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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::DeviceScan provides device-wide, parallel operations for computing a prefix scan across a sequence of data items residing within device-accessible memory.
*/
#pragma once
#include <stdio.h>
#include <iterator>
#include "dispatch/dispatch_scan.cuh"
#include "../util_namespace.cuh"
/// Optional outer namespace(s)
CUB_NS_PREFIX
/// CUB namespace
namespace cub {
/**
* \brief DeviceScan provides device-wide, parallel operations for computing a prefix scan across a sequence of data items residing within device-accessible memory. 
* \ingroup SingleModule
*
* \par Overview
* Given a sequence of input elements and a binary reduction operator, a [<em>prefix scan</em>](http://en.wikipedia.org/wiki/Prefix_sum)
* produces an output sequence where each element is computed to be the reduction
* of the elements occurring earlier in the input sequence. <em>Prefix sum</em>
* connotes a prefix scan with the addition operator. The term \em inclusive indicates
* that the <em>i</em><sup>th</sup> output reduction incorporates the <em>i</em><sup>th</sup> input.
* The term \em exclusive indicates the <em>i</em><sup>th</sup> input is not incorporated into
* the <em>i</em><sup>th</sup> output reduction.
*
* \par
* As of CUB 1.0.1 (2013), CUB's device-wide scan APIs have implemented our <em>"decoupled look-back"</em> algorithm
* for performing global prefix scan with only a single pass through the
* input data, as described in our 2016 technical report [1]. The central
* idea is to leverage a small, constant factor of redundant work in order to overlap the latencies
* of global prefix propagation with local computation. As such, our algorithm requires only
* ~2<em>n</em> data movement (<em>n</em> inputs are read, <em>n</em> outputs are written), and typically
* proceeds at "memcpy" speeds.
*
* \par
* [1] [Duane Merrill and Michael Garland. "Single-pass Parallel Prefix Scan with Decoupled Look-back", <em>NVIDIA Technical Report NVR-2016-002</em>, 2016.](https://research.nvidia.com/publication/single-pass-parallel-prefix-scan-decoupled-look-back)
*
* \par Usage Considerations
* \cdp_class{DeviceScan}
*
* \par Performance
* \linear_performance{prefix scan}
*
* \par
* The following chart illustrates DeviceScan::ExclusiveSum
* performance across different CUDA architectures for \p int32 keys.
* \plots_below
*
* \image html scan_int32.png
*
*/
struct DeviceScan
{
/******************************************************************//**
*
ame Exclusive scans
*********************************************************************/
//@{
/**
* \brief Computes a device-wide exclusive prefix sum. The value of 0 is applied as the initial value, and is assigned to *d_out.
*
* \par
* - Supports non-commutative sum operators.
* - Provides "run-to-run" determinism for pseudo-associative reduction
* (e.g., addition of floating point types) on the same GPU device.
* However, results for pseudo-associative reduction may be inconsistent
* from one device to a another device of a different compute-capability
* because CUB can employ different tile-sizing for different architectures.
* - \devicestorage
*
* \par Performance
* The following charts illustrate saturated exclusive sum performance across different
* CUDA architectures for \p int32 and \p int64 items, respectively.
*
* \image html scan_int32.png
* \image html scan_int64.png
*
* \par Snippet
* The code snippet below illustrates the exclusive prefix sum of an \p int device vector.
* \par
* \code
* #include <cub/cub.cuh> // or equivalently <cub/device/device_scan.cuh>
*
* // Declare, allocate, and initialize device-accessible pointers for input and output
* int num_items; // e.g., 7
* int *d_in; // e.g., [8, 6, 7, 5, 3, 0, 9]
* int *d_out; // e.g., [ , , , , , , ]
* ...
