thrust / install /include /cub /device /device_scan.cuh
camenduru's picture
thanks to nvidia ❤
0dc1b04
/******************************************************************************
* Copyright (c) 2011, Duane Merrill. All rights reserved.
* Copyright (c) 2011-2022, 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 <cub/config.cuh>
#include <cub/device/dispatch/dispatch_scan.cuh>
#include <cub/device/dispatch/dispatch_scan_by_key.cuh>
#include <cub/thread/thread_operators.cuh>
#include <cub/util_deprecated.cuh>
CUB_NAMESPACE_BEGIN
/**
* @brief DeviceScan provides device-wide, parallel operations for computing a
* prefix scan across a sequence of data items residing within
* device-accessible memory. ![](device_scan.png)
*
* @ingroup SingleModule
*
* @par Overview
* Given a sequence of input elements and a binary reduction operator, a
* [*prefix scan*](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. *Prefix sum* connotes a prefix scan
* with the addition operator. The term *inclusive* indicates that the
* *i*<sup>th</sup> output reduction incorporates the *i*<sup>th</sup> input.
* The term *exclusive* indicates the *i*<sup>th</sup> input is not
* incorporated into the *i*<sup>th</sup> output reduction. When the input and
* output sequences are the same, the scan is performed in-place.
*
* @par
* As of CUB 1.0.1 (2013), CUB's device-wide scan APIs have implemented our
* *"decoupled look-back"* 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*n* data movement (*n* inputs are read, *n* outputs are written), and
* typically proceeds at "memcpy" speeds. Our algorithm supports inplace
* operations.
*
* @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 `int32` keys.
* @plots_below
*
* @image html scan_int32.png
*
*/
struct DeviceScan
{
/******************************************************************//**
* \name 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.
* - Results are not deterministic for pseudo-associative operators (e.g.,
* addition of floating-point types). Results for pseudo-associative
* operators may vary from run to run. Additional details can be found in
* the [decoupled look-back] description.
* - When `d_in` and `d_out` are equal, the scan is performed in-place. The
* range `[d_in, d_in + num_items)` and `[d_out, d_out + num_items)`
* shall not overlap in any other way.
* - @devicestorage
*
* @par Performance
* The following charts illustrate saturated exclusive sum performance across
* different CUDA architectures for `int32` and `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 `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 <-- [0, 8, 14, 21, 26, 29, 29]
*
* @endcode
*
* @tparam InputIteratorT
* **[inferred]** Random-access input iterator type for reading scan
* inputs \iterator
*
* @tparam OutputIteratorT
* **[inferred]** Random-access output iterator type for writing scan
* outputs \iterator
*
* @param[in] d_temp_storage
* Device-accessible allocation of temporary storage. When `nullptr`, the
* required allocation size is written to `temp_storage_bytes` and no
* work is done.
*
* @param[in,out] temp_storage_bytes
* Reference to size in bytes of `d_temp_storage` allocation
*
* @param[in] d_in
* Random-access iterator to the input sequence of data items
*
* @param[out] d_out
* Random-access iterator to the output sequence of data items
*
* @param[in] num_items
* Total number of input items (i.e., the length of `d_in`)
*
* @param[in] stream
* **[optional]** CUDA stream to launch kernels within.
* Default is stream<sub>0</sub>.
*
* [decoupled look-back]: https://research.nvidia.com/publication/single-pass-parallel-prefix-scan-decoupled-look-back
*/
template <typename InputIteratorT, typename OutputIteratorT>
CUB_RUNTIME_FUNCTION static cudaError_t
ExclusiveSum(void *d_temp_storage,
size_t &temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
int num_items,
cudaStream_t stream = 0)
{
// Signed integer type for global offsets
using OffsetT = int;
using InitT = cub::detail::value_t<InputIteratorT>;
// Initial value
InitT init_value{};
return DispatchScan<
InputIteratorT, OutputIteratorT, Sum, detail::InputValue<InitT>,
OffsetT>::Dispatch(d_temp_storage, temp_storage_bytes, d_in, d_out,
Sum(), detail::InputValue<InitT>(init_value),
num_items, stream);
}
template <typename InputIteratorT, typename OutputIteratorT>
CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED
CUB_RUNTIME_FUNCTION static cudaError_t
ExclusiveSum(void *d_temp_storage,
size_t &temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
int num_items,
cudaStream_t stream,
bool debug_synchronous)
{
CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG
return ExclusiveSum<InputIteratorT, OutputIteratorT>(d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
num_items,
stream);
}
/**
* @brief Computes a device-wide exclusive prefix sum in-place. The value of
* `0` is applied as the initial value, and is assigned to `*d_data`.
*
* @par
* - Supports non-commutative sum operators.
* - Results are not deterministic for pseudo-associative operators (e.g.,
* addition of floating-point types). Results for pseudo-associative
* operators may vary from run to run. Additional details can be found in
* the [decoupled look-back] description.
* - @devicestorage
*
* @par Performance
* The following charts illustrate saturated exclusive sum performance across
* different CUDA architectures for `int32` and `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 `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_data; // e.g., [8, 6, 7, 5, 3, 0, 9]
* ...
*
* // 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_data, 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_data, num_items);
*
* // d_data <-- [0, 8, 14, 21, 26, 29, 29]
*
* @endcode
*
* @tparam IteratorT
* **[inferred]** Random-access iterator type for reading scan
* inputs and wrigin scan outputs
*
* @param[in] d_temp_storage
* Device-accessible allocation of temporary storage. When `nullptr`, the
* required allocation size is written to `temp_storage_bytes` and no
* work is done.
*
* @param[in,out] temp_storage_bytes
* Reference to size in bytes of `d_temp_storage` allocation
*
* @param[in,out] d_data
* Random-access iterator to the sequence of data items
*
* @param[in] num_items
* Total number of input items (i.e., the length of `d_in`)
*
* @param[in] stream
* **[optional]** CUDA stream to launch kernels within.
* Default is stream<sub>0</sub>.
*
* [decoupled look-back]: https://research.nvidia.com/publication/single-pass-parallel-prefix-scan-decoupled-look-back
*/
template <typename IteratorT>
CUB_RUNTIME_FUNCTION static cudaError_t
ExclusiveSum(void *d_temp_storage,
size_t &temp_storage_bytes,
IteratorT d_data,
int num_items,
cudaStream_t stream = 0)
{
return ExclusiveSum(d_temp_storage,
temp_storage_bytes,
d_data,
d_data,
num_items,
stream);
}
template <typename IteratorT>
CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED
CUB_RUNTIME_FUNCTION static cudaError_t
ExclusiveSum(void *d_temp_storage,
size_t &temp_storage_bytes,
IteratorT d_data,
int num_items,
cudaStream_t stream,
bool debug_synchronous)
{
CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG
return ExclusiveSum<IteratorT>(d_temp_storage,
temp_storage_bytes,
d_data,
num_items,
stream);
}
/**
* @brief Computes a device-wide exclusive prefix scan using the specified
* binary `scan_op` functor. The `init_value` value is applied as
* the initial value, and is assigned to `*d_out`.
*
* @par
* - Supports non-commutative scan operators.
