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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::AgentSpmv implements a stateful abstraction of CUDA thread blocks for participating in device-wide SpMV.
*/
#pragma once
#include <iterator>
#include "../util_type.cuh"
#include "../block/block_reduce.cuh"
#include "../block/block_scan.cuh"
#include "../block/block_exchange.cuh"
#include "../config.cuh"
#include "../thread/thread_search.cuh"
#include "../thread/thread_operators.cuh"
#include "../iterator/cache_modified_input_iterator.cuh"
#include "../iterator/counting_input_iterator.cuh"
#include "../iterator/tex_ref_input_iterator.cuh"
/// Optional outer namespace(s)
CUB_NS_PREFIX
/// CUB namespace
namespace cub {
/******************************************************************************
* Tuning policy
******************************************************************************/
/**
* Parameterizable tuning policy type for AgentSpmv
*/
template <
int _BLOCK_THREADS, ///< Threads per thread block
int _ITEMS_PER_THREAD, ///< Items per thread (per tile of input)
CacheLoadModifier _ROW_OFFSETS_SEARCH_LOAD_MODIFIER, ///< Cache load modifier for reading CSR row-offsets during search
CacheLoadModifier _ROW_OFFSETS_LOAD_MODIFIER, ///< Cache load modifier for reading CSR row-offsets
CacheLoadModifier _COLUMN_INDICES_LOAD_MODIFIER, ///< Cache load modifier for reading CSR column-indices
CacheLoadModifier _VALUES_LOAD_MODIFIER, ///< Cache load modifier for reading CSR values
CacheLoadModifier _VECTOR_VALUES_LOAD_MODIFIER, ///< Cache load modifier for reading vector values
bool _DIRECT_LOAD_NONZEROS, ///< Whether to load nonzeros directly from global during sequential merging (vs. pre-staged through shared memory)
BlockScanAlgorithm _SCAN_ALGORITHM> ///< The BlockScan algorithm to use
struct AgentSpmvPolicy
{
enum
{
BLOCK_THREADS = _BLOCK_THREADS, ///< Threads per thread block
ITEMS_PER_THREAD = _ITEMS_PER_THREAD, ///< Items per thread (per tile of input)
DIRECT_LOAD_NONZEROS = _DIRECT_LOAD_NONZEROS, ///< Whether to load nonzeros directly from global during sequential merging (pre-staged through shared memory)
};
static const CacheLoadModifier ROW_OFFSETS_SEARCH_LOAD_MODIFIER = _ROW_OFFSETS_SEARCH_LOAD_MODIFIER; ///< Cache load modifier for reading CSR row-offsets
static const CacheLoadModifier ROW_OFFSETS_LOAD_MODIFIER = _ROW_OFFSETS_LOAD_MODIFIER; ///< Cache load modifier for reading CSR row-offsets
static const CacheLoadModifier COLUMN_INDICES_LOAD_MODIFIER = _COLUMN_INDICES_LOAD_MODIFIER; ///< Cache load modifier for reading CSR column-indices
static const CacheLoadModifier VALUES_LOAD_MODIFIER = _VALUES_LOAD_MODIFIER; ///< Cache load modifier for reading CSR values
static const CacheLoadModifier VECTOR_VALUES_LOAD_MODIFIER = _VECTOR_VALUES_LOAD_MODIFIER; ///< Cache load modifier for reading vector values
static const BlockScanAlgorithm SCAN_ALGORITHM = _SCAN_ALGORITHM; ///< The BlockScan algorithm to use
};
/******************************************************************************
* Thread block abstractions
******************************************************************************/
template <
typename ValueT, ///< Matrix and vector value type
typename OffsetT> ///< Signed integer type for sequence offsets
struct SpmvParams
{
ValueT* d_values; ///< Pointer to the array of \p num_nonzeros values of the corresponding nonzero elements of matrix <b>A</b>.
