cub/block/block_reduce.cuh
File members: cub/block/block_reduce.cuh
/******************************************************************************
* Copyright (c) 2011, Duane Merrill. All rights reserved.
* Copyright (c) 2011-2018, 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/block/specializations/block_reduce_raking.cuh>
#include <cub/block/specializations/block_reduce_raking_commutative_only.cuh>
#include <cub/block/specializations/block_reduce_warp_reductions.cuh>
#include <cub/thread/thread_operators.cuh>
#include <cub/util_ptx.cuh>
#include <cub/util_type.cuh>
#include <cuda/std/type_traits>
CUB_NAMESPACE_BEGIN
/******************************************************************************
* Algorithmic variants
******************************************************************************/
enum BlockReduceAlgorithm
{
BLOCK_REDUCE_RAKING_COMMUTATIVE_ONLY,
BLOCK_REDUCE_RAKING,
BLOCK_REDUCE_WARP_REDUCTIONS,
};
template <typename T,
int BLOCK_DIM_X,
BlockReduceAlgorithm ALGORITHM = BLOCK_REDUCE_WARP_REDUCTIONS,
int BLOCK_DIM_Y = 1,
int BLOCK_DIM_Z = 1,
int LEGACY_PTX_ARCH = 0>
class BlockReduce
{
private:
enum
{
BLOCK_THREADS = BLOCK_DIM_X * BLOCK_DIM_Y * BLOCK_DIM_Z,
};
using WarpReductions = BlockReduceWarpReductions<T, BLOCK_DIM_X, BLOCK_DIM_Y, BLOCK_DIM_Z>;
using RakingCommutativeOnly = BlockReduceRakingCommutativeOnly<T, BLOCK_DIM_X, BLOCK_DIM_Y, BLOCK_DIM_Z>;
using Raking = BlockReduceRaking<T, BLOCK_DIM_X, BLOCK_DIM_Y, BLOCK_DIM_Z>;
using InternalBlockReduce =
::cuda::std::_If<ALGORITHM == BLOCK_REDUCE_WARP_REDUCTIONS,
WarpReductions,
::cuda::std::_If<ALGORITHM == BLOCK_REDUCE_RAKING_COMMUTATIVE_ONLY,
RakingCommutativeOnly,
Raking>>; // BlockReduceRaking
using _TempStorage = typename InternalBlockReduce::TempStorage;
_CCCL_DEVICE _CCCL_FORCEINLINE _TempStorage& PrivateStorage()
{
__shared__ _TempStorage private_storage;
return private_storage;
}
_TempStorage& temp_storage;
unsigned int linear_tid;
public:
struct TempStorage : Uninitialized<_TempStorage>
{};
_CCCL_DEVICE _CCCL_FORCEINLINE BlockReduce()
: temp_storage(PrivateStorage())
, linear_tid(RowMajorTid(BLOCK_DIM_X, BLOCK_DIM_Y, BLOCK_DIM_Z))
{}
_CCCL_DEVICE _CCCL_FORCEINLINE BlockReduce(TempStorage& temp_storage)
: temp_storage(temp_storage.Alias())
, linear_tid(RowMajorTid(BLOCK_DIM_X, BLOCK_DIM_Y, BLOCK_DIM_Z))
{}
template <typename ReductionOp>
_CCCL_DEVICE _CCCL_FORCEINLINE T Reduce(T input, ReductionOp reduction_op)
{
return InternalBlockReduce(temp_storage).template Reduce<true>(input, BLOCK_THREADS, reduction_op);
}
template <int ITEMS_PER_THREAD, typename ReductionOp>
_CCCL_DEVICE _CCCL_FORCEINLINE T Reduce(T (&inputs)[ITEMS_PER_THREAD], ReductionOp reduction_op)
{
// Reduce partials
T partial = cub::ThreadReduce(inputs, reduction_op);
return Reduce(partial, reduction_op);
}
template <typename ReductionOp>
_CCCL_DEVICE _CCCL_FORCEINLINE T Reduce(T input, ReductionOp reduction_op, int num_valid)
{
// Determine if we skip bounds checking
if (num_valid >= BLOCK_THREADS)
{
return InternalBlockReduce(temp_storage).template Reduce<true>(input, num_valid, reduction_op);
}
else
{
return InternalBlockReduce(temp_storage).template Reduce<false>(input, num_valid, reduction_op);
}
}
_CCCL_DEVICE _CCCL_FORCEINLINE T Sum(T input)
{
return InternalBlockReduce(temp_storage).template Sum<true>(input, BLOCK_THREADS);
}
template <int ITEMS_PER_THREAD>
_CCCL_DEVICE _CCCL_FORCEINLINE T Sum(T (&inputs)[ITEMS_PER_THREAD])
{
// Reduce partials
T partial = cub::ThreadReduce(inputs, ::cuda::std::plus<>{});
return Sum(partial);
}
_CCCL_DEVICE _CCCL_FORCEINLINE T Sum(T input, int num_valid)
{
// Determine if we skip bounds checking
if (num_valid >= BLOCK_THREADS)
{
return InternalBlockReduce(temp_storage).template Sum<true>(input, num_valid);
}
else
{
return InternalBlockReduce(temp_storage).template Sum<false>(input, num_valid);
}
}
};
CUB_NAMESPACE_END