*
* // Determine temporary device storage requirements
* void *d_temp_storage = NULL;
* size_t temp_storage_bytes = 0;
* cub::DeviceScan::ExclusiveSum(d_temp_storage, temp_storage_bytes, d_in, d_out, num_items);
*
* // Allocate temporary storage
* cudaMalloc(&d_temp_storage, temp_storage_bytes);
*
* // Run exclusive prefix sum
* cub::DeviceScan::ExclusiveSum(d_temp_storage, temp_storage_bytes, d_in, d_out, num_items);
*
* // d_out s<-- [0, 8, 14, 21, 26, 29, 29]
*
* \endcode
*
* \tparam InputIteratorT <b>[inferred]</b> Random-access input iterator type for reading scan inputs \iterator
* \tparam OutputIteratorT <b>[inferred]</b> Random-access output iterator type for writing scan outputs \iterator
*/
template <
typename InputIteratorT,
typename OutputIteratorT>
CUB_RUNTIME_FUNCTION
static cudaError_t ExclusiveSum(
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
OutputIteratorT d_out, ///< [out] Pointer to the output sequence of data items
int num_items, ///< [in] Total number of input items (i.e., the length of \p d_in)
cudaStream_t stream = 0, ///< [in] <b>[optional]</b> CUDA stream to launch kernels within. Default is stream<sub>0</sub>.
bool debug_synchronous = false) ///< [in] <b>[optional]</b> Whether or not to synchronize the stream after every kernel launch to check for errors. May cause significant slowdown. Default is \p false.
{
// Signed integer type for global offsets
typedef int OffsetT;
// The output value type
typedef typename If<(Equals<typename std::iterator_traits<OutputIteratorT>::value_type, void>::VALUE), // OutputT = (if output iterator's value type is void) ?
typename std::iterator_traits<InputIteratorT>::value_type, // ... then the input iterator's value type,
typename std::iterator_traits<OutputIteratorT>::value_type>::Type OutputT; // ... else the output iterator's value type
// Initial value
OutputT init_value = 0;
return DispatchScan<InputIteratorT, OutputIteratorT, Sum, OutputT, OffsetT>::Dispatch(
d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
Sum(),
init_value,
num_items,
stream,
debug_synchronous);
}
/**
* \brief Computes a device-wide exclusive prefix scan using the specified binary \p scan_op functor. The \p init_value value is applied as the initial value, and is assigned to *d_out.
*
* \par
* - Supports non-commutative scan operators.
* - Provides "run-to-run" determinism for pseudo-associative reduction
* (e.g., addition of floating point types) on the same GPU device.
* However, results for pseudo-associative reduction may be inconsistent
* from one device to a another device of a different compute-capability
* because CUB can employ different tile-sizing for different architectures.
* - \devicestorage
*
* \par Snippet
* The code snippet below illustrates the exclusive prefix min-scan of an \p int device vector
* \par
* \code
* #include <cub/cub.cuh> // or equivalently <cub/device/device_scan.cuh>
*
* // CustomMin functor
* struct CustomMin
* {
* template <typename T>
* CUB_RUNTIME_FUNCTION __forceinline__
* T operator()(const T &a, const T &b) const {
* return (b < a) ? b : a;
* }
* };
*
* // Declare, allocate, and initialize device-accessible pointers for input and output
* int num_items; // e.g., 7
* int *d_in; // e.g., [8, 6, 7, 5, 3, 0, 9]
* int *d_out; // e.g., [ , , , , , , ]
* CustomMin min_op
* ...
