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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::DeviceRle provides device-wide, parallel operations for run-length-encoding sequences of data items residing within device-accessible memory.
*/
#pragma once
#include <stdio.h>
#include <iterator>
#include "dispatch_scan.cuh"
#include "../../config.cuh"
#include "../../agent/agent_rle.cuh"
#include "../../thread/thread_operators.cuh"
#include "../../grid/grid_queue.cuh"
#include "../../util_device.cuh"
#include <thrust/system/cuda/detail/core/triple_chevron_launch.h>
/// Optional outer namespace(s)
CUB_NS_PREFIX
/// CUB namespace
namespace cub {
/******************************************************************************
* Kernel entry points
*****************************************************************************/
/**
* Select kernel entry point (multi-block)
*
* Performs functor-based selection if SelectOp functor type != NullType
* Otherwise performs flag-based selection if FlagIterator's value type != NullType
* Otherwise performs discontinuity selection (keep unique)
*/
template <
typename AgentRlePolicyT, ///< Parameterized AgentRlePolicyT tuning policy type
typename InputIteratorT, ///< Random-access input iterator type for reading input items \iterator
typename OffsetsOutputIteratorT, ///< Random-access output iterator type for writing run-offset values \iterator
typename LengthsOutputIteratorT, ///< Random-access output iterator type for writing run-length values \iterator
typename NumRunsOutputIteratorT, ///< Output iterator type for recording the number of runs encountered \iterator
typename ScanTileStateT, ///< Tile status interface type
typename EqualityOpT, ///< T equality operator type
typename OffsetT> ///< Signed integer type for global offsets
__launch_bounds__ (int(AgentRlePolicyT::BLOCK_THREADS))
__global__ void DeviceRleSweepKernel(
InputIteratorT d_in, ///< [in] Pointer to input sequence of data items
OffsetsOutputIteratorT d_offsets_out, ///< [out] Pointer to output sequence of run-offsets
LengthsOutputIteratorT d_lengths_out, ///< [out] Pointer to output sequence of run-lengths
NumRunsOutputIteratorT d_num_runs_out, ///< [out] Pointer to total number of runs (i.e., length of \p d_offsets_out)
ScanTileStateT tile_status, ///< [in] Tile status interface
EqualityOpT equality_op, ///< [in] Equality operator for input items
OffsetT num_items, ///< [in] Total number of input items (i.e., length of \p d_in)
int num_tiles) ///< [in] Total number of tiles for the entire problem
{
// Thread block type for selecting data from input tiles
typedef AgentRle<
AgentRlePolicyT,
InputIteratorT,
OffsetsOutputIteratorT,
LengthsOutputIteratorT,
EqualityOpT,
OffsetT> AgentRleT;
// Shared memory for AgentRle
__shared__ typename AgentRleT::TempStorage temp_storage;
// Process tiles
AgentRleT(temp_storage, d_in, d_offsets_out, d_lengths_out, equality_op, num_items).ConsumeRange(
num_tiles,
tile_status,
d_num_runs_out);
}
/******************************************************************************
* Dispatch
******************************************************************************/
/**
* Utility class for dispatching the appropriately-tuned kernels for DeviceRle
*/
template <
typename InputIteratorT, ///< Random-access input iterator type for reading input items \iterator
typename OffsetsOutputIteratorT, ///< Random-access output iterator type for writing run-offset values \iterator
typename LengthsOutputIteratorT, ///< Random-access output iterator type for writing run-length values \iterator
typename NumRunsOutputIteratorT, ///< Output iterator type for recording the number of runs encountered \iterator
typename EqualityOpT, ///< T equality operator type
typename OffsetT> ///< Signed integer type for global offsets
struct DeviceRleDispatch
{
/******************************************************************************
* Types and constants
******************************************************************************/
// The input value type
typedef typename std::iterator_traits<InputIteratorT>::value_type T;
// The lengths output value type
typedef typename If<(Equals<typename std::iterator_traits<LengthsOutputIteratorT>::value_type, void>::VALUE), // LengthT = (if output iterator's value type is void) ?
