy<KeyT, ValueT>>
struct DispatchSegmentedSort : SelectedPolicy
{
  static constexpr int KEYS_ONLY = std::is_same<ValueT, NullType>::value;

  struct LargeSegmentsSelectorT
  {
    OffsetT value{};
    BeginOffsetIteratorT d_offset_begin{};
    EndOffsetIteratorT d_offset_end{};

    __host__ __device__ __forceinline__
    LargeSegmentsSelectorT(OffsetT value,
                           BeginOffsetIteratorT d_offset_begin,
                           EndOffsetIteratorT d_offset_end)
        : value(value)
        , d_offset_begin(d_offset_begin)
        , d_offset_end(d_offset_end)
    {}

    __host__ __device__ __forceinline__ bool
    operator()(unsigned int segment_id) const
    {
      const OffsetT segment_size = d_offset_end[segment_id] -
                                   d_offset_begin[segment_id];
      return segment_size > value;
    }
  };

  struct SmallSegmentsSelectorT
  {
    OffsetT value{};
    BeginOffsetIteratorT d_offset_begin{};
    EndOffsetIteratorT d_offset_end{};

    __host__ __device__ __forceinline__
    SmallSegmentsSelectorT(OffsetT value,
                           BeginOffsetIteratorT d_offset_begin,
                           EndOffsetIteratorT d_offset_end)
        : value(value)
        , d_offset_begin(d_offset_begin)
        , d_offset_end(d_offset_end)
    {}

    __host__ __device__ __forceinline__ bool
    operator()(unsigned int segment_id) const
    {
      const OffsetT segment_size = d_offset_end[segment_id] -
                                   d_offset_begin[segment_id];
      return segment_size < value;
    }
  };

  // Partition selects large and small groups. The middle group is not selected.
  constexpr static std::size_t num_selected_groups = 2;

  /**
   * Device-accessible allocation of temporary storage. When `nullptr`, the
   * required allocation size is written to @p temp_storage_bytes and no work
   * is done.
   */
  void *d_temp_storage;

  /// Reference to size in bytes of @p d_temp_storage allocation
  std::size_t &temp_storage_bytes;

  /**
   * Double-buffer whose current buffer contains the unsorted input keys and,
   * upon return, is updated to point to the sorted output keys
   */
  DoubleBuffer<KeyT> &d_keys;

  /**
   * Double-buffer whose current buffer contains the unsorted input values and,
   * upon return, is updated to point to the sorted output values
   */
  DoubleBuffer<ValueT> &d_values;

  /// Number of items to sort
  OffsetT num_items;

  /// The number of segments that comprise the sorting data
  int num_segments;

  /**
   * Random-access input iterator to the sequence of beginning offsets of length
   * @p num_segments, such that `d_begin_offsets[i]` is the first element of the
   * <em>i</em><sup>th</sup> data segment in `d_keys_*` and `d_values_*`
   */
  BeginOffsetIteratorT d_begin_offsets;

  /**
   * Random-access input iterator to the sequence of ending offsets of length
   * @p num_segments, such that <tt>d_end_offsets[i]-1</tt> is the last element
   * of the <em>i</em><sup>th</sup> data segment in `d_keys_*` and
   * `d_values_*`. If `d_end_offsets[i]-1 <= d_begin_offsets[i]`,
   * the <em>i</em><sup>th</sup> is considered empty.
   */
  EndOffsetIteratorT d_end_offsets;

  /// Whether is okay to overwrite source buffers
  bool is_overwrite_okay;

  /// CUDA stream to launch kernels within.
  cudaStream_t stream;

  CUB_RUNTIME_FUNCTION __forceinline__
  DispatchSegmentedSort(void *d_temp_storage,
                        std::size_t &temp_storage_bytes,
                        DoubleBuffer<KeyT> &d_keys,
                        DoubleBuffer<ValueT> &d_values,
                        OffsetT num_items,
                        int num_segments,
                        BeginOffsetIteratorT d_begin_offsets,
                        EndOffsetIteratorT d_end_offsets,
                        bool is_overwrite_okay,
                        cudaStream_t stream)
      : d_temp_storage(d_temp_storage)
      , temp_storage_bytes(temp_storage_bytes)
      , d_keys(d_keys)
      , d_values(d_values)
      , num_items(num_items)
      , num_segments(num_segments)
      , d_begin_offsets(d_begin_offsets)
      , d_end_offsets(d_end_offsets)
      , is_overwrite_okay(is_overwrite_okay)
      , stream(stream)
  {}

  CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED
  CUB_RUNTIME_FUNCTION __forceinline__
  DispatchSegmentedSort(void *d_temp_storage,
                        std::size_t &temp_storage_bytes,
                        DoubleBuffer<KeyT> &d_keys,
                        DoubleBuffer<ValueT> &d_values,
                        OffsetT num_items,
                        int num_segments,
                        BeginOffsetIteratorT d_begin_offsets,
                        EndOffsetIteratorT d_end_offsets,
                        bool is_overwrite_okay,
                        cudaStream_t stream,
                        bool debug_synchronous)
      : d_temp_storage(d_temp_storage)
      , temp_storage_bytes(temp_storage_bytes)
      , d_keys(d_keys)
      , d_values(d_values)
      , num_items(num_items)
      , num_segments(num_segments)
      , d_begin_offsets(d_begin_offsets)
      , d_end_offsets(d_end_offsets)
      , is_overwrite_okay(is_overwrite_okay)
      , stream(stream)
  {
    CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG
  }

  template <typename ActivePolicyT>
  CUB_RUNTIME_FUNCTION __forceinline__ cudaError_t Invoke()
  {
    using MaxPolicyT = typename DispatchSegmentedSort::MaxPolicy;
    using LargeSegmentPolicyT = typename ActivePolicyT::LargeSegmentPolicy;
    using SmallAndMediumPolicyT =
      typename ActivePolicyT::SmallAndMediumSegmentedSortPolicyT;

    static_assert(
      LargeSegmentPolicyT::LOAD_MODIFIER != CacheLoadModifier::LOAD_LDG,
      "The memory consistency model does not apply to texture accesses");

    static_assert(
        KEYS_ONLY
        || LargeSegmentPolicyT::LOAD_ALGORITHM != BLOCK_LOAD_STRIPED
        || SmallAndMediumPolicyT::MediumPolicyT::LOAD_ALGORITHM != WARP_LOAD_STRIPED
        || SmallAndMediumPolicyT::SmallPolicyT::LOAD_ALGORITHM != WARP_LOAD_STRIPED,
        "Striped load will make this algorithm unstable");

    static_assert(
           SmallAndMediumPolicyT::MediumPolicyT::STORE_ALGORITHM != WARP_STORE_STRIPED
        || SmallAndMediumPolicyT::SmallPolicyT::STORE_ALGORITHM != WARP_STORE_STRIPED,
        "Striped stores will produce unsorted results");

    constexpr int radix_bits = LargeSegmentPolicyT::RADIX_BITS;

    cudaError error = cudaSuccess;

    do
    {
      //------------------------------------------------------------------------
      // Prepare temporary storage layout
      //------------------------------------------------------------------------

      const bool partition_segments = num_segments >
                                      ActivePolicyT::PARTITIONING_THRESHOLD;

      cub::detail::temporary_storage::layout<5> temporary_storage_layout;

      auto keys_slot = temporary_storage_layout.get_slot(0);
      auto values_slot = temporary_storage_layout.get_slot(1);
      auto large_and_medium_partitioning_slot = temporary_storage_layout.get_slot(2);
      auto small_partitioning_slot = temporary_storage_layout.get_slot(3);
      auto group_sizes_slot = temporary_storage_layout.get_slot(4);

      auto keys_allocation = keys_slot->create_alias<KeyT>();
      auto values_allocation = values_slot->create_alias<ValueT>();

      if (!is_overwrite_okay)
      {
        keys_allocation.grow(num_items);

        if (!KEYS_ONLY)
        {
          values_allocation.grow(num_items);
        }
      }

      auto large_and_medium_segments_indices =
        large_and_medium_partitioning_slot->create_alias<unsigned int>();
      auto small_segments_indices =
        small_partitioning_slot->create_alias<unsigned int>();
      auto group_sizes = group_sizes_slot->create_alias<unsigned int>();

      std::size_t three_way_partition_temp_storage_bytes {};

      LargeSegmentsSelectorT large_segments_selector(
        SmallAndMediumPolicyT::MediumPolicyT::ITEMS_PER_TILE,
        d_begin_offsets,
        d_end_offsets);

