/******************************************************************************
 * 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
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 *       names of its contributors may be used to endorse or promote products
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/**
 * @file
 * Operations for writing linear segments of data from the CUDA thread block
 */

#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/block/block_exchange.cuh>
#include <cub/util_ptx.cuh>
#include <cub/util_type.cuh>

#include <iterator>
#include <type_traits>

CUB_NAMESPACE_BEGIN

/**
 * @addtogroup UtilIo
 * @{
 */


/******************************************************************//**
 * @name Blocked arrangement I/O (direct)
 *********************************************************************/
//@{

/**
 * @brief Store a blocked arrangement of items across a thread block into a linear segment of items.
 *
 * @blocked
 *
 * @tparam T
 *   <b>[inferred]</b> The data type to store.
 *
 * @tparam ITEMS_PER_THREAD
 *   <b>[inferred]</b> The number of consecutive items partitioned onto each thread.
 *
 * @tparam OutputIteratorT
 *   <b>[inferred]</b> The random-access iterator type for output \iterator.
 *
 * @param[in] linear_tid
 *   A suitable 1D thread-identifier for the calling thread
 *   (e.g., <tt>(threadIdx.y * blockDim.x) + linear_tid</tt> for 2D thread blocks)
 *
 * @param[in] block_itr
 *   The thread block's base output iterator for storing to
 *
 * @param[in] items
 *   Data to store
 */
template <typename T, int ITEMS_PER_THREAD, typename OutputIteratorT>
__device__ __forceinline__ void StoreDirectBlocked(int linear_tid,
                                                   OutputIteratorT block_itr,
                                                   T (&items)[ITEMS_PER_THREAD])
{
    OutputIteratorT thread_itr = block_itr + (linear_tid * ITEMS_PER_THREAD);

    // Store directly in thread-blocked order
    #pragma unroll
    for (int ITEM = 0; ITEM < ITEMS_PER_THREAD; ITEM++)
    {
        thread_itr[ITEM] = items[ITEM];
    }
}

/**
 * @brief Store a blocked arrangement of items across a
 *        thread block into a linear segment of items, guarded by range
 *
 * @blocked
 *
 * @tparam T
 *   <b>[inferred]</b> The data type to store.
 *
 * @tparam ITEMS_PER_THREAD
 *   <b>[inferred]</b> The number of consecutive items partitioned onto each thread.
 *
 * @tparam OutputIteratorT
 *   <b>[inferred]</b> The random-access iterator type for output \iterator.
 *
 * @param[in] linear_tid
 *   A suitable 1D thread-identifier for the calling thread
 *   (e.g., <tt>(threadIdx.y * blockDim.x) + linear_tid</tt> for 2D thread blocks)
 *
 * @param[in] block_itr
 *   The thread block's base output iterator for storing to
 *
 * @param[in] items
 *   Data to store
 *
 * @param[in] valid_items
 *   Number of valid items to write
 *
 */
template <typename T, int ITEMS_PER_THREAD, typename OutputIteratorT>
__device__ __forceinline__ void StoreDirectBlocked(int linear_tid,
                                                   OutputIteratorT block_itr,
                                                   T (&items)[ITEMS_PER_THREAD],
                                                   int valid_items)
{
    OutputIteratorT thread_itr = block_itr + (linear_tid * ITEMS_PER_THREAD);

    // Store directly in thread-blocked order
    #pragma unroll
    for (int ITEM = 0; ITEM < ITEMS_PER_THREAD; ITEM++)
    {
        if (ITEM + (linear_tid * ITEMS_PER_THREAD) < valid_items)
        {
            thread_itr[ITEM] = items[ITEM];
        }
    }
}

/**
 * @brief Store a blocked arrangement of items across a
 *        thread block into a linear segment of items.
 *
 * @blocked
 *
 * The output offset (@p block_ptr + @p block_offset) must be quad-item aligned,
 * which is the default starting offset returned by @p cudaMalloc()
 *
 * @par
 * The following conditions will prevent vectorization and storing will
 * fall back to cub::BLOCK_STORE_DIRECT:
 *   - @p ITEMS_PER_THREAD is odd
 *   - The data type @p T is not a built-in primitive or CUDA vector type
 *     (e.g., \p short, \p int2, \p double, \p float2, etc.)
 *
 * @tparam T
 *   <b>[inferred]</b> The data type to store.
 *
 * @tparam ITEMS_PER_THREAD
 *   <b>[inferred]</b> The number of consecutive items partitioned onto each thread.
 *
 * @param[in] linear_tid
 *   A suitable 1D thread-identifier for the calling thread
 *   (e.g., <tt>(threadIdx.y * blockDim.x) + linear_tid</tt> for 2D thread blocks)
 *
 * @param[in] block_ptr
 *   Input pointer for storing from
 *
 * @param[in] items
 *   Data to store
 */
template <typename T, int ITEMS_PER_THREAD>
__device__ __forceinline__ void StoreDirectBlockedVectorized(int linear_tid,
                                                             T *block_ptr,
                                                             T (&items)[ITEMS_PER_THREAD])
{
    enum
    {
        // Maximum CUDA vector size is 4 elements
        MAX_VEC_SIZE = CUB_MIN(4, ITEMS_PER_THREAD),

        // Vector size must be a power of two and an even divisor of the items per thread
        VEC_SIZE = ((((MAX_VEC_SIZE - 1) & MAX_VEC_SIZE) == 0) && ((ITEMS_PER_THREAD % MAX_VEC_SIZE) == 0)) ?
            MAX_VEC_SIZE :
            1,

