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/******************************************************************************
* 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.
*
******************************************************************************/
/**
* \file
* cub::WarpReduceShfl provides SHFL-based variants of parallel reduction of items partitioned across a CUDA thread warp.
*/
#pragma once
#include "../../thread/thread_operators.cuh"
#include "../../util_ptx.cuh"
#include "../../util_type.cuh"
#include "../../util_macro.cuh"
#include "../../util_namespace.cuh"
/// Optional outer namespace(s)
CUB_NS_PREFIX
/// CUB namespace
namespace cub {
/**
* \brief WarpReduceShfl provides SHFL-based variants of parallel reduction of items partitioned across a CUDA thread warp.
*
* LOGICAL_WARP_THREADS must be a power-of-two
*/
template <
typename T, ///< Data type being reduced
int LOGICAL_WARP_THREADS, ///< Number of threads per logical warp
int PTX_ARCH> ///< The PTX compute capability for which to to specialize this collective
struct WarpReduceShfl
{
//---------------------------------------------------------------------
// Constants and type definitions
//---------------------------------------------------------------------
enum
{
/// Whether the logical warp size and the PTX warp size coincide
IS_ARCH_WARP = (LOGICAL_WARP_THREADS == CUB_WARP_THREADS(PTX_ARCH)),
/// The number of warp reduction steps
STEPS = Log2<LOGICAL_WARP_THREADS>::VALUE,
/// Number of logical warps in a PTX warp
LOGICAL_WARPS = CUB_WARP_THREADS(PTX_ARCH) / LOGICAL_WARP_THREADS,
/// The 5-bit SHFL mask for logically splitting warps into sub-segments starts 8-bits up
SHFL_C = (CUB_WARP_THREADS(PTX_ARCH) - LOGICAL_WARP_THREADS) << 8
};
template <typename S>
struct IsInteger
{
enum {
///Whether the data type is a small (32b or less) integer for which we can use a single SFHL instruction per exchange
IS_SMALL_UNSIGNED = (Traits<S>::CATEGORY == UNSIGNED_INTEGER) && (sizeof(S) <= sizeof(unsigned int))
};
};
/// Shared memory storage layout type
typedef NullType TempStorage;
//---------------------------------------------------------------------
// Thread fields
//---------------------------------------------------------------------
/// Lane index in logical warp
unsigned int lane_id;
/// Logical warp index in 32-thread physical warp
unsigned int warp_id;
/// 32-thread physical warp member mask of logical warp
unsigned int member_mask;
//---------------------------------------------------------------------
// Construction
//---------------------------------------------------------------------
/// Constructor
__device__ __forceinline__ WarpReduceShfl(
TempStorage &/*temp_storage*/)
{
lane_id = LaneId();
warp_id = 0;
member_mask = 0xffffffffu >> (CUB_WARP_THREADS(PTX_ARCH) - LOGICAL_WARP_THREADS);
if (!IS_ARCH_WARP)
{
warp_id = lane_id / LOGICAL_WARP_THREADS;
lane_id = lane_id % LOGICAL_WARP_THREADS;
member_mask = member_mask << (warp_id * LOGICAL_WARP_THREADS);
}
}
//---------------------------------------------------------------------
// Reduction steps
//---------------------------------------------------------------------
/// Reduction (specialized for summation across uint32 types)
__device__ __forceinline__ unsigned int ReduceStep(
unsigned int input, ///< [in] Calling thread's input item.
cub::Sum /*reduction_op*/, ///< [in] Binary reduction operator
int last_lane, ///< [in] Index of last lane in segment
int offset) ///< [in] Up-offset to pull from
{
unsigned int output;
int shfl_c = last_lane | SHFL_C; // Shuffle control (mask and last_lane)
// Use predicate set from SHFL to guard against invalid peers
#ifdef CUB_USE_COOPERATIVE_GROUPS
asm volatile(
"{"
" .reg .u32 r0;"
" .reg .pred p;"
" shfl.sync.down.b32 r0|p, %1, %2, %3, %5;"
" @p add.u32 r0, r0, %4;"
" mov.u32 %0, r0;"
"}"
: "=r"(output) : "r"(input), "r"(offset), "r"(shfl_c), "r"(input), "r"(member_mask));
#else
asm volatile(
"{"
" .reg .u32 r0;"
" .reg .pred p;"
" shfl.down.b32 r0|p, %1, %2, %3;"
" @p add.u32 r0, r0, %4;"
" mov.u32 %0, r0;"
"}"
: "=r"(output) : "r"(input), "r"(offset), "r"(shfl_c), "r"(input));
#endif
return output;
}
/// Reduction (specialized for summation across fp32 types)
__device__ __forceinline__ float ReduceStep(
float input, ///< [in] Calling thread's input item.
