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  /**
   * \file
   * cub::BlockReduceRaking provides raking-based methods of parallel reduction across a CUDA thread block.  Supports non-commutative reduction operators.
   */
  
  #pragma once
  
  #include "../../block/block_raking_layout.cuh"
  #include "../../warp/warp_reduce.cuh"
  #include "../../thread/thread_reduce.cuh"
  #include "../../util_ptx.cuh"
  #include "../../util_namespace.cuh"
  
  /// Optional outer namespace(s)
  CUB_NS_PREFIX
  
  /// CUB namespace
  namespace cub {
  
  
  /**
   * \brief BlockReduceRaking provides raking-based methods of parallel reduction across a CUDA thread block.  Supports non-commutative reduction operators.
   *
   * Supports non-commutative binary reduction operators.  Unlike commutative
   * reduction operators (e.g., addition), the application of a non-commutative
   * reduction operator (e.g, string concatenation) across a sequence of inputs must
   * honor the relative ordering of items and partial reductions when applying the
   * reduction operator.
   *
   * Compared to the implementation of BlockReduceRaking (which does not support
   * non-commutative operators), this implementation requires a few extra
   * rounds of inter-thread communication.
   */
  template <
      typename    T,              ///< Data type being reduced
      int         BLOCK_DIM_X,    ///< The thread block length in threads along the X dimension
      int         BLOCK_DIM_Y,    ///< The thread block length in threads along the Y dimension
      int         BLOCK_DIM_Z,    ///< The thread block length in threads along the Z dimension
      int         PTX_ARCH>       ///< The PTX compute capability for which to to specialize this collective
  struct BlockReduceRaking
  {
      /// Constants
      enum
      {
          /// The thread block size in threads
          BLOCK_THREADS = BLOCK_DIM_X * BLOCK_DIM_Y * BLOCK_DIM_Z,
      };
  
      /// Layout type for padded thread block raking grid
      typedef BlockRakingLayout<T, BLOCK_THREADS, PTX_ARCH> BlockRakingLayout;
  
      ///  WarpReduce utility type
      typedef typename WarpReduce<T, BlockRakingLayout::RAKING_THREADS, PTX_ARCH>::InternalWarpReduce WarpReduce;
  
      /// Constants
      enum
      {
          /// Number of raking threads
          RAKING_THREADS = BlockRakingLayout::RAKING_THREADS,
  
          /// Number of raking elements per warp synchronous raking thread
          SEGMENT_LENGTH = BlockRakingLayout::SEGMENT_LENGTH,
  
          /// Cooperative work can be entirely warp synchronous
          WARP_SYNCHRONOUS = (RAKING_THREADS == BLOCK_THREADS),
  
          /// Whether or not warp-synchronous reduction should be unguarded (i.e., the warp-reduction elements is a power of two
          WARP_SYNCHRONOUS_UNGUARDED = PowerOfTwo<RAKING_THREADS>::VALUE,
  
          /// Whether or not accesses into smem are unguarded
          RAKING_UNGUARDED = BlockRakingLayout::UNGUARDED,
  
      };
  
  
      /// Shared memory storage layout type
      union _TempStorage
      {
          typename WarpReduce::TempStorage            warp_storage;        ///< Storage for warp-synchronous reduction
          typename BlockRakingLayout::TempStorage     raking_grid;         ///< Padded thread block raking grid
      };
  
  
      /// Alias wrapper allowing storage to be unioned
      struct TempStorage : Uninitialized<_TempStorage> {};
  
  
      // Thread fields
      _TempStorage &temp_storage;
      unsigned int linear_tid;
  
