/******************************************************************************
 * Copyright (c) 2011, Duane Merrill.  All rights reserved.
 * Copyright (c) 2011-2018, NVIDIA CORPORATION.  All rights reserved.
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 * 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.
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 *     * Neither the name of the NVIDIA CORPORATION nor the
 *       names of its contributors may be used to endorse or promote products
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/**
 * @file
 * cub::WarpScanSmem provides smem-based variants of parallel prefix scan of items partitioned
 * across a CUDA thread warp.
 */

#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/thread/thread_load.cuh>
#include <cub/thread/thread_operators.cuh>
#include <cub/thread/thread_store.cuh>
#include <cub/util_type.cuh>

CUB_NAMESPACE_BEGIN

/**
 * @brief WarpScanSmem provides smem-based variants of parallel prefix scan of items partitioned
 *        across a CUDA thread warp.
 *
 * @tparam T
 *   Data type being scanned
 *
 * @tparam LOGICAL_WARP_THREADS
 *   Number of threads per logical warp
 *
 * @tparam LEGACY_PTX_ARCH
 *   The PTX compute capability for which to to specialize this collective
 */
template <typename T, int LOGICAL_WARP_THREADS, int LEGACY_PTX_ARCH = 0>
struct WarpScanSmem
{
    /******************************************************************************
     * Constants and type definitions
     ******************************************************************************/

    enum
    {
        /// Whether the logical warp size and the PTX warp size coincide
        IS_ARCH_WARP = (LOGICAL_WARP_THREADS == CUB_WARP_THREADS(0)),

        /// The number of warp scan steps
        STEPS = Log2<LOGICAL_WARP_THREADS>::VALUE,

        /// The number of threads in half a warp
        HALF_WARP_THREADS = 1 << (STEPS - 1),

        /// The number of shared memory elements per warp
        WARP_SMEM_ELEMENTS =  LOGICAL_WARP_THREADS + HALF_WARP_THREADS,
    };

    /// Storage cell type (workaround for SM1x compiler bugs with custom-ops like Max() on signed chars)
    using CellT = T;

    /// Shared memory storage layout type (1.5 warps-worth of elements for each warp)
    typedef CellT _TempStorage[WARP_SMEM_ELEMENTS];

    // Alias wrapper allowing storage to be unioned
    struct TempStorage : Uninitialized<_TempStorage> {};


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

    _TempStorage    &temp_storage;
    unsigned int    lane_id;
    unsigned int    member_mask;


    /******************************************************************************
     * Construction
     ******************************************************************************/

    /// Constructor
    explicit __device__ __forceinline__ WarpScanSmem(
        TempStorage     &temp_storage)
    :
        temp_storage(temp_storage.Alias()),

        lane_id(IS_ARCH_WARP ?
            LaneId() :
            LaneId() % LOGICAL_WARP_THREADS),

        member_mask(
          WarpMask<LOGICAL_WARP_THREADS>(LaneId() / LOGICAL_WARP_THREADS))
    {}


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

    /// Basic inclusive scan iteration (template unrolled, inductive-case specialization)
    template <
        bool        HAS_IDENTITY,
        int         STEP,
        typename    ScanOp>
    __device__ __forceinline__ void ScanStep(
        T                       &partial,
        ScanOp                  scan_op,
        Int2Type<STEP>          /*step*/)
    {
        constexpr int OFFSET = 1 << STEP;

        // Share partial into buffer
        ThreadStore<STORE_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id], (CellT) partial);

        WARP_SYNC(member_mask);

        // Update partial if addend is in range
        if (HAS_IDENTITY || (lane_id >= OFFSET))
        {
            T addend = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id - OFFSET]);
            partial = scan_op(addend, partial);
        }
        WARP_SYNC(member_mask);

        ScanStep<HAS_IDENTITY>(partial, scan_op, Int2Type<STEP + 1>());
    }


    /// Basic inclusive scan iteration(template unrolled, base-case specialization)
    template <
        bool        HAS_IDENTITY,
        typename    ScanOp>
    __device__ __forceinline__ void ScanStep(
        T                       &/*partial*/,
        ScanOp                  /*scan_op*/,
        Int2Type<STEPS>         /*step*/)
    {}