* - Results are not deterministic for pseudo-associative operators (e.g.,
* addition of floating-point types). Results for pseudo-associative
* operators may vary from run to run. Additional details can be found in
* the [decoupled look-back] description.
* - When `d_in` and `d_out` are equal, the scan is performed in-place. The
* range `[d_in, d_in + num_items)` and `[d_out, d_out + num_items)`
* shall not overlap in any other way.
* - @devicestorage
*
* @par Snippet
* The code snippet below illustrates the exclusive prefix min-scan of an
* `int` device vector
* @par
* @code
* #include <cub/cub.cuh> // or equivalently <cub/device/device_scan.cuh>
* #include <climits> // for INT_MAX
*
* // 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) INT_MAX, 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) INT_MAX, num_items);
*
* // d_out <-- [2147483647, 8, 6, 6, 5, 3, 0]
*
* @endcode
*
* @tparam InputIteratorT
* **[inferred]** Random-access input iterator type for reading scan
* inputs \iterator
*
* @tparam OutputIteratorT
* **[inferred]** Random-access output iterator type for writing scan
* outputs \iterator
*
* @tparam ScanOp
* **[inferred]** Binary scan functor type having member
* `T operator()(const T &a, const T &b)`
*
* @tparam InitValueT
* **[inferred]** Type of the `init_value` used Binary scan functor type
* having member `T operator()(const T &a, const T &b)`
*
* @param[in] d_temp_storage
* Device-accessible allocation of temporary storage. When `nullptr`, the
* required allocation size is written to `temp_storage_bytes` and no
* work is done.
*
* @param[in,out] temp_storage_bytes
* Reference to size in bytes of `d_temp_storage` allocation
*
* @param[in] d_in
* Random-access iterator to the input sequence of data items
*
* @param[out] d_out
* Random-access iterator to the output sequence of data items
*
* @param[in] scan_op
* Binary scan functor
*
* @param[in] init_value
* Initial value to seed the exclusive scan (and is assigned to *d_out)
*
* @param[in] num_items
* Total number of input items (i.e., the length of \p d_in)
*
* @param[in] stream
* **[optional]** CUDA stream to launch kernels within. Default is
* stream<sub>0</sub>.
*
* [decoupled look-back]: https://research.nvidia.com/publication/single-pass-parallel-prefix-scan-decoupled-look-back
*/
template <typename InputIteratorT,
typename OutputIteratorT,
typename ScanOpT,
typename InitValueT>
CUB_RUNTIME_FUNCTION static cudaError_t
ExclusiveScan(void *d_temp_storage,
size_t &temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
ScanOpT scan_op,
InitValueT init_value,
int num_items,
cudaStream_t stream = 0)
{
// Signed integer type for global offsets
using OffsetT = int ;
return DispatchScan<InputIteratorT,
OutputIteratorT,
ScanOpT,
detail::InputValue<InitValueT>,
OffsetT>::Dispatch(d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
scan_op,
detail::InputValue<InitValueT>(
init_value),
num_items,
stream);
}
template <typename InputIteratorT,
typename OutputIteratorT,
typename ScanOpT,
typename InitValueT>
CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED
CUB_RUNTIME_FUNCTION static cudaError_t
ExclusiveScan(void *d_temp_storage,
size_t &temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
ScanOpT scan_op,
InitValueT init_value,
int num_items,
cudaStream_t stream,
bool debug_synchronous)
{
CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG
return ExclusiveScan<InputIteratorT, OutputIteratorT, ScanOpT, InitValueT>(
d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
scan_op,
init_value,
num_items,
stream);
}
/**
* @brief Computes a device-wide exclusive prefix scan using the specified
* binary `scan_op` functor. The `init_value` value is applied as
* the initial value, and is assigned to `*d_data`.
*
* @par
* - Supports non-commutative scan operators.
* - Results are not deterministic for pseudo-associative operators (e.g.,
* addition of floating-point types). Results for pseudo-associative
* operators may vary from run to run. Additional details can be found in
* the [decoupled look-back] description.
* - @devicestorage
*
* @par Snippet
* The code snippet below illustrates the exclusive prefix min-scan of an
* `int` device vector
* @par
* @code
* #include <cub/cub.cuh> // or equivalently <cub/device/device_scan.cuh>
* #include <climits> // for INT_MAX
*
* // 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_data; // e.g., [8, 6, 7, 5, 3, 0, 9]
* 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_data, min_op, (int) INT_MAX, 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_data, min_op, (int) INT_MAX, num_items);
*
* // d_data <-- [2147483647, 8, 6, 6, 5, 3, 0]
*
* @endcode
*
* @tparam IteratorT
* **[inferred]** Random-access input iterator type for reading scan
* inputs and writing scan outputs
*
* @tparam ScanOp
* **[inferred]** Binary scan functor type having member
* `T operator()(const T &a, const T &b)`
*
* @tparam InitValueT
* **[inferred]** Type of the `init_value` used Binary scan functor type
* having member `T operator()(const T &a, const T &b)`
*
* @param[in] d_temp_storage
* Device-accessible allocation of temporary storage. When `nullptr`, the
* required allocation size is written to `temp_storage_bytes` and no
* work is done.
*
* @param[in,out] temp_storage_bytes
* Reference to size in bytes of `d_temp_storage` allocation
*
* @param[in,out] d_data
* Random-access iterator to the sequence of data items
*
* @param[in] scan_op
* Binary scan functor
*
* @param[in] init_value
* Initial value to seed the exclusive scan (and is assigned to *d_out)
*
* @param[in] num_items
* Total number of input items (i.e., the length of \p d_in)
*
* @param[in] stream
* **[optional]** CUDA stream to launch kernels within. Default is
* stream<sub>0</sub>.
*
* [decoupled look-back]: https://research.nvidia.com/publication/single-pass-parallel-prefix-scan-decoupled-look-back
*/
template <typename IteratorT,
typename ScanOpT,
typename InitValueT>
CUB_RUNTIME_FUNCTION static cudaError_t
ExclusiveScan(void *d_temp_storage,
size_t &temp_storage_bytes,
IteratorT d_data,
ScanOpT scan_op,
InitValueT init_value,
int num_items,
cudaStream_t stream = 0)
{
return ExclusiveScan(d_temp_storage,
temp_storage_bytes,
d_data,
d_data,
scan_op,
init_value,
num_items,
stream);
}
template <typename IteratorT,
typename ScanOpT,
typename InitValueT>
CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED
CUB_RUNTIME_FUNCTION static cudaError_t
ExclusiveScan(void *d_temp_storage,
size_t &temp_storage_bytes,
IteratorT d_data,
ScanOpT scan_op,
InitValueT init_value,
int num_items,
cudaStream_t stream,
bool debug_synchronous)
{
CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG
return ExclusiveScan<IteratorT, ScanOpT, InitValueT>(d_temp_storage,
temp_storage_bytes,
d_data,
scan_op,
init_value,
num_items,
stream);
}
/**
* @brief Computes a device-wide exclusive prefix scan using the specified
* binary `scan_op` functor. The `init_value` value is provided as
* a future value.
*
* @par
* - Supports non-commutative scan operators.
