From 403271b83e8ebc2f133c3937793b9f887f3284e8 Mon Sep 17 00:00:00 2001 From: dumerrill Date: Sun, 13 Aug 2017 02:55:08 -0400 Subject: [PATCH] Replace purged file from branch --- cub/block/block_scan.cuh | 2321 +++++++++++++++++++++++ cub/block/block_scan.cuh.REMOVED.git-id | 1 - 2 files changed, 2321 insertions(+), 1 deletion(-) create mode 100644 cub/block/block_scan.cuh delete mode 100644 cub/block/block_scan.cuh.REMOVED.git-id diff --git a/cub/block/block_scan.cuh b/cub/block/block_scan.cuh new file mode 100644 index 0000000000..3c297ade99 --- /dev/null +++ b/cub/block/block_scan.cuh @@ -0,0 +1,2321 @@ +/****************************************************************************** + * Copyright (c) 2011, Duane Merrill. All rights reserved. + * Copyright (c) 2011-2014, 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 + * The cub::BlockScan class provides [collective](index.html#sec0) methods for computing a parallel prefix sum/scan of items partitioned across a CUDA thread block. + */ + +#pragma once + +#include "specializations/block_scan_raking.cuh" +#include "specializations/block_scan_warp_scans.cuh" +#include "../util_arch.cuh" +#include "../util_type.cuh" +#include "../util_namespace.cuh" + +/// Optional outer namespace(s) +CUB_NS_PREFIX + +/// CUB namespace +namespace cub { + + + +/****************************************************************************** + * Scan utility types + ******************************************************************************/ + +#ifndef DOXYGEN_SHOULD_SKIP_THIS // Do not document + +/** + * Reduce-value-by-ID scan operator + */ +template ///< Wrapped reduction operator type +struct ReduceByKeyOp +{ + ReductionOp op; ///< Wrapped reduction operator + + /// Constructor + __device__ __forceinline__ ReduceByKeyOp(ReductionOp op) : op(op) {} + + /// Scan operator + template + __device__ __forceinline__ KeyValuePair operator()( + const KeyValuePair &first, + const KeyValuePair &second) + { + KeyValuePair retval; + + retval.value = (second.key != first.key) ? + second.value : // The second value is for a different ID, return only that value + op(first.value, second.value); // The values are for the same ID so reduce them + + retval.key = second.key; + return retval; + } +}; + + + +/** + * Segmented scan operator + */ +template ///< Wrapped reduction operator type +struct SegmentedOp +{ + ReductionOp op; ///< Wrapped reduction operator + + /// Constructor + __device__ __forceinline__ SegmentedOp(ReductionOp op) : op(op) {} + + /// Scan operator + template + __device__ __forceinline__ KeyValuePair operator()( + const KeyValuePair &first, + const KeyValuePair &second) + { + if (second.key) { + KeyValuePair retval; + retval.value = second.value; + retval.key = first.key + second.key; + return retval; + } else { + KeyValuePair retval; + retval.value = op(first.value, second.value); + retval.key = first.key + second.key; + return ; + } + } +}; + +#endif // DOXYGEN_SHOULD_SKIP_THIS + + + +/****************************************************************************** + * Algorithmic variants + ******************************************************************************/ + +/** + * \brief BlockScanAlgorithm enumerates alternative algorithms for cub::BlockScan to compute a parallel prefix scan across a CUDA thread block. + */ +enum BlockScanAlgorithm +{ + + /** + * \par Overview + * An efficient "raking reduce-then-scan" prefix scan algorithm. Execution is comprised of five phases: + * -# Upsweep sequential reduction in registers (if threads contribute more than one input each). Each thread then places the partial reduction of its item(s) into shared memory. + * -# Upsweep sequential reduction in shared memory. Threads within a single warp rake across segments of shared partial reductions. + * -# A warp-synchronous Kogge-Stone style exclusive scan within the raking warp. + * -# Downsweep sequential exclusive scan in shared memory. Threads within a single warp rake across segments of shared partial reductions, seeded with the warp-scan output. + * -# Downsweep sequential scan in registers (if threads contribute more than one input), seeded with the raking scan output. + * + * \par + * \image html block_scan_raking.png + *
\p BLOCK_SCAN_RAKING data flow for a hypothetical 16-thread threadblock and 4-thread raking warp.
+ * + * \par Performance Considerations + * - Although this variant may suffer longer turnaround latencies when the + * GPU is under-occupied, it can often provide higher overall throughput + * across the GPU when suitably occupied. + */ + BLOCK_SCAN_RAKING, + + + /** + * \par Overview + * Similar to cub::BLOCK_SCAN_RAKING, but with fewer shared memory reads at + * the expense of higher register pressure. Raking threads preserve their + * "upsweep" segment of values in registers while performing warp-synchronous + * scan, allowing the "downsweep" not to re-read them from shared memory. + */ + BLOCK_SCAN_RAKING_MEMOIZE, + + + /** + * \par Overview + * A quick "tiled warpscans" prefix scan algorithm. Execution is comprised of four phases: + * -# Upsweep sequential reduction in registers (if threads contribute more than one input each). Each thread then places the partial reduction of its item(s) into shared memory. + * -# Compute a shallow, but inefficient warp-synchronous Kogge-Stone style scan within each warp. + * -# A propagation phase where the warp scan outputs in each warp are updated with the aggregate from each preceding warp. + * -# Downsweep sequential scan in registers (if threads contribute more than one input), seeded with the raking scan output. + * + * \par + * \image html block_scan_warpscans.png + *
\p BLOCK_SCAN_WARP_SCANS data flow for a hypothetical 16-thread threadblock and 4-thread raking warp.
+ * + * \par Performance Considerations + * - Although this variant may suffer lower overall throughput across the + * GPU because due to a heavy reliance on inefficient warpscans, it can + * often provide lower turnaround latencies when the GPU is under-occupied. + */ + BLOCK_SCAN_WARP_SCANS, +}; + + +/****************************************************************************** + * Block scan + ******************************************************************************/ + +/** + * \brief The BlockScan class provides [collective](index.html#sec0) methods for computing a parallel prefix sum/scan of items partitioned across a CUDA thread block. ![](block_scan_logo.png) + * \ingroup BlockModule + * + * \tparam T Data type being scanned + * \tparam BLOCK_THREADS The thread block size in threads + * \tparam ALGORITHM [optional] cub::BlockScanAlgorithm enumerator specifying the underlying algorithm to use (default: cub::BLOCK_SCAN_RAKING) + * + * \par Overview + * - Given a list of input elements and a binary reduction operator, a [prefix scan](http://en.wikipedia.org/wiki/Prefix_sum) + * produces an output list where each element is computed to be the reduction + * of the elements occurring earlier in the input list. Prefix sum + * connotes a prefix scan with the addition operator. The term \em inclusive indicates + * that the ith output reduction incorporates the ith input. + * The term \em exclusive indicates the ith input is not incorporated into + * the ith output reduction. + * - BlockScan can be optionally specialized by algorithm to accommodate different workload profiles: + * -# cub::BLOCK_SCAN_RAKING. An efficient (high throughput) "raking reduce-then-scan" prefix scan algorithm. [More...](\ref cub::BlockScanAlgorithm) + * -# cub::BLOCK_SCAN_RAKING_MEMOIZE. Similar to cub::BLOCK_SCAN_RAKING, but having higher throughput at the expense of additional register pressure for intermediate storage. [More...](\ref cub::BlockScanAlgorithm) + * -# cub::BLOCK_SCAN_WARP_SCANS. A quick (low latency) "tiled warpscans" prefix scan algorithm. [More...](\ref cub::BlockScanAlgorithm) + * + * \par Performance Considerations + * - \granularity + * - Uses special instructions when applicable (e.g., warp \p SHFL) + * - Uses synchronization-free communication between warp lanes when applicable + * - Uses only one or two block-wide synchronization barriers (depending on + * algorithm selection) + * - Incurs zero bank conflicts for most types + * - Computation is slightly more efficient (i.e., having lower instruction overhead) for: + * - Prefix sum variants (vs. generic scan) + * - Exclusive variants (vs. inclusive) + * - \p BLOCK_THREADS is a multiple of the architecture's warp size + * - See cub::BlockScanAlgorithm for performance details regarding algorithmic alternatives + * + * \par A Simple Example + * \blockcollective{BlockScan} + * \par + * The code snippet below illustrates an exclusive prefix sum of 512 integer items that + * are partitioned in a [blocked arrangement](index.html#sec5sec3) across 128 threads + * where each thread owns 4 consecutive items. + * \par + * \code + * #include // or equivalently + * + * __global__ void ExampleKernel(...) + * { + * // Specialize BlockScan for 128 threads on type int + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Obtain a segment of consecutive items that are blocked across threads + * int thread_data[4]; + * ... + * + * // Collectively compute the block-wide exclusive prefix sum + * BlockScan(temp_storage).ExclusiveSum(thread_data, thread_data); + * + * \endcode + * \par + * Suppose the set of input \p thread_data across the block of threads is + * {[1,1,1,1], [1,1,1,1], ..., [1,1,1,1]}. + * The corresponding output \p thread_data in those threads will be + * {[0,1,2,3], [4,5,6,7], ..., [508,509,510,511]}. + * + */ +template < + typename T, + int BLOCK_THREADS, + BlockScanAlgorithm ALGORITHM = BLOCK_SCAN_RAKING> +class BlockScan +{ +private: + + /****************************************************************************** + * Constants and type definitions + ******************************************************************************/ + + /** + * Ensure the template parameterization meets the requirements of the + * specified algorithm. Currently, the BLOCK_SCAN_WARP_SCANS policy + * cannot be used with threadblock sizes not a multiple of the + * architectural warp size. + */ + static const BlockScanAlgorithm SAFE_ALGORITHM = + ((ALGORITHM == BLOCK_SCAN_WARP_SCANS) && (BLOCK_THREADS % CUB_PTX_WARP_THREADS != 0)) ? + BLOCK_SCAN_RAKING : + ALGORITHM; + + /// Internal specialization. + typedef typename If<(SAFE_ALGORITHM == BLOCK_SCAN_WARP_SCANS), + BlockScanWarpScans, + BlockScanRaking >::Type InternalBlockScan; + + + /// Shared memory storage layout type for BlockScan + typedef typename InternalBlockScan::TempStorage _TempStorage; + + + /****************************************************************************** + * Thread fields + ******************************************************************************/ + + /// Shared storage reference + _TempStorage &temp_storage; + + /// Linear thread-id + int linear_tid; + + + /****************************************************************************** + * Utility methods + ******************************************************************************/ + + /// Internal storage allocator + __device__ __forceinline__ _TempStorage& PrivateStorage() + { + __shared__ _TempStorage