OffsetT* d_row_end_offsets; ///< Pointer to the array of \p m offsets demarcating the end of every row in \p d_column_indices and \p d_values
OffsetT* d_column_indices; ///< Pointer to the array of \p num_nonzeros column-indices of the corresponding nonzero elements of matrix <b>A</b>. (Indices are zero-valued.)
ValueT* d_vector_x; ///< Pointer to the array of \p num_cols values corresponding to the dense input vector <em>x</em>
ValueT* d_vector_y; ///< Pointer to the array of \p num_rows values corresponding to the dense output vector <em>y</em>
int num_rows; ///< Number of rows of matrix <b>A</b>.
int num_cols; ///< Number of columns of matrix <b>A</b>.
int num_nonzeros; ///< Number of nonzero elements of matrix <b>A</b>.
ValueT alpha; ///< Alpha multiplicand
ValueT beta; ///< Beta addend-multiplicand
TexRefInputIterator<ValueT, 66778899, OffsetT> t_vector_x;
};
/**
* \brief AgentSpmv implements a stateful abstraction of CUDA thread blocks for participating in device-wide SpMV.
*/
template <
typename AgentSpmvPolicyT, ///< Parameterized AgentSpmvPolicy tuning policy type
typename ValueT, ///< Matrix and vector value type
typename OffsetT, ///< Signed integer type for sequence offsets
bool HAS_ALPHA, ///< Whether the input parameter \p alpha is 1
bool HAS_BETA, ///< Whether the input parameter \p beta is 0
int PTX_ARCH = CUB_PTX_ARCH> ///< PTX compute capability
struct AgentSpmv
{
//---------------------------------------------------------------------
// Types and constants
//---------------------------------------------------------------------
/// Constants
enum
{
BLOCK_THREADS = AgentSpmvPolicyT::BLOCK_THREADS,
ITEMS_PER_THREAD = AgentSpmvPolicyT::ITEMS_PER_THREAD,
TILE_ITEMS = BLOCK_THREADS * ITEMS_PER_THREAD,
};
/// 2D merge path coordinate type
typedef typename CubVector<OffsetT, 2>::Type CoordinateT;
/// Input iterator wrapper types (for applying cache modifiers)
typedef CacheModifiedInputIterator<
AgentSpmvPolicyT::ROW_OFFSETS_SEARCH_LOAD_MODIFIER,
OffsetT,
OffsetT>
RowOffsetsSearchIteratorT;
typedef CacheModifiedInputIterator<
AgentSpmvPolicyT::ROW_OFFSETS_LOAD_MODIFIER,
OffsetT,
OffsetT>
RowOffsetsIteratorT;
typedef CacheModifiedInputIterator<
AgentSpmvPolicyT::COLUMN_INDICES_LOAD_MODIFIER,
OffsetT,
OffsetT>
ColumnIndicesIteratorT;
typedef CacheModifiedInputIterator<
AgentSpmvPolicyT::VALUES_LOAD_MODIFIER,
ValueT,
OffsetT>
ValueIteratorT;
typedef CacheModifiedInputIterator<
AgentSpmvPolicyT::VECTOR_VALUES_LOAD_MODIFIER,
ValueT,
OffsetT>
VectorValueIteratorT;
// Tuple type for scanning (pairs accumulated segment-value with segment-index)
typedef KeyValuePair<OffsetT, ValueT> KeyValuePairT;
// Reduce-value-by-segment scan operator
typedef ReduceByKeyOp<cub::Sum> ReduceBySegmentOpT;
// BlockReduce specialization
typedef BlockReduce<
ValueT,
BLOCK_THREADS,
BLOCK_REDUCE_WARP_REDUCTIONS>
BlockReduceT;
// BlockScan specialization
typedef BlockScan<
KeyValuePairT,
BLOCK_THREADS,
AgentSpmvPolicyT::SCAN_ALGORITHM>
BlockScanT;
// BlockScan specialization
typedef BlockScan<
ValueT,
BLOCK_THREADS,
AgentSpmvPolicyT::SCAN_ALGORITHM>
BlockPrefixSumT;
// BlockExchange specialization
