cub/thread/thread_reduce.cuh
File members: cub/thread/thread_reduce.cuh
/******************************************************************************
* Copyright (c) 2011, Duane Merrill. All rights reserved.
* Copyright (c) 2011-2024, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of the NVIDIA CORPORATION nor the
* names of its contributors may be used to endorse or promote products
* derived from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY
* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*
******************************************************************************/
#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/detail/array_utils.cuh> // to_array()
#include <cub/detail/type_traits.cuh> // are_same()
#include <cub/thread/thread_load.cuh> // UnrolledCopy
#include <cub/thread/thread_operators.cuh> // cub_operator_to_dpx_t
#include <cub/util_namespace.cuh>
#include <cuda/functional> // cuda::std::maximum
#include <cuda/std/array> // array
#include <cuda/std/bit> // bit_cast
#include <cuda/std/cassert> // assert
#include <cuda/std/cstdint> // uint16_t
#include <cuda/std/functional> // cuda::std::plus
#if defined(_CCCL_HAS_NVFP16)
# include <cuda_fp16.h>
#endif // _CCCL_HAS_NVFP16
#if defined(_CCCL_HAS_NVBF16)
_CCCL_DIAG_PUSH
_CCCL_DIAG_SUPPRESS_CLANG("-Wunused-function")
# include <cuda_bf16.h>
_CCCL_DIAG_POP
#endif // _CCCL_HAS_NVFP16
CUB_NAMESPACE_BEGIN
template <typename Input,
typename ReductionOp,
#ifndef _CCCL_DOXYGEN_INVOKED // Do not document
typename ValueT = ::cuda::std::remove_cvref_t<decltype(::cuda::std::declval<Input>()[0])>,
#else
typename ValueT = random_access_value_t<Input>,
#endif // !_CCCL_DOXYGEN_INVOKED
typename AccumT = ::cuda::std::__accumulator_t<ReductionOp, ValueT>>
_CCCL_NODISCARD _CCCL_DEVICE _CCCL_FORCEINLINE AccumT ThreadReduce(const Input& input, ReductionOp reduction_op);
// forward declaration
/***********************************************************************************************************************
* Internal Reduction Implementations
**********************************************************************************************************************/
#ifndef _CCCL_DOXYGEN_INVOKED // Do not document
namespace detail
{
// NOTE: bit_cast cannot be always used because __half, __nv_bfloat16, etc. are not trivially copyable
template <typename Output, typename Input>
_CCCL_NODISCARD _CCCL_DEVICE _CCCL_FORCEINLINE Output unsafe_bitcast(const Input& input)
{
Output output;
static_assert(sizeof(input) == sizeof(output), "wrong size");
::memcpy(&output, &input, sizeof(input));
return output;
}
} // namespace detail
namespace internal
{
/***********************************************************************************************************************
* Enable SIMD/Tree reduction heuristics
**********************************************************************************************************************/
// TODO: add Blackwell support
template <typename T, typename ReductionOp>
struct enable_generic_simd_reduction_traits
{
static constexpr bool value =
cub::detail::is_one_of<T, ::cuda::std::int16_t, ::cuda::std::uint16_t>()
&& cub::detail::
is_one_of<ReductionOp, ::cuda::minimum<>, ::cuda::minimum<T>, ::cuda::maximum<>, ::cuda::maximum<T>>();
};
# if defined(_CCCL_HAS_NVFP16)
template <typename ReductionOp>