      SmallSegmentsSelectorT small_segments_selector(
        SmallAndMediumPolicyT::SmallPolicyT::ITEMS_PER_TILE + 1,
        d_begin_offsets,
        d_end_offsets);

      auto device_partition_temp_storage =
        keys_slot->create_alias<std::uint8_t>();

      if (partition_segments)
      {
        large_and_medium_segments_indices.grow(num_segments);
        small_segments_indices.grow(num_segments);
        group_sizes.grow(num_selected_groups);

        auto medium_indices_iterator =
          THRUST_NS_QUALIFIER::make_reverse_iterator(
            large_and_medium_segments_indices.get());

        cub::DevicePartition::If(
          nullptr,
          three_way_partition_temp_storage_bytes,
          THRUST_NS_QUALIFIER::counting_iterator<OffsetT>(0),
          large_and_medium_segments_indices.get(),
          small_segments_indices.get(),
          medium_indices_iterator,
          group_sizes.get(),
          num_segments,
          large_segments_selector,
          small_segments_selector,
          stream);

        device_partition_temp_storage.grow(
          three_way_partition_temp_storage_bytes);
      }

      if (d_temp_storage == nullptr)
      {
        temp_storage_bytes = temporary_storage_layout.get_size();

        // Return if the caller is simply requesting the size of the storage
        // allocation
        break;
      }

      if (num_items == 0 || num_segments == 0)
      {
        break;
      }

      if (CubDebug(
            error = temporary_storage_layout.map_to_buffer(d_temp_storage,
                                                           temp_storage_bytes)))
      {
        break;
      }

      //------------------------------------------------------------------------
      // Sort
      //------------------------------------------------------------------------

      const bool is_num_passes_odd = GetNumPasses(radix_bits) & 1;

      /**
       * This algorithm sorts segments that don't fit into shared memory with
       * the in-global-memory radix sort. Radix sort splits key representation
       * into multiple "digits". Each digit is RADIX_BITS wide. The algorithm
       * iterates over these digits. Each of these iterations consists of a
       * couple of stages. The first stage computes a histogram for a current
       * digit in each segment key. This histogram helps to determine the
       * starting position of the keys group with a similar digit.
       * For example:
       * keys_digits  = [ 1, 0, 0, 1 ]
       * digit_prefix = [ 0, 2 ]
       * The second stage checks the keys again and increments the prefix to
       * determine the final position of the key:
       *
       *               expression            |  key  |   idx   |     result
       * ----------------------------------- | ----- | ------- | --------------
       * result[prefix[keys[0]]++] = keys[0] |   1   |    2    | [ ?, ?, 1, ? ]
       * result[prefix[keys[1]]++] = keys[0] |   0   |    0    | [ 0, ?, 1, ? ]
       * result[prefix[keys[2]]++] = keys[0] |   0   |    1    | [ 0, 0, 1, ? ]
       * result[prefix[keys[3]]++] = keys[0] |   1   |    3    | [ 0, 0, 1, 1 ]
       *
       * If the resulting memory is aliased to the input one, we'll face the
       * following issues:
       *
       *     input      |  key  |   idx   |   result/input   |      issue
       * -------------- | ----- | ------- | ---------------- | ----------------
       * [ 1, 0, 0, 1 ] |   1   |    2    | [ 1, 0, 1, 1 ]   | overwrite keys[2]
       * [ 1, 0, 1, 1 ] |   0   |    0    | [ 0, 0, 1, 1 ]   |
       * [ 0, 0, 1, 1 ] |   1   |    3    | [ 0, 0, 1, 1 ]   | extra key
       * [ 0, 0, 1, 1 ] |   1   |    4    | [ 0, 0, 1, 1 ] 1 | OOB access
       *
       * To avoid these issues, we have to use extra memory. The extra memory
       * holds temporary storage for writing intermediate results of each stage.
       * Since we iterate over digits in keys, we potentially need:
       * `sizeof(KeyT) * num_items * DivideAndRoundUp(sizeof(KeyT),RADIX_BITS)`
       * auxiliary memory bytes. To reduce the auxiliary memory storage
       * requirements, the algorithm relies on a double buffer facility. The
       * idea behind it is in swapping destination and source buffers at each
       * iteration. This way, we can use only two buffers. One of these buffers
       * can be the final algorithm output destination. Therefore, only one
       * auxiliary array is needed. Depending on the number of iterations, we
       * can initialize the double buffer so that the algorithm output array
       * will match the double buffer result one at the final iteration.
       * A user can provide this algorithm with a double buffer straightaway to
       * further reduce the auxiliary memory requirements. `is_overwrite_okay`
       * indicates this use case.
       */
      detail::device_double_buffer<KeyT> d_keys_double_buffer(
        (is_overwrite_okay || is_num_passes_odd) ? d_keys.Alternate() : keys_allocation.get(),
        (is_overwrite_okay) ? d_keys.Current() : (is_num_passes_odd) ? keys_allocation.get() : d_keys.Alternate());