typedef BlockExchange<
ValueT,
BLOCK_THREADS,
ITEMS_PER_THREAD>
BlockExchangeT;
/// Merge item type (either a non-zero value or a row-end offset)
union MergeItem
{
// Value type to pair with index type OffsetT (NullType if loading values directly during merge)
typedef typename If<AgentSpmvPolicyT::DIRECT_LOAD_NONZEROS, NullType, ValueT>::Type MergeValueT;
OffsetT row_end_offset;
MergeValueT nonzero;
};
/// Shared memory type required by this thread block
struct _TempStorage
{
CoordinateT tile_coords[2];
union Aliasable
{
// Smem needed for tile of merge items
MergeItem merge_items[ITEMS_PER_THREAD + TILE_ITEMS + 1];
// Smem needed for block exchange
typename BlockExchangeT::TempStorage exchange;
// Smem needed for block-wide reduction
typename BlockReduceT::TempStorage reduce;
// Smem needed for tile scanning
typename BlockScanT::TempStorage scan;
// Smem needed for tile prefix sum
typename BlockPrefixSumT::TempStorage prefix_sum;
} aliasable;
};
/// Temporary storage type (unionable)
struct TempStorage : Uninitialized<_TempStorage> {};
//---------------------------------------------------------------------
// Per-thread fields
//---------------------------------------------------------------------
_TempStorage& temp_storage; /// Reference to temp_storage
SpmvParams<ValueT, OffsetT>& spmv_params;
ValueIteratorT wd_values; ///< Wrapped pointer to the array of \p num_nonzeros values of the corresponding nonzero elements of matrix <b>A</b>.
RowOffsetsIteratorT wd_row_end_offsets; ///< Wrapped Pointer to the array of \p m offsets demarcating the end of every row in \p d_column_indices and \p d_values
ColumnIndicesIteratorT wd_column_indices; ///< Wrapped Pointer to the array of \p num_nonzeros column-indices of the corresponding nonzero elements of matrix <b>A</b>. (Indices are zero-valued.)
VectorValueIteratorT wd_vector_x; ///< Wrapped Pointer to the array of \p num_cols values corresponding to the dense input vector <em>x</em>
VectorValueIteratorT wd_vector_y; ///< Wrapped Pointer to the array of \p num_cols values corresponding to the dense input vector <em>x</em>
//---------------------------------------------------------------------
// Interface
//---------------------------------------------------------------------
/**
* Constructor
*/
__device__ __forceinline__ AgentSpmv(
TempStorage& temp_storage, ///< Reference to temp_storage
SpmvParams<ValueT, OffsetT>& spmv_params) ///< SpMV input parameter bundle
:
temp_storage(temp_storage.Alias()),
spmv_params(spmv_params),
wd_values(spmv_params.d_values),
wd_row_end_offsets(spmv_params.d_row_end_offsets),
wd_column_indices(spmv_params.d_column_indices),
wd_vector_x(spmv_params.d_vector_x),
wd_vector_y(spmv_params.d_vector_y)
{}
/**
* Consume a merge tile, specialized for direct-load of nonzeros
*/
__device__ __forceinline__ KeyValuePairT ConsumeTile(
int tile_idx,
CoordinateT tile_start_coord,
CoordinateT tile_end_coord,
Int2Type<true> is_direct_load) ///< Marker type indicating whether to load nonzeros directly during path-discovery or beforehand in batch
{
int tile_num_rows = tile_end_coord.x - tile_start_coord.x;