  
      /// Constructor
      __device__ __forceinline__ BlockReduceRaking(
          TempStorage &temp_storage)
      :
          temp_storage(temp_storage.Alias()),
          linear_tid(RowMajorTid(BLOCK_DIM_X, BLOCK_DIM_Y, BLOCK_DIM_Z))
      {}
  
  
      template <bool IS_FULL_TILE, typename ReductionOp, int ITERATION>
      __device__ __forceinline__ T RakingReduction(
          ReductionOp                 reduction_op,       ///< [in] Binary scan operator
          T                           *raking_segment,
          T                           partial,            ///< [in] <b>[<em>lane</em><sub>0</sub> only]</b> Warp-wide aggregate reduction of input items
          int                         num_valid,          ///< [in] Number of valid elements (may be less than BLOCK_THREADS)
          Int2Type<ITERATION>         /*iteration*/)
      {
          // Update partial if addend is in range
          if ((IS_FULL_TILE && RAKING_UNGUARDED) || ((linear_tid * SEGMENT_LENGTH) + ITERATION < num_valid))
          {
              T addend = raking_segment[ITERATION];
              partial = reduction_op(partial, addend);
          }
          return RakingReduction<IS_FULL_TILE>(reduction_op, raking_segment, partial, num_valid, Int2Type<ITERATION + 1>());
      }
  
      template <bool IS_FULL_TILE, typename ReductionOp>
      __device__ __forceinline__ T RakingReduction(
          ReductionOp                 /*reduction_op*/,   ///< [in] Binary scan operator
          T                           * /*raking_segment*/,
          T                           partial,            ///< [in] <b>[<em>lane</em><sub>0</sub> only]</b> Warp-wide aggregate reduction of input items
          int                         /*num_valid*/,      ///< [in] Number of valid elements (may be less than BLOCK_THREADS)
          Int2Type<SEGMENT_LENGTH>    /*iteration*/)
      {
          return partial;
      }
  
  
  
      /// Computes a thread block-wide reduction using the specified reduction operator. The first num_valid threads each contribute one reduction partial.  The return value is only valid for thread<sub>0</sub>.
      template <
          bool                IS_FULL_TILE,
          typename            ReductionOp>
      __device__ __forceinline__ T Reduce(
          T                   partial,            ///< [in] Calling thread's input partial reductions
          int                 num_valid,          ///< [in] Number of valid elements (may be less than BLOCK_THREADS)
          ReductionOp         reduction_op)       ///< [in] Binary reduction operator
      {
          if (WARP_SYNCHRONOUS)
          {
              // Short-circuit directly to warp synchronous reduction (unguarded if active threads is a power-of-two)
              partial = WarpReduce(temp_storage.warp_storage).template Reduce<IS_FULL_TILE>(
                  partial,
                  num_valid,
                  reduction_op);
          }
          else
          {
              // Place partial into shared memory grid.
              *BlockRakingLayout::PlacementPtr(temp_storage.raking_grid, linear_tid) = partial;
  
              CTA_SYNC();
  
              // Reduce parallelism to one warp
              if (linear_tid < RAKING_THREADS)
              {
                  // Raking reduction in grid
                  T *raking_segment = BlockRakingLayout::RakingPtr(temp_storage.raking_grid, linear_tid);
                  partial = raking_segment[0];
  
                  partial = RakingReduction<IS_FULL_TILE>(reduction_op, raking_segment, partial, num_valid, Int2Type<1>());
  
                  int valid_raking_threads = (IS_FULL_TILE) ?
                      RAKING_THREADS :
                      (num_valid + SEGMENT_LENGTH - 1) / SEGMENT_LENGTH;
  
                  partial = WarpReduce(temp_storage.warp_storage).template Reduce<IS_FULL_TILE && RAKING_UNGUARDED>(
                      partial,
                      valid_raking_threads,
                      reduction_op);
  
              }
          }
  
          return partial;
      }
  
  
      /// Computes a thread block-wide reduction using addition (+) as the reduction operator. The first num_valid threads each contribute one reduction partial.  The return value is only valid for thread<sub>0</sub>.
      template <bool IS_FULL_TILE>
      __device__ __forceinline__ T Sum(
          T                   partial,            ///< [in] Calling thread's input partial reductions
          int                 num_valid)          ///< [in] Number of valid elements (may be less than BLOCK_THREADS)
      {
          cub::Sum reduction_op;
  
          return Reduce<IS_FULL_TILE>(partial, num_valid, reduction_op);
      }
  
  
  
  };
  
  }               // CUB namespace
  CUB_NS_POSTFIX  // Optional outer namespace(s)