        VECTORS_PER_THREAD = ITEMS_PER_THREAD / VEC_SIZE,
    };

    // Vector type
    typedef typename CubVector<T, VEC_SIZE>::Type Vector;

    // Alias global pointer
    Vector *block_ptr_vectors = reinterpret_cast<Vector*>(const_cast<T*>(block_ptr));

    // Alias pointers (use "raw" array here which should get optimized away to prevent conservative PTXAS lmem spilling)
    Vector raw_vector[VECTORS_PER_THREAD];
    T *raw_items = reinterpret_cast<T*>(raw_vector);

    // Copy
    #pragma unroll
    for (int ITEM = 0; ITEM < ITEMS_PER_THREAD; ITEM++)
    {
        raw_items[ITEM] = items[ITEM];
    }

    // Direct-store using vector types
    StoreDirectBlocked(linear_tid, block_ptr_vectors, raw_vector);
}



//@}  end member group
/******************************************************************//**
 * @name Striped arrangement I/O (direct)
 *********************************************************************/
//@{

/**
 * @brief Store a striped arrangement of data across the thread block into a
 *        linear segment of items.
 *
 * @striped
 *
 * @tparam BLOCK_THREADS
 *   The thread block size in threads
 *
 * @tparam T
 *   <b>[inferred]</b> The data type to store.
 *
 * @tparam ITEMS_PER_THREAD
 *   <b>[inferred]</b> The number of consecutive items partitioned onto each thread.
 *
 * @tparam OutputIteratorT
 *   <b>[inferred]</b> The random-access iterator type for output @iterator.
 *
 * @param[in] linear_tid
 *   A suitable 1D thread-identifier for the calling thread
 *   (e.g., <tt>(threadIdx.y * blockDim.x) + linear_tid</tt> for 2D thread blocks)
 *
 * @param[in] block_itr
 *   The thread block's base output iterator for storing to
 *
 * @param[in] items
 *   Data to store
 */
template <int BLOCK_THREADS, typename T, int ITEMS_PER_THREAD, typename OutputIteratorT>
__device__ __forceinline__ void StoreDirectStriped(int linear_tid,
                                                   OutputIteratorT block_itr,
                                                   T (&items)[ITEMS_PER_THREAD])
{
    OutputIteratorT thread_itr = block_itr + linear_tid;

    // Store directly in striped order
    #pragma unroll
    for (int ITEM = 0; ITEM < ITEMS_PER_THREAD; ITEM++)
    {
        thread_itr[(ITEM * BLOCK_THREADS)] = items[ITEM];
    }
}

/**
 * @brief Store a striped arrangement of data across the thread block into
 *        a linear segment of items, guarded by range
 *
 * @striped
 *
 * @tparam BLOCK_THREADS
 *   The thread block size in threads
 *
 * @tparam T
 *   <b>[inferred]</b> The data type to store.
 *
 * @tparam ITEMS_PER_THREAD
 *   <b>[inferred]</b> The number of consecutive items partitioned onto each thread.
 *
 * @tparam OutputIteratorT
 *   <b>[inferred]</b> The random-access iterator type for output \iterator.
 *
 * @param[in] linear_tid
 *   A suitable 1D thread-identifier for the calling thread
 *   (e.g., <tt>(threadIdx.y * blockDim.x) + linear_tid</tt> for 2D thread blocks)
 *
 * @param[in] block_itr
 *   The thread block's base output iterator for storing to
 *
 * @param[in] items
 *   Data to store
 *
 * @param[in] valid_items
 *   Number of valid items to write
 */
template <int BLOCK_THREADS, typename T, int ITEMS_PER_THREAD, typename OutputIteratorT>
__device__ __forceinline__ void StoreDirectStriped(int linear_tid,
                                                   OutputIteratorT block_itr,
                                                   T (&items)[ITEMS_PER_THREAD],
                                                   int valid_items)
{
    OutputIteratorT thread_itr = block_itr + linear_tid;

    // Store directly in striped order
    #pragma unroll
    for (int ITEM = 0; ITEM < ITEMS_PER_THREAD; ITEM++)
    {
        if ((ITEM * BLOCK_THREADS) + linear_tid < valid_items)
        {
            thread_itr[(ITEM * BLOCK_THREADS)] = items[ITEM];
        }
    }
}



//@}  end member group
/******************************************************************//**
 * @name Warp-striped arrangement I/O (direct)
 *********************************************************************/
//@{

/**
 * @brief Store a warp-striped arrangement of data across the
 *        thread block into a linear segment of items.
 *
 * @warpstriped
 *
 * @par Usage Considerations
 * The number of threads in the thread block must be a multiple of the architecture's warp size.
 *
 * @tparam T
 *   <b>[inferred]</b> The data type to store.
 *
 * @tparam ITEMS_PER_THREAD
 *   <b>[inferred]</b> The number of consecutive items partitioned onto each thread.
 *
 * @tparam OutputIteratorT
 *   <b>[inferred]</b> The random-access iterator type for output \iterator.
 *
 * @param[in] linear_tid
 *   A suitable 1D thread-identifier for the calling thread
 *   (e.g., <tt>(threadIdx.y * blockDim.x) + linear_tid</tt> for 2D thread blocks)
 *
 * @param[in] block_itr
 *   The thread block's base output iterator for storing to
 *
 * @param[out] items
 *   Data to load
 */
template <typename T, int ITEMS_PER_THREAD, typename OutputIteratorT>
__device__ __forceinline__ void StoreDirectWarpStriped(int linear_tid,
                                                       OutputIteratorT block_itr,
                                                       T (&items)[ITEMS_PER_THREAD])
{
    int tid         = linear_tid & (CUB_PTX_WARP_THREADS - 1);
    int wid         = linear_tid >> CUB_PTX_LOG_WARP_THREADS;
    int warp_offset = wid * CUB_PTX_WARP_THREADS * ITEMS_PER_THREAD;