int tile_num_nonzeros = tile_end_coord.y - tile_start_coord.y;
OffsetT* s_tile_row_end_offsets = &temp_storage.aliasable.merge_items[0].row_end_offset;
// Gather the row end-offsets for the merge tile into shared memory
for (int item = threadIdx.x; item <= tile_num_rows; item += BLOCK_THREADS)
{
s_tile_row_end_offsets[item] = wd_row_end_offsets[tile_start_coord.x + item];
}
CTA_SYNC();
// Search for the thread's starting coordinate within the merge tile
CountingInputIterator<OffsetT> tile_nonzero_indices(tile_start_coord.y);
CoordinateT thread_start_coord;
MergePathSearch(
OffsetT(threadIdx.x * ITEMS_PER_THREAD), // Diagonal
s_tile_row_end_offsets, // List A
tile_nonzero_indices, // List B
tile_num_rows,
tile_num_nonzeros,
thread_start_coord);
CTA_SYNC(); // Perf-sync
// Compute the thread's merge path segment
CoordinateT thread_current_coord = thread_start_coord;
KeyValuePairT scan_segment[ITEMS_PER_THREAD];
ValueT running_total = 0.0;
#pragma unroll
for (int ITEM = 0; ITEM < ITEMS_PER_THREAD; ++ITEM)
{
OffsetT nonzero_idx = CUB_MIN(tile_nonzero_indices[thread_current_coord.y], spmv_params.num_nonzeros - 1);
OffsetT column_idx = wd_column_indices[nonzero_idx];
ValueT value = wd_values[nonzero_idx];
ValueT vector_value = spmv_params.t_vector_x[column_idx];
#if (CUB_PTX_ARCH >= 350)
vector_value = wd_vector_x[column_idx];
#endif
ValueT nonzero = value * vector_value;
OffsetT row_end_offset = s_tile_row_end_offsets[thread_current_coord.x];
if (tile_nonzero_indices[thread_current_coord.y] < row_end_offset)
{
// Move down (accumulate)
running_total += nonzero;
scan_segment[ITEM].value = running_total;
scan_segment[ITEM].key = tile_num_rows;
++thread_current_coord.y;
}
else
{
// Move right (reset)
scan_segment[ITEM].value = running_total;
scan_segment[ITEM].key = thread_current_coord.x;
running_total = 0.0;
++thread_current_coord.x;
}
}
CTA_SYNC();
// Block-wide reduce-value-by-segment
KeyValuePairT tile_carry;
ReduceBySegmentOpT scan_op;
KeyValuePairT scan_item;
scan_item.value = running_total;
scan_item.key = thread_current_coord.x;
BlockScanT(temp_storage.aliasable.scan).ExclusiveScan(scan_item, scan_item, scan_op, tile_carry);
if (tile_num_rows > 0)
{
if (threadIdx.x == 0)
scan_item.key = -1;
// Direct scatter
#pragma unroll
for (int ITEM = 0; ITEM < ITEMS_PER_THREAD; ++ITEM)
{
if (scan_segment[ITEM].key < tile_num_rows)
{
if (scan_item.key == scan_segment[ITEM].key)
scan_segment[ITEM].value = scan_item.value + scan_segment[ITEM].value;
if (HAS_ALPHA)
{
scan_segment[ITEM].value *= spmv_params.alpha;
}
if (HAS_BETA)
{
// Update the output vector element
ValueT addend = spmv_params.beta * wd_vector_y[tile_start_coord.x + scan_segment[ITEM].key];
scan_segment[ITEM].value += addend;
}
// Set the output vector element
spmv_params.d_vector_y[tile_start_coord.x + scan_segment[ITEM].key] = scan_segment[ITEM].value;
}
}
}
// Return the tile's running carry-out
return tile_carry;
}
/**
* Consume a merge tile, specialized for indirect load of nonzeros
*/
__device__ __forceinline__ KeyValuePairT ConsumeTile(
int tile_idx,
CoordinateT tile_start_coord,
CoordinateT tile_end_coord,