struct enable_generic_simd_reduction_traits<__half, ReductionOp>
{
static constexpr bool value = cub::detail::is_one_of<
ReductionOp,
::cuda::minimum<>,
::cuda::minimum<__half>,
::cuda::maximum<>,
::cuda::maximum<__half>,
::cuda::std::plus<>,
::cuda::std::plus<__half>,
::cuda::std::multiplies<>,
::cuda::std::multiplies<__half>>();
};
# endif // defined(_CCCL_HAS_NVFP16)
# if defined(_CCCL_HAS_NVBF16)
template <typename ReductionOp>
struct enable_generic_simd_reduction_traits<__nv_bfloat16, ReductionOp>
{
static constexpr bool value = cub::detail::is_one_of<
ReductionOp,
::cuda::minimum<>,
::cuda::minimum<__nv_bfloat16>,
::cuda::maximum<>,
::cuda::maximum<__nv_bfloat16>,
::cuda::std::plus<>,
::cuda::std::plus<__nv_bfloat16>,
::cuda::std::multiplies<>,
::cuda::std::multiplies<__nv_bfloat16>>();
};
# endif // defined(_CCCL_HAS_NVBF16)
template <typename Input, typename ReductionOp>
_CCCL_NODISCARD _CCCL_DEVICE constexpr bool enable_generic_simd_reduction()
{
using cub::detail::is_one_of;
using T = ::cuda::std::remove_cvref_t<decltype(::cuda::std::declval<Input>()[0])>;
using Length = ::cuda::std::integral_constant<int, cub::detail::static_size_v<Input>()>;
return enable_generic_simd_reduction_traits<T, ReductionOp>::value && Length{} >= 4;
}
template <typename T, typename ReductionOp, int Length>
_CCCL_NODISCARD _CCCL_DEVICE constexpr bool enable_sm90_simd_reduction()
{
using cub::detail::is_one_of;
// ::cuda::std::plus<> not handled: IADD3 always produces less instructions than VIADD2
return is_one_of<T, ::cuda::std::int16_t, ::cuda::std::uint16_t>() && //
is_one_of<ReductionOp, ::cuda::minimum<>, ::cuda::minimum<T>, ::cuda::maximum<>, ::cuda::maximum<T>>()
&& Length >= 10;
}
template <typename T, typename ReductionOp, int Length>
_CCCL_NODISCARD _CCCL_DEVICE constexpr bool enable_sm80_simd_reduction()
{
using cub::detail::is_one_of;
using ::cuda::std::is_same;
return is_one_of<ReductionOp,
::cuda::minimum<>,
::cuda::minimum<T>,
::cuda::maximum<>,
::cuda::maximum<T>,
::cuda::std::plus<>,
::cuda::std::plus<T>,
::cuda::std::multiplies<>,
::cuda::std::multiplies<T>>()
&& Length >= 4
# if defined(_CCCL_HAS_NVFP16) && defined(_CCCL_HAS_NVBF16)
&& (is_same<T, __half>::value || is_same<T, __nv_bfloat16>::value)
# elif defined(_CCCL_HAS_NVFP16)
&& is_same<T, __half>::value
# elif defined(_CCCL_HAS_NVBF16)
&& is_same<T, __nv_bfloat16>::value
# endif
;
}
template <typename T, typename ReductionOp, int Length>
_CCCL_NODISCARD _CCCL_DEVICE constexpr bool enable_sm70_simd_reduction()
{
using cub::detail::is_one_of;
using ::cuda::std::is_same;
# if defined(_CCCL_HAS_NVFP16)
return is_same<T, __half>::value
&& is_one_of<ReductionOp,
::cuda::std::plus<>,
::cuda::std::plus<T>,
::cuda::std::multiplies<>,
::cuda::std::multiplies<T>>()
&& Length >= 4;
# else
return false;
# endif
}
template <typename Input, typename ReductionOp, typename AccumT>
_CCCL_NODISCARD _CCCL_DEVICE _CCCL_FORCEINLINE _CCCL_CONSTEXPR_CXX14 bool enable_simd_reduction()
{
using cub::detail::is_one_of;
using ::cuda::std::is_same;
using T = ::cuda::std::remove_cvref_t<decltype(::cuda::std::declval<Input>()[0])>;
_CCCL_IF_CONSTEXPR (!is_same<T, AccumT>::value)
{
return false;
}
else
{
constexpr auto length = cub::detail::static_size_v<Input>();
// clang-format off
_NV_TARGET_DISPATCH(
