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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>

CUB_NAMESPACE_BEGIN

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

//! @rst
//! Store a blocked arrangement of items across a thread block into a linear segment of items
//!
//! @blocked
//!
//! @endrst
//!
//! @tparam T
//!   **[inferred]** The data type to store.
//!
//! @tparam ITEMS_PER_THREAD
//!   **[inferred]** The number of consecutive items partitioned onto each thread.
//!
//! @tparam OutputIteratorT
//!   **[inferred]** The random-access iterator type for output @iterator.
//!
//! @param[in] linear_tid
//!   A suitable 1D thread-identifier for the calling thread
//!   (e.g., ``(threadIdx.y * blockDim.x) + linear_tid`` 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>
_CCCL_DEVICE _CCCL_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];
    }
}

//! @rst
//! Store a blocked arrangement of items across a
//! thread block into a linear segment of items, guarded by range
//!
//! @blocked
//!
//! @endrst
//!
//! @tparam T
//!   **[inferred]** The data type to store.
//!
//! @tparam ITEMS_PER_THREAD
//!   **[inferred]** The number of consecutive items partitioned onto each thread.
//!
//! @tparam OutputIteratorT
//!   **[inferred]** The random-access iterator type for output @iterator.
//!
//! @param[in] linear_tid
//!   A suitable 1D thread-identifier for the calling thread
//!   (e.g., `(threadIdx.y * blockDim.x) + linear_tid` 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>
_CCCL_DEVICE _CCCL_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];
        }
    }
}

//! @rst
//! Store a blocked arrangement of items across a
//! thread block into a linear segment of items.
//!
//! @blocked
//!
//! The output offset (``block_ptr + block_offset``) must be quad-item aligned,
//! which is the default starting offset returned by ``cudaMalloc()``
//!
//! The following conditions will prevent vectorization and storing will
//! fall back to cub::BLOCK_STORE_DIRECT:
//!
//!   - ``ITEMS_PER_THREAD`` is odd
//!   - The data type ``T`` is not a built-in primitive or CUDA vector type
//!     (e.g., ``short``, ``int2``, ``double``, ``float2``, etc.)
//!
//! @endrst
//!
//! @tparam T
//!   **[inferred]** The data type to store.
//!
//! @tparam ITEMS_PER_THREAD
//!   **[inferred]** The number of consecutive items partitioned onto each thread.
//!
//! @param[in] linear_tid
//!   A suitable 1D thread-identifier for the calling thread
//!   (e.g., ``(threadIdx.y * blockDim.x) + linear_tid`` 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>
_CCCL_DEVICE _CCCL_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)
//! @{

//! @rst
//! Store a striped arrangement of data across the thread block into a
//! linear segment of items.
//!
//! @striped
//!
//! @endrst
//!
//! @tparam BLOCK_THREADS
//!   The thread block size in threads
//!
//! @tparam T
//!   **[inferred]** The data type to store.
//!
//! @tparam ITEMS_PER_THREAD
//!   **[inferred]** The number of consecutive items partitioned onto each thread.
//!
//! @tparam OutputIteratorT
//!   **[inferred]** The random-access iterator type for output @iterator.
//!
//! @param[in] linear_tid
//!   A suitable 1D thread-identifier for the calling thread
//!   (e.g., `(threadIdx.y * blockDim.x) + linear_tid` 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>
_CCCL_DEVICE _CCCL_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];
    }
}

//! @rst
//! Store a striped arrangement of data across the thread block into
//! a linear segment of items, guarded by range
//!
//! @striped
//!
//! @endrst
//!
//! @tparam BLOCK_THREADS
//!   The thread block size in threads
//!
//! @tparam T
//!   **[inferred]** The data type to store.
//!
//! @tparam ITEMS_PER_THREAD
//!   **[inferred]** The number of consecutive items partitioned onto each thread.
//!
//! @tparam OutputIteratorT
//!   **[inferred]** The random-access iterator type for output @iterator.
//!
//! @param[in] linear_tid
//!   A suitable 1D thread-identifier for the calling thread
//!   (e.g., `(threadIdx.y * blockDim.x) + linear_tid` 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>
_CCCL_DEVICE _CCCL_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)
//! @{