Int2Type<false> is_direct_load) ///< Marker type indicating whether to load nonzeros directly during path-discovery or beforehand in batch
{
int tile_num_rows = tile_end_coord.x - tile_start_coord.x;
int tile_num_nonzeros = tile_end_coord.y - tile_start_coord.y;
#if (CUB_PTX_ARCH >= 520)
OffsetT* s_tile_row_end_offsets = &temp_storage.aliasable.merge_items[0].row_end_offset;
ValueT* s_tile_nonzeros = &temp_storage.aliasable.merge_items[tile_num_rows + ITEMS_PER_THREAD].nonzero;
// Gather the nonzeros for the merge tile into shared memory
#pragma unroll
for (int ITEM = 0; ITEM < ITEMS_PER_THREAD; ++ITEM)
{
int nonzero_idx = threadIdx.x + (ITEM * BLOCK_THREADS);
ValueIteratorT a = wd_values + tile_start_coord.y + nonzero_idx;
ColumnIndicesIteratorT ci = wd_column_indices + tile_start_coord.y + nonzero_idx;
ValueT* s = s_tile_nonzeros + nonzero_idx;
if (nonzero_idx < tile_num_nonzeros)
{
OffsetT column_idx = *ci;
ValueT value = *a;
ValueT vector_value = spmv_params.t_vector_x[column_idx];
vector_value = wd_vector_x[column_idx];
ValueT nonzero = value * vector_value;
*s = nonzero;
}
}
#else
OffsetT* s_tile_row_end_offsets = &temp_storage.aliasable.merge_items[0].row_end_offset;
ValueT* s_tile_nonzeros = &temp_storage.aliasable.merge_items[tile_num_rows + ITEMS_PER_THREAD].nonzero;
// Gather the nonzeros for the merge tile into shared memory
if (tile_num_nonzeros > 0)
{
#pragma unroll
for (int ITEM = 0; ITEM < ITEMS_PER_THREAD; ++ITEM)
{
int nonzero_idx = threadIdx.x + (ITEM * BLOCK_THREADS);
nonzero_idx = CUB_MIN(nonzero_idx, tile_num_nonzeros - 1);
OffsetT column_idx = wd_column_indices[tile_start_coord.y + nonzero_idx];
ValueT value = wd_values[tile_start_coord.y + nonzero_idx];
ValueT vector_value = spmv_params.t_vector_x[column_idx];
#if (CUB_PTX_ARCH >= 350)
vector_value = wd_vector_x[column_idx];
#endif
ValueT nonzero = value * vector_value;
s_tile_nonzeros[nonzero_idx] = nonzero;
}
}
#endif
// Gather the row end-offsets for the merge tile into shared memory
#pragma unroll 1
for (int item = threadIdx.x; item <= tile_num_rows; item += BLOCK_THREADS)
{
s_tile_row_end_offsets[item] = wd_row_end_offsets[tile_start_coord.x + item];
}
CTA_SYNC();
// Search for the thread's starting coordinate within the merge tile
CountingInputIterator<OffsetT> tile_nonzero_indices(tile_start_coord.y);
CoordinateT thread_start_coord;
MergePathSearch(
OffsetT(threadIdx.x * ITEMS_PER_THREAD), // Diagonal
s_tile_row_end_offsets, // List A
tile_nonzero_indices, // List B
tile_num_rows,
tile_num_nonzeros,
thread_start_coord);
CTA_SYNC(); // Perf-sync
// Compute the thread's merge path segment
CoordinateT thread_current_coord = thread_start_coord;
KeyValuePairT scan_segment[ITEMS_PER_THREAD];
ValueT running_total = 0.0;
OffsetT row_end_offset = s_tile_row_end_offsets[thread_current_coord.x];
ValueT nonzero = s_tile_nonzeros[thread_current_coord.y];
#pragma unroll
for (int ITEM = 0; ITEM < ITEMS_PER_THREAD; ++ITEM)
{
if (tile_nonzero_indices[thread_current_coord.y] < row_end_offset)
{
// Move down (accumulate)
scan_segment[ITEM].value = nonzero;
running_total += nonzero;
++thread_current_coord.y;