cub::Sum /*reduction_op*/, ///< [in] Binary reduction operator
int last_lane, ///< [in] Index of last lane in segment
int offset) ///< [in] Up-offset to pull from
{
float output;
int shfl_c = last_lane | SHFL_C; // Shuffle control (mask and last_lane)
// Use predicate set from SHFL to guard against invalid peers
#ifdef CUB_USE_COOPERATIVE_GROUPS
asm volatile(
"{"
" .reg .f32 r0;"
" .reg .pred p;"
" shfl.sync.down.b32 r0|p, %1, %2, %3, %5;"
" @p add.f32 r0, r0, %4;"
" mov.f32 %0, r0;"
"}"
: "=f"(output) : "f"(input), "r"(offset), "r"(shfl_c), "f"(input), "r"(member_mask));
#else
asm volatile(
"{"
" .reg .f32 r0;"
" .reg .pred p;"
" shfl.down.b32 r0|p, %1, %2, %3;"
" @p add.f32 r0, r0, %4;"
" mov.f32 %0, r0;"
"}"
: "=f"(output) : "f"(input), "r"(offset), "r"(shfl_c), "f"(input));
#endif
return output;
}
/// Reduction (specialized for summation across unsigned long long types)
__device__ __forceinline__ unsigned long long ReduceStep(
unsigned long long input, ///< [in] Calling thread's input item.
cub::Sum /*reduction_op*/, ///< [in] Binary reduction operator
int last_lane, ///< [in] Index of last lane in segment
int offset) ///< [in] Up-offset to pull from
{
unsigned long long output;
int shfl_c = last_lane | SHFL_C; // Shuffle control (mask and last_lane)
#ifdef CUB_USE_COOPERATIVE_GROUPS
asm volatile(
"{"
" .reg .u32 lo;"
" .reg .u32 hi;"
" .reg .pred p;"
" mov.b64 {lo, hi}, %1;"
" shfl.sync.down.b32 lo|p, lo, %2, %3, %4;"
" shfl.sync.down.b32 hi|p, hi, %2, %3, %4;"
" mov.b64 %0, {lo, hi};"
" @p add.u64 %0, %0, %1;"
"}"
: "=l"(output) : "l"(input), "r"(offset), "r"(shfl_c), "r"(member_mask));
#else
asm volatile(
"{"
" .reg .u32 lo;"
" .reg .u32 hi;"
" .reg .pred p;"
" mov.b64 {lo, hi}, %1;"
" shfl.down.b32 lo|p, lo, %2, %3;"
" shfl.down.b32 hi|p, hi, %2, %3;"
" mov.b64 %0, {lo, hi};"
" @p add.u64 %0, %0, %1;"
"}"
: "=l"(output) : "l"(input), "r"(offset), "r"(shfl_c));
#endif
return output;
}
/// Reduction (specialized for summation across long long types)
__device__ __forceinline__ long long ReduceStep(
long long input, ///< [in] Calling thread's input item.
cub::Sum /*reduction_op*/, ///< [in] Binary reduction operator
int last_lane, ///< [in] Index of last lane in segment
int offset) ///< [in] Up-offset to pull from
{
long long output;
int shfl_c = last_lane | SHFL_C; // Shuffle control (mask and last_lane)
// Use predicate set from SHFL to guard against invalid peers
#ifdef CUB_USE_COOPERATIVE_GROUPS
asm volatile(
"{"
" .reg .u32 lo;"
" .reg .u32 hi;"
" .reg .pred p;"
" mov.b64 {lo, hi}, %1;"
" shfl.sync.down.b32 lo|p, lo, %2, %3, %4;"
" shfl.sync.down.b32 hi|p, hi, %2, %3, %4;"
" mov.b64 %0, {lo, hi};"
" @p add.s64 %0, %0, %1;"
"}"
: "=l"(output) : "l"(input), "r"(offset), "r"(shfl_c), "r"(member_mask));
#else
asm volatile(
"{"
" .reg .u32 lo;"
" .reg .u32 hi;"
" .reg .pred p;"
" mov.b64 {lo, hi}, %1;"
" shfl.down.b32 lo|p, lo, %2, %3;"
" shfl.down.b32 hi|p, hi, %2, %3;"
" mov.b64 %0, {lo, hi};"
" @p add.s64 %0, %0, %1;"
"}"
: "=l"(output) : "l"(input), "r"(offset), "r"(shfl_c));
#endif
return output;
}
/// Reduction (specialized for summation across double types)
__device__ __forceinline__ double ReduceStep(
double input, ///< [in] Calling thread's input item.