private_storage; + return private_storage; + } + + +public: + + /// \smemstorage{BlockScan} + struct TempStorage : Uninitialized<_TempStorage> {}; + + + /******************************************************************//** + * \name Collective constructors + *********************************************************************/ + //@{ + + /** + * \brief Collective constructor for 1D thread blocks using a private static allocation of shared memory as temporary storage. Threads are identified using threadIdx.x. + */ + __device__ __forceinline__ BlockScan() + : + temp_storage(PrivateStorage()), + linear_tid(threadIdx.x) + {} + + + /** + * \brief Collective constructor for 1D thread blocks using the specified memory allocation as temporary storage. Threads are identified using threadIdx.x. + */ + __device__ __forceinline__ BlockScan( + TempStorage &temp_storage) ///< [in] Reference to memory allocation having layout type TempStorage + : + temp_storage(temp_storage.Alias()), + linear_tid(threadIdx.x) + {} + + + /** + * \brief Collective constructor using a private static allocation of shared memory as temporary storage. Each thread is identified using the supplied linear thread identifier + */ + __device__ __forceinline__ BlockScan( + int linear_tid) ///< [in] A suitable 1D thread-identifier for the calling thread (e.g., (threadIdx.y * blockDim.x) + linear_tid for 2D thread blocks) + : + temp_storage(PrivateStorage()), + linear_tid(linear_tid) + {} + + + /** + * \brief Collective constructor using the specified memory allocation as temporary storage. Each thread is identified using the supplied linear thread identifier. + */ + __device__ __forceinline__ BlockScan( + TempStorage &temp_storage, ///< [in] Reference to memory allocation having layout type TempStorage + int linear_tid) ///< [in] [optional] A suitable 1D thread-identifier for the calling thread (e.g., (threadIdx.y * blockDim.x) + linear_tid for 2D thread blocks) + : + temp_storage(temp_storage.Alias()), + linear_tid(linear_tid) + {} + + + + //@} end member group + /******************************************************************//** + * \name Exclusive prefix sum operations + *********************************************************************/ + //@{ + + + /** + * \brief Computes an exclusive block-wide prefix scan using addition (+) as the scan operator. Each thread contributes one input element. + * + * \par + * - \blocked + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates an exclusive prefix sum of 128 integer items that + * are partitioned across 128 threads. + * \par + * \code + * #include // or equivalently + * + * __global__ void ExampleKernel(...) + * { + * // Specialize BlockScan for 128 threads on type int + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Obtain input item for each thread + * int thread_data; + * ... + * + * // Collectively compute the block-wide exclusive prefix sum + * BlockScan(temp_storage).ExclusiveSum(thread_data, thread_data); + * + * \endcode + * \par + * Suppose the set of input \p thread_data across the block of threads is 1, 1, ..., 1. The + * corresponding output \p thread_data in those threads will be 0, 1, ..., 127. + * + */ + __device__ __forceinline__ void ExclusiveSum( + T input, ///< [in] Calling thread's input item + T &output) ///< [out] Calling thread's output item (may be aliased to \p input) + { + T block_aggregate; + InternalBlockScan(temp_storage, linear_tid).ExclusiveSum(input, output, block_aggregate); + } + + + /** + * \brief Computes an exclusive block-wide prefix scan using addition (+) as the scan operator. Each thread contributes one input element. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * \par + * - \blocked + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates an exclusive prefix sum of 128 integer items that + * are partitioned across 128 threads. + * \par + * \code + * #include // or equivalently + * + * __global__ void ExampleKernel(...) + * { + * // Specialize BlockScan for 128 threads on type int + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Obtain input item for each thread + * int thread_data; + * ... + * + * // Collectively compute the block-wide exclusive prefix sum + * int block_aggregate; + * BlockScan(temp_storage).ExclusiveSum(thread_data, thread_data, block_aggregate); + * + * \endcode + * \par + * Suppose the set of input \p thread_data across the block of threads is 1, 1, ..., 1. The + * corresponding output \p thread_data in those threads will be 0, 1, ..., 127. + * Furthermore the value \p 128 will be stored in \p block_aggregate for all threads. + * + */ + __device__ __forceinline__ void ExclusiveSum( + T input, ///< [in] Calling thread's input item + T &output, ///< [out] Calling thread's output item (may be aliased to \p input) + T &block_aggregate) ///< [out] block-wide aggregate reduction of input items + { + InternalBlockScan(temp_storage, linear_tid).ExclusiveSum(input, output, block_aggregate); + } + + + /** + * \brief Computes an exclusive block-wide prefix scan using addition (+) as the scan operator. Each thread contributes one input element. Instead of using 0 as the block-wide prefix, the call-back functor \p block_prefix_callback_op is invoked by the first warp in the block, and the value returned by lane0 in that warp is used as the "seed" value that logically prefixes the threadblock's scan inputs. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * \par + * - The \p block_prefix_callback_op functor must implement a member function T operator()(T block_aggregate). + * The functor's input parameter \p block_aggregate is the same value also returned by the scan operation. + * The functor will be invoked by the first warp of threads in the block, however only the return value from + * lane0 is applied as the block-wide prefix. Can be stateful. + * - \blocked + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates a single thread block that progressively + * computes an exclusive prefix sum over multiple "tiles" of input using a + * prefix functor to maintain a running total between block-wide scans. Each tile consists + * of 128 integer items that are partitioned across 128 threads. + * \par + * \code + * #include // or equivalently + * + * // A stateful callback functor that maintains a running prefix to be applied + * // during consecutive scan operations. + * struct BlockPrefixCallbackOp + * { + * // Running prefix + * int running_total; + * + * // Constructor + * __device__ BlockPrefixCallbackOp(int running_total) : running_total(running_total) {} + * + * // Callback operator to be entered by the first warp of threads in the block. + * // Thread-0 is responsible for returning a value for seeding the block-wide scan. + * __device__ int operator()(int block_aggregate) + * { + * int old_prefix = running_total; + * running_total += block_aggregate; + * return old_prefix; + * } + * }; + * + * __global__ void ExampleKernel(int *d_data, int num_items, ...) + * { + * // Specialize BlockScan for 128 threads + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Initialize running total + * BlockPrefixCallbackOp prefix_op(0); + * + * // Have the block iterate over segments of items + * for (int block_offset = 0; block_offset < num_items; block_offset += 128) + * { + * // Load a segment of consecutive items that are blocked across threads + * int thread_data = d_data[block_offset]; + * + * // Collectively compute the block-wide exclusive prefix sum + * int block_aggregate; + * BlockScan(temp_storage).ExclusiveSum( + * thread_data, thread_data, block_aggregate, prefix_op); + * __syncthreads(); + * + * // Store scanned items to output segment + * d_data[block_offset] = thread_data; + * } + * \endcode + * \par + * Suppose the input \p d_data is 1, 1, 1, 1, 1, 1, 1, 1, .... + * The corresponding output for the first segment will be 0, 1, ..., 127. + * The output for the second segment will be 128, 129, ..., 255. Furthermore, + * the value \p 128 will be stored in \p block_aggregate for all threads after each scan. + * + * \tparam BlockPrefixCallbackOp [inferred] Call-back functor type having member T operator()(T block_aggregate) + */ + template + __device__ __forceinline__ void ExclusiveSum( + T input, ///< [in] Calling thread's input item + T &output, ///< [out] Calling thread's output item (may be aliased to \p input) + T &block_aggregate, ///< [out] block-wide aggregate reduction of input items (exclusive of the \p block_prefix_callback_op value) + BlockPrefixCallbackOp &block_prefix_callback_op) ///< [in-out] [warp0 only] Call-back functor for specifying a block-wide prefix to be applied to all inputs. + { + InternalBlockScan(temp_storage, linear_tid).ExclusiveSum(input, output, block_aggregate, block_prefix_callback_op); + } + + + //@} end member group + /******************************************************************//** + * \name Exclusive prefix sum operations (multiple data per thread) + *********************************************************************/ + //@{ + + + /** + * \brief Computes an exclusive block-wide prefix scan using addition (+) as the scan operator. Each thread contributes an array of consecutive input elements. + * + * \par + * - \blocked + * - \granularity + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates an exclusive prefix sum of 512 integer items that + * are partitioned in a [blocked arrangement](index.html#sec5sec3) across 128 threads + * where each thread owns 4 consecutive items. + * \par + * \code + * #include // or equivalently + * + * __global__ void ExampleKernel(...) + * { + * // Specialize BlockScan for 128 threads on type int + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Obtain a segment of consecutive items that are blocked across threads + * int thread_data[4]; + * ... + * + * // Collectively compute the block-wide exclusive prefix sum + * BlockScan(temp_storage).ExclusiveSum(thread_data, thread_data); + * + * \endcode + * \par + * Suppose the set of input \p thread_data across the block of threads is { [1,1,1,1], [1,1,1,1], ..., [1,1,1,1] }. The + * corresponding output \p thread_data in those threads will be { [0,1,2,3], [4,5,6,7], ..., [508,509,510,511] }. + * + * \tparam ITEMS_PER_THREAD [inferred] The number of consecutive items partitioned onto each thread. + */ + template + __device__ __forceinline__ void ExclusiveSum( + T (&input)[ITEMS_PER_THREAD], ///< [in] Calling thread's input items + T (&output)[ITEMS_PER_THREAD]) ///< [out] Calling thread's output items (may be aliased to \p input) + { + // Reduce consecutive thread items in registers + Sum scan_op; + T thread_partial = ThreadReduce(input, scan_op); + + // Exclusive threadblock-scan + ExclusiveSum(thread_partial, thread_partial); + + // Exclusive scan in registers with prefix + ThreadScanExclusive(input, output, scan_op, thread_partial); + } + + + /** + * \brief Computes an exclusive block-wide prefix scan using addition (+) as the scan operator. Each thread contributes an array of consecutive input elements. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * \par + * - \blocked + * - \granularity + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates an exclusive prefix sum of 512 integer items that + * are partitioned in a [blocked arrangement](index.html#sec5sec3) across 128 threads + * where each thread owns 4 consecutive items. + * \par + * \code + * #include // or equivalently + * + * __global__ void ExampleKernel(...) + * { + * // Specialize BlockScan for 128 threads on type int + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Obtain a segment of consecutive items that are blocked across threads + * int thread_data[4]; + * ... + * + * // Collectively compute the block-wide exclusive prefix sum + * int block_aggregate; + * BlockScan(temp_storage).ExclusiveSum(thread_data, thread_data, block_aggregate); + * + * \endcode + * \par + * Suppose the set of input \p thread_data across the block of threads is { [1,1,1,1], [1,1,1,1], ..., [1,1,1,1] }. The + * corresponding output \p thread_data in those threads will be { [0,1,2,3], [4,5,6,7], ..., [508,509,510,511] }. + * Furthermore the value \p 512 will be stored in \p block_aggregate for all threads. + * + * \tparam ITEMS_PER_THREAD [inferred] The number of consecutive items partitioned onto each thread. + */ + template + __device__ __forceinline__ void ExclusiveSum( + T (&input)[ITEMS_PER_THREAD], ///< [in] Calling thread's input items + T (&output)[ITEMS_PER_THREAD], ///< [out] Calling thread's output items (may be aliased to \p input) + T &block_aggregate) ///< [out] block-wide aggregate reduction of input items + { + // Reduce consecutive thread items in registers + Sum scan_op; + T thread_partial = ThreadReduce(input, scan_op); + + // Exclusive threadblock-scan + ExclusiveSum(thread_partial, thread_partial, block_aggregate); + + // Exclusive scan in registers with prefix + ThreadScanExclusive(input, output, scan_op, thread_partial); + } + + + /** + * \brief Computes an exclusive block-wide prefix scan using addition (+) as the scan operator. Each thread contributes an array of consecutive input elements. Instead of using 0 as the block-wide prefix, the call-back functor \p block_prefix_callback_op is invoked by the first warp in the block, and the value returned by lane0 in that warp is used as the "seed" value that logically prefixes the threadblock's scan inputs. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * \par + * - The \p block_prefix_callback_op functor must implement a member function T operator()(T block_aggregate). + * The functor's input parameter \p block_aggregate is the same value also returned by the scan operation. + * The functor will be invoked by the first warp of threads in the block, however only the return value from + * lane0 is applied as the block-wide prefix. Can be stateful. + * - \blocked + * - \granularity + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates a single thread block that progressively + * computes an exclusive prefix sum over multiple "tiles" of input using a + * prefix functor to maintain a running total between block-wide scans. Each tile consists + * of 512 integer items that are partitioned in a [blocked arrangement](index.html#sec5sec3) + * across 128 threads where each thread owns 4 consecutive items. + * \par + * \code + * #include // or equivalently + * + * // A stateful callback functor that maintains a running prefix to be applied + * // during consecutive scan operations. + * struct BlockPrefixCallbackOp + * { + * // Running prefix + * int running_total; + * + * // Constructor + * __device__ BlockPrefixCallbackOp(int running_total) : running_total(running_total) {} + * + * // Callback operator to be entered by the first warp of threads in the block. + * // Thread-0 is responsible for returning a value for seeding the block-wide scan. + * __device__ int operator()(int block_aggregate) + * { + * int old_prefix = running_total; + * running_total += block_aggregate; + * return old_prefix; + * } + * }; + * + * __global__ void ExampleKernel(int *d_data, int num_items, ...) + * { + * // Specialize BlockLoad, BlockStore, and BlockScan for 128 threads, 4 ints per thread + * typedef cub::BlockLoad BlockLoad; + * typedef cub::BlockStore BlockStore; + * typedef cub::BlockScan BlockScan; + * + * // Allocate aliased shared memory for BlockLoad, BlockStore, and BlockScan + * __shared__ union { + * typename BlockLoad::TempStorage load; + * typename BlockScan::TempStorage scan; + * typename BlockStore::TempStorage store; + * } temp_storage; + * + * // Initialize running total + * BlockPrefixCallbackOp prefix_op(0); + * + * // Have the block iterate over segments of items + * for (int block_offset = 0; block_offset < num_items; block_offset += 128 * 4) + * { + * // Load a segment of consecutive items that are blocked across threads + * int thread_data[4]; + * BlockLoad(temp_storage.load).Load(d_data + block_offset, thread_data); + * __syncthreads(); + * + * // Collectively compute the block-wide exclusive prefix sum + * int block_aggregate; + * BlockScan(temp_storage.scan).ExclusiveSum( + * thread_data, thread_data, block_aggregate, prefix_op); + * __syncthreads(); + * + * // Store scanned items to output segment + * BlockStore(temp_storage.store).Store(d_data + block_offset, thread_data); + * __syncthreads(); + * } + * \endcode + * \par + * Suppose the input \p d_data is 1, 1, 1, 1, 1, 1, 1, 1, .... + * The corresponding output for the first segment will be 0, 1, 2, 3, ..., 510, 511. + * The output for the second segment will be 512, 513, 514, 515, ..., 1022, 1023. Furthermore, + * the value \p 512 will be stored in \p block_aggregate for all threads after each scan. + * + * \tparam ITEMS_PER_THREAD [inferred] The number of consecutive items partitioned onto each thread. + * \tparam BlockPrefixCallbackOp [inferred] Call-back functor type having member T operator()(T block_aggregate) + */ + template < + int ITEMS_PER_THREAD, + typename BlockPrefixCallbackOp> + __device__ __forceinline__ void ExclusiveSum( + T (&input)[ITEMS_PER_THREAD], ///< [in] Calling thread's input items + T (&output)[ITEMS_PER_THREAD], ///< [out] Calling thread's output items (may be aliased to \p input) + T &block_aggregate, ///< [out] block-wide aggregate reduction of input items (exclusive of the \p block_prefix_callback_op value) + BlockPrefixCallbackOp &block_prefix_callback_op) ///< [in-out] [warp0 only] Call-back functor for specifying a block-wide prefix to be applied to all inputs. + { + // Reduce consecutive thread items in registers + Sum scan_op; + T thread_partial = ThreadReduce(input, scan_op); + + // Exclusive threadblock-scan + ExclusiveSum(thread_partial, thread_partial, block_aggregate, block_prefix_callback_op); + + // Exclusive scan in registers with prefix + ThreadScanExclusive(input, output, scan_op, thread_partial); + } + + + + //@} end member group // Inclusive prefix sums + /******************************************************************//** + * \name Exclusive prefix scan operations + *********************************************************************/ + //@{ + + + /** + * \brief Computes an exclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes one input element. + * + * \par + * - Supports non-commutative scan operators. + * - \blocked + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates an exclusive prefix max scan of 128 integer items that + * are partitioned across 128 threads. + * \par + * \code + * #include // or equivalently + * + * __global__ void ExampleKernel(...) + * { + * // Specialize BlockScan for 128 threads on type int + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Obtain input item for each thread + * int thread_data; + * ... + * + * // Collectively compute the block-wide exclusive prefix max scan + * BlockScan(temp_storage).ExclusiveScan(thread_data, thread_data, INT_MIN, cub::Max()); + * + * \endcode + * \par + * Suppose the set of input \p thread_data across the block of threads is 0, -1, 2, -3, ..., 126, -127. The + * corresponding output \p thread_data in those threads will be INT_MIN, 0, 0, 2, ..., 124, 126. + * + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + */ + template + __device__ __forceinline__ void ExclusiveScan( + T input, ///< [in] Calling thread's input item + T &output, ///< [out] Calling thread's output item (may be aliased to \p input) + T identity, ///< [in] Identity value + ScanOp scan_op) ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + { + T block_aggregate; + InternalBlockScan(temp_storage, linear_tid).ExclusiveScan(input, output, identity, scan_op, block_aggregate); + } + + + /** + * \brief Computes an exclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes one input element. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * \par + * - Supports non-commutative scan operators. + * - \blocked + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates an exclusive prefix max scan of 128 integer items that + * are partitioned across 128 threads. + * \par + * \code + * #include // or equivalently + * + * __global__ void ExampleKernel(...) + * { + * // Specialize BlockScan for 128 threads on type int + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Obtain input item for each thread + * int thread_data; + * ... + * + * // Collectively compute the block-wide exclusive prefix max scan + * int block_aggregate; + * BlockScan(temp_storage).ExclusiveScan(thread_data, thread_data, INT_MIN, cub::Max(), block_aggregate); + * + * \endcode + * \par + * Suppose the set of input \p thread_data across the block of threads is 0, -1, 2, -3, ..., 126, -127. The + * corresponding output \p thread_data in those threads will be INT_MIN, 0, 0, 2, ..., 124, 126. + * Furthermore the value \p 126 will be stored in \p block_aggregate for all threads. + * + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + */ + template + __device__ __forceinline__ void ExclusiveScan( + T input, ///< [in] Calling thread's input items + T &output, ///< [out] Calling thread's output items (may be aliased to \p input) + T identity, ///< [in] Identity value + ScanOp scan_op, ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + T &block_aggregate) ///< [out] block-wide aggregate reduction of input items + { + InternalBlockScan(temp_storage, linear_tid).ExclusiveScan(input, output, identity, scan_op, block_aggregate); + } + + + /** + * \brief Computes an exclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes one input element. the call-back functor \p block_prefix_callback_op is invoked by the first warp in the block, and the value returned by lane0 in that warp is used as the "seed" value that logically prefixes the threadblock's scan inputs. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * \par + * - The \p block_prefix_callback_op functor must implement a member function T operator()(T block_aggregate). + * The functor's input parameter \p block_aggregate is the same value also returned by the scan operation. + * The functor will be invoked by the first warp of threads in the block, however only the return value from + * lane0 is applied as the block-wide prefix. Can be stateful. + * - Supports non-commutative scan operators. + * - \blocked + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates a single thread block that progressively + * computes an exclusive prefix max scan over multiple "tiles" of input using a + * prefix functor to maintain a running total between block-wide scans. Each tile consists + * of 128 integer items that are partitioned across 128 threads. + * \par + * \code + * #include // or equivalently + * + * // A stateful callback functor that maintains a running prefix to be applied + * // during consecutive scan operations. + * struct BlockPrefixCallbackOp + * { + * // Running prefix + * int running_total; + * + * // Constructor + * __device__ BlockPrefixCallbackOp(int running_total) : running_total(running_total) {} + * + * // Callback operator to be entered by the first warp of threads in the block. + * // Thread-0 is responsible for returning a value for seeding the block-wide scan. + * __device__ int operator()(int block_aggregate) + * { + * int old_prefix = running_total; + * running_total = (block_aggregate > old_prefix) ? block_aggregate : old_prefix; + * return old_prefix; + * } + * }; + * + * __global__ void ExampleKernel(int *d_data, int num_items, ...) + * { + * // Specialize BlockScan for 128 threads + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Initialize running total + * BlockPrefixCallbackOp prefix_op(INT_MIN); + * + * // Have the block iterate over segments of items + * for (int block_offset = 0; block_offset < num_items; block_offset += 128) + * { + * // Load a segment of consecutive items that are blocked across threads + * int thread_data = d_data[block_offset]; + * + * // Collectively compute the block-wide exclusive prefix max scan + * int block_aggregate; + * BlockScan(temp_storage).ExclusiveScan( + * thread_data, thread_data, INT_MIN, cub::Max(), block_aggregate, prefix_op); + * __syncthreads(); + * + * // Store scanned items to output segment + * d_data[block_offset] = thread_data; + * } + * \endcode + * \par + * Suppose the input \p d_data is 0, -1, 2, -3, 4, -5, .... + * The corresponding output for the first segment will be INT_MIN, 0, 0, 2, ..., 124, 126. + * The output for the second segment will be 126, 128, 128, 130, ..., 252, 254. Furthermore, + * \p block_aggregate will be assigned \p 126 in all threads after the first scan, assigned \p 254 after the second + * scan, etc. + * + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + * \tparam BlockPrefixCallbackOp [inferred] Call-back functor type having member T operator()(T block_aggregate) + */ + template < + typename ScanOp, + typename BlockPrefixCallbackOp> + __device__ __forceinline__ void ExclusiveScan( + T input, ///< [in] Calling thread's input item + T &output, ///< [out] Calling thread's output item (may be aliased to \p input) + T identity, ///< [in] Identity value + ScanOp scan_op, ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + T &block_aggregate, ///< [out] block-wide aggregate reduction of input items (exclusive of the \p block_prefix_callback_op value) + BlockPrefixCallbackOp &block_prefix_callback_op) ///< [in-out] [warp0 only] Call-back functor for specifying a block-wide prefix to be applied to all inputs. + { + InternalBlockScan(temp_storage, linear_tid).ExclusiveScan(input, output, identity, scan_op, block_aggregate, block_prefix_callback_op); + } + + + //@} end member group // Inclusive prefix sums + /******************************************************************//** + * \name Exclusive prefix scan operations (multiple data per thread) + *********************************************************************/ + //@{ + + + /** + * \brief Computes an exclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes an array of consecutive input elements. + * + * \par + * - Supports non-commutative scan operators. + * - \blocked + * - \granularity + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates an exclusive prefix max scan of 512 integer items that + * are partitioned in a [blocked arrangement](index.html#sec5sec3) across 128 threads + * where each thread owns 4 consecutive items. + * \par + * \code + * #include // or equivalently + * + * __global__ void ExampleKernel(...) + * { + * // Specialize BlockScan for 128 threads on type int + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Obtain a segment of consecutive items that are blocked across threads + * int thread_data[4]; + * ... + * + * // Collectively compute the block-wide exclusive prefix max scan + * BlockScan(temp_storage).ExclusiveScan(thread_data, thread_data, INT_MIN, cub::Max()); + * + * \endcode + * \par + * Suppose the set of input \p thread_data across the block of threads is + * { [0,-1,2,-3], [4,-5,6,-7], ..., [508,-509,510,-511] }. + * The corresponding output \p thread_data in those threads will be + * { [INT_MIN,0,0,2], [2,4,4,6], ..., [506,508,508,510] }. + * + * \tparam ITEMS_PER_THREAD [inferred] The number of consecutive items partitioned onto each thread. + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + */ + template < + int ITEMS_PER_THREAD, + typename ScanOp> + __device__ __forceinline__ void ExclusiveScan( + T (&input)[ITEMS_PER_THREAD], ///< [in] Calling thread's input items + T (&output)[ITEMS_PER_THREAD], ///< [out] Calling thread's output items (may be aliased to \p input) + T identity, ///< [in] Identity value + ScanOp scan_op) ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + { + // Reduce consecutive thread items in registers + T thread_partial = ThreadReduce(input, scan_op); + + // Exclusive threadblock-scan + ExclusiveScan(thread_partial, thread_partial, identity, scan_op); + + // Exclusive scan in registers with prefix + ThreadScanExclusive(input, output, scan_op, thread_partial); + } + + + /** + * \brief Computes an exclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes an array of consecutive input elements. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * \par + * - Supports non-commutative scan operators. + * - \blocked + * - \granularity + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates an exclusive prefix max scan of 512 integer items that + * are partitioned in a [blocked arrangement](index.html#sec5sec3) across 128 threads + * where each thread owns 4 consecutive items. + * \par + * \code + * #include // or equivalently + * + * __global__ void ExampleKernel(...) + * { + * // Specialize BlockScan for 128 threads on type int + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Obtain a segment of consecutive items that are blocked across threads + * int thread_data[4]; + * ... + * + * // Collectively compute the block-wide exclusive prefix max scan + * int block_aggregate; + * BlockScan(temp_storage).ExclusiveScan(thread_data, thread_data, INT_MIN, cub::Max(), block_aggregate); + * + * \endcode + * \par + * Suppose the set of input \p thread_data across the block of threads is { [0,-1,2,-3], [4,-5,6,-7], ..., [508,-509,510,-511] }. The + * corresponding output \p thread_data in those threads will be { [INT_MIN,0,0,2], [2,4,4,6], ..., [506,508,508,510] }. + * Furthermore the value \p 510 will be stored in \p block_aggregate for all threads. + * + * \tparam ITEMS_PER_THREAD [inferred] The number of consecutive items partitioned onto each thread. + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + */ + template < + int ITEMS_PER_THREAD, + typename ScanOp> + __device__ __forceinline__ void ExclusiveScan( + T (&input)[ITEMS_PER_THREAD], ///< [in] Calling thread's input items + T (&output)[ITEMS_PER_THREAD], ///< [out] Calling thread's output items (may be aliased to \p input) + T identity, ///< [in] Identity value + ScanOp scan_op, ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + T &block_aggregate) ///< [out] block-wide aggregate reduction of input items + { + // Reduce consecutive thread items in registers + T thread_partial = ThreadReduce(input, scan_op); + + // Exclusive threadblock-scan + ExclusiveScan(thread_partial, thread_partial, identity, scan_op, block_aggregate); + + // Exclusive scan in registers with prefix + ThreadScanExclusive(input, output, scan_op, thread_partial); + } + + + /** + * \brief Computes an exclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes an array of consecutive input elements. the call-back functor \p block_prefix_callback_op is invoked by the first warp in the block, and the value returned by lane0 in that warp is used as the "seed" value that logically prefixes the threadblock's scan inputs. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * \par + * - The \p block_prefix_callback_op functor must implement a member function T operator()(T block_aggregate). + * The functor's input parameter \p block_aggregate is the same value also returned by the scan operation. + * The functor will be invoked by the first warp of threads in the block, however only the return value from + * lane0 is applied as the block-wide prefix. Can be stateful. + * - Supports non-commutative scan operators. + * - \blocked + * - \granularity + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates a single thread block that progressively + * computes an exclusive prefix max scan over multiple "tiles" of input using a + * prefix functor to maintain a running total between block-wide scans. Each tile consists + * of 128 integer items that are partitioned across 128 threads. + * \par + * \code + * #include // or equivalently + * + * // A stateful callback functor that maintains a running prefix to be applied + * // during consecutive scan operations. + * struct BlockPrefixCallbackOp + * { + * // Running prefix + * int running_total; + * + * // Constructor + * __device__ BlockPrefixCallbackOp(int running_total) : running_total(running_total) {} + * + * // Callback operator to be entered by the first warp of threads in the block. + * // Thread-0 is responsible for returning a value for seeding the block-wide scan. + * __device__ int operator()(int block_aggregate) + * { + * int old_prefix = running_total; + * running_total = (block_aggregate > old_prefix) ? block_aggregate : old_prefix; + * return old_prefix; + * } + * }; + * + * __global__ void ExampleKernel(int *d_data, int num_items, ...) + * { + * // Specialize BlockLoad, BlockStore, and BlockScan for 128 threads, 4 ints per thread + * typedef cub::BlockLoad BlockLoad; + * typedef cub::BlockStore BlockStore; + * typedef cub::BlockScan BlockScan; + * + * // Allocate aliased shared memory for BlockLoad, BlockStore, and BlockScan + * __shared__ union { + * typename BlockLoad::TempStorage load; + * typename BlockScan::TempStorage scan; + * typename BlockStore::TempStorage store; + * } temp_storage; + * + * // Initialize running total + * BlockPrefixCallbackOp prefix_op(0); + * + * // Have the block iterate over segments of items + * for (int block_offset = 0; block_offset < num_items; block_offset += 128 * 4) + * { + * // Load a segment of consecutive items that are blocked across threads + * int thread_data[4]; + * BlockLoad(temp_storage.load).Load(d_data + block_offset, thread_data); + * __syncthreads(); + * + * // Collectively compute the block-wide exclusive prefix max scan + * int block_aggregate; + * BlockScan(temp_storage.scan).ExclusiveScan( + * thread_data, thread_data, INT_MIN, cub::Max(), block_aggregate, prefix_op); + * __syncthreads(); + * + * // Store scanned items to output segment + * BlockStore(temp_storage.store).Store(d_data + block_offset, thread_data); + * __syncthreads(); + * } + * \endcode + * \par + * Suppose the input \p d_data is 