      detail::device_double_buffer<ValueT> d_values_double_buffer(
        (is_overwrite_okay || is_num_passes_odd) ? d_values.Alternate() : values_allocation.get(),
        (is_overwrite_okay) ? d_values.Current() : (is_num_passes_odd) ? values_allocation.get() : d_values.Alternate());

      if (partition_segments)
      {
        // Partition input segments into size groups and assign specialized
        // kernels for each of them.
        error =
          SortWithPartitioning<LargeSegmentPolicyT, SmallAndMediumPolicyT>(
            DeviceSegmentedSortKernelLarge<IS_DESCENDING,
                                           MaxPolicyT,
                                           KeyT,
                                           ValueT,
                                           BeginOffsetIteratorT,
                                           EndOffsetIteratorT,
                                           OffsetT>,
            DeviceSegmentedSortKernelSmall<IS_DESCENDING,
                                           MaxPolicyT,
                                           KeyT,
                                           ValueT,
                                           BeginOffsetIteratorT,
                                           EndOffsetIteratorT,
                                           OffsetT>,
            three_way_partition_temp_storage_bytes,
            d_keys_double_buffer,
            d_values_double_buffer,
            large_segments_selector,
            small_segments_selector,
            device_partition_temp_storage,
            large_and_medium_segments_indices,
            small_segments_indices,
            group_sizes);
      }
      else
      {
        // If there are not enough segments, there's no reason to spend time
        // on extra partitioning steps.

        error = SortWithoutPartitioning<LargeSegmentPolicyT>(
          DeviceSegmentedSortFallbackKernel<IS_DESCENDING,
                                            MaxPolicyT,
                                            KeyT,
                                            ValueT,
                                            BeginOffsetIteratorT,
                                            EndOffsetIteratorT,
                                            OffsetT>,
          d_keys_double_buffer,
          d_values_double_buffer);
      }

      d_keys.selector = GetFinalSelector(d_keys.selector, radix_bits);
      d_values.selector = GetFinalSelector(d_values.selector, radix_bits);

    } while (false);

    return error;
  }

  CUB_RUNTIME_FUNCTION __forceinline__ static cudaError_t
  Dispatch(void *d_temp_storage,
           std::size_t &temp_storage_bytes,
           DoubleBuffer<KeyT> &d_keys,
           DoubleBuffer<ValueT> &d_values,
           OffsetT num_items,
           int num_segments,
           BeginOffsetIteratorT d_begin_offsets,
           EndOffsetIteratorT d_end_offsets,
           bool is_overwrite_okay,
           cudaStream_t stream)
  {
    using MaxPolicyT = typename DispatchSegmentedSort::MaxPolicy;

    cudaError error = cudaSuccess;

    do
    {
      // Get PTX version
      int ptx_version = 0;
      if (CubDebug(error = PtxVersion(ptx_version)))
      {
        break;
      }

      // Create dispatch functor
      DispatchSegmentedSort dispatch(d_temp_storage,
                                     temp_storage_bytes,
                                     d_keys,
                                     d_values,
                                     num_items,
                                     num_segments,
                                     d_begin_offsets,
                                     d_end_offsets,
                                     is_overwrite_okay,
                                     stream);

