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tools/cub-1.8.0/cub/warp/specializations/warp_scan_smem.cuh
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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::WarpScanSmem provides smem-based variants of parallel prefix scan of items partitioned across a CUDA thread warp.
*/
#pragma once
#include "../../thread/thread_operators.cuh"
#include "../../thread/thread_load.cuh"
#include "../../thread/thread_store.cuh"
#include "../../util_type.cuh"
#include "../../util_namespace.cuh"
/// Optional outer namespace(s)
CUB_NS_PREFIX
/// CUB namespace
namespace cub {
/**
* \brief WarpScanSmem provides smem-based variants of parallel prefix scan of items partitioned across a CUDA thread warp.
*/
template <
typename T, ///< Data type being scanned
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 WarpScanSmem
{
/******************************************************************************
* 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)),
/// Whether the logical warp size is a power-of-two
IS_POW_OF_TWO = PowerOfTwo<LOGICAL_WARP_THREADS>::VALUE,
/// The number of warp scan steps
STEPS = Log2<LOGICAL_WARP_THREADS>::VALUE,
/// The number of threads in half a warp
HALF_WARP_THREADS = 1 << (STEPS - 1),
/// The number of shared memory elements per warp
WARP_SMEM_ELEMENTS = LOGICAL_WARP_THREADS + HALF_WARP_THREADS,
};
/// Storage cell type (workaround for SM1x compiler bugs with custom-ops like Max() on signed chars)
typedef typename If<((Equals<T, char>::VALUE || Equals<T, signed char>::VALUE) && (PTX_ARCH < 200)), int, T>::Type CellT;
/// Shared memory storage layout type (1.5 warps-worth of elements for each warp)
typedef CellT _TempStorage[WARP_SMEM_ELEMENTS];
// Alias wrapper allowing storage to be unioned
struct TempStorage : Uninitialized<_TempStorage> {};
/******************************************************************************
* Thread fields
******************************************************************************/
_TempStorage &temp_storage;
unsigned int lane_id;
unsigned int member_mask;
/******************************************************************************
* Construction
******************************************************************************/
/// Constructor
__device__ __forceinline__ WarpScanSmem(
TempStorage &temp_storage)
:
temp_storage(temp_storage.Alias()),
lane_id(IS_ARCH_WARP ?
LaneId() :
LaneId() % LOGICAL_WARP_THREADS),
member_mask((0xffffffff >> (32 - LOGICAL_WARP_THREADS)) << ((IS_ARCH_WARP || !IS_POW_OF_TWO ) ?
0 : // arch-width and non-power-of-two subwarps cannot be tiled with the arch-warp
((LaneId() / LOGICAL_WARP_THREADS) * LOGICAL_WARP_THREADS)))
{}
/******************************************************************************
* Utility methods
******************************************************************************/
/// Basic inclusive scan iteration (template unrolled, inductive-case specialization)
template <
bool HAS_IDENTITY,
int STEP,
typename ScanOp>
__device__ __forceinline__ void ScanStep(
T &partial,
ScanOp scan_op,
Int2Type<STEP> /*step*/)
{
const int OFFSET = 1 << STEP;
// Share partial into buffer
ThreadStore<STORE_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id], (CellT) partial);
WARP_SYNC(member_mask);
// Update partial if addend is in range
if (HAS_IDENTITY || (lane_id >= OFFSET))
{
T addend = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id - OFFSET]);
partial = scan_op(addend, partial);
}
WARP_SYNC(member_mask);
ScanStep<HAS_IDENTITY>(partial, scan_op, Int2Type<STEP + 1>());
}
/// Basic inclusive scan iteration(template unrolled, base-case specialization)
template <
bool HAS_IDENTITY,
typename ScanOp>
__device__ __forceinline__ void ScanStep(
T &/*partial*/,
ScanOp /*scan_op*/,
Int2Type<STEPS> /*step*/)
{}
/// Inclusive prefix scan (specialized for summation across primitive types)
__device__ __forceinline__ void InclusiveScan(
T input, ///< [in] Calling thread's input item.
T &output, ///< [out] Calling thread's output item. May be aliased with \p input.
Sum scan_op, ///< [in] Binary scan operator
Int2Type<true> /*is_primitive*/) ///< [in] Marker type indicating whether T is primitive type
{
T identity = 0;
ThreadStore<STORE_VOLATILE>(&temp_storage[lane_id], (CellT) identity);
WARP_SYNC(member_mask);
// Iterate scan steps
output = input;
ScanStep<true>(output, scan_op, Int2Type<0>());
}
/// Inclusive prefix scan
template <typename ScanOp, int IS_PRIMITIVE>
__device__ __forceinline__ void InclusiveScan(
T input, ///< [in] Calling thread's input item.
T &output, ///< [out] Calling thread's output item. May be aliased with \p input.
ScanOp scan_op, ///< [in] Binary scan operator
Int2Type<IS_PRIMITIVE> /*is_primitive*/) ///< [in] Marker type indicating whether T is primitive type
{
// Iterate scan steps
output = input;
ScanStep<false>(output, scan_op, Int2Type<0>());
}
/******************************************************************************
* Interface
******************************************************************************/
//---------------------------------------------------------------------
// Broadcast
//---------------------------------------------------------------------
/// Broadcast
__device__ __forceinline__ T Broadcast(
T input, ///< [in] The value to broadcast
unsigned int src_lane) ///< [in] Which warp lane is to do the broadcasting
{
if (lane_id == src_lane)
{
ThreadStore<STORE_VOLATILE>(temp_storage, (CellT) input);
}
WARP_SYNC(member_mask);
return (T)ThreadLoad<LOAD_VOLATILE>(temp_storage);
}
//---------------------------------------------------------------------
// Inclusive operations
//---------------------------------------------------------------------
/// Inclusive scan
template <typename ScanOp>
__device__ __forceinline__ void InclusiveScan(
T input, ///< [in] Calling thread's input item.