OffsetT, // ... then the OffsetT type,
typename std::iterator_traits<LengthsOutputIteratorT>::value_type>::Type LengthT; // ... else the output iterator's value type
enum
{
INIT_KERNEL_THREADS = 128,
};
// Tile status descriptor interface type
typedef ReduceByKeyScanTileState<LengthT, OffsetT> ScanTileStateT;
/******************************************************************************
* Tuning policies
******************************************************************************/
/// SM35
struct Policy350
{
enum {
NOMINAL_4B_ITEMS_PER_THREAD = 15,
ITEMS_PER_THREAD = CUB_MIN(NOMINAL_4B_ITEMS_PER_THREAD, CUB_MAX(1, (NOMINAL_4B_ITEMS_PER_THREAD * 4 / sizeof(T)))),
};
typedef AgentRlePolicy<
96,
ITEMS_PER_THREAD,
BLOCK_LOAD_DIRECT,
LOAD_LDG,
true,
BLOCK_SCAN_WARP_SCANS>
RleSweepPolicy;
};
/// SM30
struct Policy300
{
enum {
NOMINAL_4B_ITEMS_PER_THREAD = 5,
ITEMS_PER_THREAD = CUB_MIN(NOMINAL_4B_ITEMS_PER_THREAD, CUB_MAX(1, (NOMINAL_4B_ITEMS_PER_THREAD * 4 / sizeof(T)))),
};
typedef AgentRlePolicy<
256,
ITEMS_PER_THREAD,
BLOCK_LOAD_WARP_TRANSPOSE,
LOAD_DEFAULT,
true,
BLOCK_SCAN_RAKING_MEMOIZE>
RleSweepPolicy;
};
/// SM20
struct Policy200
{
enum {
NOMINAL_4B_ITEMS_PER_THREAD = 15,
ITEMS_PER_THREAD = CUB_MIN(NOMINAL_4B_ITEMS_PER_THREAD, CUB_MAX(1, (NOMINAL_4B_ITEMS_PER_THREAD * 4 / sizeof(T)))),
};
typedef AgentRlePolicy<
128,
ITEMS_PER_THREAD,
BLOCK_LOAD_WARP_TRANSPOSE,
LOAD_DEFAULT,
false,
BLOCK_SCAN_WARP_SCANS>
RleSweepPolicy;
};
/// SM13
struct Policy130
{
enum {
NOMINAL_4B_ITEMS_PER_THREAD = 9,
ITEMS_PER_THREAD = CUB_MIN(NOMINAL_4B_ITEMS_PER_THREAD, CUB_MAX(1, (NOMINAL_4B_ITEMS_PER_THREAD * 4 / sizeof(T)))),
};
typedef AgentRlePolicy<
64,
ITEMS_PER_THREAD,
BLOCK_LOAD_WARP_TRANSPOSE,
LOAD_DEFAULT,
true,
BLOCK_SCAN_RAKING_MEMOIZE>
RleSweepPolicy;
};
/// SM10
struct Policy100
{
enum {
NOMINAL_4B_ITEMS_PER_THREAD = 9,
ITEMS_PER_THREAD = CUB_MIN(NOMINAL_4B_ITEMS_PER_THREAD, CUB_MAX(1, (NOMINAL_4B_ITEMS_PER_THREAD * 4 / sizeof(T)))),
};
typedef AgentRlePolicy<
256,
ITEMS_PER_THREAD,
BLOCK_LOAD_WARP_TRANSPOSE,
LOAD_DEFAULT,
true,
BLOCK_SCAN_RAKING_MEMOIZE>
RleSweepPolicy;
};
/******************************************************************************
* Tuning policies of current PTX compiler pass
******************************************************************************/
#if (CUB_PTX_ARCH >= 350)
typedef Policy350 PtxPolicy;
#elif (CUB_PTX_ARCH >= 300)
typedef Policy300 PtxPolicy;
#elif (CUB_PTX_ARCH >= 200)
typedef Policy200 PtxPolicy;
#elif (CUB_PTX_ARCH >= 130)
typedef Policy130 PtxPolicy;
#else
typedef Policy100 PtxPolicy;
#endif
// "Opaque" policies (whose parameterizations aren't reflected in the type signature)
struct PtxRleSweepPolicy : PtxPolicy::RleSweepPolicy {};
/******************************************************************************
* Utilities
******************************************************************************/
/**
* Initialize kernel dispatch configurations with the policies corresponding to the PTX assembly we will use
*/
template <typename KernelConfig>
CUB_RUNTIME_FUNCTION __forceinline__
static void InitConfigs(
int ptx_version,
KernelConfig& device_rle_config)
{
if (CUB_IS_DEVICE_CODE) {
#if CUB_INCLUDE_DEVICE_CODE
// We're on the device, so initialize the kernel dispatch configurations with the current PTX policy
device_rle_config.template Init<PtxRleSweepPolicy>();
#endif
}
else
{
#if CUB_INCLUDE_HOST_CODE
// We're on the host, so lookup and initialize the kernel dispatch configurations with the policies that match the device's PTX version
if (ptx_version >= 350)
{
device_rle_config.template Init<typename Policy350::RleSweepPolicy>();
}
else if (ptx_version >= 300)
{
device_rle_config.template Init<typename Policy300::RleSweepPolicy>();
}
else if (ptx_version >= 200)
{
device_rle_config.template Init<typename Policy200::RleSweepPolicy>();
}
else if (ptx_version >= 130)
{
device_rle_config.template Init<typename Policy130::RleSweepPolicy>();
}
else
{
device_rle_config.template Init<typename Policy100::RleSweepPolicy>();
}
#endif
}
}
/**
* Kernel kernel dispatch configuration. Mirrors the constants within AgentRlePolicyT.
