/****************************************************************************** * Copyright (c) 2011, Duane Merrill. All rights reserved. * Copyright (c) 2011-2018, NVIDIA CORPORATION. All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are met: * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of the NVIDIA CORPORATION nor the * names of its contributors may be used to endorse or promote products * derived from this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE * DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY * DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * ******************************************************************************/ /** * \file * cub::DeviceRle provides device-wide, parallel operations for run-length-encoding sequences of data items residing within device-accessible memory. */ #pragma once #include #include #include "dispatch_scan.cuh" #include "../../agent/agent_rle.cuh" #include "../../thread/thread_operators.cuh" #include "../../grid/grid_queue.cuh" #include "../../util_device.cuh" #include "../../util_namespace.cuh" /// Optional outer namespace(s) CUB_NS_PREFIX /// CUB namespace namespace cub { /****************************************************************************** * Kernel entry points *****************************************************************************/ /** * Select kernel entry point (multi-block) * * Performs functor-based selection if SelectOp functor type != NullType * Otherwise performs flag-based selection if FlagIterator's value type != NullType * Otherwise performs discontinuity selection (keep unique) */ template < typename AgentRlePolicyT, ///< Parameterized AgentRlePolicyT tuning policy type typename InputIteratorT, ///< Random-access input iterator type for reading input items \iterator typename OffsetsOutputIteratorT, ///< Random-access output iterator type for writing run-offset values \iterator typename LengthsOutputIteratorT, ///< Random-access output iterator type for writing run-length values \iterator typename NumRunsOutputIteratorT, ///< Output iterator type for recording the number of runs encountered \iterator typename ScanTileStateT, ///< Tile status interface type typename EqualityOpT, ///< T equality operator type typename OffsetT> ///< Signed integer type for global offsets __launch_bounds__ (int(AgentRlePolicyT::BLOCK_THREADS)) __global__ void DeviceRleSweepKernel( InputIteratorT d_in, ///< [in] Pointer to input sequence of data items OffsetsOutputIteratorT d_offsets_out, ///< [out] Pointer to output sequence of run-offsets LengthsOutputIteratorT d_lengths_out, ///< [out] Pointer to output sequence of run-lengths NumRunsOutputIteratorT d_num_runs_out, ///< [out] Pointer to total number of runs (i.e., length of \p d_offsets_out) ScanTileStateT tile_status, ///< [in] Tile status interface EqualityOpT equality_op, ///< [in] Equality operator for input items OffsetT num_items, ///< [in] Total number of input items (i.e., length of \p d_in) int num_tiles) ///< [in] Total number of tiles for the entire problem { // Thread block type for selecting data from input tiles typedef AgentRle< AgentRlePolicyT, InputIteratorT, OffsetsOutputIteratorT, LengthsOutputIteratorT, EqualityOpT, OffsetT> AgentRleT; // Shared memory for AgentRle __shared__ typename AgentRleT::TempStorage temp_storage; // Process tiles AgentRleT(temp_storage, d_in, d_offsets_out, d_lengths_out, equality_op, num_items).ConsumeRange( num_tiles, tile_status, d_num_runs_out); } /****************************************************************************** * Dispatch ******************************************************************************/ /** * Utility class for dispatching the appropriately-tuned kernels for DeviceRle */ template < typename InputIteratorT, ///< Random-access input iterator type for reading input items \iterator typename OffsetsOutputIteratorT, ///< Random-access output iterator type for writing run-offset values \iterator typename