      // Dispatch to chained policy
      if (CubDebug(error = MaxPolicyT::Invoke(ptx_version, dispatch)))
      {
        break;
      }
    } while (false);

    return error;
  }

  CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED
  CUB_RUNTIME_FUNCTION __forceinline__ static cudaError_t
  Dispatch(void *d_temp_storage,
           std::size_t &temp_storage_bytes,
           DoubleBuffer<KeyT> &d_keys,
           DoubleBuffer<ValueT> &d_values,
           OffsetT num_items,
           int num_segments,
           BeginOffsetIteratorT d_begin_offsets,
           EndOffsetIteratorT d_end_offsets,
           bool is_overwrite_okay,
           cudaStream_t stream,
           bool debug_synchronous)
  {
    CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG

    return Dispatch(d_temp_storage,
                    temp_storage_bytes,
                    d_keys,
                    d_values,
                    num_items,
                    num_segments,
                    d_begin_offsets,
                    d_end_offsets,
                    is_overwrite_okay,
                    stream);
  }

private:
  CUB_RUNTIME_FUNCTION __forceinline__
  int GetNumPasses(int radix_bits)
  {
    const int byte_size  = 8;
    const int num_bits   = sizeof(KeyT) * byte_size;
    const int num_passes = DivideAndRoundUp(num_bits, radix_bits);
    return num_passes;
  }

  CUB_RUNTIME_FUNCTION __forceinline__
  int GetFinalSelector(int selector, int radix_bits)
  {
    // Sorted data always ends up in the other vector
    if (!is_overwrite_okay)
    {
      return (selector + 1) & 1;
    }

    return (selector + GetNumPasses(radix_bits)) & 1;
  }

  template <typename T>
  CUB_RUNTIME_FUNCTION __forceinline__
  T* GetFinalOutput(int radix_bits,
                    DoubleBuffer<T> &buffer)
  {
    const int final_selector = GetFinalSelector(buffer.selector, radix_bits);
    return buffer.d_buffers[final_selector];
  }

  template <typename LargeSegmentPolicyT,
            typename SmallAndMediumPolicyT,
            typename LargeKernelT,
            typename SmallKernelT>
  CUB_RUNTIME_FUNCTION __forceinline__ cudaError_t
  SortWithPartitioning(
    LargeKernelT large_kernel,
    SmallKernelT small_kernel,
    std::size_t three_way_partition_temp_storage_bytes,
    cub::detail::device_double_buffer<KeyT> &d_keys_double_buffer,
    cub::detail::device_double_buffer<ValueT> &d_values_double_buffer,
    LargeSegmentsSelectorT &large_segments_selector,
    SmallSegmentsSelectorT &small_segments_selector,
    cub::detail::temporary_storage::alias<std::uint8_t> &device_partition_temp_storage,
    cub::detail::temporary_storage::alias<unsigned int> &large_and_medium_segments_indices,
    cub::detail::temporary_storage::alias<unsigned int> &small_segments_indices,
    cub::detail::temporary_storage::alias<unsigned int> &group_sizes)
  {
    cudaError_t error = cudaSuccess;

    auto medium_indices_iterator =
      THRUST_NS_QUALIFIER::make_reverse_iterator(
        large_and_medium_segments_indices.get() + num_segments);

    error = cub::DevicePartition::If(
      device_partition_temp_storage.get(),
      three_way_partition_temp_storage_bytes,
      THRUST_NS_QUALIFIER::counting_iterator<OffsetT>(0),
      large_and_medium_segments_indices.get(),
      small_segments_indices.get(),
      medium_indices_iterator,
      group_sizes.get(),
      num_segments,
      large_segments_selector,
      small_segments_selector,
      stream);
    if (CubDebug(error))
    {
      return error;
    }

    // The device path is only used (and only compiles) when CDP is enabled.
    // It's defined in a macro since we can't put `#ifdef`s inside of
    // `NV_IF_TARGET`.
#ifndef CUB_RDC_ENABLED

#define CUB_TEMP_DEVICE_CODE

#else // CUB_RDC_ENABLED

#define CUB_TEMP_DEVICE_CODE                                                   \
  using MaxPolicyT = typename DispatchSegmentedSort::MaxPolicy;                \
  error =                                                                      \
    THRUST_NS_QUALIFIER::cuda_cub::launcher::triple_chevron(1, 1, 0, stream)   \
      .doit(DeviceSegmentedSortContinuationKernel<MaxPolicyT,                  \
                                                  LargeKernelT,                \
                                                  SmallKernelT,                \
                                                  KeyT,                        \
                                                  ValueT,                      \
                                                  BeginOffsetIteratorT,        \
                                                  EndOffsetIteratorT>,         \
            large_kernel,                                                      \
            small_kernel,                                                      \
            num_segments,                                                      \
            d_keys.Current(),                                                  \
            GetFinalOutput<KeyT>(LargeSegmentPolicyT::RADIX_BITS, d_keys),     \
            d_keys_double_buffer,                                              \
            d_values.Current(),                                                \
            GetFinalOutput<ValueT>(LargeSegmentPolicyT::RADIX_BITS, d_values), \
            d_values_double_buffer,                                            \
            d_begin_offsets,                                                   \
            d_end_offsets,                                                     \
            group_sizes.get(),                                                 \
            large_and_medium_segments_indices.get(),                           \
            small_segments_indices.get());                                     \
                                                                               \
  if (CubDebug(error))                                                         \
  {                                                                            \
    return error;                                                              \
  }                                                                            \
                                                                               \
  error = detail::DebugSyncStream(stream);                                     \
  if (CubDebug(error))                                                         \
  {                                                                            \
    return error;                                                              \
  }