* - Results are not deterministic for pseudo-associative operators (e.g.,
* addition of floating-point types). Results for pseudo-associative
* operators may vary from run to run. Additional details can be found in
* the [decoupled look-back] description.
* - When `d_in` and `d_out` are equal, the scan is performed in-place. The
* range `[d_in, d_in + num_items)` and `[d_out, d_out + num_items)`
* shall not overlap in any other way.
* - @devicestorage
*
* @par Snippet
* The code snippet below illustrates the exclusive prefix min-scan of an
* `int` device vector
* @par
* @code
* #include <cub/cub.cuh> // or equivalently <cub/device/device_scan.cuh>
* #include <climits> // for INT_MAX
*
* // 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., [ , , , , , , ]
* int *d_init_iter; // e.g., INT_MAX
* CustomMin min_op;
*
* auto future_init_value =
* cub::FutureValue<InitialValueT, IterT>(d_init_iter);
*
* ...
*
* // 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, future_init_value, 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, future_init_value, num_items);
*
* // d_out <-- [2147483647, 8, 6, 6, 5, 3, 0]
*
* @endcode
*
* @tparam InputIteratorT
* **[inferred]** Random-access input iterator type for reading scan
* inputs \iterator
*
* @tparam OutputIteratorT
* **[inferred]** Random-access output iterator type for writing scan
* outputs \iterator
*
* @tparam ScanOp
* **[inferred]** Binary scan functor type having member
* `T operator()(const T &a, const T &b)`
*
* @tparam InitValueT
* **[inferred]** Type of the `init_value` used Binary scan functor type
* having member `T operator()(const T &a, const T &b)`
*
* @param[in] d_temp_storage
* Device-accessible allocation of temporary storage. When `nullptr`, the
* required allocation size is written to `temp_storage_bytes` and no work
* is done.
*
* @param[in,out] temp_storage_bytes
* Reference to size in bytes of \p d_temp_storage allocation
*
* @param[in] d_in
* Pointer to the input sequence of data items
*
* @param[out] d_out
* Pointer to the output sequence of data items
*
* @param[in] scan_op
* Binary scan functor
*
* @param[in] init_value
* Initial value to seed the exclusive scan (and is assigned to `*d_out`)
*
* @param[in] num_items
* Total number of input items (i.e., the length of `d_in`)
*
* @param[in] stream
* **[optional]** CUDA stream to launch kernels within.
* Default is stream<sub>0</sub>.
*
* [decoupled look-back]: https://research.nvidia.com/publication/single-pass-parallel-prefix-scan-decoupled-look-back
*/
template <typename InputIteratorT,
typename OutputIteratorT,
typename ScanOpT,
typename InitValueT,
typename InitValueIterT = InitValueT *>
CUB_RUNTIME_FUNCTION static cudaError_t
ExclusiveScan(void *d_temp_storage,
size_t &temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
ScanOpT scan_op,
FutureValue<InitValueT, InitValueIterT> init_value,
int num_items,
cudaStream_t stream = 0)
{
// Signed integer type for global offsets
using OffsetT = int;
return DispatchScan<InputIteratorT,
OutputIteratorT,
ScanOpT,
detail::InputValue<InitValueT>,
OffsetT>::Dispatch(d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
scan_op,
detail::InputValue<InitValueT>(
init_value),
num_items,
stream);
}
template <typename InputIteratorT,
typename OutputIteratorT,
typename ScanOpT,
typename InitValueT,
typename InitValueIterT = InitValueT *>
CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED
CUB_RUNTIME_FUNCTION static cudaError_t
ExclusiveScan(void *d_temp_storage,
size_t &temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
ScanOpT scan_op,
FutureValue<InitValueT, InitValueIterT> init_value,
int num_items,
cudaStream_t stream,
bool debug_synchronous)
{
CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG
return ExclusiveScan<InputIteratorT,
OutputIteratorT,
ScanOpT,
InitValueT,
InitValueIterT>(d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
scan_op,
init_value,
num_items,
stream);
}
/**
* @brief Computes a device-wide exclusive prefix scan using the specified
* binary `scan_op` functor. The `init_value` value is provided as
* a future value.
*
* @par
* - Supports non-commutative scan operators.
* - Results are not deterministic for pseudo-associative operators (e.g.,
* addition of floating-point types). Results for pseudo-associative
* operators may vary from run to run. Additional details can be found in
* the [decoupled look-back] description.
* - @devicestorage
*
* @par Snippet
* The code snippet below illustrates the exclusive prefix min-scan of an
* `int` device vector
* @par
* @code
* #include <cub/cub.cuh> // or equivalently <cub/device/device_scan.cuh>
* #include <climits> // for INT_MAX
*
* // 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_data; // e.g., [8, 6, 7, 5, 3, 0, 9]
* int *d_init_iter; // e.g., INT_MAX
* CustomMin min_op;
*
* auto future_init_value =
* cub::FutureValue<InitialValueT, IterT>(d_init_iter);
*
* ...
*
* // 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_data, min_op, future_init_value, 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_data, min_op, future_init_value, num_items);
*
* // d_data <-- [2147483647, 8, 6, 6, 5, 3, 0]
*
* @endcode
*
* @tparam IteratorT
* **[inferred]** Random-access input iterator type for reading scan
* inputs and writing scan outputs
*
* @tparam ScanOp
* **[inferred]** Binary scan functor type having member
* `T operator()(const T &a, const T &b)`
*
* @tparam InitValueT
* **[inferred]** Type of the `init_value` used Binary scan functor type
* having member `T operator()(const T &a, const T &b)`
*
* @param[in] d_temp_storage
* Device-accessible allocation of temporary storage. When `nullptr`, the
* required allocation size is written to `temp_storage_bytes` and no work
* is done.
*
* @param[in,out] temp_storage_bytes
* Reference to size in bytes of \p d_temp_storage allocation
*
* @param[in,out] d_data
* Pointer to the sequence of data items
*
* @param[in] scan_op
* Binary scan functor
*
* @param[in] init_value
* Initial value to seed the exclusive scan (and is assigned to `*d_out`)
*
* @param[in] num_items
* Total number of input items (i.e., the length of `d_in`)
*
* @param[in] stream
* **[optional]** CUDA stream to launch kernels within.
* Default is stream<sub>0</sub>.
*
* [decoupled look-back]: https://research.nvidia.com/publication/single-pass-parallel-prefix-scan-decoupled-look-back
*/
template <typename IteratorT,
typename ScanOpT,
typename InitValueT,
typename InitValueIterT = InitValueT *>
CUB_RUNTIME_FUNCTION static cudaError_t
ExclusiveScan(void *d_temp_storage,
size_t &temp_storage_bytes,
IteratorT d_data,
ScanOpT scan_op,
FutureValue<InitValueT, InitValueIterT> init_value,
int num_items,
cudaStream_t stream = 0)
{
return ExclusiveScan(d_temp_storage,
temp_storage_bytes,
d_data,
d_data,
scan_op,
init_value,
num_items,
stream);
}
template <typename IteratorT,
typename ScanOpT,
typename InitValueT,
typename InitValueIterT = InitValueT *>
CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED
CUB_RUNTIME_FUNCTION static cudaError_t
ExclusiveScan(void *d_temp_storage,
size_t &temp_storage_bytes,
IteratorT d_data,
ScanOpT scan_op,
FutureValue<InitValueT, InitValueIterT> init_value,
int num_items,
cudaStream_t stream,
bool debug_synchronous)
{
CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG
return ExclusiveScan<IteratorT, ScanOpT, InitValueT, InitValueIterT>(
d_temp_storage,
temp_storage_bytes,
d_data,
scan_op,
init_value,
num_items,
stream);
}
//@} end member group
/******************************************************************//**
* @name Inclusive scans
*********************************************************************/
//@{
/**
* @brief Computes a device-wide inclusive prefix sum.