T &inclusive_output, ///< [out] Calling thread's output item. May be aliased with \p input.
ScanOp scan_op) ///< [in] Binary scan operator
{
InclusiveScan(input, inclusive_output, scan_op, Int2Type<Traits<T>::PRIMITIVE>());
}
/// Inclusive scan with aggregate
template <typename ScanOp>
__device__ __forceinline__ void InclusiveScan(
T input, ///< [in] Calling thread's input item.
T &inclusive_output, ///< [out] Calling thread's output item. May be aliased with \p input.
ScanOp scan_op, ///< [in] Binary scan operator
T &warp_aggregate) ///< [out] Warp-wide aggregate reduction of input items.
{
InclusiveScan(input, inclusive_output, scan_op);
// Retrieve aggregate
ThreadStore<STORE_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id], (CellT) inclusive_output);
WARP_SYNC(member_mask);
warp_aggregate = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[WARP_SMEM_ELEMENTS - 1]);
WARP_SYNC(member_mask);
}
//---------------------------------------------------------------------
// Get exclusive from inclusive
//---------------------------------------------------------------------
/// Update inclusive and exclusive using input and inclusive
template <typename ScanOpT, typename IsIntegerT>
__device__ __forceinline__ void Update(
T /*input*/, ///< [in]
T &inclusive, ///< [in, out]
T &exclusive, ///< [out]
ScanOpT /*scan_op*/, ///< [in]
IsIntegerT /*is_integer*/) ///< [in]
{
// initial value unknown
ThreadStore<STORE_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id], (CellT) inclusive);
WARP_SYNC(member_mask);
exclusive = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id - 1]);
}
/// Update inclusive and exclusive using input and inclusive (specialized for summation of integer types)
__device__ __forceinline__ void Update(
T input,
T &inclusive,
T &exclusive,
cub::Sum /*scan_op*/,
Int2Type<true> /*is_integer*/)
{
// initial value presumed 0
exclusive = inclusive - input;
}
/// Update inclusive and exclusive using initial value using input, inclusive, and initial value
template <typename ScanOpT, typename IsIntegerT>
__device__ __forceinline__ void Update (
T /*input*/,
T &inclusive,
T &exclusive,
ScanOpT scan_op,
T initial_value,
IsIntegerT /*is_integer*/)
{
inclusive = scan_op(initial_value, inclusive);
ThreadStore<STORE_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id], (CellT) inclusive);
WARP_SYNC(member_mask);
exclusive = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id - 1]);
if (lane_id == 0)
exclusive = initial_value;
}
/// Update inclusive and exclusive using initial value using input and inclusive (specialized for summation of integer types)
__device__ __forceinline__ void Update (
T input,
T &inclusive,
T &exclusive,
cub::Sum scan_op,
T initial_value,
Int2Type<true> /*is_integer*/)
{
inclusive = scan_op(initial_value, inclusive);
exclusive = inclusive - input;
}
/// Update inclusive, exclusive, and warp aggregate using input and inclusive
template <typename ScanOpT, typename IsIntegerT>
__device__ __forceinline__ void Update (
T /*input*/,
T &inclusive,
T &exclusive,
T &warp_aggregate,
ScanOpT /*scan_op*/,
IsIntegerT /*is_integer*/)
{
// Initial value presumed to be unknown or identity (either way our padding is correct)
ThreadStore<STORE_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id], (CellT) inclusive);
WARP_SYNC(member_mask);
exclusive = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id - 1]);
warp_aggregate = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[WARP_SMEM_ELEMENTS - 1]);
}
/// Update inclusive, exclusive, and warp aggregate using input and inclusive (specialized for summation of integer types)
__device__ __forceinline__ void Update (
T input,
T &inclusive,
T &exclusive,
T &warp_aggregate,
cub::Sum /*scan_o*/,
Int2Type<true> /*is_integer*/)
{
// Initial value presumed to be unknown or identity (either way our padding is correct)
ThreadStore<STORE_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id], (CellT) inclusive);
WARP_SYNC(member_mask);
warp_aggregate = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[WARP_SMEM_ELEMENTS - 1]);
exclusive = inclusive - input;
}
/// Update inclusive, exclusive, and warp aggregate using input, inclusive, and initial value
template <typename ScanOpT, typename IsIntegerT>
__device__ __forceinline__ void Update (
T /*input*/,
T &inclusive,
T &exclusive,
T &warp_aggregate,
ScanOpT scan_op,
T initial_value,
IsIntegerT /*is_integer*/)
{
// Broadcast warp aggregate
ThreadStore<STORE_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id], (CellT) inclusive);
WARP_SYNC(member_mask);
warp_aggregate = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[WARP_SMEM_ELEMENTS - 1]);
WARP_SYNC(member_mask);
// Update inclusive with initial value
inclusive = scan_op(initial_value, inclusive);
// Get exclusive from exclusive
ThreadStore<STORE_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id - 1], (CellT) inclusive);
WARP_SYNC(member_mask);
exclusive = (T) ThreadLoad<LOAD_VOLATILE>(&temp_storage[HALF_WARP_THREADS + lane_id - 2]);
if (lane_id == 0)
exclusive = initial_value;
}
};
} // CUB namespace
CUB_NS_POSTFIX // Optional outer namespace(s)
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