0, -1, 2, -3, 4, -5, .... + * The corresponding output for the first segment will be INT_MIN, 0, 0, 2, 2, 4, ..., 508, 510. + * The output for the second segment will be 510, 512, 512, 514, 514, 516, ..., 1020, 1022. Furthermore, + * \p block_aggregate will be assigned \p 510 in all threads after the first scan, assigned \p 1022 after the second + * scan, etc. + * + * \tparam ITEMS_PER_THREAD [inferred] The number of consecutive items partitioned onto each thread. + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + * \tparam BlockPrefixCallbackOp [inferred] Call-back functor type having member T operator()(T block_aggregate) + */ + template < + int ITEMS_PER_THREAD, + typename ScanOp, + typename BlockPrefixCallbackOp> + __device__ __forceinline__ void ExclusiveScan( + T (&input)[ITEMS_PER_THREAD], ///< [in] Calling thread's input items + T (&output)[ITEMS_PER_THREAD], ///< [out] Calling thread's output items (may be aliased to \p input) + T identity, ///< [in] Identity value + ScanOp scan_op, ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + T &block_aggregate, ///< [out] block-wide aggregate reduction of input items (exclusive of the \p block_prefix_callback_op value) + BlockPrefixCallbackOp &block_prefix_callback_op) ///< [in-out] [warp0 only] Call-back functor for specifying a block-wide prefix to be applied to all inputs. + { + // Reduce consecutive thread items in registers + T thread_partial = ThreadReduce(input, scan_op); + + // Exclusive threadblock-scan + ExclusiveScan(thread_partial, thread_partial, identity, scan_op, block_aggregate, block_prefix_callback_op); + + // Exclusive scan in registers with prefix + ThreadScanExclusive(input, output, scan_op, thread_partial); + } + + + //@} end member group + +#ifndef DOXYGEN_SHOULD_SKIP_THIS // Do not document + + /******************************************************************//** + * \name Exclusive prefix scan operations (identityless, single datum per thread) + *********************************************************************/ + //@{ + + + /** + * \brief Computes an exclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes one input element. With no identity value, the output computed for thread0 is undefined. + * + * \par + * - Supports non-commutative scan operators. + * - \blocked + * - \smemreuse + * + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + */ + template + __device__ __forceinline__ void ExclusiveScan( + T input, ///< [in] Calling thread's input item + T &output, ///< [out] Calling thread's output item (may be aliased to \p input) + ScanOp scan_op) ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + { + T block_aggregate; + InternalBlockScan(temp_storage, linear_tid).ExclusiveScan(input, output, scan_op, block_aggregate); + } + + + /** + * \brief Computes an exclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes one input element. Also provides every thread with the block-wide \p block_aggregate of all inputs. With no identity value, the output computed for thread0 is undefined. + * + * \par + * - Supports non-commutative scan operators. + * - \blocked + * - \smemreuse + * + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + */ + template + __device__ __forceinline__ void ExclusiveScan( + T input, ///< [in] Calling thread's input item + T &output, ///< [out] Calling thread's output item (may be aliased to \p input) + ScanOp scan_op, ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + T &block_aggregate) ///< [out] block-wide aggregate reduction of input items + { + InternalBlockScan(temp_storage, linear_tid).ExclusiveScan(input, output, scan_op, block_aggregate); + } + + + /** + * \brief Computes an exclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes one input element. the call-back functor \p block_prefix_callback_op is invoked by the first warp in the block, and the value returned by lane0 in that warp is used as the "seed" value that logically prefixes the threadblock's scan inputs. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * The \p block_prefix_callback_op functor must implement a member function T operator()(T block_aggregate). + * The functor's input parameter \p block_aggregate is the same value also returned by the scan operation. + * The functor will be invoked by the first warp of threads in the block, however only the return value from + * lane0 is applied as the block-wide prefix. Can be stateful. + * + * \par + * - Supports non-commutative scan operators. + * - \blocked + * - \smemreuse + * + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + * \tparam BlockPrefixCallbackOp [inferred] Call-back functor type having member T operator()(T block_aggregate) + */ + template < + typename ScanOp, + typename BlockPrefixCallbackOp> + __device__ __forceinline__ void ExclusiveScan( + T input, ///< [in] Calling thread's input item + T &output, ///< [out] Calling thread's output item (may be aliased to \p input) + ScanOp scan_op, ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + T &block_aggregate, ///< [out] block-wide aggregate reduction of input items (exclusive of the \p block_prefix_callback_op value) + BlockPrefixCallbackOp &block_prefix_callback_op) ///< [in-out] [warp0 only] Call-back functor for specifying a block-wide prefix to be applied to all inputs. + { + InternalBlockScan(temp_storage, linear_tid).ExclusiveScan(input, output, scan_op, block_aggregate, block_prefix_callback_op); + } + + + //@} end member group + /******************************************************************//** + * \name Exclusive prefix scan operations (identityless, multiple data per thread) + *********************************************************************/ + //@{ + + + /** + * \brief Computes an exclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes an array of consecutive input elements. With no identity value, the output computed for thread0 is undefined. + * + * \par + * - Supports non-commutative scan operators. + * - \blocked + * - \granularity + * - \smemreuse + * + * \tparam ITEMS_PER_THREAD [inferred] The number of consecutive items partitioned onto each thread. + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + */ + template < + int ITEMS_PER_THREAD, + typename ScanOp> + __device__ __forceinline__ void ExclusiveScan( + T (&input)[ITEMS_PER_THREAD], ///< [in] Calling thread's input items + T (&output)[ITEMS_PER_THREAD], ///< [out] Calling thread's output items (may be aliased to \p input) + ScanOp scan_op) ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + { + // Reduce consecutive thread items in registers + T thread_partial = ThreadReduce(input, scan_op); + + // Exclusive threadblock-scan + ExclusiveScan(thread_partial, thread_partial, scan_op); + + // Exclusive scan in registers with prefix + ThreadScanExclusive(input, output, scan_op, thread_partial, (linear_tid != 0)); + } + + + /** + * \brief Computes an exclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes an array of consecutive input elements. Also provides every thread with the block-wide \p block_aggregate of all inputs. With no identity value, the output computed for thread0 is undefined. + * + * \par + * - Supports non-commutative scan operators. + * - \blocked + * - \granularity + * - \smemreuse + * + * \tparam ITEMS_PER_THREAD [inferred] The number of consecutive items partitioned onto each thread. + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + */ + template < + int ITEMS_PER_THREAD, + typename ScanOp> + __device__ __forceinline__ void ExclusiveScan( + T (&input)[ITEMS_PER_THREAD], ///< [in] Calling thread's input items + T (&output)[ITEMS_PER_THREAD], ///< [out] Calling thread's output items (may be aliased to \p input) + ScanOp scan_op, ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + T &block_aggregate) ///< [out] block-wide aggregate reduction of input items + { + // Reduce consecutive thread items in registers + T thread_partial = ThreadReduce(input, scan_op); + + // Exclusive threadblock-scan + ExclusiveScan(thread_partial, thread_partial, scan_op, block_aggregate); + + // Exclusive scan in registers with prefix + ThreadScanExclusive(input, output, scan_op, thread_partial, (linear_tid != 0)); + } + + + /** + * \brief Computes an exclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes an array of consecutive input elements. the call-back functor \p block_prefix_callback_op is invoked by the first warp in the block, and the value returned by lane0 in that warp is used as the "seed" value that logically prefixes the threadblock's scan inputs. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * The \p block_prefix_callback_op functor must implement a member function T operator()(T block_aggregate). + * The functor's input parameter \p block_aggregate is the same value also returned by the scan operation. + * The functor will be invoked by the first warp of threads in the block, however only the return value from + * lane0 is applied as the block-wide prefix. Can be stateful. + * + * \par + * - Supports non-commutative scan operators. + * - \blocked + * - \granularity + * - \smemreuse + * + * \tparam ITEMS_PER_THREAD [inferred] The number of consecutive items partitioned onto each thread. + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + * \tparam BlockPrefixCallbackOp [inferred] Call-back functor type having member T operator()(T block_aggregate) + */ + template < + int ITEMS_PER_THREAD, + typename ScanOp, + typename BlockPrefixCallbackOp> + __device__ __forceinline__ void ExclusiveScan( + T (&input)[ITEMS_PER_THREAD], ///< [in] Calling thread's input items + T (&output)[ITEMS_PER_THREAD], ///< [out] Calling thread's output items (may be aliased to \p input) + ScanOp scan_op, ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + T &block_aggregate, ///< [out] block-wide aggregate reduction of input items (exclusive of the \p block_prefix_callback_op value) + BlockPrefixCallbackOp &block_prefix_callback_op) ///< [in-out] [warp0 only] Call-back functor for specifying a block-wide prefix to be applied to all inputs. + { + // Reduce consecutive thread items in registers + T thread_partial = ThreadReduce(input, scan_op); + + // Exclusive threadblock-scan + ExclusiveScan(thread_partial, thread_partial, scan_op, block_aggregate, block_prefix_callback_op); + + // Exclusive scan in registers with prefix + ThreadScanExclusive(input, output, scan_op, thread_partial); + } + + + //@} end member group + +#endif // DOXYGEN_SHOULD_SKIP_THIS + + /******************************************************************//** + * \name Inclusive prefix sum operations + *********************************************************************/ + //@{ + + + /** + * \brief Computes an inclusive block-wide prefix scan using addition (+) as the scan operator. Each thread contributes one input element. + * + * \par + * - \blocked + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates an inclusive prefix sum of 128 integer items that + * are partitioned across 128 threads. + * \par + * \code + * #include // or equivalently + * + * __global__ void ExampleKernel(...) + * { + * // Specialize BlockScan for 128 threads on type int + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Obtain input item for each thread + * int thread_data; + * ... + * + * // Collectively compute the block-wide inclusive prefix sum + * BlockScan(temp_storage).InclusiveSum(thread_data, thread_data); + * + * \endcode + * \par + * Suppose the set of input \p thread_data across the block of threads is 1, 1, ..., 1. The + * corresponding output \p thread_data in those threads will be 1, 2, ..., 128. + * + */ + __device__ __forceinline__ void InclusiveSum( + T input, ///< [in] Calling thread's input item + T &output) ///< [out] Calling thread's output item (may be aliased to \p input) + { + T block_aggregate; + InternalBlockScan(temp_storage, linear_tid).InclusiveSum(input, output, block_aggregate); + } + + + /** + * \brief Computes an inclusive block-wide prefix scan using addition (+) as the scan operator. Each thread contributes one input element. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * \par + * - \blocked + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates an inclusive prefix sum of 128 integer items that + * are partitioned across 128 threads. + * \par + * \code + * #include // or equivalently + * + * __global__ void ExampleKernel(...) + * { + * // Specialize BlockScan for 128 threads on type int + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Obtain input item for each thread + * int thread_data; + * ... + * + * // Collectively compute the block-wide inclusive prefix sum + * int block_aggregate; + * BlockScan(temp_storage).InclusiveSum(thread_data, thread_data, block_aggregate); + * + * \endcode + * \par + * Suppose the set of input \p thread_data across the block of threads is 1, 1, ..., 1. The + * corresponding output \p thread_data in those threads will be 1, 2, ..., 128. + * Furthermore the value \p 128 will be stored in \p block_aggregate for all threads. + * + */ + __device__ __forceinline__ void InclusiveSum( + T input, ///< [in] Calling thread's input item + T &output, ///< [out] Calling thread's output item (may be aliased to \p input) + T &block_aggregate) ///< [out] block-wide aggregate reduction of input items + { + InternalBlockScan(temp_storage, linear_tid).InclusiveSum(input, output, block_aggregate); + } + + + + /** + * \brief Computes an inclusive block-wide prefix scan using addition (+) as the scan operator. Each thread contributes one input element. Instead of using 0 as the block-wide prefix, the call-back functor \p block_prefix_callback_op is invoked by the first warp in the block, and the value returned by lane0 in that warp is used as the "seed" value that logically prefixes the threadblock's scan inputs. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * \par + * - The \p block_prefix_callback_op functor must implement a member function T operator()(T block_aggregate). + * The functor's input parameter \p block_aggregate is the same value also returned by the scan operation. + * The functor will be invoked by the first warp of threads in the block, however only the return value from + * lane0 is applied as the block-wide prefix. Can be stateful. + * - \blocked + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates a single thread block that progressively + * computes an inclusive prefix sum over multiple "tiles" of input using a + * prefix functor to maintain a running total between block-wide scans. Each tile consists + * of 128 integer items that are partitioned across 128 threads. + * \par + * \code + * #include // or equivalently + * + * // A stateful callback functor that maintains a running prefix to be applied + * // during consecutive scan operations. + * struct BlockPrefixCallbackOp + * { + * // Running prefix + * int running_total; + * + * // Constructor + * __device__ BlockPrefixCallbackOp(int running_total) : running_total(running_total) {} + * + * // Callback operator to be entered by the first warp of threads in the block. + * // Thread-0 is responsible for returning a value for seeding the block-wide scan. + * __device__ int operator()(int block_aggregate) + * { + * int old_prefix = running_total; + * running_total += block_aggregate; + * return old_prefix; + * } + * }; + * + * __global__ void ExampleKernel(int *d_data, int num_items, ...) + * { + * // Specialize BlockScan for 128 threads + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Initialize running total + * BlockPrefixCallbackOp prefix_op(0); + * + * // Have the block iterate over segments of items + * for (int block_offset = 0; block_offset < num_items; block_offset += 128) + * { + * // Load a segment of consecutive items that are blocked across threads + * int thread_data = d_data[block_offset]; + * + * // Collectively compute the block-wide inclusive prefix sum + * int block_aggregate; + * BlockScan(temp_storage).InclusiveSum( + * thread_data, thread_data, block_aggregate, prefix_op); + * __syncthreads(); + * + * // Store scanned items to output segment + * d_data[block_offset] = thread_data; + * } + * \endcode + * \par + * Suppose the input \p d_data is 1, 1, 1, 1, 1, 1, 1, 1, .... + * The corresponding output for the first segment will be 1, 2, ..., 128. + * The output for the second segment will be 129, 130, ..., 256. Furthermore, + * the value \p 128 will be stored in \p block_aggregate for all threads after each scan. + * + * \tparam BlockPrefixCallbackOp [inferred] Call-back functor type having member T operator()(T block_aggregate) + */ + template + __device__ __forceinline__ void InclusiveSum( + T input, ///< [in] Calling thread's input item + T &output, ///< [out] Calling thread's output item (may be aliased to \p input) + T &block_aggregate, ///< [out] block-wide aggregate reduction of input items (exclusive of the \p block_prefix_callback_op value) + BlockPrefixCallbackOp &block_prefix_callback_op) ///< [in-out] [warp0 only] Call-back functor for specifying a block-wide prefix to be applied to all inputs. + { + InternalBlockScan(temp_storage, linear_tid).InclusiveSum(input, output, block_aggregate, block_prefix_callback_op); + } + + + //@} end member group + /******************************************************************//** + * \name Inclusive prefix sum operations (multiple data per thread) + *********************************************************************/ + //@{ + + + /** + * \brief Computes an inclusive block-wide prefix scan using addition (+) as the scan operator. Each thread contributes an array of consecutive input elements. + * + * \par + * - \blocked + * - \granularity + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates an inclusive prefix sum of 512 integer items that + * are partitioned in a [blocked arrangement](index.html#sec5sec3) across 128 threads + * where each thread owns 4 consecutive items. + * \par + * \code + * #include // or equivalently + * + * __global__ void ExampleKernel(...) + * { + * // Specialize BlockScan for 128 threads on type int + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Obtain a segment of consecutive items that are blocked across threads + * int thread_data[4]; + * ... + * + * // Collectively compute the block-wide inclusive prefix sum + * BlockScan(temp_storage).InclusiveSum(thread_data, thread_data); + * + * \endcode + * \par + * Suppose the set of input \p thread_data across the block of threads is { [1,1,1,1], [1,1,1,1], ..., [1,1,1,1] }. The + * corresponding output \p thread_data in those threads will be { [1,2,3,4], [5,6,7,8], ..., [509,510,511,512] }. + * + * \tparam ITEMS_PER_THREAD [inferred] The number of consecutive items partitioned onto each thread. + */ + template + __device__ __forceinline__ void InclusiveSum( + T (&input)[ITEMS_PER_THREAD], ///< [in] Calling thread's input items + T (&output)[ITEMS_PER_THREAD]) ///< [out] Calling thread's output items (may be aliased to \p input) + { + if (ITEMS_PER_THREAD == 1) + { + InclusiveSum(input[0], output[0]); + } + else + { + // Reduce consecutive thread items in registers + Sum scan_op; + T thread_partial = ThreadReduce(input, scan_op); + + // Exclusive threadblock-scan + ExclusiveSum(thread_partial, thread_partial); + + // Inclusive scan in registers with prefix + ThreadScanInclusive(input, output, scan_op, thread_partial, (linear_tid != 0)); + } + } + + + /** + * \brief Computes an inclusive block-wide prefix scan using addition (+) as the scan operator. Each thread contributes an array of consecutive input elements. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * \par + * - \blocked + * - \granularity + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates an inclusive prefix sum of 512 integer items that + * are partitioned in a [blocked arrangement](index.html#sec5sec3) across 128 threads + * where each thread owns 4 consecutive items. + * \par + * \code + * #include // or equivalently + * + * __global__ void ExampleKernel(...) + * { + * // Specialize BlockScan for 128 threads on type int + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Obtain a segment of consecutive items that are blocked across threads + * int thread_data[4]; + * ... + * + * // Collectively compute the block-wide inclusive prefix sum + * int block_aggregate; + * BlockScan(temp_storage).InclusiveSum(thread_data, thread_data, block_aggregate); + * + * \endcode + * \par + * Suppose the set of input \p thread_data across the block of threads is + * { [1,1,1,1], [1,1,1,1], ..., [1,1,1,1] }. The + * corresponding output \p thread_data in those threads will be + * { [1,2,3,4], [5,6,7,8], ..., [509,510,511,512] }. + * Furthermore the value \p 512 will be stored in \p block_aggregate for all threads. + * + * \tparam ITEMS_PER_THREAD [inferred] The number of consecutive items partitioned onto each thread. + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + */ + template + __device__ __forceinline__ void InclusiveSum( + T (&input)[ITEMS_PER_THREAD], ///< [in] Calling thread's input items + T (&output)[ITEMS_PER_THREAD], ///< [out] Calling thread's output items (may be aliased to \p input) + T &block_aggregate) ///< [out] block-wide aggregate reduction of input items + { + if (ITEMS_PER_THREAD == 1) + { + InclusiveSum(input[0], output[0], block_aggregate); + } + else + { + // Reduce consecutive thread items in registers + Sum scan_op; + T thread_partial = ThreadReduce(input, scan_op); + + // Exclusive threadblock-scan + ExclusiveSum(thread_partial, thread_partial, block_aggregate); + + // Inclusive scan in registers with prefix + ThreadScanInclusive(input, output, scan_op, thread_partial, (linear_tid != 0)); + } + } + + + /** + * \brief Computes an inclusive block-wide prefix scan using addition (+) as the scan operator. Each thread contributes an array of consecutive input elements. Instead of using 0 as the block-wide prefix, the call-back functor \p block_prefix_callback_op is invoked by the first warp in the block, and the value returned by lane0 in that warp is used as the "seed" value that logically prefixes the threadblock's scan inputs. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * \par + * - The \p block_prefix_callback_op functor must implement a member function T operator()(T block_aggregate). + * The functor's input parameter \p block_aggregate is the same value also returned by the scan operation. + * The functor will be invoked by the first warp of threads in the block, however only the return value from + * lane0 is applied as the block-wide prefix. Can be stateful. + * - \blocked + * - \granularity + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates a single thread block that progressively + * computes an inclusive prefix sum over multiple "tiles" of input using a + * prefix functor to maintain a running total between block-wide scans. Each tile consists + * of 512 integer items that are partitioned in a [blocked arrangement](index.html#sec5sec3) + * across 128 threads where each thread owns 4 consecutive items. + * \par + * \code + * #include // or equivalently + * + * // A stateful callback functor that maintains a running prefix to be applied + * // during consecutive scan operations. + * struct BlockPrefixCallbackOp + * { + * // Running prefix + * int running_total; + * + * // Constructor + * __device__ BlockPrefixCallbackOp(int running_total) : running_total(running_total) {} + * + * // Callback operator to be entered by the first warp of threads in the block. + * // Thread-0 is responsible for returning a value for seeding the block-wide scan. + * __device__ int operator()(int block_aggregate) + * { + * int old_prefix = running_total; + * running_total += block_aggregate; + * return old_prefix; + * } + * }; + * + * __global__ void ExampleKernel(int *d_data, int num_items, ...) + * { + * // Specialize BlockLoad, BlockStore, and BlockScan for 128 threads, 4 ints per thread + * typedef cub::BlockLoad BlockLoad; + * typedef cub::BlockStore BlockStore; + * typedef cub::BlockScan BlockScan; + * + * // Allocate aliased shared memory for BlockLoad, BlockStore, and BlockScan + * __shared__ union { + * typename BlockLoad::TempStorage load; + * typename BlockScan::TempStorage scan; + * typename BlockStore::TempStorage store; + * } temp_storage; + * + * // Initialize running total + * BlockPrefixCallbackOp prefix_op(0); + * + * // Have the block iterate over segments of items + * for (int block_offset = 0; block_offset < num_items; block_offset += 128 * 4) + * { + * // Load a segment of consecutive items that are blocked across threads + * int thread_data[4]; + * BlockLoad(temp_storage.load).Load(d_data + block_offset, thread_data); + * __syncthreads(); + * + * // Collectively compute the block-wide inclusive prefix sum + * int block_aggregate; + * BlockScan(temp_storage.scan).IncluisveSum( + * thread_data, thread_data, block_aggregate, prefix_op); + * __syncthreads(); + * + * // Store scanned items to output segment + * BlockStore(temp_storage.store).Store(d_data + block_offset, thread_data); + * __syncthreads(); + * } + * \endcode + * \par + * Suppose the input \p d_data is 1, 1, 1, 1, 1, 1, 1, 1, .... + * The corresponding output for the first segment will be 1, 2, 3, 4, ..., 511, 512. + * The output for the second segment will be 513, 514, 515, 516, ..., 1023, 1024. Furthermore, + * the value \p 512 will be stored in \p block_aggregate for all threads after each scan. + * + * \tparam ITEMS_PER_THREAD [inferred] The number of consecutive items partitioned onto each thread. + * \tparam BlockPrefixCallbackOp [inferred] Call-back functor type having member T operator()(T block_aggregate) + */ + template < + int ITEMS_PER_THREAD, + typename BlockPrefixCallbackOp> + __device__ __forceinline__ void InclusiveSum( + T (&input)[ITEMS_PER_THREAD], ///< [in] Calling thread's input items + T (&output)[ITEMS_PER_THREAD], ///< [out] Calling thread's output items (may be aliased to \p input) + T &block_aggregate, ///< [out] block-wide aggregate reduction of input items (exclusive of the \p block_prefix_callback_op value) + BlockPrefixCallbackOp &block_prefix_callback_op) ///< [in-out] [warp0 only] Call-back functor for specifying a block-wide prefix to be applied to all inputs. + { + if (ITEMS_PER_THREAD == 1) + { + InclusiveSum(input[0], output[0], block_aggregate, block_prefix_callback_op); + } + else + { + // Reduce consecutive thread items in registers + Sum scan_op; + T thread_partial = ThreadReduce(input, scan_op); + + // Exclusive threadblock-scan + ExclusiveSum(thread_partial, thread_partial, block_aggregate, block_prefix_callback_op); + + // Inclusive scan in registers with prefix + ThreadScanInclusive(input, output, scan_op, thread_partial); + } + } + + + //@} end member group + /******************************************************************//** + * \name Inclusive prefix scan operations + *********************************************************************/ + //@{ + + + /** + * \brief Computes an inclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes one input element. + * + * \par + * - Supports non-commutative scan operators. + * - \blocked + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates an inclusive prefix max scan of 128 integer items that + * are partitioned across 128 threads. + * \par + * \code + * #include // or equivalently + * + * __global__ void ExampleKernel(...) + * { + * // Specialize BlockScan for 128 threads on type int + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Obtain input item for each thread + * int thread_data; + * ... + * + * // Collectively compute the block-wide inclusive prefix max scan + * BlockScan(temp_storage).InclusiveScan(thread_data, thread_data, cub::Max()); + * + * \endcode + * \par + * Suppose the set of input \p thread_data across the block of threads is 0, -1, 2, -3, ..., 126, -127. The + * corresponding output \p thread_data in those threads will be 0, 0, 2, 2, ..., 126, 126. + * + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + */ + template + __device__ __forceinline__ void InclusiveScan( + T input, ///< [in] Calling thread's input item + T &output, ///< [out] Calling thread's output item (may be aliased to \p input) + ScanOp scan_op) ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + { + T block_aggregate; + InclusiveScan(input, output, scan_op, block_aggregate); + } + + + /** + * \brief Computes an inclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes one input element. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * \par + * - Supports non-commutative scan operators. + * - \blocked + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates an inclusive prefix max scan of 128 integer items that + * are partitioned across 128 threads. + * \par + * \code + * #include // or equivalently + * + * __global__ void ExampleKernel(...) + * { + * // Specialize BlockScan for 128 threads on type int + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Obtain input item for each thread + * int thread_data; + * ... + * + * // Collectively compute the block-wide inclusive prefix max scan + * int block_aggregate; + * BlockScan(temp_storage).InclusiveScan(thread_data, thread_data, cub::Max(), block_aggregate); + * + * \endcode + * \par + * Suppose the set of input \p thread_data across the block of threads is 0, -1, 2, -3, ..., 126, -127. The + * corresponding output \p thread_data in those threads will be 0, 0, 2, 2, ..., 126, 126. + * Furthermore the value \p 126 will be stored in \p block_aggregate for all threads. + * + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + */ + template + __device__ __forceinline__ void InclusiveScan( + T input, ///< [in] Calling thread's input item + T &output, ///< [out] Calling thread's output item (may be aliased to \p input) + ScanOp scan_op, ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + T &block_aggregate) ///< [out] block-wide aggregate reduction of input items + { + InternalBlockScan(temp_storage, linear_tid).InclusiveScan(input, output, scan_op, block_aggregate); + } + + + /** + * \brief Computes an inclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes one input element. the call-back functor \p block_prefix_callback_op is invoked by the first warp in the block, and the value returned by lane0 in that warp is used as the "seed" value that logically prefixes the threadblock's scan inputs. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * \par + * - The \p block_prefix_callback_op functor must implement a member function T operator()(T block_aggregate). + * The functor's input parameter \p block_aggregate is the same value also returned by the scan operation. + * The functor will be invoked by the first warp of threads in the block, however only the return value from + * lane0 is applied as the block-wide prefix. Can be stateful. + * - Supports non-commutative scan operators. + * - \blocked + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates a single thread block that progressively + * computes an inclusive prefix max scan over multiple "tiles" of input using a + * prefix functor to maintain a running total between block-wide scans. Each tile consists + * of 128 integer items that are partitioned across 128 threads. + * \par + * \code + * #include // or equivalently + * + * // A stateful callback functor that maintains a running prefix to be applied + * // during consecutive scan operations. + * struct BlockPrefixCallbackOp + * { + * // Running prefix + * int running_total; + * + * // Constructor + * __device__ BlockPrefixCallbackOp(int running_total) : running_total(running_total) {} + * + * // Callback operator to be entered by the first warp of threads in the block. + * // Thread-0 is responsible for returning a value for seeding the block-wide scan. + * __device__ int operator()(int block_aggregate) + * { + * int old_prefix = running_total; + * running_total = (block_aggregate > old_prefix) ? block_aggregate : old_prefix; + * return old_prefix; + * } + * }; + * + * __global__ void ExampleKernel(int *d_data, int num_items, ...) + * { + * // Specialize BlockScan for 128 threads + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Initialize running total + * BlockPrefixCallbackOp prefix_op(INT_MIN); + * + * // Have the block iterate over segments of items + * for (int block_offset = 0; block_offset < num_items; block_offset += 128) + * { + * // Load a segment of consecutive items that are blocked across threads + * int thread_data = d_data[block_offset]; + * + * // Collectively compute the block-wide inclusive prefix max scan + * int block_aggregate; + * BlockScan(temp_storage).InclusiveScan( + * thread_data, thread_data, cub::Max(), block_aggregate, prefix_op); + * __syncthreads(); + * + * // Store scanned items to output segment + * d_data[block_offset] = thread_data; + * } + * \endcode + * \par + * Suppose the input \p d_data is 0, -1, 2, -3, 4, -5, .... + * The corresponding output for the first segment will be 0, 0, 2, 2, ..., 126, 126. + * The output for the second segment will be 128, 128, 130, 130, ..., 254, 254. Furthermore, + * \p block_aggregate will be assigned \p 126 in all threads after the first scan, assigned \p 254 after the second + * scan, etc. + * + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + * \tparam BlockPrefixCallbackOp [inferred] Call-back functor type having member T operator()(T block_aggregate) + */ + template < + typename ScanOp, + typename BlockPrefixCallbackOp> + __device__ __forceinline__ void InclusiveScan( + T input, ///< [in] Calling thread's input item + T &output, ///< [out] Calling thread's output item (may be aliased to \p input) + ScanOp scan_op, ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + T &block_aggregate, ///< [out] block-wide aggregate reduction of input items (exclusive of the \p block_prefix_callback_op value) + BlockPrefixCallbackOp &block_prefix_callback_op) ///< [in-out] [warp0 only] Call-back functor for specifying a block-wide prefix to be applied to all inputs. + { + InternalBlockScan(temp_storage, linear_tid).InclusiveScan(input, output, scan_op, block_aggregate, block_prefix_callback_op); + } + + + //@} end member group + /******************************************************************//** + * \name Inclusive prefix scan operations (multiple data per thread) + *********************************************************************/ + //@{ + + + /** + * \brief Computes an inclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes an array of consecutive input elements. + * + * \par + * - Supports non-commutative scan operators. + * - \blocked + * - \granularity + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates an inclusive prefix max scan of 512 integer items that + * are partitioned in a [blocked arrangement](index.html#sec5sec3) across 128 threads + * where each thread owns 4 consecutive items. + * \par + * \code + * #include // or equivalently + * + * __global__ void ExampleKernel(...) + * { + * // Specialize BlockScan for 128 threads on type int + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Obtain a segment of consecutive items that are blocked across threads + * int thread_data[4]; + * ... + * + * // Collectively compute the block-wide inclusive prefix max scan + * BlockScan(temp_storage).InclusiveScan(thread_data, thread_data, cub::Max()); + * + * \endcode + * \par + * Suppose the set of input \p thread_data across the block of threads is { [0,-1,2,-3], [4,-5,6,-7], ..., [508,-509,510,-511] }. The + * corresponding output \p thread_data in those threads will be { [0,0,2,2], [4,4,6,6], ..., [508,508,510,510] }. + * + * \tparam ITEMS_PER_THREAD [inferred] The number of consecutive items partitioned onto each thread. + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + */ + template < + int ITEMS_PER_THREAD, + typename ScanOp> + __device__ __forceinline__ void InclusiveScan( + T (&input)[ITEMS_PER_THREAD], ///< [in] Calling thread's input items + T (&output)[ITEMS_PER_THREAD], ///< [out] Calling thread's output items (may be aliased to \p input) + ScanOp scan_op) ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + { + if (ITEMS_PER_THREAD == 1) + { + InclusiveScan(input[0], output[0], scan_op); + } + else + { + // Reduce consecutive thread items in registers + T thread_partial = ThreadReduce(input, scan_op); + + // Exclusive threadblock-scan + ExclusiveScan(thread_partial, thread_partial, scan_op); + + // Inclusive scan in registers with prefix + ThreadScanInclusive(input, output, scan_op, thread_partial, (linear_tid != 0)); + } + } + + + /** + * \brief Computes an inclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes an array of consecutive input elements. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * \par + * - Supports non-commutative scan operators. + * - \blocked + * - \granularity + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates an inclusive prefix max scan of 512 integer items that + * are partitioned in a [blocked arrangement](index.html#sec5sec3) across 128 threads + * where each thread owns 4 consecutive items. + * \par + * \code + * #include // or equivalently + * + * __global__ void ExampleKernel(...) + * { + * // Specialize BlockScan for 128 threads on type int + * typedef cub::BlockScan BlockScan; + * + * // Allocate shared memory for BlockScan + * __shared__ typename BlockScan::TempStorage temp_storage; + * + * // Obtain a segment of consecutive items that are blocked across threads + * int thread_data[4]; + * ... + * + * // Collectively compute the block-wide inclusive prefix max scan + * int block_aggregate; + * BlockScan(temp_storage).InclusiveScan(thread_data, thread_data, cub::Max(), block_aggregate); + * + * \endcode + * \par + * Suppose the set of input \p thread_data across the block of threads is + * { [0,-1,2,-3], [4,-5,6,-7], ..., [508,-509,510,-511] }. + * The corresponding output \p thread_data in those threads will be + * { [0,0,2,2], [4,4,6,6], ..., [508,508,510,510] }. + * Furthermore the value \p 510 will be stored in \p block_aggregate for all threads. + * + * \tparam ITEMS_PER_THREAD [inferred] The number of consecutive items partitioned onto each thread. + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + */ + template < + int ITEMS_PER_THREAD, + typename ScanOp> + __device__ __forceinline__ void InclusiveScan( + T (&input)[ITEMS_PER_THREAD], ///< [in] Calling thread's input items + T (&output)[ITEMS_PER_THREAD], ///< [out] Calling thread's output items (may be aliased to \p input) + ScanOp scan_op, ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + T &block_aggregate) ///< [out] block-wide aggregate reduction of input items + { + if (ITEMS_PER_THREAD == 1) + { + InclusiveScan(input[0], output[0], scan_op, block_aggregate); + } + else + { + // Reduce consecutive thread items in registers + T thread_partial = ThreadReduce(input, scan_op); + + // Exclusive threadblock-scan + ExclusiveScan(thread_partial, thread_partial, scan_op, block_aggregate); + + // Inclusive scan in registers with prefix + ThreadScanInclusive(input, output, scan_op, thread_partial, (linear_tid != 0)); + } + } + + + /** + * \brief Computes an inclusive block-wide prefix scan using the specified binary \p scan_op functor. Each thread contributes an array of consecutive input elements. the call-back functor \p block_prefix_callback_op is invoked by the first warp in the block, and the value returned by lane0 in that warp is used as the "seed" value that logically prefixes the threadblock's scan inputs. Also provides every thread with the block-wide \p block_aggregate of all inputs. + * + * \par + * - The \p block_prefix_callback_op functor must implement a member function T operator()(T block_aggregate). + * The functor's input parameter \p block_aggregate is the same value also returned by the scan operation. + * The functor will be invoked by the first warp of threads in the block, however only the return value from + * lane0 is applied as the block-wide prefix. Can be stateful. + * - Supports non-commutative scan operators. + * - \blocked + * - \granularity + * - \smemreuse + * + * \par Snippet + * The code snippet below illustrates a single thread block that progressively + * computes an inclusive prefix max scan over multiple "tiles" of input using a + * prefix functor to maintain a running total between block-wide scans. Each tile consists + * of 128 integer items that are partitioned across 128 threads. + * \par + * \code + * #include // or equivalently + * + * // A stateful callback functor that maintains a running prefix to be applied + * // during consecutive scan operations. + * struct BlockPrefixCallbackOp + * { + * // Running prefix + * int running_total; + * + * // Constructor + * __device__ BlockPrefixCallbackOp(int running_total) : running_total(running_total) {} + * + * // Callback operator to be entered by the first warp of threads in the block. + * // Thread-0 is responsible for returning a value for seeding the block-wide scan. + * __device__ int operator()(int block_aggregate) + * { + * int old_prefix = running_total; + * running_total = (block_aggregate > old_prefix) ? block_aggregate : old_prefix; + * return old_prefix; + * } + * }; + * + * __global__ void ExampleKernel(int *d_data, int num_items, ...) + * { + * // Specialize BlockLoad, BlockStore, and BlockScan for 128 threads, 4 ints per thread + * typedef cub::BlockLoad BlockLoad; + * typedef cub::BlockStore BlockStore; + * typedef cub::BlockScan BlockScan; + * + * // Allocate aliased shared memory for BlockLoad, BlockStore, and BlockScan + * __shared__ union { + * typename BlockLoad::TempStorage load; + * typename BlockScan::TempStorage scan; + * typename BlockStore::TempStorage store; + * } temp_storage; + * + * // Initialize running total + * BlockPrefixCallbackOp prefix_op(0); + * + * // Have the block iterate over segments of items + * for (int block_offset = 0; block_offset < num_items; block_offset += 128 * 4) + * { + * // Load a segment of consecutive items that are blocked across threads + * int thread_data[4]; + * BlockLoad(temp_storage.load).Load(d_data + block_offset, thread_data); + * __syncthreads(); + * + * // Collectively compute the block-wide inclusive prefix max scan + * int block_aggregate; + * BlockScan(temp_storage.scan).InclusiveScan( + * thread_data, thread_data, cub::Max(), block_aggregate, prefix_op); + * __syncthreads(); + * + * // Store scanned items to output segment + * BlockStore(temp_storage.store).Store(d_data + block_offset, thread_data); + * __syncthreads(); + * } + * \endcode + * \par + * Suppose the input \p d_data is 0, -1, 2, -3, 4, -5, .... + * The corresponding output for the first segment will be 0, 0, 2, 2, 4, 4, ..., 510, 510. + * The output for the second segment will be 512, 512, 514, 514, 516, 516, ..., 1022, 1022. Furthermore, + * \p block_aggregate will be assigned \p 510 in all threads after the first scan, assigned \p 1022 after the second + * scan, etc. + * + * \tparam ITEMS_PER_THREAD [inferred] The number of consecutive items partitioned onto each thread. + * \tparam ScanOp [inferred] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) type having member T operator()(const T &a, const T &b) + * \tparam BlockPrefixCallbackOp [inferred] Call-back functor type having member T operator()(T block_aggregate) + */ + template < + int ITEMS_PER_THREAD, + typename ScanOp, + typename BlockPrefixCallbackOp> + __device__ __forceinline__ void InclusiveScan( + T (&input)[ITEMS_PER_THREAD], ///< [in] Calling thread's input items + T (&output)[ITEMS_PER_THREAD], ///< [out] Calling thread's output items (may be aliased to \p input) + ScanOp scan_op, ///< [in] Binary scan functor (e.g., an instance of cub::Sum, cub::Min, cub::Max, etc.) + T &block_aggregate, ///< [out] block-wide aggregate reduction of input items (exclusive of the \p block_prefix_callback_op value) + BlockPrefixCallbackOp &block_prefix_callback_op) ///< [in-out] [warp0 only] Call-back functor for specifying a block-wide prefix to be applied to all inputs. + { + if (ITEMS_PER_THREAD == 1) + { + InclusiveScan(input[0], output[0], scan_op, block_aggregate, block_prefix_callback_op); + } + else + { + // Reduce consecutive thread items in registers + T thread_partial = ThreadReduce(input, scan_op); + + // Exclusive threadblock-scan + ExclusiveScan(thread_partial, thread_partial, scan_op, block_aggregate, block_prefix_callback_op); + + // Inclusive scan in registers with prefix + ThreadScanInclusive(input, output, scan_op, thread_partial); + } + } + + //@} end member group + + +}; + +/** + * \example example_block_scan.cu + */ + +} // CUB namespace +CUB_NS_POSTFIX // Optional outer namespace(s) diff --git a/cub/block/block_scan.cuh.REMOVED.git-id b/cub/block/block_scan.cuh.REMOVED.git-id deleted file mode 100644 index 555b48ead8..0000000000 --- a/cub/block/block_scan.cuh.REMOVED.git-id +++ /dev/null @@ -1 +0,0 @@ -bfb784614991e6978b1bcd4c9aec1126e49ef83a \ No newline at end of file