*
* @par
* - Supports non-commutative sum operators.
* - Results are not deterministic for pseudo-associative operators (e.g.,
* addition of floating-point types). Results for pseudo-associative
* operators may vary from run to run. Additional details can be found in
* the [decoupled look-back] description.
* - When `d_in` and `d_out` are equal, the scan is performed in-place. The
* range `[d_in, d_in + num_items)` and `[d_out, d_out + num_items)`
* shall not overlap in any other way.
* - @devicestorage
*
* @par Snippet
* The code snippet below illustrates the inclusive prefix sum of an `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 = nullptr;
* 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
* **[inferred]** Random-access input iterator type for reading scan
* inputs \iterator
*
* @tparam OutputIteratorT
* **[inferred]** Random-access output iterator type for writing scan
* outputs \iterator
*
* @param[in] d_temp_storage
* Device-accessible allocation of temporary storage. When `nullptr`, the
* required allocation size is written to `temp_storage_bytes` and no
* work is done.
*
* @param[in,out] temp_storage_bytes
* Reference to size in bytes of `d_temp_storage` allocation
*
* @param[in] d_in
* Random-access iterator to the input sequence of data items
*
* @param[out] d_out
* Random-access iterator to the output sequence of data items
*
* @param[in] num_items
* Total number of input items (i.e., the length of `d_in`)
*
* @param[in] stream
* **[optional]** CUDA stream to launch kernels within.
* Default is stream<sub>0</sub>.
*
* [decoupled look-back]: https://research.nvidia.com/publication/single-pass-parallel-prefix-scan-decoupled-look-back
*/
template <typename InputIteratorT, typename OutputIteratorT>
CUB_RUNTIME_FUNCTION static cudaError_t
InclusiveSum(void *d_temp_storage,
size_t &temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
int num_items,
cudaStream_t stream = 0)
{
// Signed integer type for global offsets
using OffsetT = int;
return DispatchScan<InputIteratorT,
OutputIteratorT,
Sum,
NullType,
OffsetT>::Dispatch(d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
Sum(),
NullType(),
num_items,
stream);
}
template <typename InputIteratorT, typename OutputIteratorT>
CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED
CUB_RUNTIME_FUNCTION static cudaError_t
InclusiveSum(void *d_temp_storage,
size_t &temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
int num_items,
cudaStream_t stream,
bool debug_synchronous)
{
CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG
return InclusiveSum<InputIteratorT, OutputIteratorT>(d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
num_items,
stream);
}
/**
* @brief Computes a device-wide inclusive prefix sum in-place.
*
* @par
* - Supports non-commutative sum operators.
* - Results are not deterministic for pseudo-associative operators (e.g.,
* addition of floating-point types). Results for pseudo-associative
* operators may vary from run to run. Additional details can be found in
* the [decoupled look-back] description.
* - @devicestorage
*
* @par Snippet
* The code snippet below illustrates the inclusive prefix sum of an `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_data; // e.g., [8, 6, 7, 5, 3, 0, 9]
* ...
*
* // Determine temporary device storage requirements for inclusive
* // prefix sum
* void *d_temp_storage = nullptr;
* size_t temp_storage_bytes = 0;
* cub::DeviceScan::InclusiveSum(
* d_temp_storage, temp_storage_bytes,
* d_data, 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_data, num_items);
*
* // d_data <-- [8, 14, 21, 26, 29, 29, 38]
*
* @endcode
*
* @tparam IteratorT
* **[inferred]** Random-access input iterator type for reading scan
* inputs and writing scan outputs
*
* @param[in] d_temp_storage
* Device-accessible allocation of temporary storage. When `nullptr`, the
* required allocation size is written to `temp_storage_bytes` and no
* work is done.
*
* @param[in,out] temp_storage_bytes
* Reference to size in bytes of `d_temp_storage` allocation
*
* @param[in,out] d_data
* Random-access iterator to the sequence of data items
*
* @param[in] num_items
* Total number of input items (i.e., the length of `d_in`)
*
* @param[in] stream
* **[optional]** CUDA stream to launch kernels within.
* Default is stream<sub>0</sub>.
*
* [decoupled look-back]: https://research.nvidia.com/publication/single-pass-parallel-prefix-scan-decoupled-look-back
*/
template <typename IteratorT>
CUB_RUNTIME_FUNCTION static cudaError_t
InclusiveSum(void *d_temp_storage,
size_t &temp_storage_bytes,
IteratorT d_data,
int num_items,
cudaStream_t stream = 0)
{
return InclusiveSum(d_temp_storage,
temp_storage_bytes,
d_data,
d_data,
num_items,
stream);
}
template <typename IteratorT>
CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED
CUB_RUNTIME_FUNCTION static cudaError_t
InclusiveSum(void *d_temp_storage,
size_t &temp_storage_bytes,
IteratorT d_data,
int num_items,
cudaStream_t stream,
bool debug_synchronous)
{
CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG
return InclusiveSum<IteratorT>(d_temp_storage,
temp_storage_bytes,
d_data,
num_items,
stream);
}
/**
* @brief Computes a device-wide inclusive prefix scan using the specified
* binary `scan_op` functor.
*
* @par
* - Supports non-commutative scan operators.
* - Results are not deterministic for pseudo-associative operators (e.g.,
* addition of floating-point types). Results for pseudo-associative
* operators may vary from run to run. Additional details can be found in
* the [decoupled look-back] description.
* - When `d_in` and `d_out` are equal, the scan is performed in-place. The
* range `[d_in, d_in + num_items)` and `[d_out, d_out + num_items)`
* shall not overlap in any other way.
* - @devicestorage
*
* @par Snippet
* The code snippet below illustrates the inclusive prefix min-scan of an
* `int` device vector.
*
* @par
* @code
* #include <cub/cub.cuh> // or equivalently <cub/device/device_scan.cuh>
* #include <climits> // for INT_MAX
*
* // 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 = nullptr;
* 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
* **[inferred]** Random-access input iterator type for reading scan
* inputs \iterator
*
* @tparam OutputIteratorT
* **[inferred]** Random-access output iterator type for writing scan
* outputs \iterator
*
* @tparam ScanOp
* **[inferred]** Binary scan functor type having member
* `T operator()(const T &a, const T &b)`
*
* @param[in]
* d_temp_storage Device-accessible allocation of temporary storage.
* When `nullptr`, the required allocation size is written to
* `temp_storage_bytes` and no work is done.