*/
struct KernelConfig
{
int block_threads;
int items_per_thread;
BlockLoadAlgorithm load_policy;
bool store_warp_time_slicing;
BlockScanAlgorithm scan_algorithm;
template <typename AgentRlePolicyT>
CUB_RUNTIME_FUNCTION __forceinline__
void Init()
{
block_threads = AgentRlePolicyT::BLOCK_THREADS;
items_per_thread = AgentRlePolicyT::ITEMS_PER_THREAD;
load_policy = AgentRlePolicyT::LOAD_ALGORITHM;
store_warp_time_slicing = AgentRlePolicyT::STORE_WARP_TIME_SLICING;
scan_algorithm = AgentRlePolicyT::SCAN_ALGORITHM;
}
CUB_RUNTIME_FUNCTION __forceinline__
void Print()
{
printf("%d, %d, %d, %d, %d",
block_threads,
items_per_thread,
load_policy,
store_warp_time_slicing,
scan_algorithm);
}
};
/******************************************************************************
* Dispatch entrypoints
******************************************************************************/
/**
* Internal dispatch routine for computing a device-wide run-length-encode using the
* specified kernel functions.
*/
template <
typename DeviceScanInitKernelPtr, ///< Function type of cub::DeviceScanInitKernel
typename DeviceRleSweepKernelPtr> ///< Function type of cub::DeviceRleSweepKernelPtr
CUB_RUNTIME_FUNCTION __forceinline__
static cudaError_t Dispatch(
void* d_temp_storage, ///< [in] %Device-accessible allocation of temporary storage. When NULL, the required allocation size is written to \p temp_storage_bytes and no work is done.
size_t& temp_storage_bytes, ///< [in,out] Reference to size in bytes of \p d_temp_storage allocation
InputIteratorT d_in, ///< [in] Pointer to the input sequence of data items
OffsetsOutputIteratorT d_offsets_out, ///< [out] Pointer to the output sequence of run-offsets
LengthsOutputIteratorT d_lengths_out, ///< [out] Pointer to the output sequence of run-lengths
NumRunsOutputIteratorT d_num_runs_out, ///< [out] Pointer to the total number of runs encountered (i.e., length of \p d_offsets_out)
EqualityOpT equality_op, ///< [in] Equality operator for input items
OffsetT num_items, ///< [in] Total number of input items (i.e., length of \p d_in)
cudaStream_t stream, ///< [in] CUDA stream to launch kernels within. Default is stream<sub>0</sub>.
bool debug_synchronous, ///< [in] Whether or not to synchronize the stream after every kernel launch to check for errors. Also causes launch configurations to be printed to the console. Default is \p false.
int /*ptx_version*/, ///< [in] PTX version of dispatch kernels
DeviceScanInitKernelPtr device_scan_init_kernel, ///< [in] Kernel function pointer to parameterization of cub::DeviceScanInitKernel
DeviceRleSweepKernelPtr device_rle_sweep_kernel, ///< [in] Kernel function pointer to parameterization of cub::DeviceRleSweepKernel
KernelConfig device_rle_config) ///< [in] Dispatch parameters that match the policy that \p device_rle_sweep_kernel was compiled for
{
#ifndef CUB_RUNTIME_ENABLED
// Kernel launch not supported from this device
return CubDebug(cudaErrorNotSupported);
#else
cudaError error = cudaSuccess;
do
{
// Get device ordinal
int device_ordinal;
if (CubDebug(error = cudaGetDevice(&device_ordinal))) break;
// Get SM count
int sm_count;
if (CubDebug(error = cudaDeviceGetAttribute (&sm_count, cudaDevAttrMultiProcessorCount, device_ordinal))) break;
// Number of input tiles
int tile_size = device_rle_config.block_threads * device_rle_config.items_per_thread;
int num_tiles = (num_items + tile_size - 1) / tile_size;
// Specify temporary storage allocation requirements
size_t allocation_sizes[1];
if (CubDebug(error = ScanTileStateT::AllocationSize(num_tiles, allocation_sizes[0]))) break; // bytes needed for tile status descriptors
// Compute allocation pointers into the single storage blob (or compute the necessary size of the blob)
void* allocations[1] = {};
if (CubDebug(error = AliasTemporaries(d_temp_storage, temp_storage_bytes, allocations, allocation_sizes))) break;
if (d_temp_storage == NULL)
{
// Return if the caller is simply requesting the size of the storage allocation
break;
}
// Construct the tile status interface
ScanTileStateT tile_status;
if (CubDebug(error = tile_status.Init(num_tiles, allocations[0], allocation_sizes[0]))) break;
