thrust / install /include /cub /device /dispatch /dispatch_three_way_partition.cuh
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/******************************************************************************
* Copyright (c) 2011-2021, 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/agent/agent_three_way_partition.cuh>
#include <cub/config.cuh>
#include <cub/device/dispatch/dispatch_scan.cuh>
#include <cub/thread/thread_operators.cuh>
#include <cub/util_deprecated.cuh>
#include <cub/util_device.cuh>
#include <cub/util_math.cuh>
#include <thrust/system/cuda/detail/core/triple_chevron_launch.h>
#include <cstdio>
#include <iterator>
#include <nv/target>
CUB_NAMESPACE_BEGIN
/******************************************************************************
* Kernel entry points
*****************************************************************************/
template <typename ChainedPolicyT,
typename InputIteratorT,
typename FirstOutputIteratorT,
typename SecondOutputIteratorT,
typename UnselectedOutputIteratorT,
typename NumSelectedIteratorT,
typename ScanTileStateT,
typename SelectFirstPartOp,
typename SelectSecondPartOp,
typename OffsetT>
__launch_bounds__(int(ChainedPolicyT::ActivePolicy::ThreeWayPartitionPolicy::BLOCK_THREADS)) __global__
void DeviceThreeWayPartitionKernel(InputIteratorT d_in,
FirstOutputIteratorT d_first_part_out,
SecondOutputIteratorT d_second_part_out,
UnselectedOutputIteratorT d_unselected_out,
NumSelectedIteratorT d_num_selected_out,
ScanTileStateT tile_status_1,
ScanTileStateT tile_status_2,
SelectFirstPartOp select_first_part_op,
SelectSecondPartOp select_second_part_op,
OffsetT num_items,
int num_tiles)
{
using AgentThreeWayPartitionPolicyT =
typename ChainedPolicyT::ActivePolicy::ThreeWayPartitionPolicy;
// Thread block type for selecting data from input tiles
using AgentThreeWayPartitionT = AgentThreeWayPartition<AgentThreeWayPartitionPolicyT,
InputIteratorT,
FirstOutputIteratorT,
SecondOutputIteratorT,
UnselectedOutputIteratorT,
SelectFirstPartOp,
SelectSecondPartOp,
OffsetT>;
// Shared memory for AgentThreeWayPartition
__shared__ typename AgentThreeWayPartitionT::TempStorage temp_storage;
// Process tiles
AgentThreeWayPartitionT(temp_storage,
d_in,
d_first_part_out,
d_second_part_out,
d_unselected_out,
select_first_part_op,
select_second_part_op,
num_items)
.ConsumeRange(num_tiles, tile_status_1, tile_status_2, d_num_selected_out);
}
/**
* @brief Initialization kernel for tile status initialization (multi-block)
*
* @tparam ScanTileStateT
* Tile status interface type
*
* @tparam NumSelectedIteratorT
* Output iterator type for recording the number of items selected
*
* @param[in] tile_state_1
* Tile status interface
*
* @param[in] tile_state_2
* Tile status interface
*
* @param[in] num_tiles
* Number of tiles
*
* @param[out] d_num_selected_out
* Pointer to the total number of items selected
* (i.e., length of @p d_selected_out)
*/
template <typename ScanTileStateT, typename NumSelectedIteratorT>
__global__ void DeviceThreeWayPartitionInitKernel(ScanTileStateT tile_state_1,
ScanTileStateT tile_state_2,
int num_tiles,
NumSelectedIteratorT d_num_selected_out)
{
// Initialize tile status
tile_state_1.InitializeStatus(num_tiles);
tile_state_2.InitializeStatus(num_tiles);
// Initialize d_num_selected_out
if (blockIdx.x == 0)
{
if (threadIdx.x < 2)
{
d_num_selected_out[threadIdx.x] = 0;
}
}
}
namespace detail
{
template <class InputT>
struct device_three_way_partition_policy_hub
{
/// SM35
struct Policy350 : ChainedPolicy<350, Policy350, Policy350>
{
constexpr static int ITEMS_PER_THREAD = Nominal4BItemsToItems<InputT>(9);
using ThreeWayPartitionPolicy = cub::AgentThreeWayPartitionPolicy<256,
ITEMS_PER_THREAD,
cub::BLOCK_LOAD_DIRECT,
cub::LOAD_DEFAULT,
cub::BLOCK_SCAN_WARP_SCANS>;
};
using MaxPolicy = Policy350;
};
} // namespace detail
/******************************************************************************
* Dispatch
******************************************************************************/
template <typename InputIteratorT,
typename FirstOutputIteratorT,
typename SecondOutputIteratorT,