*
* @param[in,out] temp_storage_bytes
* Reference to size in bytes of `d_temp_storage` allocation
*
* @param[in] d_in
* Random-access iterator to the input sequence of data items
*
* @param[out] d_out
* Random-access iterator to the output sequence of data items
*
* @param[in] scan_op
* Binary scan functor
*
* @param[in] num_items
* Total number of input items (i.e., the length of `d_in`)
*
* @param[in] stream
* **[optional]** CUDA stream to launch kernels within.
* Default is stream<sub>0</sub>.
*
* [decoupled look-back]: https://research.nvidia.com/publication/single-pass-parallel-prefix-scan-decoupled-look-back
*/
template <typename InputIteratorT, typename OutputIteratorT, typename ScanOpT>
CUB_RUNTIME_FUNCTION static cudaError_t
InclusiveScan(void *d_temp_storage,
size_t &temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
ScanOpT scan_op,
int num_items,
cudaStream_t stream = 0)
{
// Signed integer type for global offsets
using OffsetT = int;
return DispatchScan<InputIteratorT,
OutputIteratorT,
ScanOpT,
NullType,
OffsetT>::Dispatch(d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
scan_op,
NullType(),
num_items,
stream);
}
template <typename InputIteratorT, typename OutputIteratorT, typename ScanOpT>
CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED
CUB_RUNTIME_FUNCTION static cudaError_t
InclusiveScan(void *d_temp_storage,
size_t &temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
ScanOpT scan_op,
int num_items,
cudaStream_t stream,
bool debug_synchronous)
{
CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG
return InclusiveScan<InputIteratorT, OutputIteratorT, ScanOpT>(
d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
scan_op,
num_items,
stream);
}
/**
* @brief Computes a device-wide inclusive prefix scan using the specified
* binary `scan_op` functor.
*
* @par
* - Supports non-commutative scan operators.
* - Results are not deterministic for pseudo-associative operators (e.g.,
* addition of floating-point types). Results for pseudo-associative
* operators may vary from run to run. Additional details can be found in
* the [decoupled look-back] description.
* - @devicestorage
*
* @par Snippet
* The code snippet below illustrates the inclusive prefix min-scan of an
* `int` device vector.
*
* @par
* @code
* #include <cub/cub.cuh> // or equivalently <cub/device/device_scan.cuh>
* #include <climits> // for INT_MAX
*
* // 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_data; // e.g., [8, 6, 7, 5, 3, 0, 9]
* CustomMin min_op;
* ...
*
* // Determine temporary device storage requirements for inclusive
* // prefix scan
* void *d_temp_storage = nullptr;
* size_t temp_storage_bytes = 0;
* cub::DeviceScan::InclusiveScan(
* d_temp_storage, temp_storage_bytes,
* d_data, 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_data <-- [8, 6, 6, 5, 3, 0, 0]
*
* @endcode
*
* @tparam IteratorT
* **[inferred]** Random-access input iterator type for reading scan
* inputs and writing scan outputs
*
* @tparam ScanOp
* **[inferred]** Binary scan functor type having member
* `T operator()(const T &a, const T &b)`
*
* @param[in]
* d_temp_storage Device-accessible allocation of temporary storage.
* When `nullptr`, the required allocation size is written to
* `temp_storage_bytes` and no work is done.
*
* @param[in,out] temp_storage_bytes
* Reference to size in bytes of `d_temp_storage` allocation
*
* @param[in] d_data
* Random-access iterator to the sequence of data items
*
* @param[in] scan_op
* Binary scan functor
*
* @param[in] num_items
* Total number of input items (i.e., the length of `d_in`)
*
* @param[in] stream
* **[optional]** CUDA stream to launch kernels within.
* Default is stream<sub>0</sub>.
*
* [decoupled look-back]: https://research.nvidia.com/publication/single-pass-parallel-prefix-scan-decoupled-look-back
*/
template <typename IteratorT, typename ScanOpT>
CUB_RUNTIME_FUNCTION static cudaError_t
InclusiveScan(void *d_temp_storage,
size_t &temp_storage_bytes,
IteratorT d_data,
ScanOpT scan_op,
int num_items,
cudaStream_t stream = 0)
{
return InclusiveScan(d_temp_storage,
temp_storage_bytes,
d_data,
d_data,
scan_op,
num_items,
stream);
}
template <typename IteratorT, typename ScanOpT>
CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED
CUB_RUNTIME_FUNCTION static cudaError_t
InclusiveScan(void *d_temp_storage,
size_t &temp_storage_bytes,
IteratorT d_data,
ScanOpT scan_op,
int num_items,
cudaStream_t stream,
bool debug_synchronous)
{
CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG
return InclusiveScan<IteratorT, ScanOpT>(d_temp_storage,
temp_storage_bytes,
d_data,
scan_op,
num_items,
stream);
}
/**
* @brief Computes a device-wide exclusive prefix sum-by-key with key equality
* defined by `equality_op`. The value of `0` is applied as the initial
* value, and is assigned to the beginning of each segment in
* `d_values_out`.
*
* @par
* - Supports non-commutative sum operators.
* - Results are not deterministic for pseudo-associative operators (e.g.,
* addition of floating-point types). Results for pseudo-associative
* operators may vary from run to run. Additional details can be found in
* the [decoupled look-back] description.
* - `d_keys_in` may equal `d_values_out` but the range
* `[d_keys_in, d_keys_in + num_items)` and the range
* `[d_values_out, d_values_out + num_items)` shall not overlap otherwise.
* - `d_values_in` may equal `d_values_out` but the range
* `[d_values_in, d_values_in + num_items)` and the range
* `[d_values_out, d_values_out + num_items)` shall not overlap otherwise.
* - @devicestorage
*
* @par Snippet
* The code snippet below illustrates the exclusive prefix sum-by-key of an
* `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_keys_in; // e.g., [0, 0, 1, 1, 1, 2, 2]
* int *d_values_in; // e.g., [8, 6, 7, 5, 3, 0, 9]
* int *d_values_out; // e.g., [ , , , , , , ]
* ...
*
* // Determine temporary device storage requirements
* void *d_temp_storage = nullptr;
* size_t temp_storage_bytes = 0;
* cub::DeviceScan::ExclusiveSumByKey(
* d_temp_storage, temp_storage_bytes,
* d_keys_in, d_values_in, d_values_out, num_items);
*
* // Allocate temporary storage
* cudaMalloc(&d_temp_storage, temp_storage_bytes);
*
* // Run exclusive prefix sum
* cub::DeviceScan::ExclusiveSumByKey(
* d_temp_storage, temp_storage_bytes,
* d_keys_in, d_values_in, d_values_out, num_items);
*
* // d_values_out <-- [0, 8, 0, 7, 12, 0, 0]
*
* @endcode
*
* @tparam KeysInputIteratorT
* **[inferred]** Random-access input iterator type for reading scan keys
* inputs \iterator
*
* @tparam ValuesInputIteratorT
* **[inferred]** Random-access input iterator type for reading scan
* values inputs \iterator
*
* @tparam ValuesOutputIteratorT
* **[inferred]** Random-access output iterator type for writing scan
* values outputs \iterator
*
* @tparam EqualityOpT
* **[inferred]** Functor type having member
* `T operator()(const T &a, const T &b)` for binary operations that
* defines the equality of keys
*
* @param[in] d_temp_storage
* Device-accessible allocation of temporary storage. When `nullptr`, the
* required allocation size is written to `temp_storage_bytes` and no
* work is done.