NV_PROVIDES_SM_90,
(return enable_sm90_simd_reduction<T, ReductionOp, length>() ||
enable_sm80_simd_reduction<T, ReductionOp, length>() ||
enable_sm70_simd_reduction<T, ReductionOp, length>();),
NV_PROVIDES_SM_80,
(return enable_sm80_simd_reduction<T, ReductionOp, length>() ||
enable_sm70_simd_reduction<T, ReductionOp, length>();),
NV_PROVIDES_SM_70,
(return enable_sm70_simd_reduction<T, ReductionOp, length>();),
NV_IS_DEVICE,
(static_cast<void>(length); // maybe unused
return false;)
);
// clang-format on
return false;
}
return false; // nvcc 11.x warning workaround
}
/***********************************************************************************************************************
* enable_ternary_reduction
**********************************************************************************************************************/
template <typename T, typename ReductionOp>
struct enable_ternary_reduction_sm90
{
static constexpr bool value =
cub::detail::is_one_of<T, ::cuda::std::int32_t, ::cuda::std::uint32_t>()
&& cub::detail::is_one_of<
ReductionOp,
::cuda::minimum<>,
::cuda::minimum<T>,
::cuda::maximum<>,
::cuda::maximum<T>,
::cuda::std::plus<>,
::cuda::std::plus<T>,
::cuda::std::bit_and<>,
::cuda::std::bit_and<T>,
::cuda::std::bit_or<>,
::cuda::std::bit_or<T>,
::cuda::std::bit_xor<>,
::cuda::std::bit_xor<T>>();
};
# if defined(_CCCL_HAS_NVFP16)
template <typename ReductionOp>
struct enable_ternary_reduction_sm90<__half2, ReductionOp>
{
static constexpr bool value =
cub::detail::is_one_of<ReductionOp,
::cuda::minimum<>,
::cuda::minimum<__half2>,
::cuda::maximum<>,
::cuda::maximum<__half2>,
SimdMin<__half>,
SimdMax<__half>>();
};
# endif // defined(_CCCL_HAS_NVFP16)
# if defined(_CCCL_HAS_NVBF16)
template <typename ReductionOp>
struct enable_ternary_reduction_sm90<__nv_bfloat162, ReductionOp>
{
static constexpr bool value =
cub::detail::is_one_of<ReductionOp,
::cuda::minimum<>,
::cuda::minimum<__nv_bfloat162>,
::cuda::maximum<>,
::cuda::maximum<__nv_bfloat162>,
SimdMin<__nv_bfloat16>,
SimdMax<__nv_bfloat16>>();
};
# endif // defined(_CCCL_HAS_NVBF16)
template <typename Input, typename ReductionOp, typename AccumT>
_CCCL_NODISCARD _CCCL_DEVICE _CCCL_FORCEINLINE _CCCL_CONSTEXPR_CXX14 bool enable_ternary_reduction()
{
using cub::detail::is_one_of;
using ::cuda::std::is_same;
using T = ::cuda::std::remove_cvref_t<decltype(::cuda::std::declval<Input>()[0])>;
constexpr auto length = cub::detail::static_size_v<Input>();
_CCCL_IF_CONSTEXPR (length < 6)
{
return false;
}
else
{
// clang-format off
NV_DISPATCH_TARGET(
NV_PROVIDES_SM_90,
(return enable_ternary_reduction_sm90<T, ReductionOp>::value;),
NV_PROVIDES_SM_50,
(return is_one_of<AccumT, ::cuda::std::int32_t, ::cuda::std::uint32_t>()
&& is_one_of<ReductionOp, ::cuda::std::plus<>, ::cuda::std::plus<T>,
::cuda::std::bit_and<>, ::cuda::std::bit_and<T>,
::cuda::std::bit_or<>, ::cuda::std::bit_or<T>,
::cuda::std::bit_xor<>, ::cuda::std::bit_xor<T>>();),
NV_ANY_TARGET,
(return false;)
);
// clang-format on
}
return false; // nvcc 11.x warning workaround
}
template <typename Input, typename ReductionOp, typename AccumT>
_CCCL_NODISCARD _CCCL_DEVICE constexpr bool enable_promotion()
{
using cub::detail::is_one_of;
using ::cuda::std::is_same;
using T = ::cuda::std::remove_cvref_t<decltype(::cuda::std::declval<Input>()[0])>;