    OutputIteratorT thread_itr = block_itr + warp_offset + tid;

    // Store directly in warp-striped order
    #pragma unroll
    for (int ITEM = 0; ITEM < ITEMS_PER_THREAD; ITEM++)
    {
        thread_itr[(ITEM * CUB_PTX_WARP_THREADS)] = items[ITEM];
    }
}

/**
 * @brief Store a warp-striped arrangement of data across the thread block into a
 *        linear segment of items, guarded by range
 *
 * @warpstriped
 *
 * @par Usage Considerations
 * The number of threads in the thread block must be a multiple of the architecture's warp size.
 *
 * @tparam T
 *   <b>[inferred]</b> The data type to store.
 *
 * @tparam ITEMS_PER_THREAD
 *   <b>[inferred]</b> The number of consecutive items partitioned onto each thread.
 *
 * @tparam OutputIteratorT
 *   <b>[inferred]</b> The random-access iterator type for output \iterator.
 *
 * @param[in] linear_tid
 *   A suitable 1D thread-identifier for the calling thread
 *   (e.g., <tt>(threadIdx.y * blockDim.x) + linear_tid</tt> for 2D thread blocks)
 *
 * @param[in] block_itr
 *   The thread block's base output iterator for storing to
 *
 * @param[in] items
 *   Data to store
 *
 * @param[in] valid_items
 *   Number of valid items to write
 */
template <typename T, int ITEMS_PER_THREAD, typename OutputIteratorT>
__device__ __forceinline__ void StoreDirectWarpStriped(int linear_tid,
                                                       OutputIteratorT block_itr,
                                                       T (&items)[ITEMS_PER_THREAD],
                                                       int valid_items)
{
    int tid         = linear_tid & (CUB_PTX_WARP_THREADS - 1);
    int wid         = linear_tid >> CUB_PTX_LOG_WARP_THREADS;
    int warp_offset = wid * CUB_PTX_WARP_THREADS * ITEMS_PER_THREAD;

    OutputIteratorT thread_itr = block_itr + warp_offset + tid;

    // Store directly in warp-striped order
    #pragma unroll
    for (int ITEM = 0; ITEM < ITEMS_PER_THREAD; ITEM++)
    {
        if (warp_offset + tid + (ITEM * CUB_PTX_WARP_THREADS) < valid_items)
        {
            thread_itr[(ITEM * CUB_PTX_WARP_THREADS)] = items[ITEM];
        }
    }
}


//@}  end member group


/** @} */       // end group UtilIo


//-----------------------------------------------------------------------------
// Generic BlockStore abstraction
//-----------------------------------------------------------------------------

/**
 * @brief cub::BlockStoreAlgorithm enumerates alternative algorithms for cub::BlockStore to write a
 *        blocked arrangement of items across a CUDA thread block to a linear segment of memory.
 */
enum BlockStoreAlgorithm
{
    /**
     * @par Overview
     *
     * A [<em>blocked arrangement</em>](index.html#sec5sec3) of data is written
     * directly to memory.
     *
     * @par Performance Considerations
     * - The utilization of memory transactions (coalescing) decreases as the
     *   access stride between threads increases (i.e., the number items per thread).
     */
    BLOCK_STORE_DIRECT,

    /**
     * @par Overview
     * A [<em>striped arrangement</em>](index.html#sec5sec3) of data is written
     * directly to memory.
     *
     * @par Performance Considerations
     * The utilization of memory transactions (coalescing) remains high regardless
     * of items written per thread.
     */
    BLOCK_STORE_STRIPED,

    /**
     * @par Overview
     *
     * A [<em>blocked arrangement</em>](index.html#sec5sec3) of data is written directly
     * to memory using CUDA's built-in vectorized stores as a coalescing optimization.
     * For example, <tt>st.global.v4.s32</tt> instructions will be generated
     * when @p T = @p int and @p ITEMS_PER_THREAD % 4 == 0.
     *
     * @par Performance Considerations
     * - The utilization of memory transactions (coalescing) remains high until the the
     *   access stride between threads (i.e., the number items per thread) exceeds the
     *   maximum vector store width (typically 4 items or 64B, whichever is lower).
     * - The following conditions will prevent vectorization and writing will fall back to cub::BLOCK_STORE_DIRECT:
     *   - @p ITEMS_PER_THREAD is odd
     *   - The @p OutputIteratorT is not a simple pointer type
     *   - The block output offset is not quadword-aligned
     *   - The data type @p T is not a built-in primitive or CUDA vector type
     *     (e.g., @p short, @p int2, @p double, @p float2, etc.)
     */
    BLOCK_STORE_VECTORIZE,

    /**
     * @par Overview
     * A [<em>blocked arrangement</em>](index.html#sec5sec3) is locally
     * transposed and then efficiently written to memory as a
     * [<em>striped arrangement</em>](index.html#sec5sec3).
     *
     * @par Performance Considerations
     * - The utilization of memory transactions (coalescing) remains high regardless
     *   of items written per thread.
     * - The local reordering incurs slightly longer latencies and throughput than the
     *   direct cub::BLOCK_STORE_DIRECT and cub::BLOCK_STORE_VECTORIZE alternatives.
     */
    BLOCK_STORE_TRANSPOSE,