*
* @param[in,out] temp_storage_bytes
* Reference to size in bytes of `d_temp_storage` allocation
*
* @param[in] d_keys_in
* Random-access input iterator to the input sequence of key items
*
* @param[in] d_values_in
* Random-access input iterator to the input sequence of value items
*
* @param[out] d_values_out
* Random-access output iterator to the output sequence of value items
*
* @param[in] num_items
* Total number of input items (i.e., the length of `d_keys_in` and
* `d_values_in`)
*
* @param[in] equality_op
* Binary functor that defines the equality of keys.
* Default is cub::Equality().
*
* @param[in] stream
* **[optional]** CUDA stream to launch kernels within.
* Default is stream<sub>0</sub>.
*
* [decoupled look-back]: https://research.nvidia.com/publication/single-pass-parallel-prefix-scan-decoupled-look-back
*/
template <typename KeysInputIteratorT,
typename ValuesInputIteratorT,
typename ValuesOutputIteratorT,
typename EqualityOpT = Equality>
CUB_RUNTIME_FUNCTION static cudaError_t
ExclusiveSumByKey(void *d_temp_storage,
size_t &temp_storage_bytes,
KeysInputIteratorT d_keys_in,
ValuesInputIteratorT d_values_in,
ValuesOutputIteratorT d_values_out,
int num_items,
EqualityOpT equality_op = EqualityOpT(),
cudaStream_t stream = 0)
{
// Signed integer type for global offsets
using OffsetT = int;
using InitT = cub::detail::value_t<ValuesInputIteratorT>;
// Initial value
InitT init_value{};
return DispatchScanByKey<KeysInputIteratorT,
ValuesInputIteratorT,
ValuesOutputIteratorT,
EqualityOpT,
Sum,
InitT,
OffsetT>::Dispatch(d_temp_storage,
temp_storage_bytes,
d_keys_in,
d_values_in,
d_values_out,
equality_op,
Sum(),
init_value,
num_items,
stream);
}
template <typename KeysInputIteratorT,
typename ValuesInputIteratorT,
typename ValuesOutputIteratorT,
typename EqualityOpT = Equality>
CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED
CUB_RUNTIME_FUNCTION static cudaError_t
ExclusiveSumByKey(void *d_temp_storage,
size_t &temp_storage_bytes,
KeysInputIteratorT d_keys_in,
ValuesInputIteratorT d_values_in,
ValuesOutputIteratorT d_values_out,
int num_items,
EqualityOpT equality_op,
cudaStream_t stream,
bool debug_synchronous)
{
CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG
return ExclusiveSumByKey<KeysInputIteratorT,
ValuesInputIteratorT,
ValuesOutputIteratorT,
EqualityOpT>(d_temp_storage,
temp_storage_bytes,
d_keys_in,
d_values_in,
d_values_out,
num_items,
equality_op,
stream);
}
/**
* @brief Computes a device-wide exclusive prefix scan-by-key using the
* specified binary `scan_op` functor. The key equality is defined by
* `equality_op`. The `init_value` value is applied as the initial
* value, and is assigned to the beginning of each segment in
* `d_values_out`.
*
* @par
* - Supports non-commutative scan operators.
* - Results are not deterministic for pseudo-associative operators (e.g.,
* addition of floating-point types). Results for pseudo-associative
* operators may vary from run to run. Additional details can be found in
* the [decoupled look-back] description.
* - `d_keys_in` may equal `d_values_out` but the range
* `[d_keys_in, d_keys_in + num_items)` and the range
* `[d_values_out, d_values_out + num_items)` shall not overlap otherwise.
* - `d_values_in` may equal `d_values_out` but the range
* `[d_values_in, d_values_in + num_items)` and the range
* `[d_values_out, d_values_out + num_items)` shall not overlap otherwise.
* - @devicestorage
*
* @par Snippet
* The code snippet below illustrates the exclusive prefix min-scan-by-key of
* an `int` device vector
* @par
* @code
* #include <cub/cub.cuh> // or equivalently <cub/device/device_scan.cuh>
* #include <climits> // for INT_MAX
*
* // 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;
* }
* };
*
* // CustomEqual functor
* struct CustomEqual
* {
* template <typename T>
* CUB_RUNTIME_FUNCTION __forceinline__
* T operator()(const T &a, const T &b) const {
* return a == b;
* }
* };
*
* // Declare, allocate, and initialize device-accessible pointers for
* // input and output
* int num_items; // e.g., 7
* int *d_keys_in; // e.g., [0, 0, 1, 1, 1, 2, 2]
* int *d_values_in; // e.g., [8, 6, 7, 5, 3, 0, 9]
* int *d_values_out; // e.g., [ , , , , , , ]
* CustomMin min_op;
* CustomEqual equality_op;
* ...
*
* // Determine temporary device storage requirements for exclusive
* // prefix scan
* void *d_temp_storage = NULL;
* size_t temp_storage_bytes = 0;
* cub::DeviceScan::ExclusiveScanByKey(
* d_temp_storage, temp_storage_bytes,
* d_keys_in, d_values_in, d_values_out, min_op,
* (int) INT_MAX, num_items, equality_op);
*
* // Allocate temporary storage for exclusive prefix scan
* cudaMalloc(&d_temp_storage, temp_storage_bytes);
*
* // Run exclusive prefix min-scan
* cub::DeviceScan::ExclusiveScanByKey(
* d_temp_storage, temp_storage_bytes,
* d_keys_in, d_values_in, d_values_out, min_op,
* (int) INT_MAX, num_items, equality_op);
*
* // d_values_out <-- [2147483647, 8, 2147483647, 7, 5, 2147483647, 0]
*
* @endcode
*
* @tparam KeysInputIteratorT
* **[inferred]** Random-access input iterator type for reading scan keys
* inputs \iterator
*
* @tparam ValuesInputIteratorT
* **[inferred]** Random-access input iterator type for reading scan values
* inputs \iterator
*
* @tparam ValuesOutputIteratorT
* **[inferred]** Random-access output iterator type for writing scan values
* outputs \iterator
*
* @tparam ScanOp
* **[inferred]** Binary scan functor type having member
* `T operator()(const T &a, const T &b)`
*
* @tparam InitValueT
* **[inferred]** Type of the `init_value` value used in Binary scan
* functor type having member `T operator()(const T &a, const T &b)`
*
* @tparam EqualityOpT
* **[inferred]** Functor type having member
* `T operator()(const T &a, const T &b)` for binary operations that
* defines the equality of keys
*
* @param[in] d_temp_storage
* Device-accessible allocation of temporary storage. When `nullptr`, the
* required allocation size is written to `temp_storage_bytes` and no work
* is done.
*
* @param[in,out] temp_storage_bytes
* Reference to size in bytes of `d_temp_storage` allocation
*
* @param[in] d_keys_in
* Random-access input iterator to the input sequence of key items
*
* @param[in] d_values_in
* Random-access input iterator to the input sequence of value items
*
* @param[out] d_values_out
* Random-access output iterator to the output sequence of value items
*
* @param[in] scan_op
* Binary scan functor
*
* @param[in] init_value
* Initial value to seed the exclusive scan (and is assigned to the
* beginning of each segment in `d_values_out`)
*
* @param[in] num_items
* Total number of input items (i.e., the length of `d_keys_in` and
* `d_values_in`)
*
* @param[in] equality_op
* Binary functor that defines the equality of keys.