return ::cuda::std::is_integral<T>::value && sizeof(T) <= 2
&& is_one_of<ReductionOp,
::cuda::std::plus<>,
::cuda::std::plus<T>,
::cuda::std::multiplies<>,
::cuda::std::multiplies<T>,
::cuda::std::bit_and<>,
::cuda::std::bit_and<T>,
::cuda::std::bit_or<>,
::cuda::std::bit_or<T>,
::cuda::std::bit_xor<>,
::cuda::std::bit_xor<T>,
::cuda::maximum<>,
::cuda::maximum<T>,
::cuda::minimum<>,
::cuda::minimum<T>>();
}
/***********************************************************************************************************************
* Internal Reduction Algorithms: Sequential, Binary, Ternary
**********************************************************************************************************************/
template <typename AccumT, typename Input, typename ReductionOp>
_CCCL_NODISCARD _CCCL_DEVICE _CCCL_FORCEINLINE AccumT
ThreadReduceSequential(const Input& input, ReductionOp reduction_op)
{
AccumT retval = input[0];
# pragma unroll
for (int i = 1; i < cub::detail::static_size_v<Input>(); ++i)
{
retval = reduction_op(retval, input[i]);
}
return retval;
}
template <typename AccumT, typename Input, typename ReductionOp>
_CCCL_NODISCARD _CCCL_DEVICE _CCCL_FORCEINLINE AccumT
ThreadReduceBinaryTree(const Input& input, ReductionOp reduction_op)
{
constexpr auto length = cub::detail::static_size_v<Input>();
auto array = cub::detail::to_array<AccumT>(input);
# pragma unroll
for (int i = 1; i < length; i *= 2)
{
# pragma unroll
for (int j = 0; j + i < length; j += i * 2)
{
array[j] = reduction_op(array[j], array[j + i]);
}
}
return array[0];
}
template <typename AccumT, typename Input, typename ReductionOp>
_CCCL_NODISCARD _CCCL_DEVICE _CCCL_FORCEINLINE AccumT
ThreadReduceTernaryTree(const Input& input, ReductionOp reduction_op)
{
constexpr auto length = cub::detail::static_size_v<Input>();
auto array = cub::detail::to_array<AccumT>(input);
# pragma unroll
for (int i = 1; i < length; i *= 3)
{
# pragma unroll
for (int j = 0; j + i < length; j += i * 3)
{
auto value = reduction_op(array[j], array[j + i]);
array[j] = (j + i * 2 < length) ? reduction_op(value, array[j + i * 2]) : value;
}
}
return array[0];
}
/***********************************************************************************************************************
* SIMD Reduction
**********************************************************************************************************************/
// never reached. Protect instantion of ThreadReduceSimd with arbitrary types and operators
_CCCL_TEMPLATE(typename Input, typename ReductionOp)
_CCCL_REQUIRES((!cub::internal::enable_generic_simd_reduction<Input, ReductionOp>()))
_CCCL_NODISCARD _CCCL_DEVICE _CCCL_FORCEINLINE auto
ThreadReduceSimd(const Input& input, ReductionOp) -> ::cuda::std::remove_cvref_t<decltype(input[0])>
{
assert(false);
return input[0];
}
_CCCL_TEMPLATE(typename Input, typename ReductionOp)
_CCCL_REQUIRES((cub::internal::enable_generic_simd_reduction<Input, ReductionOp>()))
_CCCL_NODISCARD _CCCL_DEVICE _CCCL_FORCEINLINE auto
ThreadReduceSimd(const Input& input, ReductionOp reduction_op) -> ::cuda::std::remove_cvref_t<decltype(input[0])>
{
using cub::detail::unsafe_bitcast;
using T = ::cuda::std::remove_cvref_t<decltype(input[0])>;
using SimdReduceOp = cub::internal::cub_operator_to_simd_operator_t<ReductionOp, T>;
using SimdType = simd_type_t<ReductionOp, T>;