typename UnselectedOutputIteratorT,
typename NumSelectedIteratorT,
typename SelectFirstPartOp,
typename SelectSecondPartOp,
typename OffsetT,
typename SelectedPolicy =
detail::device_three_way_partition_policy_hub<cub::detail::value_t<InputIteratorT>>>
struct DispatchThreeWayPartitionIf
{
/*****************************************************************************
* Types and constants
****************************************************************************/
using ScanTileStateT = cub::ScanTileState<OffsetT>;
constexpr static int INIT_KERNEL_THREADS = 256;
void *d_temp_storage;
std::size_t &temp_storage_bytes;
InputIteratorT d_in;
FirstOutputIteratorT d_first_part_out;
SecondOutputIteratorT d_second_part_out;
UnselectedOutputIteratorT d_unselected_out;
NumSelectedIteratorT d_num_selected_out;
SelectFirstPartOp select_first_part_op;
SelectSecondPartOp select_second_part_op;
OffsetT num_items;
cudaStream_t stream;
CUB_RUNTIME_FUNCTION __forceinline__
DispatchThreeWayPartitionIf(void *d_temp_storage,
std::size_t &temp_storage_bytes,
InputIteratorT d_in,
FirstOutputIteratorT d_first_part_out,
SecondOutputIteratorT d_second_part_out,
UnselectedOutputIteratorT d_unselected_out,
NumSelectedIteratorT d_num_selected_out,
SelectFirstPartOp select_first_part_op,
SelectSecondPartOp select_second_part_op,
OffsetT num_items,
cudaStream_t stream)
: d_temp_storage(d_temp_storage)
, temp_storage_bytes(temp_storage_bytes)
, d_in(d_in)
, d_first_part_out(d_first_part_out)
, d_second_part_out(d_second_part_out)
, d_unselected_out(d_unselected_out)
, d_num_selected_out(d_num_selected_out)
, select_first_part_op(select_first_part_op)
, select_second_part_op(select_second_part_op)
, num_items(num_items)
, stream(stream)
{}
/*****************************************************************************
* Dispatch entrypoints
****************************************************************************/
template <typename ActivePolicyT, typename ScanInitKernelPtrT, typename SelectIfKernelPtrT>
CUB_RUNTIME_FUNCTION __forceinline__ cudaError_t
Invoke(ScanInitKernelPtrT three_way_partition_init_kernel,
SelectIfKernelPtrT three_way_partition_kernel)
{
cudaError error = cudaSuccess;
const int block_threads = ActivePolicyT::ThreeWayPartitionPolicy::BLOCK_THREADS;
const int items_per_thread = ActivePolicyT::ThreeWayPartitionPolicy::ITEMS_PER_THREAD;
do
{
// Get device ordinal
int device_ordinal;
if (CubDebug(error = cudaGetDevice(&device_ordinal)))
{
break;
}
// Number of input tiles
int tile_size = block_threads * items_per_thread;
int num_tiles = static_cast<int>(DivideAndRoundUp(num_items, tile_size));
// Specify temporary storage allocation requirements
size_t allocation_sizes[2]; // bytes needed for tile status descriptors
if (CubDebug(error = ScanTileStateT::AllocationSize(num_tiles, allocation_sizes[0])))
{
break;
}
allocation_sizes[1] = allocation_sizes[0];
// Compute allocation pointers into the single storage blob (or compute
// the necessary size of the blob)
void *allocations[2] = {};
if (CubDebug(error = cub::AliasTemporaries(d_temp_storage,
temp_storage_bytes,
allocations,
allocation_sizes)))
{
break;
}
if (d_temp_storage == nullptr)
{
// Return if the caller is simply requesting the size of the storage
// allocation
break;
}
// Return if empty problem
if (num_items == 0)
{
break;
}
// Construct the tile status interface
ScanTileStateT tile_status_1;
ScanTileStateT tile_status_2;
if (CubDebug(error = tile_status_1.Init(num_tiles, allocations[0], allocation_sizes[0])))
{
break;
}
if (CubDebug(error = tile_status_2.Init(num_tiles, allocations[1], allocation_sizes[1])))
{
break;
}
// Log three_way_partition_init_kernel configuration
int init_grid_size = CUB_MAX(1, DivideAndRoundUp(num_tiles, INIT_KERNEL_THREADS));
#ifdef CUB_DETAIL_DEBUG_ENABLE_LOG
_CubLog("Invoking three_way_partition_init_kernel<<<%d, %d, 0, %lld>>>()\n",
init_grid_size,
INIT_KERNEL_THREADS,
reinterpret_cast<long long>(stream));
#endif
// Invoke three_way_partition_init_kernel to initialize tile descriptors
THRUST_NS_QUALIFIER::cuda_cub::launcher::triple_chevron(init_grid_size,