// Log device_scan_init_kernel configuration
int init_grid_size = CUB_MAX(1, (num_tiles + INIT_KERNEL_THREADS - 1) / INIT_KERNEL_THREADS);
if (debug_synchronous) _CubLog("Invoking device_scan_init_kernel<<<%d, %d, 0, %lld>>>()\n", init_grid_size, INIT_KERNEL_THREADS, (long long) stream);
// Invoke device_scan_init_kernel to initialize tile descriptors and queue descriptors
thrust::cuda_cub::launcher::triple_chevron(
init_grid_size, INIT_KERNEL_THREADS, 0, stream
).doit(device_scan_init_kernel,
tile_status,
num_tiles,
d_num_runs_out);
// Check for failure to launch
if (CubDebug(error = cudaPeekAtLastError())) break;
// Sync the stream if specified to flush runtime errors
if (debug_synchronous && (CubDebug(error = SyncStream(stream)))) break;
// Return if empty problem
if (num_items == 0)
break;
// Get SM occupancy for device_rle_sweep_kernel
int device_rle_kernel_sm_occupancy;
if (CubDebug(error = MaxSmOccupancy(
device_rle_kernel_sm_occupancy, // out
device_rle_sweep_kernel,
device_rle_config.block_threads))) 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 = ((unsigned int) num_tiles + max_dim_x - 1) / max_dim_x;
scan_grid_size.x = CUB_MIN(num_tiles, max_dim_x);
// Log device_rle_sweep_kernel configuration
if (debug_synchronous) _CubLog("Invoking device_rle_sweep_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, device_rle_config.block_threads, (long long) stream, device_rle_config.items_per_thread, device_rle_kernel_sm_occupancy);
// Invoke device_rle_sweep_kernel
thrust::cuda_cub::launcher::triple_chevron(
scan_grid_size, device_rle_config.block_threads, 0, stream
).doit(device_rle_sweep_kernel,
d_in,
d_offsets_out,
d_lengths_out,
d_num_runs_out,
tile_status,
equality_op,
num_items,
num_tiles);
// Check for failure to launch
if (CubDebug(error = cudaPeekAtLastError())) break;
// Sync the stream if specified to flush runtime errors
if (debug_synchronous && (CubDebug(error = SyncStream(stream)))) break;
}
while (0);
return error;
#endif // CUB_RUNTIME_ENABLED
}
/**
* Internal dispatch routine
*/
CUB_RUNTIME_FUNCTION __forceinline__
static cudaError_t Dispatch(
void* d_temp_storage, ///< [in] %Device-accessible allocation of temporary storage. When NULL, the required allocation size is written to \p temp_storage_bytes and no work is done.
size_t& temp_storage_bytes, ///< [in,out] Reference to size in bytes of \p d_temp_storage allocation
InputIteratorT d_in, ///< [in] Pointer to input sequence of data items
OffsetsOutputIteratorT d_offsets_out, ///< [out] Pointer to output sequence of run-offsets
LengthsOutputIteratorT d_lengths_out, ///< [out] Pointer to output sequence of run-lengths
NumRunsOutputIteratorT d_num_runs_out, ///< [out] Pointer to total number of runs (i.e., length of \p d_offsets_out)
EqualityOpT equality_op, ///< [in] Equality operator for input items
OffsetT num_items, ///< [in] Total number of input items (i.e., length of \p d_in)
cudaStream_t stream, ///< [in] <b>[optional]</b> CUDA stream to launch kernels within. Default is stream<sub>0</sub>.
bool debug_synchronous) ///< [in] <b>[optional]</b> Whether or not to synchronize the stream after every kernel launch to check for errors. Also causes launch configurations to be printed to the console. Default is \p false.
{
cudaError error = cudaSuccess;
do
{
// Get PTX version
int ptx_version = 0;
if (CubDebug(error = PtxVersion(ptx_version))) break;
// Get kernel kernel dispatch configurations
KernelConfig device_rle_config;
InitConfigs(ptx_version, device_rle_config);
// Dispatch
if (CubDebug(error = Dispatch(
d_temp_storage,
temp_storage_bytes,
d_in,
d_offsets_out,
d_lengths_out,
d_num_runs_out,
equality_op,
num_items,
stream,
debug_synchronous,
ptx_version,
DeviceCompactInitKernel<ScanTileStateT, NumRunsOutputIteratorT>,
DeviceRleSweepKernel<PtxRleSweepPolicy, InputIteratorT, OffsetsOutputIteratorT, LengthsOutputIteratorT, NumRunsOutputIteratorT, ScanTileStateT, EqualityOpT, OffsetT>,
device_rle_config))) break;
}
while (0);
return error;
}
};
} // CUB namespace
CUB_NS_POSTFIX // Optional outer namespace(s)
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