    /**
     * @brief Inclusive prefix scan (specialized for summation across primitive types)
     *
     * @param[in] input
     *   Calling thread's input item
     *
     * @param[out] output
     *   Calling thread's output item. May be aliased with @p input
     *
     * @param[in] scan_op
     *   Binary scan operator
     *
     * @param[in]
     *   Marker type indicating whether T is primitive type
     */
    __device__ __forceinline__ void
    InclusiveScan(T input, T &output, Sum scan_op, Int2Type<true> /*is_primitive*/)
    {
        T identity = 0;
        ThreadStore<STORE_VOLATILE>(&temp_storage[lane_id], (CellT) identity);

        WARP_SYNC(member_mask);

        // Iterate scan steps
        output = input;
        ScanStep<true>(output, scan_op, Int2Type<0>());
    }

    /**
     * @brief Inclusive prefix scan
     *
     * @param[in] input
     *   Calling thread's input item
     *
     * @param[out] output
     *   Calling thread's output item. May be aliased with @p input
     *
     * @param[in] scan_op
     *   Binary scan operator
     *
     * @param[in] is_primitive
     *   Marker type indicating whether T is primitive type
     */
    template <typename ScanOp, int IS_PRIMITIVE>
    __device__ __forceinline__ void
    InclusiveScan(T input, T &output, ScanOp scan_op, Int2Type<IS_PRIMITIVE> /*is_primitive*/)
    {
        // Iterate scan steps
        output = input;
        ScanStep<false>(output, scan_op, Int2Type<0>());
    }


    /******************************************************************************
     * Interface
     ******************************************************************************/

    //---------------------------------------------------------------------
    // Broadcast
    //---------------------------------------------------------------------

    /**
     * @brief Broadcast
     *
     * @param[in] input
     *   The value to broadcast
     *
     * @param[in] src_lane
     *   Which warp lane is to do the broadcasting
     */
    __device__ __forceinline__ T Broadcast(T input, unsigned int src_lane)
    {
        if (lane_id == src_lane)
        {
            ThreadStore<STORE_VOLATILE>(temp_storage, (CellT) input);
        }

        WARP_SYNC(member_mask);

        return (T)ThreadLoad<LOAD_VOLATILE>(temp_storage);
    }


    //---------------------------------------------------------------------
    // Inclusive operations
    //---------------------------------------------------------------------

    /**
     * @brief Inclusive scan
     *
     * @param[in] input
     *   Calling thread's input item.
     *
     * @param[out] inclusive_output
     *   Calling thread's output item. May be aliased with @p input
     *
     * @param[in] scan_op
     *   Binary scan operator
     */
    template <typename ScanOp>
    __device__ __forceinline__ void InclusiveScan(T input, T &inclusive_output, ScanOp scan_op)
    {
        InclusiveScan(input, inclusive_output, scan_op, Int2Type<Traits<T>::PRIMITIVE>());
    }

    /**
     * @brief Inclusive scan with aggregate
     *
     * @param[in] input
     *   Calling thread's input item
     *
     * @param[out] inclusive_output
     *   Calling thread's output item. May be aliased with @p input
     *
     * @param[in] scan_op
     *   Binary scan operator
     *
     * @param[out] warp_aggregate
     *   Warp-wide aggregate reduction of input items.
     */
    template <typename ScanOp>
    __device__ __forceinline__ void
    InclusiveScan(T input, T &inclusive_output, ScanOp scan_op, T &warp_aggregate)
    {
        InclusiveScan(input, inclusive_output, scan_op);

        // Retrieve aggregate
        ThreadStore<STORE_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id], (CellT) inclusive_output);

        WARP_SYNC(member_mask);

        warp_aggregate = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[WARP_SMEM_ELEMENTS - 1]);

        WARP_SYNC(member_mask);
    }


    //---------------------------------------------------------------------
    // Get exclusive from inclusive
    //---------------------------------------------------------------------

    /**
     * @brief Update inclusive and exclusive using input and inclusive
     *
     * @param[in] input
     *
     * @param[in, out] inclusive
     *
     * @param[out] exclusive
     *
     * @param[in] scan_op
     *
     * @param[in] is_integer
     */
    template <typename ScanOpT, typename IsIntegerT>
    __device__ __forceinline__ void
    Update(T /*input*/, T &inclusive, T &exclusive, ScanOpT /*scan_op*/, IsIntegerT /*is_integer*/)
    {
        // initial value unknown
        ThreadStore<STORE_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id], (CellT) inclusive);