nonzero = s_tile_nonzeros[thread_current_coord.y];
}
else
{
// Move right (reset)
scan_segment[ITEM].value = 0.0;
running_total = 0.0;
++thread_current_coord.x;
row_end_offset = s_tile_row_end_offsets[thread_current_coord.x];
}
scan_segment[ITEM].key = thread_current_coord.x;
}
CTA_SYNC();
// Block-wide reduce-value-by-segment
KeyValuePairT tile_carry;
ReduceBySegmentOpT scan_op;
KeyValuePairT scan_item;
scan_item.value = running_total;
scan_item.key = thread_current_coord.x;
BlockScanT(temp_storage.aliasable.scan).ExclusiveScan(scan_item, scan_item, scan_op, tile_carry);
if (threadIdx.x == 0)
{
scan_item.key = thread_start_coord.x;
scan_item.value = 0.0;
}
if (tile_num_rows > 0)
{
CTA_SYNC();
// Scan downsweep and scatter
ValueT* s_partials = &temp_storage.aliasable.merge_items[0].nonzero;
if (scan_item.key != scan_segment[0].key)
{
s_partials[scan_item.key] = scan_item.value;
}
else
{
scan_segment[0].value += scan_item.value;
}
#pragma unroll
for (int ITEM = 1; ITEM < ITEMS_PER_THREAD; ++ITEM)
{
if (scan_segment[ITEM - 1].key != scan_segment[ITEM].key)
{
s_partials[scan_segment[ITEM - 1].key] = scan_segment[ITEM - 1].value;
}
else
{
scan_segment[ITEM].value += scan_segment[ITEM - 1].value;
}
}
CTA_SYNC();
#pragma unroll 1
for (int item = threadIdx.x; item < tile_num_rows; item += BLOCK_THREADS)
{
spmv_params.d_vector_y[tile_start_coord.x + item] = s_partials[item];
}
}
// Return the tile's running carry-out
return tile_carry;
}
/**
* Consume input tile
*/
__device__ __forceinline__ void ConsumeTile(
CoordinateT* d_tile_coordinates, ///< [in] Pointer to the temporary array of tile starting coordinates
KeyValuePairT* d_tile_carry_pairs, ///< [out] Pointer to the temporary array carry-out dot product row-ids, one per block
int num_merge_tiles) ///< [in] Number of merge tiles
{
int tile_idx = (blockIdx.x * gridDim.y) + blockIdx.y; // Current tile index
if (tile_idx >= num_merge_tiles)
return;
// Read our starting coordinates
if (threadIdx.x < 2)
{
if (d_tile_coordinates == NULL)
{
// Search our starting coordinates
OffsetT diagonal = (tile_idx + threadIdx.x) * TILE_ITEMS;
CoordinateT tile_coord;
CountingInputIterator<OffsetT> nonzero_indices(0);
// Search the merge path
MergePathSearch(
diagonal,
RowOffsetsSearchIteratorT(spmv_params.d_row_end_offsets),
nonzero_indices,
spmv_params.num_rows,
spmv_params.num_nonzeros,
tile_coord);
temp_storage.tile_coords[threadIdx.x] = tile_coord;
}
else
{
temp_storage.tile_coords[threadIdx.x] = d_tile_coordinates[tile_idx + threadIdx.x];
}
}
CTA_SYNC();
CoordinateT tile_start_coord = temp_storage.tile_coords[0];
CoordinateT tile_end_coord = temp_storage.tile_coords[1];
// Consume multi-segment tile
KeyValuePairT tile_carry = ConsumeTile(
tile_idx,
tile_start_coord,
tile_end_coord,
Int2Type<AgentSpmvPolicyT::DIRECT_LOAD_NONZEROS>());
// Output the tile's carry-out
if (threadIdx.x == 0)
{
if (HAS_ALPHA)
tile_carry.value *= spmv_params.alpha;
tile_carry.key += tile_start_coord.x;
d_tile_carry_pairs[tile_idx] = tile_carry;
}
}
};
} // CUB namespace
CUB_NS_POSTFIX // Optional outer namespace(s)
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