//! @rst
//! Store a warp-striped arrangement of data across the
//! thread block into a linear segment of items.
//!
//! @warpstriped
//!
//! Usage Considerations
//! ++++++++++++++++++++
//!
//! The number of threads in the thread block must be a multiple of the architecture's warp size.
//!
//! @endrst
//!
//! @tparam T
//!   **[inferred]** The data type to store.
//!
//! @tparam ITEMS_PER_THREAD
//!   **[inferred]** The number of consecutive items partitioned onto each thread.
//!
//! @tparam OutputIteratorT
//!   **[inferred]** The random-access iterator type for output @iterator.
//!
//! @param[in] linear_tid
//!   A suitable 1D thread-identifier for the calling thread
//!   (e.g., `(threadIdx.y * blockDim.x) + linear_tid` 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>
_CCCL_DEVICE _CCCL_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];
    }
}

//! @rst
//! Store a warp-striped arrangement of data across the thread block into a
//! linear segment of items, guarded by range
//!
//! @warpstriped
//!
//! Usage Considerations
//! ++++++++++++++++++++
//!
//! The number of threads in the thread block must be a multiple of the architecture's warp size.
//!
//! @endrst
//!
//! @tparam T
//!   **[inferred]** The data type to store.
//!
//! @tparam ITEMS_PER_THREAD
//!   **[inferred]** The number of consecutive items partitioned onto each thread.
//!
//! @tparam OutputIteratorT
//!   **[inferred]** The random-access iterator type for output @iterator.
//!
//! @param[in] linear_tid
//!   A suitable 1D thread-identifier for the calling thread
//!   (e.g., `(threadIdx.y * blockDim.x) + linear_tid` 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>
_CCCL_DEVICE _CCCL_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


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

//! 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
{
  //! @rst
  //! Overview
  //! ++++++++++++++++++++++++++
  //!
  //! A :ref:`blocked arrangement <flexible-data-arrangement>` of data is written directly to memory.
  //!
  //! Performance Considerations
  //! ++++++++++++++++++++++++++
  //!
  //! - The utilization of memory transactions (coalescing) decreases as the
  //!   access stride between threads increases (i.e., the number items per thread).
  //!
  //! @endrst
  BLOCK_STORE_DIRECT,

  //! @rst
  //! Overview
  //! ++++++++++++++++++++++++++
  //!
  //! A :ref:`striped arrangement <flexible-data-arrangement>` of data is written directly to memory.
  //!
  //! Performance Considerations
  //! ++++++++++++++++++++++++++
  //!
  //! The utilization of memory transactions (coalescing) remains high regardless
  //! of items written per thread.
  //!
  //! @endrst
  BLOCK_STORE_STRIPED,

  //! @rst
  //! Overview
  //! ++++++++++++++++++++++++++
  //!
  //! A :ref:`blocked arrangement <flexible-data-arrangement>` of data is written directly
  //! to memory using CUDA's built-in vectorized stores as a coalescing optimization.
  //! For example, ``st.global.v4.s32`` instructions will be generated
  //! when ``T = int`` and ``ITEMS_PER_THREAD % 4 == 0``.
  //!
  //! 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:
  //!   - ``ITEMS_PER_THREAD`` is odd
  //!   - The ``OutputIteratorT`` is not a simple pointer type
  //!   - The block output offset is not quadword-aligned
  //!   - The data type ``T`` is not a built-in primitive or CUDA vector type
  //!     (e.g., ``short``, ``int2``, ``double``, ``float2``, etc.)
  //!
  //! @endrst
  BLOCK_STORE_VECTORIZE,

  //! @rst
  //! Overview
  //! ++++++++++++++++++++++++++
  //!
  //! A :ref:`blocked arrangement <flexible-data-arrangement>` is locally
  //! transposed and then efficiently written to memory as a :ref:`striped arrangement <flexible-data-arrangement>`.
  //!
  //! 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.
  //!
  //! @endrst
  BLOCK_STORE_TRANSPOSE,