cub::Sum /*reduction_op*/, ///< [in] Binary reduction operator
int last_lane, ///< [in] Index of last lane in segment
int offset) ///< [in] Up-offset to pull from
{
double output;
int shfl_c = last_lane | SHFL_C; // Shuffle control (mask and last_lane)
// Use predicate set from SHFL to guard against invalid peers
#ifdef CUB_USE_COOPERATIVE_GROUPS
asm volatile(
"{"
" .reg .u32 lo;"
" .reg .u32 hi;"
" .reg .pred p;"
" .reg .f64 r0;"
" mov.b64 %0, %1;"
" mov.b64 {lo, hi}, %1;"
" shfl.sync.down.b32 lo|p, lo, %2, %3, %4;"
" shfl.sync.down.b32 hi|p, hi, %2, %3, %4;"
" mov.b64 r0, {lo, hi};"
" @p add.f64 %0, %0, r0;"
"}"
: "=d"(output) : "d"(input), "r"(offset), "r"(shfl_c), "r"(member_mask));
#else
asm volatile(
"{"
" .reg .u32 lo;"
" .reg .u32 hi;"
" .reg .pred p;"
" .reg .f64 r0;"
" mov.b64 %0, %1;"
" mov.b64 {lo, hi}, %1;"
" shfl.down.b32 lo|p, lo, %2, %3;"
" shfl.down.b32 hi|p, hi, %2, %3;"
" mov.b64 r0, {lo, hi};"
" @p add.f64 %0, %0, r0;"
"}"
: "=d"(output) : "d"(input), "r"(offset), "r"(shfl_c));
#endif
return output;
}
/// Reduction (specialized for swizzled ReduceByKeyOp<cub::Sum> across KeyValuePair<KeyT, ValueT> types)
template <typename ValueT, typename KeyT>
__device__ __forceinline__ KeyValuePair<KeyT, ValueT> ReduceStep(
KeyValuePair<KeyT, ValueT> input, ///< [in] Calling thread's input item.
SwizzleScanOp<ReduceByKeyOp<cub::Sum> > /*reduction_op*/, ///< [in] Binary reduction operator
int last_lane, ///< [in] Index of last lane in segment
int offset) ///< [in] Up-offset to pull from
{
KeyValuePair<KeyT, ValueT> output;
KeyT other_key = ShuffleDown<LOGICAL_WARP_THREADS>(input.key, offset, last_lane, member_mask);
output.key = input.key;
output.value = ReduceStep(
input.value,
cub::Sum(),
last_lane,
offset,
Int2Type<IsInteger<ValueT>::IS_SMALL_UNSIGNED>());
if (input.key != other_key)
output.value = input.value;
return output;
}
/// Reduction (specialized for swizzled ReduceBySegmentOp<cub::Sum> across KeyValuePair<OffsetT, ValueT> types)
template <typename ValueT, typename OffsetT>
__device__ __forceinline__ KeyValuePair<OffsetT, ValueT> ReduceStep(
KeyValuePair<OffsetT, ValueT> input, ///< [in] Calling thread's input item.
SwizzleScanOp<ReduceBySegmentOp<cub::Sum> > /*reduction_op*/, ///< [in] Binary reduction operator
int last_lane, ///< [in] Index of last lane in segment
int offset) ///< [in] Up-offset to pull from
{
KeyValuePair<OffsetT, ValueT> output;
output.value = ReduceStep(input.value, cub::Sum(), last_lane, offset, Int2Type<IsInteger<ValueT>::IS_SMALL_UNSIGNED>());
output.key = ReduceStep(input.key, cub::Sum(), last_lane, offset, Int2Type<IsInteger<OffsetT>::IS_SMALL_UNSIGNED>());
if (input.key > 0)
output.value = input.value;
return output;
}
/// Reduction step (generic)
template <typename _T, typename ReductionOp>
__device__ __forceinline__ _T ReduceStep(
_T input, ///< [in] Calling thread's input item.
ReductionOp reduction_op, ///< [in] Binary reduction operator
int last_lane, ///< [in] Index of last lane in segment
int offset) ///< [in] Up-offset to pull from
{
_T output = input;
_T temp = ShuffleDown<LOGICAL_WARP_THREADS>(output, offset, last_lane, member_mask);
// Perform reduction op if valid
if (offset + lane_id <= last_lane)
output = reduction_op(input, temp);
return output;
}
/// Reduction step (specialized for small unsigned integers size 32b or less)
template <typename _T, typename ReductionOp>
__device__ __forceinline__ _T ReduceStep(
_T input, ///< [in] Calling thread's input item.