*
* // Determine temporary device storage requirements for exclusive prefix scan
* void *d_temp_storage = NULL;
* size_t temp_storage_bytes = 0;
* cub::DeviceScan::ExclusiveScan(d_temp_storage, temp_storage_bytes, d_in, d_out, min_op, (int) MAX_INT, num_items);
*
* // Allocate temporary storage for exclusive prefix scan
* cudaMalloc(&d_temp_storage, temp_storage_bytes);
*
* // Run exclusive prefix min-scan
* cub::DeviceScan::ExclusiveScan(d_temp_storage, temp_storage_bytes, d_in, d_out, min_op, (int) MAX_INT, num_items);
*
* // d_out <-- [2147483647, 8, 6, 6, 5, 3, 0]
*
* \endcode
*
* \tparam InputIteratorT <b>[inferred]</b> Random-access input iterator type for reading scan inputs \iterator
* \tparam OutputIteratorT <b>[inferred]</b> Random-access output iterator type for writing scan outputs \iterator
* \tparam ScanOp <b>[inferred]</b> Binary scan functor type having member <tt>T operator()(const T &a, const T &b)</tt>
* \tparam Identity <b>[inferred]</b> Type of the \p identity value used Binary scan functor type having member <tt>T operator()(const T &a, const T &b)</tt>
*/
template <
typename InputIteratorT,
typename OutputIteratorT,
typename ScanOpT,
typename InitValueT>
CUB_RUNTIME_FUNCTION
static cudaError_t ExclusiveScan(
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
OutputIteratorT d_out, ///< [out] Pointer to the output sequence of data items
ScanOpT scan_op, ///< [in] Binary scan functor
InitValueT init_value, ///< [in] Initial value to seed the exclusive scan (and is assigned to *d_out)
int num_items, ///< [in] Total number of input items (i.e., the length of \p d_in)
cudaStream_t stream = 0, ///< [in] <b>[optional]</b> CUDA stream to launch kernels within. Default is stream<sub>0</sub>.
bool debug_synchronous = false) ///< [in] <b>[optional]</b> Whether or not to synchronize the stream after every kernel launch to check for errors. May cause significant slowdown. Default is \p false.
{
// Signed integer type for global offsets
typedef int OffsetT;
return DispatchScan<InputIteratorT, OutputIteratorT, ScanOpT, InitValueT, OffsetT>::Dispatch(
d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
scan_op,
init_value,
num_items,
stream,
debug_synchronous);
}
//@} end member group
/******************************************************************//**
*
ame Inclusive scans
*********************************************************************/
//@{
/**
* \brief Computes a device-wide inclusive prefix sum.
*
* \par
* - Supports non-commutative sum operators.
* - Provides "run-to-run" determinism for pseudo-associative reduction
* (e.g., addition of floating point types) on the same GPU device.
* However, results for pseudo-associative reduction may be inconsistent
* from one device to a another device of a different compute-capability
* because CUB can employ different tile-sizing for different architectures.
* - \devicestorage
*
* \par Snippet
* The code snippet below illustrates the inclusive prefix sum of an \p int device vector.
* \par
* \code
* #include <cub/cub.cuh> // or equivalently <cub/device/device_scan.cuh>
*
* // Declare, allocate, and initialize device-accessible pointers for input and output
* int num_items; // e.g., 7
* int *d_in; // e.g., [8, 6, 7, 5, 3, 0, 9]
* int *d_out; // e.g., [ , , , , , , ]
* ...
*
* // Determine temporary device storage requirements for inclusive prefix sum
* void *d_temp_storage = NULL;
* size_t temp_storage_bytes = 0;
* cub::DeviceScan::InclusiveSum(d_temp_storage, temp_storage_bytes, d_in, d_out, num_items);
*
* // Allocate temporary storage for inclusive prefix sum
* cudaMalloc(&d_temp_storage, temp_storage_bytes);
*
* // Run inclusive prefix sum
* cub::DeviceScan::InclusiveSum(d_temp_storage, temp_storage_bytes, d_in, d_out, num_items);
*
* // d_out <-- [8, 14, 21, 26, 29, 29, 38]
*
* \endcode
*
* \tparam InputIteratorT <b>[inferred]</b> Random-access input iterator type for reading scan inputs \iterator
* \tparam OutputIteratorT <b>[inferred]</b> Random-access output iterator type for writing scan outputs \iterator
*/
template <
typename InputIteratorT,
typename OutputIteratorT>
CUB_RUNTIME_FUNCTION
static cudaError_t InclusiveSum(
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
OutputIteratorT d_out, ///< [out] Pointer to the output sequence of data items
int num_items, ///< [in] Total number of input items (i.e., the length of \p d_in)
cudaStream_t stream = 0, ///< [in] <b>[optional]</b> CUDA stream to launch kernels within. Default is stream<sub>0</sub>.
bool debug_synchronous = false) ///< [in] <b>[optional]</b> Whether or not to synchronize the stream after every kernel launch to check for errors. May cause significant slowdown. Default is \p false.