#endif // CUB_RDC_ENABLED

    // Clang format mangles some of this NV_IF_TARGET block
    // clang-format off
    NV_IF_TARGET(
      NV_IS_HOST,
      (
        unsigned int h_group_sizes[num_selected_groups];

        if (CubDebug(error = cudaMemcpyAsync(h_group_sizes,
                                             group_sizes.get(),
                                             num_selected_groups *
                                               sizeof(unsigned int),
                                             cudaMemcpyDeviceToHost,
                                             stream)))
        {
            return error;
        }

        if (CubDebug(error = SyncStream(stream)))
        {
          return error;
        }

        error = DeviceSegmentedSortContinuation<LargeSegmentPolicyT,
                                                SmallAndMediumPolicyT>(
          large_kernel,
          small_kernel,
          num_segments,
          d_keys.Current(),
          GetFinalOutput<KeyT>(LargeSegmentPolicyT::RADIX_BITS, d_keys),
          d_keys_double_buffer,
          d_values.Current(),
          GetFinalOutput<ValueT>(LargeSegmentPolicyT::RADIX_BITS, d_values),
          d_values_double_buffer,
          d_begin_offsets,
          d_end_offsets,
          h_group_sizes,
          large_and_medium_segments_indices.get(),
          small_segments_indices.get(),
          stream);),
      // NV_IS_DEVICE:
      (CUB_TEMP_DEVICE_CODE));
    // clang-format on

#undef CUB_TEMP_DEVICE_CODE

    return error;
  }

  template <typename LargeSegmentPolicyT,
            typename FallbackKernelT>
  CUB_RUNTIME_FUNCTION __forceinline__ cudaError_t SortWithoutPartitioning(
    FallbackKernelT fallback_kernel,
    cub::detail::device_double_buffer<KeyT> &d_keys_double_buffer,
    cub::detail::device_double_buffer<ValueT> &d_values_double_buffer)
  {
    cudaError_t error = cudaSuccess;

    const auto blocks_in_grid = static_cast<unsigned int>(num_segments);
    const auto threads_in_block =
      static_cast<unsigned int>(LargeSegmentPolicyT::BLOCK_THREADS);

    // Log kernel configuration
    #ifdef CUB_DETAIL_DEBUG_ENABLE_LOG
    _CubLog("Invoking DeviceSegmentedSortFallbackKernel<<<%d, %d, "
            "0, %lld>>>(), %d items per thread, bit_grain %d\n",
            blocks_in_grid,
            threads_in_block,
            (long long)stream,
            LargeSegmentPolicyT::ITEMS_PER_THREAD,
            LargeSegmentPolicyT::RADIX_BITS);
    #endif

    // Invoke fallback kernel
    THRUST_NS_QUALIFIER::cuda_cub::launcher::triple_chevron(blocks_in_grid,
                                                            threads_in_block,
                                                            0,
                                                            stream)
      .doit(fallback_kernel,
            d_keys.Current(),
            GetFinalOutput(LargeSegmentPolicyT::RADIX_BITS, d_keys),
            d_keys_double_buffer,
            d_values.Current(),
            GetFinalOutput(LargeSegmentPolicyT::RADIX_BITS, d_values),
            d_values_double_buffer,
            d_begin_offsets,
            d_end_offsets);

    // Check for failure to launch
    if (CubDebug(error = cudaPeekAtLastError()))
    {
      return error;
    }

    // Sync the stream if specified to flush runtime errors
    error = detail::DebugSyncStream(stream);
    if (CubDebug(error))
    {
      return error;
    }

    return error;
  }
};


CUB_NAMESPACE_END