ReductionOp reduction_op, ///< [in] Binary reduction operator
int last_lane, ///< [in] Index of last lane in segment
int offset, ///< [in] Up-offset to pull from
Int2Type<true> /*is_small_unsigned*/) ///< [in] Marker type indicating whether T is a small unsigned integer
{
return ReduceStep(input, reduction_op, last_lane, offset);
}
/// Reduction step (specialized for types other than small unsigned integers size 32b or less)
template <typename _T, typename ReductionOp>
__device__ __forceinline__ _T ReduceStep(
_T input, ///< [in] Calling thread's input item.
ReductionOp reduction_op, ///< [in] Binary reduction operator
int last_lane, ///< [in] Index of last lane in segment
int offset, ///< [in] Up-offset to pull from
Int2Type<false> /*is_small_unsigned*/) ///< [in] Marker type indicating whether T is a small unsigned integer
{
return ReduceStep(input, reduction_op, last_lane, offset);
}
//---------------------------------------------------------------------
// Templated inclusive scan iteration
//---------------------------------------------------------------------
template <typename ReductionOp, int STEP>
__device__ __forceinline__ void ReduceStep(
T& input, ///< [in] Calling thread's input item.
ReductionOp reduction_op, ///< [in] Binary reduction operator
int last_lane, ///< [in] Index of last lane in segment
Int2Type<STEP> /*step*/)
{
input = ReduceStep(input, reduction_op, last_lane, 1 << STEP, Int2Type<IsInteger<T>::IS_SMALL_UNSIGNED>());
ReduceStep(input, reduction_op, last_lane, Int2Type<STEP + 1>());
}
template <typename ReductionOp>
__device__ __forceinline__ void ReduceStep(
T& /*input*/, ///< [in] Calling thread's input item.
ReductionOp /*reduction_op*/, ///< [in] Binary reduction operator
int /*last_lane*/, ///< [in] Index of last lane in segment
Int2Type<STEPS> /*step*/)
{}
//---------------------------------------------------------------------
// Reduction operations
//---------------------------------------------------------------------
/// Reduction
template <
bool ALL_LANES_VALID, ///< Whether all lanes in each warp are contributing a valid fold of items
typename ReductionOp>
__device__ __forceinline__ T Reduce(
T input, ///< [in] Calling thread's input
int valid_items, ///< [in] Total number of valid items across the logical warp
ReductionOp reduction_op) ///< [in] Binary reduction operator
{
int last_lane = (ALL_LANES_VALID) ?
LOGICAL_WARP_THREADS - 1 :
valid_items - 1;
T output = input;
// // Iterate reduction steps
// #pragma unroll
// for (int STEP = 0; STEP < STEPS; STEP++)
// {
// output = ReduceStep(output, reduction_op, last_lane, 1 << STEP, Int2Type<IsInteger<T>::IS_SMALL_UNSIGNED>());
// }
// Template-iterate reduction steps
ReduceStep(output, reduction_op, last_lane, Int2Type<0>());
return output;
}
/// Segmented reduction
template <
bool HEAD_SEGMENTED, ///< Whether flags indicate a segment-head or a segment-tail
typename FlagT,
typename ReductionOp>
__device__ __forceinline__ T SegmentedReduce(
T input, ///< [in] Calling thread's input
FlagT flag, ///< [in] Whether or not the current lane is a segment head/tail
ReductionOp reduction_op) ///< [in] Binary reduction operator
{
// Get the start flags for each thread in the warp.
int warp_flags = WARP_BALLOT(flag, member_mask);
// Convert to tail-segmented
if (HEAD_SEGMENTED)
warp_flags >>= 1;
// Mask out the bits below the current thread
warp_flags &= LaneMaskGe();
// Mask of physical lanes outside the logical warp and convert to logical lanemask
if (!IS_ARCH_WARP)
{
warp_flags = (warp_flags & member_mask) >> (warp_id * LOGICAL_WARP_THREADS);
}
// Mask in the last lane of logical warp
warp_flags |= 1u << (LOGICAL_WARP_THREADS - 1);
// Find the next set flag
int last_lane = __clz(__brev(warp_flags));
T output = input;
// // Iterate reduction steps
// #pragma unroll
// for (int STEP = 0; STEP < STEPS; STEP++)
// {
// output = ReduceStep(output, reduction_op, last_lane, 1 << STEP, Int2Type<IsInteger<T>::IS_SMALL_UNSIGNED>());
// }
// Template-iterate reduction steps
ReduceStep(output, reduction_op, last_lane, Int2Type<0>());
return output;
}
};
} // CUB namespace
CUB_NS_POSTFIX // Optional outer namespace(s)
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