INIT_KERNEL_THREADS,
0,
stream)
.doit(three_way_partition_init_kernel,
tile_status_1,
tile_status_2,
num_tiles,
d_num_selected_out);
// Check for failure to launch
if (CubDebug(error = cudaPeekAtLastError()))
{
break;
}
// Sync the stream if specified to flush runtime errors
error = detail::DebugSyncStream(stream);
if (CubDebug(error))
{
break;
}
// Get max x-dimension of grid
int max_dim_x;
if (CubDebug(
error = cudaDeviceGetAttribute(&max_dim_x, cudaDevAttrMaxGridDimX, device_ordinal)))
{
break;
}
// Get grid size for scanning tiles
dim3 scan_grid_size;
scan_grid_size.z = 1;
scan_grid_size.y = DivideAndRoundUp(num_tiles, max_dim_x);
scan_grid_size.x = CUB_MIN(num_tiles, max_dim_x);
// Log select_if_kernel configuration
#ifdef CUB_DETAIL_DEBUG_ENABLE_LOG
{
// Get SM occupancy for select_if_kernel
int range_select_sm_occupancy;
if (CubDebug(error = MaxSmOccupancy(range_select_sm_occupancy, // out
three_way_partition_kernel,
block_threads)))
{
break;
}
_CubLog("Invoking three_way_partition_kernel<<<{%d,%d,%d}, %d, 0, %lld>>>(), %d "
"items per thread, %d SM occupancy\n",
scan_grid_size.x,
scan_grid_size.y,
scan_grid_size.z,
block_threads,
reinterpret_cast<long long>(stream),
items_per_thread,
range_select_sm_occupancy);
}
#endif
// Invoke select_if_kernel
THRUST_NS_QUALIFIER::cuda_cub::launcher::triple_chevron(
scan_grid_size,
block_threads,
0,
stream)
.doit(three_way_partition_kernel,
d_in,
d_first_part_out,
d_second_part_out,
d_unselected_out,
d_num_selected_out,
tile_status_1,
tile_status_2,
select_first_part_op,
select_second_part_op,
num_items,
num_tiles);
// Check for failure to launch
if (CubDebug(error = cudaPeekAtLastError()))
{
break;
}
// Sync the stream if specified to flush runtime errors
error = detail::DebugSyncStream(stream);
if (CubDebug(error))
{
break;
}
} while (0);
return error;
}
template <typename ActivePolicyT>
CUB_RUNTIME_FUNCTION __forceinline__ cudaError_t
Invoke()
{
using MaxPolicyT = typename SelectedPolicy::MaxPolicy;
return Invoke<ActivePolicyT>(
DeviceThreeWayPartitionInitKernel<ScanTileStateT, NumSelectedIteratorT>,
DeviceThreeWayPartitionKernel<MaxPolicyT,
InputIteratorT,
FirstOutputIteratorT,
SecondOutputIteratorT,
UnselectedOutputIteratorT,
NumSelectedIteratorT,
ScanTileStateT,
SelectFirstPartOp,
SelectSecondPartOp,
OffsetT>);
}
/**
* Internal dispatch routine
*/
CUB_RUNTIME_FUNCTION __forceinline__ static cudaError_t
Dispatch(void *d_temp_storage,
std::size_t &temp_storage_bytes,
InputIteratorT d_in,
FirstOutputIteratorT d_first_part_out,
SecondOutputIteratorT d_second_part_out,
UnselectedOutputIteratorT d_unselected_out,
NumSelectedIteratorT d_num_selected_out,
SelectFirstPartOp select_first_part_op,
SelectSecondPartOp select_second_part_op,
OffsetT num_items,
cudaStream_t stream)
{
using MaxPolicyT = typename SelectedPolicy::MaxPolicy;
cudaError error = cudaSuccess;
do
{
// Get PTX version
int ptx_version = 0;
if (CubDebug(error = cub::PtxVersion(ptx_version)))
{
break;
}
DispatchThreeWayPartitionIf dispatch(d_temp_storage,
temp_storage_bytes,
d_in,
d_first_part_out,
d_second_part_out,
d_unselected_out,
d_num_selected_out,
select_first_part_op,
select_second_part_op,
num_items,
stream);
// Dispatch
if (CubDebug(error = MaxPolicyT::Invoke(ptx_version, dispatch)))
{
break;
}
} while (0);
return error;
}
CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED
CUB_RUNTIME_FUNCTION __forceinline__ static cudaError_t
Dispatch(void *d_temp_storage,
std::size_t &temp_storage_bytes,
InputIteratorT d_in,
FirstOutputIteratorT d_first_part_out,
SecondOutputIteratorT d_second_part_out,
UnselectedOutputIteratorT d_unselected_out,
NumSelectedIteratorT d_num_selected_out,
SelectFirstPartOp select_first_part_op,
SelectSecondPartOp select_second_part_op,
OffsetT num_items,
cudaStream_t stream,
bool debug_synchronous)
{
CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG
return Dispatch(d_temp_storage,
temp_storage_bytes,
d_in,
d_first_part_out,
d_second_part_out,
d_unselected_out,
d_num_selected_out,
select_first_part_op,
select_second_part_op,
num_items,
stream);
}
};
CUB_NAMESPACE_END