    /**
     * @par Overview
     * A [<em>blocked arrangement</em>](index.html#sec5sec3) is locally
     * transposed and then efficiently written to memory as a
     * [<em>warp-striped arrangement</em>](index.html#sec5sec3)
     *
     * @par Usage Considerations
     * - BLOCK_THREADS must be a multiple of WARP_THREADS
     *
     * @par Performance Considerations
     * - The utilization of memory transactions (coalescing) remains high regardless
     *   of items written per thread.
     * - The local reordering incurs slightly longer latencies and throughput than the
     *   direct cub::BLOCK_STORE_DIRECT and cub::BLOCK_STORE_VECTORIZE alternatives.
     */
    BLOCK_STORE_WARP_TRANSPOSE,

    /**
     * @par Overview
     * A [<em>blocked arrangement</em>](index.html#sec5sec3) is locally
     * transposed and then efficiently written to memory as a
     * [<em>warp-striped arrangement</em>](index.html#sec5sec3)
     * To reduce the shared memory requirement, only one warp's worth of shared
     * memory is provisioned and is subsequently time-sliced among warps.
     *
     * @par Usage Considerations
     * - BLOCK_THREADS must be a multiple of WARP_THREADS
     *
     * @par Performance Considerations
     * - The utilization of memory transactions (coalescing) remains high regardless
     *   of items written per thread.
     * - Provisions less shared memory temporary storage, but incurs larger
     *   latencies than the BLOCK_STORE_WARP_TRANSPOSE alternative.
     */
    BLOCK_STORE_WARP_TRANSPOSE_TIMESLICED,
};


/**
 * @brief The BlockStore class provides [<em>collective</em>](index.html#sec0) data movement
 *        methods for writing a [<em>blocked arrangement</em>](index.html#sec5sec3) of items
 *        partitioned across a CUDA thread block to a linear segment of memory.
 *        ![](block_store_logo.png)
 *
 * @ingroup BlockModule
 *
 * @ingroup UtilIo
 *
 * @tparam T
 *   The type of data to be written.
 *
 * @tparam BLOCK_DIM_X
 *   The thread block length in threads along the X dimension
 *
 * @tparam ITEMS_PER_THREAD
 *   The number of consecutive items partitioned onto each thread.
 *
 * @tparam ALGORITHM
 *   <b>[optional]</b> cub::BlockStoreAlgorithm tuning policy enumeration.
 *   default: cub::BLOCK_STORE_DIRECT.
 *
 * @tparam BLOCK_DIM_Y
 *   <b>[optional]</b> The thread block length in threads along the Y dimension (default: 1)
 *
 * @tparam BLOCK_DIM_Z
 *   <b>[optional]</b> The thread block length in threads along the Z dimension (default: 1)
 *
 * @tparam LEGACY_PTX_ARCH
 *   <b>[optional]</b> Unused.
 *
 * @par Overview
 * - The BlockStore class provides a single data movement abstraction that can be specialized
 *   to implement different cub::BlockStoreAlgorithm strategies.  This facilitates different
 *   performance policies for different architectures, data types, granularity sizes, etc.
 * - BlockStore can be optionally specialized by different data movement strategies:
 *   -# <b>cub::BLOCK_STORE_DIRECT</b>.  A [<em>blocked arrangement</em>](index.html#sec5sec3) of data is written
 *      directly to memory. [More...](\ref cub::BlockStoreAlgorithm)
 *   -# <b>cub::BLOCK_STORE_STRIPED</b>.  A [<em>striped arrangement</em>](index.html#sec5sec3)
 *      of data is written directly to memory. [More...](\ref cub::BlockStoreAlgorithm)
 *   -# <b>cub::BLOCK_STORE_VECTORIZE</b>.  A [<em>blocked arrangement</em>](index.html#sec5sec3)
 *      of data is written directly to memory using CUDA's built-in vectorized stores as a
 *      coalescing optimization.  [More...](\ref cub::BlockStoreAlgorithm)
 *   -# <b>cub::BLOCK_STORE_TRANSPOSE</b>.  A [<em>blocked arrangement</em>](index.html#sec5sec3)
 *      is locally transposed into a [<em>striped arrangement</em>](index.html#sec5sec3) which is
 *      then written to memory.  [More...](\ref cub::BlockStoreAlgorithm)
 *   -# <b>cub::BLOCK_STORE_WARP_TRANSPOSE</b>.  A [<em>blocked arrangement</em>](index.html#sec5sec3)
 *      is locally transposed into a [<em>warp-striped arrangement</em>](index.html#sec5sec3) which is
 *      then written to memory.  [More...](\ref cub::BlockStoreAlgorithm)
 *   -# <b>cub::BLOCK_STORE_WARP_TRANSPOSE_TIMESLICED</b>.  A [<em>blocked arrangement</em>](index.html#sec5sec3)
 *      is locally transposed into a [<em>warp-striped arrangement</em>](index.html#sec5sec3) which is
 *      then written to memory. To reduce the shared memory requireent, only one warp's worth of shared
 *      memory is provisioned and is subsequently time-sliced among warps.  [More...](\ref cub::BlockStoreAlgorithm)
 * - \rowmajor
 *
 * @par A Simple Example
 * \blockcollective{BlockStore}
 * @par
 * The code snippet below illustrates the storing of a "blocked" arrangement
 * of 512 integers across 128 threads (where each thread owns 4 consecutive items)
 * into a linear segment of memory. The store is specialized for @p BLOCK_STORE_WARP_TRANSPOSE,
 * meaning items are locally reordered among threads so that memory references will be
 * efficiently coalesced using a warp-striped access pattern.
 * @par
 * @code
 * #include <cub/cub.cuh>   // or equivalently <cub/block/block_store.cuh>
 *
 * __global__ void ExampleKernel(int *d_data, ...)
 * {
 *     // Specialize BlockStore for a 1D block of 128 threads owning 4 integer items each
 *     typedef cub::BlockStore<int, 128, 4, BLOCK_STORE_WARP_TRANSPOSE> BlockStore;
 *
 *     // Allocate shared memory for BlockStore
 *     __shared__ typename BlockStore::TempStorage temp_storage;
 *
 *     // Obtain a segment of consecutive items that are blocked across threads
 *     int thread_data[4];
 *     ...
 *
 *     // Store items to linear memory
 *     BlockStore(temp_storage).Store(d_data, thread_data);
 *
 * @endcode
 * @par
 * Suppose the set of @p thread_data across the block of threads is
 * <tt>{ [0,1,2,3], [4,5,6,7], ..., [508,509,510,511] }</tt>.
 * The output @p d_data will be <tt>0, 1, 2, 3, 4, 5, ...</tt>.
 *
 * @par Re-using dynamically allocating shared memory
 * The following example under the examples/block folder illustrates usage of
 * dynamically shared memory with BlockReduce and how to re-purpose
 * the same memory region:
 * <a href="../../examples/block/example_block_reduce_dyn_smem.cu">example_block_reduce_dyn_smem.cu</a>
 *
 * This example can be easily adapted to the storage required by BlockStore.
 */
template <
    typename                T,
    int                     BLOCK_DIM_X,
    int                     ITEMS_PER_THREAD,
    BlockStoreAlgorithm     ALGORITHM           = BLOCK_STORE_DIRECT,
    int                     BLOCK_DIM_Y         = 1,
    int                     BLOCK_DIM_Z         = 1,
    int                     LEGACY_PTX_ARCH     = 0>
class BlockStore
{
private:
    /******************************************************************************
     * Constants and typed definitions
     ******************************************************************************/