  //! @rst
  //! Overview
  //! ++++++++++++++++++++++++++
  //! A :ref:`blocked arrangement <flexible-data-arrangement>` is locally
  //! transposed and then efficiently written to memory as a
  //! :ref:`warp-striped arrangement <flexible-data-arrangement>`.
  //!
  //! Usage Considerations
  //! ++++++++++++++++++++++++++
  //!
  //! - BLOCK_THREADS must be a multiple of WARP_THREADS
  //!
  //! 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.
  //!
  //! @endrst
  BLOCK_STORE_WARP_TRANSPOSE,

  //! @rst
  //! Overview
  //! ++++++++++++++++++++++++++
  //!
  //! A :ref:`blocked arrangement <flexible-data-arrangement>` is locally
  //! transposed and then efficiently written to memory as a
  //! :ref:`warp-striped arrangement <flexible-data-arrangement>`.
  //! To reduce the shared memory requirement, only one warp's worth of shared
  //! memory is provisioned and is subsequently time-sliced among warps.
  //!
  //! Usage Considerations
  //! ++++++++++++++++++++++++++
  //!
  //! - BLOCK_THREADS must be a multiple of WARP_THREADS
  //!
  //! 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.
  //!
  //! @endrst
  BLOCK_STORE_WARP_TRANSPOSE_TIMESLICED,
};

//! @rst
//! The BlockStore class provides :ref:`collective <collective-primitives>` data movement
//! methods for writing a :ref:`blocked arrangement <flexible-data-arrangement>` of items
//! partitioned across a CUDA thread block to a linear segment of memory.
//!
//! 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:
//!
//!   #. :cpp:enumerator:`cub::BLOCK_STORE_DIRECT`:
//!      A :ref:`blocked arrangement <flexible-data-arrangement>` of data is written directly to memory.
//!   #. :cpp:enumerator:`cub::BLOCK_STORE_STRIPED`:
//!      A :ref:`striped arrangement <flexible-data-arrangement>` of data is written directly to memory.
//!   #. :cpp:enumerator:`cub::BLOCK_STORE_VECTORIZE`:
//!      A :ref:`blocked arrangement <flexible-data-arrangement>` of data is written directly to memory
//!      using CUDA's built-in vectorized stores as a coalescing optimization.
//!   #. :cpp:enumerator:`cub::BLOCK_STORE_TRANSPOSE`
//!      A :ref:`blocked arrangement <flexible-data-arrangement>` is locally transposed into
//!      a :ref:`striped arrangement <flexible-data-arrangement>` which is then written to memory.
//!   #. :cpp:enumerator:`cub::BLOCK_STORE_WARP_TRANSPOSE:
//!      A :ref:`blocked arrangement <flexible-data-arrangement>` is locally transposed into
//!      a :ref:`warp-striped arrangement <flexible-data-arrangement>` which is then written to memory.
//!   #. :cpp:enumerator:`cub::BLOCK_STORE_WARP_TRANSPOSE_TIMESLICED`:
//!      A :ref:`blocked arrangement <flexible-data-arrangement>` is locally transposed into
//!      a :ref:`warp-striped arrangement <flexible-data-arrangement>` 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.
//!
//! - @rowmajor
//!
//! A Simple Example
//! +++++++++++++++++++++++++++++++++++++++++++++
//!
//! @blockcollective{BlockStore}
//!
//! 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 ``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.
//!
//! .. code-block:: c++
//!
//!    #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);
//!
//! Suppose the set of ``thread_data`` across the block of threads is
//! ``{ [0,1,2,3], [4,5,6,7], ..., [508,509,510,511] }``.
//! The output ``d_data`` will be ``0, 1, 2, 3, 4, 5, ...``.
//!
//! Re-using dynamically allocating shared memory
//! +++++++++++++++++++++++++++++++++++++++++++++
//!
//! The ``block/example_block_reduce_dyn_smem.cu`` example illustrates usage of
//! dynamically shared memory with BlockReduce and how to re-purpose the same memory region.
//! This example can be easily adapted to the storage required by BlockStore.
//!
//! @endrst
//!
//! @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
//!   **[optional]** cub::BlockStoreAlgorithm tuning policy enumeration (default: cub::BLOCK_STORE_DIRECT)
//!
//! @tparam BLOCK_DIM_Y
//!   **[optional]** The thread block length in threads along the Y dimension (default: 1)
//!
//! @tparam BLOCK_DIM_Z
//!   **[optional]** The thread block length in threads along the Z dimension (default: 1)
//!
//! @tparam LEGACY_PTX_ARCH
//!   **[optional]** Unused.
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:

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

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

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

        /// Linear thread-id
        int linear_tid;

        /// Constructor
        _CCCL_DEVICE _CCCL_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>
        _CCCL_DEVICE _CCCL_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>
        _CCCL_DEVICE _CCCL_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
        _CCCL_DEVICE _CCCL_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>
        _CCCL_DEVICE _CCCL_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>
        _CCCL_DEVICE _CCCL_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
        _CCCL_DEVICE _CCCL_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
         */
        _CCCL_DEVICE _CCCL_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>
        _CCCL_DEVICE _CCCL_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>
        _CCCL_DEVICE _CCCL_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
        _CCCL_DEVICE _CCCL_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>
        _CCCL_DEVICE _CCCL_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>
        _CCCL_DEVICE _CCCL_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
        _CCCL_DEVICE _CCCL_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>
        _CCCL_DEVICE _CCCL_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>
        _CCCL_DEVICE _CCCL_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
        _CCCL_DEVICE _CCCL_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>
        _CCCL_DEVICE _CCCL_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>
        _CCCL_DEVICE _CCCL_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);
        }
    };


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

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

    /// Internal storage allocator
    _CCCL_DEVICE _CCCL_FORCEINLINE _TempStorage& PrivateStorage()
    {
        __shared__ _TempStorage private_storage;
        return private_storage;
    }

    /// 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.
     */
    _CCCL_DEVICE _CCCL_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
     */
    _CCCL_DEVICE _CCCL_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
    //! @{

    //! @rst
    //! Store items into a linear segment of memory
    //!
    //! - @blocked
    //! - @smemreuse
    //!
    //! 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 ``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.
    //!
    //! .. code-block:: c++
    //!
    //!    #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);
    //!
    //! Suppose the set of ``thread_data`` across the block of threads is
    //! ``{ [0,1,2,3], [4,5,6,7], ..., [508,509,510,511] }``.
    //! The output ``d_data`` will be ``0, 1, 2, 3, 4, 5, ...``.
    //!
    //! @endrst
    //!
    //! @param block_itr[out]
    //!   The thread block's base output iterator for storing to
    //!
    //! @param items[in]
    //!   Data to store
    template <typename OutputIteratorT>
    _CCCL_DEVICE _CCCL_FORCEINLINE void Store(OutputIteratorT block_itr, T (&items)[ITEMS_PER_THREAD])
    {
        InternalStore(temp_storage, linear_tid).Store(block_itr, items);
    }

    //! @rst
    //! Store items into a linear segment of memory, guarded by range.
    //!
    //! - @blocked
    //! - @smemreuse
    //!
    //! 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 ``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.
    //!
    //! .. code-block:: c++
    //!
    //!    #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);
    //!
    //! Suppose the set of ``thread_data`` across the block of threads is
    //! ``{ [0,1,2,3], [4,5,6,7], ..., [508,509,510,511] }`` and ``valid_items`` is ``5``.
    //! The output ``d_data`` will be ``0, 1, 2, 3, 4, ?, ?, ?, ...``, with
    //! only the first two threads being unmasked to store portions of valid data.
    //!
    //! @endrst
    //!
    //! @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>
    _CCCL_DEVICE _CCCL_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

