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/**
 * \file
 * Thread utilities for sequential reduction over statically-sized array types
 */

#pragma once

#include "../thread/thread_operators.cuh"
#include "../util_namespace.cuh"

/// Optional outer namespace(s)
CUB_NS_PREFIX

/// CUB namespace
namespace cub {

/// Internal namespace (to prevent ADL mishaps between static functions when mixing different CUB installations)
namespace internal {

/**
 * Sequential reduction over statically-sized array types
 */
template <
    int         LENGTH,
    typename    T,
    typename    ReductionOp>
__device__ __forceinline__ T ThreadReduce(
    T*                  input,                  ///< [in] Input array
    ReductionOp         reduction_op,           ///< [in] Binary reduction operator
    T                   prefix,                 ///< [in] Prefix to seed reduction with
    Int2Type<LENGTH>    /*length*/)
{
    T retval = prefix;

    #pragma unroll
    for (int i = 0; i < LENGTH; ++i)
        retval = reduction_op(retval, input[i]);

    return retval;
}


/**
 * \brief Perform a sequential reduction over \p LENGTH elements of the \p input array, seeded with the specified \p prefix.  The aggregate is returned.
 *
 * \tparam LENGTH     LengthT of input array
 * \tparam T          <b>[inferred]</b> The data type to be reduced.
 * \tparam ScanOp     <b>[inferred]</b> Binary reduction operator type having member <tt>T operator()(const T &a, const T &b)</tt>
 */
template <
    int         LENGTH,
    typename    T,
    typename    ReductionOp>
__device__ __forceinline__ T ThreadReduce(
    T*          input,                  ///< [in] Input array
    ReductionOp reduction_op,           ///< [in] Binary reduction operator
    T           prefix)                 ///< [in] Prefix to seed reduction with
{
    return ThreadReduce(input, reduction_op, prefix, Int2Type<LENGTH>());
}


/**
 * \brief Perform a sequential reduction over \p LENGTH elements of the \p input array.  The aggregate is returned.
 *
 * \tparam LENGTH     LengthT of input array
 * \tparam T          <b>[inferred]</b> The data type to be reduced.
 * \tparam ScanOp     <b>[inferred]</b> Binary reduction operator type having member <tt>T operator()(const T &a, const T &b)</tt>
 */
template <
    int         LENGTH,
    typename    T,
    typename    ReductionOp>
__device__ __forceinline__ T ThreadReduce(
    T*          input,                  ///< [in] Input array
    ReductionOp reduction_op)           ///< [in] Binary reduction operator
{
    T prefix = input[0];
    return ThreadReduce<LENGTH - 1>(input + 1, reduction_op, prefix);
}


/**
 * \brief Perform a sequential reduction over the statically-sized \p input array, seeded with the specified \p prefix.  The aggregate is returned.
 *
 * \tparam LENGTH     <b>[inferred]</b> LengthT of \p input array
 * \tparam T          <b>[inferred]</b> The data type to be reduced.
 * \tparam ScanOp     <b>[inferred]</b> Binary reduction operator type having member <tt>T operator()(const T &a, const T &b)</tt>
 */
template <
    int         LENGTH,
    typename    T,
    typename    ReductionOp>
__device__ __forceinline__ T ThreadReduce(
    T           (&input)[LENGTH],       ///< [in] Input array
    ReductionOp reduction_op,           ///< [in] Binary reduction operator
    T           prefix)                 ///< [in] Prefix to seed reduction with
{
    return ThreadReduce(input, reduction_op, prefix, Int2Type<LENGTH>());
}


/**
 * \brief Serial reduction with the specified operator
 *
 * \tparam LENGTH     <b>[inferred]</b> LengthT of \p input array
 * \tparam T          <b>[inferred]</b> The data type to be reduced.
 * \tparam ScanOp     <b>[inferred]</b> Binary reduction operator type having member <tt>T operator()(const T &a, const T &b)</tt>
 */
template <
    int         LENGTH,
    typename    T,
    typename    ReductionOp>
__device__ __forceinline__ T ThreadReduce(
    T           (&input)[LENGTH],       ///< [in] Input array
    ReductionOp reduction_op)           ///< [in] Binary reduction operator
{
    return ThreadReduce<LENGTH>((T*) input, reduction_op);
}


}               // internal namespace
}               // CUB namespace
CUB_NS_POSTFIX  // Optional outer namespace(s)