constexpr auto length = cub::detail::static_size_v<Input>();
constexpr auto simd_ratio = sizeof(SimdType) / sizeof(T);
constexpr auto length_rounded = (length / simd_ratio) * simd_ratio; // TODO: replace with round_up()
using UnpackedType = ::cuda::std::array<T, simd_ratio>;
using SimdArray = ::cuda::std::array<SimdType, length / simd_ratio>;
static_assert(simd_ratio == 1 || simd_ratio == 2, "Only SIMD size <= 2 is supported");
T local_array[length_rounded];
UnrolledCopy<length_rounded>(input, local_array);
auto simd_input = unsafe_bitcast<SimdArray>(local_array);
SimdType simd_reduction = cub::ThreadReduce(simd_input, SimdReduceOp{});
auto unpacked_values = unsafe_bitcast<UnpackedType>(simd_reduction);
_CCCL_IF_CONSTEXPR (simd_ratio == 1)
{
return unpacked_values[0];
}
else // simd_ratio == 2
{
// Create a reversed copy of the SIMD reduction result and apply the SIMD operator.
// This avoids redundant instructions for converting to and from 32-bit register size
T unpacked_values_rev[] = {unpacked_values[1], unpacked_values[0]};
auto simd_reduction_rev = unsafe_bitcast<SimdType>(unpacked_values_rev);
SimdType result = SimdReduceOp{}(simd_reduction, simd_reduction_rev);
// repeat the same optimization for the last element
_CCCL_IF_CONSTEXPR (length % simd_ratio == 1)
{
T tail[] = {input[length - 1], T{}};
auto tail_simd = unsafe_bitcast<SimdType>(tail);
result = SimdReduceOp{}(result, tail_simd);
}
return unsafe_bitcast<UnpackedType>(result)[0];
}
_CCCL_UNREACHABLE(); // nvcc 11.x warning workaround (never reached)
}
} // namespace internal
/***********************************************************************************************************************
* Reduction Interface/Dispatch (public)
**********************************************************************************************************************/
template <typename Input, typename ReductionOp, typename ValueT, typename AccumT>
_CCCL_NODISCARD _CCCL_DEVICE _CCCL_FORCEINLINE AccumT ThreadReduce(const Input& input, ReductionOp reduction_op)
{
static_assert(detail::is_fixed_size_random_access_range_t<Input>::value,
"Input must support the subscript operator[] and have a compile-time size");
static_assert(cub::detail::has_binary_call_operator<ReductionOp, ValueT>::value,
"ReductionOp must have the binary call operator: operator(ValueT, ValueT)");
using cub::internal::enable_promotion;
using cub::internal::enable_simd_reduction;
using cub::internal::enable_ternary_reduction;
using PromT = ::cuda::std::_If<enable_promotion<Input, ReductionOp, AccumT>(), int, AccumT>;
_CCCL_IF_CONSTEXPR (!cub::detail::is_one_of<
ReductionOp,
::cuda::std::plus<>,
::cuda::std::plus<ValueT>,
::cuda::std::multiplies<>,
::cuda::std::multiplies<ValueT>,
::cuda::std::bit_and<>,
::cuda::std::bit_and<ValueT>,
::cuda::std::bit_or<>,
::cuda::std::bit_or<ValueT>,
::cuda::std::bit_xor<>,
::cuda::std::bit_xor<ValueT>,
::cuda::maximum<>,
::cuda::maximum<ValueT>,
::cuda::minimum<>,
::cuda::minimum<ValueT>,
cub::internal::SimdMin<ValueT>,
cub::internal::SimdMax<ValueT>>())
{
return cub::internal::ThreadReduceSequential<AccumT>(input, reduction_op);
}
_CCCL_IF_CONSTEXPR (cub::detail::is_one_of<ReductionOp, ::cuda::std::plus<>, ::cuda::std::plus<ValueT>>()
&& cub::detail::is_one_of<ValueT, int, ::cuda::std::uint32_t>())