    /// Constants
    enum
    {
        /// The thread block size in threads
        BLOCK_THREADS = BLOCK_DIM_X * BLOCK_DIM_Y * BLOCK_DIM_Z,
    };


    /******************************************************************************
     * Algorithmic variants
     ******************************************************************************/

    /// Store helper
    template <BlockStoreAlgorithm _POLICY, int DUMMY>
    struct StoreInternal;


    /**
     * BLOCK_STORE_DIRECT specialization of store helper
     */
    template <int DUMMY>
    struct StoreInternal<BLOCK_STORE_DIRECT, DUMMY>
    {
        /// Shared memory storage layout type
        typedef NullType TempStorage;

        /// Linear thread-id
        int linear_tid;

        /// Constructor
        __device__ __forceinline__ StoreInternal(
            TempStorage &/*temp_storage*/,
            int linear_tid)
        :
            linear_tid(linear_tid)
        {}

        /**
         * @brief Store items into a linear segment of memory
         *
         * @param[in] block_itr
         *   The thread block's base output iterator for storing to
         *
         * @param[in] items
         *   Data to store
         */
        template <typename OutputIteratorT>
        __device__ __forceinline__ void Store(OutputIteratorT block_itr,
                                              T (&items)[ITEMS_PER_THREAD])
        {
            StoreDirectBlocked(linear_tid, block_itr, items);
        }

        /**
         * @brief Store items into a linear segment of memory, guarded by range
         *
         * @param[in] block_itr
         *   The thread block's base output iterator for storing to
         *
         * @param[in] items
         *   Data to store
         *
         * @param[in] valid_items
         *   Number of valid items to write
         */
        template <typename OutputIteratorT>
        __device__ __forceinline__ void Store(OutputIteratorT block_itr,
                                              T (&items)[ITEMS_PER_THREAD],
                                              int valid_items)
        {
            StoreDirectBlocked(linear_tid, block_itr, items, valid_items);
        }
    };


    /**
    * BLOCK_STORE_STRIPED specialization of store helper
    */
    template <int DUMMY>
    struct StoreInternal<BLOCK_STORE_STRIPED, DUMMY>
    {
        /// Shared memory storage layout type
        typedef NullType TempStorage;

        /// Linear thread-id
        int linear_tid;

        /// Constructor
        __device__ __forceinline__ StoreInternal(
            TempStorage &/*temp_storage*/,
            int linear_tid)
        :
            linear_tid(linear_tid)
        {}

        /**
         * @brief Store items into a linear segment of memory
         *
         * @param[in] block_itr
         *   The thread block's base output iterator for storing to
         *
         * @param[in] items
         *   Data to store
         */
        template <typename OutputIteratorT>
        __device__ __forceinline__ void Store(OutputIteratorT block_itr,
                                              T (&items)[ITEMS_PER_THREAD])
        {
            StoreDirectStriped<BLOCK_THREADS>(linear_tid, block_itr, items);
        }

        /**
         * @brief Store items into a linear segment of memory, guarded by range
         *
         * @param[in] block_itr
         *   The thread block's base output iterator for storing to
         *
         * @param[in] items
         *   Data to store
         *
         * @param[in] valid_items
         *   Number of valid items to write
         */
        template <typename OutputIteratorT>
        __device__ __forceinline__ void Store(OutputIteratorT block_itr,
                                              T (&items)[ITEMS_PER_THREAD],
                                              int valid_items)
        {
            StoreDirectStriped<BLOCK_THREADS>(linear_tid, block_itr, items, valid_items);
        }
    };