* Default is cub::Equality().
*
* @param[in] stream
* **[optional]** CUDA stream to launch kernels within.
* Default is stream<sub>0</sub>.
*
* [decoupled look-back]: https://research.nvidia.com/publication/single-pass-parallel-prefix-scan-decoupled-look-back
*/
template <typename KeysInputIteratorT,
typename ValuesInputIteratorT,
typename ValuesOutputIteratorT,
typename ScanOpT,
typename InitValueT,
typename EqualityOpT = Equality>
CUB_RUNTIME_FUNCTION static cudaError_t
ExclusiveScanByKey(void *d_temp_storage,
size_t &temp_storage_bytes,
KeysInputIteratorT d_keys_in,
ValuesInputIteratorT d_values_in,
ValuesOutputIteratorT d_values_out,
ScanOpT scan_op,
InitValueT init_value,
int num_items,
EqualityOpT equality_op = EqualityOpT(),
cudaStream_t stream = 0)
{
// Signed integer type for global offsets
using OffsetT = int ;
return DispatchScanByKey<KeysInputIteratorT,
ValuesInputIteratorT,
ValuesOutputIteratorT,
EqualityOpT,
ScanOpT,
InitValueT,
OffsetT>::Dispatch(d_temp_storage,
temp_storage_bytes,
d_keys_in,
d_values_in,
d_values_out,
equality_op,
scan_op,
init_value,
num_items,
stream);
}
template <typename KeysInputIteratorT,
typename ValuesInputIteratorT,
typename ValuesOutputIteratorT,
typename ScanOpT,
typename InitValueT,
typename EqualityOpT = Equality>
CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED
CUB_RUNTIME_FUNCTION static cudaError_t
ExclusiveScanByKey(void *d_temp_storage,
size_t &temp_storage_bytes,
KeysInputIteratorT d_keys_in,
ValuesInputIteratorT d_values_in,
ValuesOutputIteratorT d_values_out,
ScanOpT scan_op,
InitValueT init_value,
int num_items,
EqualityOpT equality_op,
cudaStream_t stream,
bool debug_synchronous)
{
CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG
return ExclusiveScanByKey<KeysInputIteratorT,
ValuesInputIteratorT,
ValuesOutputIteratorT,
ScanOpT,
InitValueT,
EqualityOpT>(d_temp_storage,
temp_storage_bytes,
d_keys_in,
d_values_in,
d_values_out,
scan_op,
init_value,
num_items,
equality_op,
stream);
}
/**
* @brief Computes a device-wide inclusive prefix sum-by-key with key
* equality defined by `equality_op`.
*
* @par
* - Supports non-commutative sum operators.
* - Results are not deterministic for pseudo-associative operators (e.g.,
* addition of floating-point types). Results for pseudo-associative
* operators may vary from run to run. Additional details can be found in
* the [decoupled look-back] description.
* - `d_keys_in` may equal `d_values_out` but the range
* `[d_keys_in, d_keys_in + num_items)` and the range
* `[d_values_out, d_values_out + num_items)` shall not overlap otherwise.
* - `d_values_in` may equal `d_values_out` but the range
* `[d_values_in, d_values_in + num_items)` and the range
* `[d_values_out, d_values_out + num_items)` shall not overlap otherwise.
* - @devicestorage
*
* @par Snippet
* The code snippet below illustrates the inclusive prefix sum-by-key of an
* `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_keys_in; // e.g., [0, 0, 1, 1, 1, 2, 2]
* int *d_values_in; // e.g., [8, 6, 7, 5, 3, 0, 9]
* int *d_values_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::InclusiveSumByKey(
* d_temp_storage, temp_storage_bytes,
* d_keys_in, d_values_in, d_values_out, num_items);
*
* // Allocate temporary storage for inclusive prefix sum
* cudaMalloc(&d_temp_storage, temp_storage_bytes);
*
* // Run inclusive prefix sum
* cub::DeviceScan::InclusiveSumByKey(
* d_temp_storage, temp_storage_bytes,
* d_keys_in, d_values_in, d_values_out, num_items);
*
* // d_out <-- [8, 14, 7, 12, 15, 0, 9]
*
* @endcode
*
* @tparam KeysInputIteratorT
* **[inferred]** Random-access input iterator type for reading scan
* keys inputs \iterator
*
* @tparam ValuesInputIteratorT
* **[inferred]** Random-access input iterator type for reading scan
* values inputs \iterator
*
* @tparam ValuesOutputIteratorT
* **[inferred]** Random-access output iterator type for writing scan
* values outputs \iterator
*
* @tparam EqualityOpT
* **[inferred]** Functor type having member
* `T operator()(const T &a, const T &b)` for binary operations that
* defines the equality of keys
*
* @param[in] d_temp_storage
* Device-accessible allocation of temporary storage.
* When `nullptr`, the required allocation size is written to
* `temp_storage_bytes` and no work is done.
*
* @param[in,out] temp_storage_bytes
* Reference to size in bytes of `d_temp_storage` allocation
*
* @param[in] d_keys_in
* Random-access input iterator to the input sequence of key items
*
* @param[in] d_values_in
* Random-access input iterator to the input sequence of value items
*
* @param[out] d_values_out
* Random-access output iterator to the output sequence of value items
*
* @param[in] num_items
* Total number of input items (i.e., the length of `d_keys_in` and
* `d_values_in`)
*
* @param[in] equality_op
* Binary functor that defines the equality of keys.
* Default is cub::Equality().
*
* @param[in] stream
* **[optional]** CUDA stream to launch kernels within.
* Default is stream<sub>0</sub>.
*
* [decoupled look-back]: https://research.nvidia.com/publication/single-pass-parallel-prefix-scan-decoupled-look-back
*/
template <typename KeysInputIteratorT,
typename ValuesInputIteratorT,
typename ValuesOutputIteratorT,
typename EqualityOpT = Equality>
CUB_RUNTIME_FUNCTION static cudaError_t
InclusiveSumByKey(void *d_temp_storage,
size_t &temp_storage_bytes,
KeysInputIteratorT d_keys_in,
ValuesInputIteratorT d_values_in,
ValuesOutputIteratorT d_values_out,
int num_items,
EqualityOpT equality_op = EqualityOpT(),
cudaStream_t stream = 0)
{
// Signed integer type for global offsets
using OffsetT = int ;
return DispatchScanByKey<KeysInputIteratorT,
ValuesInputIteratorT,
ValuesOutputIteratorT,
EqualityOpT,
Sum,
NullType,
OffsetT>::Dispatch(d_temp_storage,
temp_storage_bytes,
d_keys_in,
d_values_in,
d_values_out,
equality_op,
Sum(),
NullType(),
num_items,
stream);
}
template <typename KeysInputIteratorT,
typename ValuesInputIteratorT,
typename ValuesOutputIteratorT,
typename EqualityOpT = Equality>
CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED
CUB_RUNTIME_FUNCTION static cudaError_t
InclusiveSumByKey(void *d_temp_storage,
size_t &temp_storage_bytes,
KeysInputIteratorT d_keys_in,
ValuesInputIteratorT d_values_in,
ValuesOutputIteratorT d_values_out,
int num_items,
EqualityOpT equality_op,
cudaStream_t stream,
bool debug_synchronous)
{
CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG
return InclusiveSumByKey<KeysInputIteratorT,
ValuesInputIteratorT,
ValuesOutputIteratorT,
EqualityOpT>(d_temp_storage,
temp_storage_bytes,
d_keys_in,
d_values_in,
d_values_out,
num_items,
equality_op,
stream);
}
/**
* @brief Computes a device-wide inclusive prefix scan-by-key using the
* specified binary `scan_op` functor. The key equality is defined
* by `equality_op`.