{
// Signed integer type for global offsets
typedef int OffsetT;
return DispatchScan<InputIteratorT, OutputIteratorT, Sum, NullType, OffsetT>::Dispatch(
d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
Sum(),
NullType(),
num_items,
stream,
debug_synchronous);
}
/**
* \brief Computes a device-wide inclusive prefix scan using the specified binary \p scan_op functor.
*
* \par
* - Supports non-commutative scan operators.
* - Provides "run-to-run" determinism for pseudo-associative reduction
* (e.g., addition of floating point types) on the same GPU device.
* However, results for pseudo-associative reduction may be inconsistent
* from one device to a another device of a different compute-capability
* because CUB can employ different tile-sizing for different architectures.
* - \devicestorage
*
* \par Snippet
* The code snippet below illustrates the inclusive prefix min-scan of an \p int device vector.
* \par
* \code
* #include <cub/cub.cuh> // or equivalently <cub/device/device_scan.cuh>
*
* // CustomMin functor
* struct CustomMin
* {
* template <typename T>
* CUB_RUNTIME_FUNCTION __forceinline__
* T operator()(const T &a, const T &b) const {
* return (b < a) ? b : a;
* }
* };
*
* // Declare, allocate, and initialize device-accessible pointers for input and output
* int num_items; // e.g., 7
* int *d_in; // e.g., [8, 6, 7, 5, 3, 0, 9]
* int *d_out; // e.g., [ , , , , , , ]
* CustomMin min_op;
* ...
*
* // Determine temporary device storage requirements for inclusive prefix scan
* void *d_temp_storage = NULL;
* size_t temp_storage_bytes = 0;
* cub::DeviceScan::InclusiveScan(d_temp_storage, temp_storage_bytes, d_in, d_out, min_op, num_items);
*
* // Allocate temporary storage for inclusive prefix scan
* cudaMalloc(&d_temp_storage, temp_storage_bytes);
*
* // Run inclusive prefix min-scan
* cub::DeviceScan::InclusiveScan(d_temp_storage, temp_storage_bytes, d_in, d_out, min_op, num_items);
*
* // d_out <-- [8, 6, 6, 5, 3, 0, 0]
*
* \endcode
*
* \tparam InputIteratorT <b>[inferred]</b> Random-access input iterator type for reading scan inputs \iterator
* \tparam OutputIteratorT <b>[inferred]</b> Random-access output iterator type for writing scan outputs \iterator
* \tparam ScanOp <b>[inferred]</b> Binary scan functor type having member <tt>T operator()(const T &a, const T &b)</tt>
*/
template <
typename InputIteratorT,
typename OutputIteratorT,
typename ScanOpT>
CUB_RUNTIME_FUNCTION
static cudaError_t InclusiveScan(
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
OutputIteratorT d_out, ///< [out] Pointer to the output sequence of data items
ScanOpT scan_op, ///< [in] Binary scan functor
int num_items, ///< [in] Total number of input items (i.e., the length of \p d_in)
cudaStream_t stream = 0, ///< [in] <b>[optional]</b> CUDA stream to launch kernels within. Default is stream<sub>0</sub>.
bool debug_synchronous = false) ///< [in] <b>[optional]</b> Whether or not to synchronize the stream after every kernel launch to check for errors. May cause significant slowdown. Default is \p false.
{
// Signed integer type for global offsets
typedef int OffsetT;
return DispatchScan<InputIteratorT, OutputIteratorT, ScanOpT, NullType, OffsetT>::Dispatch(
d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
scan_op,
NullType(),
num_items,
stream,
debug_synchronous);
}
//@} end member group
};
/**
* \example example_device_scan.cu
*/
} // CUB namespace
CUB_NS_POSTFIX // Optional outer namespace(s)
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