    /**
     * BLOCK_STORE_VECTORIZE specialization of store helper
     */
    template <int DUMMY>
    struct StoreInternal<BLOCK_STORE_VECTORIZE, DUMMY>
    {
        /// Shared memory storage layout type
        typedef NullType TempStorage;

        /// Linear thread-id
        int linear_tid;

        /// Constructor
        __device__ __forceinline__ StoreInternal(
            TempStorage &/*temp_storage*/,
            int linear_tid)
        :
            linear_tid(linear_tid)
        {}

        /**
         * @brief Store items into a linear segment of memory,
         *        specialized for native pointer types (attempts vectorization)
         *
         * @param[in] block_ptr
         *   The thread block's base output iterator for storing to
         *
         * @param[in] items
         *   Data to store
         */
        __device__ __forceinline__ void Store(T *block_ptr, T (&items)[ITEMS_PER_THREAD])
        {
            StoreDirectBlockedVectorized(linear_tid, block_ptr, items);
        }

        /**
         * @brief Store items into a linear segment of memory,
         *        specialized for opaque input iterators (skips vectorization)
         *
         * @param[in] block_itr
         *   The thread block's base output iterator for storing to
         *
         * @param[in] items
         *   Data to store
         */
        template <typename OutputIteratorT>
        __device__ __forceinline__ void Store(OutputIteratorT block_itr,
                                              T (&items)[ITEMS_PER_THREAD])
        {
            StoreDirectBlocked(linear_tid, block_itr, items);
        }

        /**
         * @brief Store items into a linear segment of memory, guarded by range
         *
         * @param[in] block_itr
         *   The thread block's base output iterator for storing to
         *
         * @param[in] items
         *   Data to store
         *
         * @param[in] valid_items
         *   Number of valid items to write
         */
        template <typename OutputIteratorT>
        __device__ __forceinline__ void Store(OutputIteratorT block_itr,
                                              T (&items)[ITEMS_PER_THREAD],
                                              int valid_items)
        {
            StoreDirectBlocked(linear_tid, block_itr, items, valid_items);
        }
    };


    /**
     * BLOCK_STORE_TRANSPOSE specialization of store helper
     */
    template <int DUMMY>
    struct StoreInternal<BLOCK_STORE_TRANSPOSE, DUMMY>
    {
        // BlockExchange utility type for keys
        typedef BlockExchange<T, BLOCK_DIM_X, ITEMS_PER_THREAD, false, BLOCK_DIM_Y, BLOCK_DIM_Z> BlockExchange;

        /// Shared memory storage layout type
        struct _TempStorage : BlockExchange::TempStorage
        {
            /// Temporary storage for partially-full block guard
            volatile int valid_items;
        };

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

        /// Thread reference to shared storage
        _TempStorage &temp_storage;

        /// Linear thread-id
        int linear_tid;

        /// Constructor
        __device__ __forceinline__ StoreInternal(
            TempStorage &temp_storage,
            int linear_tid)
        :
            temp_storage(temp_storage.Alias()),
            linear_tid(linear_tid)
        {}

        /**
         * @brief Store items into a linear segment of memory
         *
         * @param[in] block_itr
         *   The thread block's base output iterator for storing to
         *
         * @param[in] items
         *   Data to store
         */
        template <typename OutputIteratorT>
        __device__ __forceinline__ void Store(OutputIteratorT block_itr,
                                              T (&items)[ITEMS_PER_THREAD])
        {
            BlockExchange(temp_storage).BlockedToStriped(items);
            StoreDirectStriped<BLOCK_THREADS>(linear_tid, block_itr, items);
        }

        /**
         * @brief Store items into a linear segment of memory, guarded by range
         *
         * @param[in] block_itr
         *   The thread block's base output iterator for storing to
         *
         * @param[in] items
         *   Data to store
         *
         * @param[in] valid_items
         *   Number of valid items to write
         */
        template <typename OutputIteratorT>
        __device__ __forceinline__ void Store(OutputIteratorT block_itr,
                                              T (&items)[ITEMS_PER_THREAD],
                                              int valid_items)
        {
            BlockExchange(temp_storage).BlockedToStriped(items);
            if (linear_tid == 0)
            {
              // Move through volatile smem as a workaround to prevent RF spilling on
              // subsequent loads
              temp_storage.valid_items = valid_items;
            }
            CTA_SYNC();
            StoreDirectStriped<BLOCK_THREADS>(linear_tid, block_itr, items, temp_storage.valid_items);
        }
    };


    /**
     * BLOCK_STORE_WARP_TRANSPOSE specialization of store helper
     */
    template <int DUMMY>
    struct StoreInternal<BLOCK_STORE_WARP_TRANSPOSE, DUMMY>
    {
        enum
        {
            WARP_THREADS = CUB_WARP_THREADS(0)
        };

        // Assert BLOCK_THREADS must be a multiple of WARP_THREADS
        CUB_STATIC_ASSERT((int(BLOCK_THREADS) % int(WARP_THREADS) == 0), "BLOCK_THREADS must be a multiple of WARP_THREADS");

        // BlockExchange utility type for keys
        typedef BlockExchange<T, BLOCK_DIM_X, ITEMS_PER_THREAD, false, BLOCK_DIM_Y, BLOCK_DIM_Z> BlockExchange;