*
* @par
* - Supports non-commutative scan operators.
* - Results are not deterministic for pseudo-associative operators (e.g.,
* addition of floating-point types). Results for pseudo-associative
* operators may vary from run to run. Additional details can be found in
* the [decoupled look-back] description.
* - `d_keys_in` may equal `d_values_out` but the range
* `[d_keys_in, d_keys_in + num_items)` and the range
* `[d_values_out, d_values_out + num_items)` shall not overlap otherwise.
* - `d_values_in` may equal `d_values_out` but the range
* `[d_values_in, d_values_in + num_items)` and the range
* `[d_values_out, d_values_out + num_items)` shall not overlap otherwise.
* - @devicestorage
*
* @par Snippet
* The code snippet below illustrates the inclusive prefix min-scan-by-key
* of an `int` device vector.
* @par
* @code
* #include <cub/cub.cuh> // or equivalently <cub/device/device_scan.cuh>
* #include <climits> // for INT_MAX
*
* // 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;
* }
* };
*
* // CustomEqual functor
* struct CustomEqual
* {
* template <typename T>
* CUB_RUNTIME_FUNCTION __forceinline__
* T operator()(const T &a, const T &b) const {
* return a == b;
* }
* };
*
* // Declare, allocate, and initialize device-accessible pointers for
* // input and output
* int num_items; // e.g., 7
* int *d_keys_in; // e.g., [0, 0, 1, 1, 1, 2, 2]
* int *d_values_in; // e.g., [8, 6, 7, 5, 3, 0, 9]
* int *d_values_out; // e.g., [ , , , , , , ]
* CustomMin min_op;
* CustomEqual equality_op;
* ...
*
* // Determine temporary device storage requirements for inclusive prefix scan
* void *d_temp_storage = NULL;
* size_t temp_storage_bytes = 0;
* cub::DeviceScan::InclusiveScanByKey(
* d_temp_storage, temp_storage_bytes,
* d_keys_in, d_values_in, d_values_out, min_op, num_items, equality_op);
*
* // Allocate temporary storage for inclusive prefix scan
* cudaMalloc(&d_temp_storage, temp_storage_bytes);
*
* // Run inclusive prefix min-scan
* cub::DeviceScan::InclusiveScanByKey(
* d_temp_storage, temp_storage_bytes,
* d_keys_in, d_values_in, d_values_out, min_op, num_items, equality_op);
*
* // d_out <-- [8, 6, 7, 5, 3, 0, 0]
*
* @endcode
*
* @tparam KeysInputIteratorT
* **[inferred]** Random-access input iterator type for reading scan keys
* inputs \iterator
*
* @tparam ValuesInputIteratorT
* **[inferred]** Random-access input iterator type for reading scan
* values inputs \iterator
*
* @tparam ValuesOutputIteratorT
* **[inferred]** Random-access output iterator type for writing scan
* values outputs \iterator
*
* @tparam ScanOp
* **[inferred]** Binary scan functor type having member
* `T operator()(const T &a, const T &b)`
*
* @tparam EqualityOpT
* **[inferred]** Functor type having member
* `T operator()(const T &a, const T &b)` for binary operations that
* defines the equality of keys
*
* @param[in] d_temp_storage
* Device-accessible allocation of temporary storage.
* When `nullptr`, the required allocation size is written to
* `temp_storage_bytes` and no work is done.
*
* @param[in,out] temp_storage_bytes
* Reference to size in bytes of `d_temp_storage` allocation
*
* @param[in] d_keys_in
* Random-access input iterator to the input sequence of key items
*
* @param[in] d_values_in
* Random-access input iterator to the input sequence of value items
*
* @param[out] d_values_out
* Random-access output iterator to the output sequence of value items
*
* @param[in] scan_op
* Binary scan functor
*
* @param[in] num_items
* Total number of input items (i.e., the length of `d_keys_in` and
* `d_values_in`)
*
* @param[in] equality_op
* Binary functor that defines the equality of keys.
* Default is cub::Equality().
*
* @param[in] stream
* **[optional]** CUDA stream to launch kernels within.
* Default is stream<sub>0</sub>.
*
* [decoupled look-back]: https://research.nvidia.com/publication/single-pass-parallel-prefix-scan-decoupled-look-back
*/
template <typename KeysInputIteratorT,
typename ValuesInputIteratorT,
typename ValuesOutputIteratorT,
typename ScanOpT,
typename EqualityOpT = Equality>
CUB_RUNTIME_FUNCTION static cudaError_t
InclusiveScanByKey(void *d_temp_storage,
size_t &temp_storage_bytes,
KeysInputIteratorT d_keys_in,
ValuesInputIteratorT d_values_in,
ValuesOutputIteratorT d_values_out,
ScanOpT scan_op,
int num_items,
EqualityOpT equality_op = EqualityOpT(),
cudaStream_t stream = 0)
{
// Signed integer type for global offsets
using OffsetT = int;
return DispatchScanByKey<KeysInputIteratorT,
ValuesInputIteratorT,
ValuesOutputIteratorT,
EqualityOpT,
ScanOpT,
NullType,
OffsetT>::Dispatch(d_temp_storage,
temp_storage_bytes,
d_keys_in,
d_values_in,
d_values_out,
equality_op,
scan_op,
NullType(),
num_items,
stream);
}
template <typename KeysInputIteratorT,
typename ValuesInputIteratorT,
typename ValuesOutputIteratorT,
typename ScanOpT,
typename EqualityOpT = Equality>
CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED
CUB_RUNTIME_FUNCTION static cudaError_t
InclusiveScanByKey(void *d_temp_storage,
size_t &temp_storage_bytes,
KeysInputIteratorT d_keys_in,
ValuesInputIteratorT d_values_in,
ValuesOutputIteratorT d_values_out,
ScanOpT scan_op,
int num_items,
EqualityOpT equality_op,
cudaStream_t stream,
bool debug_synchronous)
{
CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG
return InclusiveScanByKey<KeysInputIteratorT,
ValuesInputIteratorT,
ValuesOutputIteratorT,
ScanOpT,
EqualityOpT>(d_temp_storage,
temp_storage_bytes,
d_keys_in,
d_values_in,
d_values_out,
scan_op,
num_items,
equality_op,
stream);
}
//@} end member group
};
/**
* @example example_device_scan.cu
*/
CUB_NAMESPACE_END