{
// clang-format off
NV_IF_TARGET(NV_PROVIDES_SM_90,
(return cub::internal::ThreadReduceSequential<AccumT>(input, reduction_op);),
(return cub::internal::ThreadReduceTernaryTree<PromT>(input, reduction_op);)
);
// clang-format on
}
if (enable_simd_reduction<Input, ReductionOp, AccumT>())
{
return cub::internal::ThreadReduceSimd(input, reduction_op);
}
if (enable_ternary_reduction<Input, ReductionOp, PromT>())
{
return cub::internal::ThreadReduceTernaryTree<PromT>(input, reduction_op);
}
return cub::internal::ThreadReduceBinaryTree<PromT>(input, reduction_op);
}
template <typename Input,
typename ReductionOp,
typename PrefixT,
typename ValueT = ::cuda::std::remove_cvref_t<decltype(::cuda::std::declval<Input>()[0])>,
typename AccumT = ::cuda::std::__accumulator_t<ReductionOp, ValueT, PrefixT>>
_CCCL_NODISCARD _CCCL_DEVICE _CCCL_FORCEINLINE AccumT
ThreadReduce(const Input& input, ReductionOp reduction_op, PrefixT prefix)
{
static_assert(detail::is_fixed_size_random_access_range_t<Input>::value,
"Input must support the subscript operator[] and have a compile-time size");
static_assert(detail::has_binary_call_operator<ReductionOp, ValueT>::value,
"ReductionOp must have the binary call operator: operator(ValueT, ValueT)");
constexpr int length = cub::detail::static_size_v<Input>();
// copy to a temporary array of type AccumT
AccumT array[length + 1];
array[0] = prefix;
# pragma unroll
for (int i = 0; i < length; ++i)
{
array[i + 1] = input[i];
}
return cub::ThreadReduce<decltype(array), ReductionOp, AccumT, AccumT>(array, reduction_op);
}
/***********************************************************************************************************************
* Pointer Interfaces with explicit Length (internal use only)
**********************************************************************************************************************/
namespace internal
{
template <int Length, typename T, typename ReductionOp, typename AccumT = ::cuda::std::__accumulator_t<ReductionOp, T>>
_CCCL_NODISCARD _CCCL_DEVICE _CCCL_FORCEINLINE AccumT ThreadReduce(const T* input, ReductionOp reduction_op)
{
static_assert(Length > 0, "Length must be greater than 0");
static_assert(cub::detail::has_binary_call_operator<ReductionOp, T>::value,
"ReductionOp must have the binary call operator: operator(V1, V2)");
using ArrayT = T[Length];
auto array = reinterpret_cast<const T(*)[Length]>(input);
return cub::ThreadReduce(*array, reduction_op);
}
_CCCL_TEMPLATE(int Length,
typename T,
typename ReductionOp,
typename PrefixT,
typename AccumT = ::cuda::std::__accumulator_t<ReductionOp, T, PrefixT>)
_CCCL_REQUIRES((Length > 0))
_CCCL_NODISCARD _CCCL_DEVICE _CCCL_FORCEINLINE AccumT
ThreadReduce(const T* input, ReductionOp reduction_op, PrefixT prefix)
{
static_assert(detail::has_binary_call_operator<ReductionOp, T>::value,
"ReductionOp must have the binary call operator: operator(V1, V2)");
auto array = reinterpret_cast<const T(*)[Length]>(input);
return cub::ThreadReduce(*array, reduction_op, prefix);
}
_CCCL_TEMPLATE(int Length, typename T, typename ReductionOp, typename PrefixT)
_CCCL_REQUIRES((Length == 0))
_CCCL_NODISCARD _CCCL_DEVICE _CCCL_FORCEINLINE T ThreadReduce(const T*, ReductionOp, PrefixT prefix)
{
return prefix;
}
} // namespace internal
#endif // !_CCCL_DOXYGEN_INVOKED
CUB_NAMESPACE_END