        /// Shared memory storage layout type
        struct _TempStorage : BlockExchange::TempStorage
        {
            /// Temporary storage for partially-full block guard
            volatile int valid_items;
        };

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

        /// Thread reference to shared storage
        _TempStorage &temp_storage;

        /// Linear thread-id
        int linear_tid;

        /// Constructor
        __device__ __forceinline__ StoreInternal(
            TempStorage &temp_storage,
            int linear_tid)
        :
            temp_storage(temp_storage.Alias()),
            linear_tid(linear_tid)
        {}

        /**
         * @brief Store items into a linear segment of memory
         *
         * @param[in] block_itr
         *   The thread block's base output iterator for storing to
         *
         * @param[in] items
         *   Data to store
         */
        template <typename OutputIteratorT>
        __device__ __forceinline__ void Store(OutputIteratorT block_itr,
                                              T (&items)[ITEMS_PER_THREAD])
        {
            BlockExchange(temp_storage).BlockedToWarpStriped(items);
            StoreDirectWarpStriped(linear_tid, block_itr, items);
        }

        /**
         * @brief Store items into a linear segment of memory, guarded by range
         *
         * @param[in] block_itr
         *   The thread block's base output iterator for storing to
         *
         * @param[in] items
         *   Data to store
         *
         * @param[in] valid_items
         *   Number of valid items to write
         */
        template <typename OutputIteratorT>
        __device__ __forceinline__ void Store(OutputIteratorT block_itr,
                                              T (&items)[ITEMS_PER_THREAD],
                                              int valid_items)
        {
            BlockExchange(temp_storage).BlockedToWarpStriped(items);
            if (linear_tid == 0)
            {
              // Move through volatile smem as a workaround to prevent RF spilling on
              // subsequent loads
              temp_storage.valid_items = valid_items;
            }
            CTA_SYNC();
            StoreDirectWarpStriped(linear_tid, block_itr, items, temp_storage.valid_items);
        }
    };


    /**
     * BLOCK_STORE_WARP_TRANSPOSE_TIMESLICED specialization of store helper
     */
    template <int DUMMY>
    struct StoreInternal<BLOCK_STORE_WARP_TRANSPOSE_TIMESLICED, DUMMY>
    {
        enum
        {
            WARP_THREADS = CUB_WARP_THREADS(0)
        };

        // Assert BLOCK_THREADS must be a multiple of WARP_THREADS
        CUB_STATIC_ASSERT((int(BLOCK_THREADS) % int(WARP_THREADS) == 0), "BLOCK_THREADS must be a multiple of WARP_THREADS");

        // BlockExchange utility type for keys
        typedef BlockExchange<T, BLOCK_DIM_X, ITEMS_PER_THREAD, true, BLOCK_DIM_Y, BLOCK_DIM_Z> BlockExchange;

        /// Shared memory storage layout type
        struct _TempStorage : BlockExchange::TempStorage
        {
            /// Temporary storage for partially-full block guard
            volatile int valid_items;
        };

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

        /// Thread reference to shared storage
        _TempStorage &temp_storage;

        /// Linear thread-id
        int linear_tid;

        /// Constructor
        __device__ __forceinline__ StoreInternal(
            TempStorage &temp_storage,
            int linear_tid)
        :
            temp_storage(temp_storage.Alias()),
            linear_tid(linear_tid)
        {}

        /**
         * @brief Store items into a linear segment of memory
         *
         * @param[in] block_itr
         *   The thread block's base output iterator for storing to
         *
         * @param[in] items
         *   Data to store
         */
        template <typename OutputIteratorT>
        __device__ __forceinline__ void Store(OutputIteratorT block_itr,
                                              T (&items)[ITEMS_PER_THREAD])
        {
            BlockExchange(temp_storage).BlockedToWarpStriped(items);
            StoreDirectWarpStriped(linear_tid, block_itr, items);
        }

        /**
         * @brief Store items into a linear segment of memory, guarded by range
         *
         * @param[in] block_itr
         *   The thread block's base output iterator for storing to
         *
         * @param[in] items
         *   Data to store
         *
         * @param[in] valid_items
         *   Number of valid items to write
         */
        template <typename OutputIteratorT>
        __device__ __forceinline__ void Store(OutputIteratorT block_itr,
                                              T (&items)[ITEMS_PER_THREAD],
                                              int valid_items)
        {
            BlockExchange(temp_storage).BlockedToWarpStriped(items);
            if (linear_tid == 0)
            {
              // Move through volatile smem as a workaround to prevent RF spilling on
              // subsequent loads
              temp_storage.valid_items = valid_items;
            }
            CTA_SYNC();
            StoreDirectWarpStriped(linear_tid, block_itr, items, temp_storage.valid_items);
        }
    };


    /******************************************************************************
     * Type definitions
     ******************************************************************************/

    /// Internal load implementation to use
    typedef StoreInternal<ALGORITHM, 0> InternalStore;


    /// Shared memory storage layout type
    typedef typename InternalStore::TempStorage _TempStorage;


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

    /// Internal storage allocator
    __device__ __forceinline__ _TempStorage& PrivateStorage()
    {
        __shared__ _TempStorage private_storage;
        return private_storage;
    }


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

    /// Thread reference to shared storage
    _TempStorage &temp_storage;

    /// Linear thread-id
    int linear_tid;

public:


    /// @smemstorage{BlockStore}
    struct TempStorage : Uninitialized<_TempStorage> {};


    /******************************************************************//**
     * @name Collective constructors
     *********************************************************************/
    //@{