        WARP_SYNC(member_mask);

        exclusive = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id - 1]);
    }

    /**
     * @brief Update inclusive and exclusive using input and inclusive (specialized for summation of
     *        integer types)
     */
    __device__ __forceinline__ void Update(
        T                       input,
        T                       &inclusive,
        T                       &exclusive,
        cub::Sum                /*scan_op*/,
        Int2Type<true>          /*is_integer*/)
    {
        // initial value presumed 0
        exclusive = inclusive - input;
    }

    /**
     * @brief Update inclusive and exclusive using initial value using input, inclusive, and initial
     *        value
     */
    template <typename ScanOpT, typename IsIntegerT>
    __device__ __forceinline__ void Update (
        T                       /*input*/,
        T                       &inclusive,
        T                       &exclusive,
        ScanOpT                 scan_op,
        T                       initial_value,
        IsIntegerT              /*is_integer*/)
    {
        inclusive = scan_op(initial_value, inclusive);
        ThreadStore<STORE_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id], (CellT) inclusive);

        WARP_SYNC(member_mask);

        exclusive = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id - 1]);
        if (lane_id == 0)
            exclusive = initial_value;
    }

    /**
     * @brief Update inclusive and exclusive using initial value using input and inclusive
     *        (specialized for summation of integer types)
     */
    __device__ __forceinline__ void Update (
        T                       input,
        T                       &inclusive,
        T                       &exclusive,
        cub::Sum                scan_op,
        T                       initial_value,
        Int2Type<true>          /*is_integer*/)
    {
        inclusive = scan_op(initial_value, inclusive);
        exclusive = inclusive - input;
    }

    /**
     * @brief Update inclusive, exclusive, and warp aggregate using input and inclusive
     */
    template <typename ScanOpT, typename IsIntegerT>
    __device__ __forceinline__ void Update (
        T                       /*input*/,
        T                       &inclusive,
        T                       &exclusive,
        T                       &warp_aggregate,
        ScanOpT                 /*scan_op*/,
        IsIntegerT              /*is_integer*/)
    {
        // Initial value presumed to be unknown or identity (either way our padding is correct)
        ThreadStore<STORE_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id], (CellT) inclusive);

        WARP_SYNC(member_mask);

        exclusive = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id - 1]);
        warp_aggregate = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[WARP_SMEM_ELEMENTS - 1]);
    }

    /**
     * @brief Update inclusive, exclusive, and warp aggregate using input and inclusive (specialized
     *        for summation of integer types)
     */
    __device__ __forceinline__ void Update (
        T                       input,
        T                       &inclusive,
        T                       &exclusive,
        T                       &warp_aggregate,
        cub::Sum                /*scan_o*/,
        Int2Type<true>          /*is_integer*/)
    {
        // Initial value presumed to be unknown or identity (either way our padding is correct)
        ThreadStore<STORE_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id], (CellT) inclusive);

        WARP_SYNC(member_mask);

        warp_aggregate = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[WARP_SMEM_ELEMENTS - 1]);
        exclusive = inclusive - input;
    }

    /**
     * @brief Update inclusive, exclusive, and warp aggregate using input, inclusive, and initial
     *        value
     */
    template <typename ScanOpT, typename IsIntegerT>
    __device__ __forceinline__ void Update (
        T                       /*input*/,
        T                       &inclusive,
        T                       &exclusive,
        T                       &warp_aggregate,
        ScanOpT                 scan_op,
        T                       initial_value,
        IsIntegerT              /*is_integer*/)
    {
        // Broadcast warp aggregate
        ThreadStore<STORE_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id], (CellT) inclusive);

        WARP_SYNC(member_mask);

        warp_aggregate = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[WARP_SMEM_ELEMENTS - 1]);

        WARP_SYNC(member_mask);

        // Update inclusive with initial value
        inclusive = scan_op(initial_value, inclusive);

        // Get exclusive from exclusive
        ThreadStore<STORE_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id - 1], (CellT) inclusive);

        WARP_SYNC(member_mask);

        exclusive = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id - 2]);

        if (lane_id == 0)
            exclusive = initial_value;
    }


};


CUB_NAMESPACE_END