    /**
     * @brief Collective constructor using a private static allocation of shared memory as temporary storage.
     */
    __device__ __forceinline__ BlockStore()
    :
        temp_storage(PrivateStorage()),
        linear_tid(RowMajorTid(BLOCK_DIM_X, BLOCK_DIM_Y, BLOCK_DIM_Z))
    {}

    /**
     * @brief Collective constructor using the specified memory allocation as temporary storage.
     *
     * @param temp_storage[in]
     *   Reference to memory allocation having layout type TempStorage
     */
    __device__ __forceinline__ BlockStore(TempStorage &temp_storage)
        : temp_storage(temp_storage.Alias())
        , linear_tid(RowMajorTid(BLOCK_DIM_X, BLOCK_DIM_Y, BLOCK_DIM_Z))
    {}


    //@}  end member group
    /******************************************************************//**
     * @name Data movement
     *********************************************************************/
    //@{

    /**
     * @brief Store items into a linear segment of memory.
     *
     * @par
     * - @blocked
     * - @smemreuse
     *
     * @par Snippet
     * The code snippet below illustrates the storing of a "blocked" arrangement
     * of 512 integers across 128 threads (where each thread owns 4 consecutive items)
     * into a linear segment of memory. The store is specialized for @p BLOCK_STORE_WARP_TRANSPOSE,
     * meaning items are locally reordered among threads so that memory references will be
     * efficiently coalesced using a warp-striped access pattern.
     * @par
     * @code
     * #include <cub/cub.cuh>   // or equivalently <cub/block/block_store.cuh>
     *
     * __global__ void ExampleKernel(int *d_data, ...)
     * {
     *     // Specialize BlockStore for a 1D block of 128 threads owning 4 integer items each
     *     typedef cub::BlockStore<int, 128, 4, BLOCK_STORE_WARP_TRANSPOSE> BlockStore;
     *
     *     // Allocate shared memory for BlockStore
     *     __shared__ typename BlockStore::TempStorage temp_storage;
     *
     *     // Obtain a segment of consecutive items that are blocked across threads
     *     int thread_data[4];
     *     ...
     *
     *     // Store items to linear memory
     *     int thread_data[4];
     *     BlockStore(temp_storage).Store(d_data, thread_data);
     *
     * @endcode
     * @par
     * Suppose the set of @p thread_data across the block of threads is
     * <tt>{ [0,1,2,3], [4,5,6,7], ..., [508,509,510,511] }</tt>.
     * The output @p d_data will be <tt>0, 1, 2, 3, 4, 5, ...</tt>.
     *
     * @param block_itr[out]
     *   The thread block's base output iterator for storing to
     *
     * @param items[in]
     *   Data to store
     *
     */
    template <typename OutputIteratorT>
    __device__ __forceinline__ void Store(OutputIteratorT block_itr, T (&items)[ITEMS_PER_THREAD])
    {
        InternalStore(temp_storage, linear_tid).Store(block_itr, items);
    }

    /**
     * @brief Store items into a linear segment of memory, guarded by range.
     *
     * @par
     * - @blocked
     * - @smemreuse
     *
     * @par Snippet
     * The code snippet below illustrates the guarded storing of a "blocked" arrangement
     * of 512 integers across 128 threads (where each thread owns 4 consecutive items)
     * into a linear segment of memory. The store is specialized for @p BLOCK_STORE_WARP_TRANSPOSE,
     * meaning items are locally reordered among threads so that memory references will be
     * efficiently coalesced using a warp-striped access pattern.
     * @par
     * @code
     * #include <cub/cub.cuh>   // or equivalently <cub/block/block_store.cuh>
     *
     * __global__ void ExampleKernel(int *d_data, int valid_items, ...)
     * {
     *     // Specialize BlockStore for a 1D block of 128 threads owning 4 integer items each
     *     typedef cub::BlockStore<int, 128, 4, BLOCK_STORE_WARP_TRANSPOSE> BlockStore;
     *
     *     // Allocate shared memory for BlockStore
     *     __shared__ typename BlockStore::TempStorage temp_storage;
     *
     *     // Obtain a segment of consecutive items that are blocked across threads
     *     int thread_data[4];
     *     ...
     *
     *     // Store items to linear memory
     *     int thread_data[4];
     *     BlockStore(temp_storage).Store(d_data, thread_data, valid_items);
     *
     * @endcode
     * @par
     * Suppose the set of @p thread_data across the block of threads is
     * <tt>{ [0,1,2,3], [4,5,6,7], ..., [508,509,510,511] }</tt> and @p valid_items is @p 5.
     * The output @p d_data will be <tt>0, 1, 2, 3, 4, ?, ?, ?, ...</tt>, with
     * only the first two threads being unmasked to store portions of valid data.
     *
     * @param block_itr[out]
     *   The thread block's base output iterator for storing to
     *
     * @param items[in]
     *   Data to store
     *
     * @param valid_items[in]
     *   Number of valid items to write
     */
    template <typename OutputIteratorT>
    __device__ __forceinline__ void Store(OutputIteratorT block_itr,
                                          T (&items)[ITEMS_PER_THREAD],
                                          int valid_items)
    {
        InternalStore(temp_storage, linear_tid).Store(block_itr, items, valid_items);
    }

    //@}  end member group
};

template <class Policy,
          class It,
          class T = cub::detail::value_t<It>>
struct BlockStoreType
{
  using type = cub::BlockStore<T,
                               Policy::BLOCK_THREADS,
                               Policy::ITEMS_PER_THREAD,
                               Policy::STORE_ALGORITHM>;
};

CUB_NAMESPACE_END