LengthsOutputIteratorT, ///< Random-access output iterator type for writing run-length values \iterator typename NumRunsOutputIteratorT, ///< Output iterator type for recording the number of runs encountered \iterator typename EqualityOpT, ///< T equality operator type typename OffsetT> ///< Signed integer type for global offsets struct DeviceRleDispatch { /****************************************************************************** * Types and constants ******************************************************************************/ // The input value type typedef typename std::iterator_traits::value_type T; // The lengths output value type typedef typename If<(Equals::value_type, void>::VALUE), // LengthT = (if output iterator's value type is void) ? OffsetT, // ... then the OffsetT type, typename std::iterator_traits::value_type>::Type LengthT; // ... else the output iterator's value type enum { INIT_KERNEL_THREADS = 128, }; // Tile status descriptor interface type typedef ReduceByKeyScanTileState ScanTileStateT; /****************************************************************************** * Tuning policies ******************************************************************************/ /// SM35 struct Policy350 { enum { NOMINAL_4B_ITEMS_PER_THREAD = 15, ITEMS_PER_THREAD = CUB_MIN(NOMINAL_4B_ITEMS_PER_THREAD, CUB_MAX(1, (NOMINAL_4B_ITEMS_PER_THREAD * 4 / sizeof(T)))), }; typedef AgentRlePolicy< 96, ITEMS_PER_THREAD, BLOCK_LOAD_DIRECT, LOAD_LDG, true, BLOCK_SCAN_WARP_SCANS> RleSweepPolicy; }; /// SM30 struct Policy300 { enum { NOMINAL_4B_ITEMS_PER_THREAD = 5, ITEMS_PER_THREAD = CUB_MIN(NOMINAL_4B_ITEMS_PER_THREAD, CUB_MAX(1, (NOMINAL_4B_ITEMS_PER_THREAD * 4 / sizeof(T)))), }; typedef AgentRlePolicy< 256, ITEMS_PER_THREAD, BLOCK_LOAD_WARP_TRANSPOSE, LOAD_DEFAULT, true, BLOCK_SCAN_RAKING_MEMOIZE> RleSweepPolicy; }; /// SM20 struct Policy200 { enum { NOMINAL_4B_ITEMS_PER_THREAD = 15, ITEMS_PER_THREAD = CUB_MIN(NOMINAL_4B_ITEMS_PER_THREAD, CUB_MAX(1, (NOMINAL_4B_ITEMS_PER_THREAD * 4 / sizeof(T)))), }; typedef AgentRlePolicy< 128, ITEMS_PER_THREAD, BLOCK_LOAD_WARP_TRANSPOSE, LOAD_DEFAULT, false, BLOCK_SCAN_WARP_SCANS> RleSweepPolicy; }; /// SM13 struct Policy130 { enum { NOMINAL_4B_ITEMS_PER_THREAD = 9, ITEMS_PER_THREAD = CUB_MIN(NOMINAL_4B_ITEMS_PER_THREAD, CUB_MAX(1, (NOMINAL_4B_ITEMS_PER_THREAD * 4 / sizeof(T)))), }; typedef AgentRlePolicy< 64, ITEMS_PER_THREAD, BLOCK_LOAD_WARP_TRANSPOSE, LOAD_DEFAULT, true, BLOCK_SCAN_RAKING_MEMOIZE> RleSweepPolicy; }; /// SM10 struct Policy100 { enum { NOMINAL_4B_ITEMS_PER_THREAD = 9, ITEMS_PER_THREAD = CUB_MIN(NOMINAL_4B_ITEMS_PER_THREAD, CUB_MAX(1, (NOMINAL_4B_ITEMS_PER_THREAD * 4 / sizeof(T)))), }; typedef AgentRlePolicy< 256, ITEMS_PER_THREAD, BLOCK_LOAD_WARP_TRANSPOSE, LOAD_DEFAULT, true, BLOCK_SCAN_RAKING_MEMOIZE> RleSweepPolicy; }; /****************************************************************************** * Tuning policies of current PTX compiler pass ******************************************************************************/ #if (CUB_PTX_ARCH >= 350) typedef Policy350 PtxPolicy; #elif (CUB_PTX_ARCH >= 300) typedef Policy300 PtxPolicy; #elif (CUB_PTX_ARCH >= 200) typedef Policy200 PtxPolicy; #elif (CUB_PTX_ARCH >= 130) typedef Policy130 PtxPolicy; #else typedef Policy100 PtxPolicy; #endif // "Opaque" policies (whose parameterizations aren't reflected in the type signature) struct PtxRleSweepPolicy : PtxPolicy::RleSweepPolicy {}; /****************************************************************************** * Utilities ******************************************************************************/ /** * Initialize kernel dispatch configurations with the policies corresponding to the PTX assembly we will use */ template CUB_RUNTIME_FUNCTION __forceinline__ static void InitConfigs( int ptx_version, KernelConfig& device_rle_config) { #if (CUB_PTX_ARCH > 0) // We're on the device, so initialize the kernel dispatch configurations with the current PTX policy device_rle_config.template Init(); #else // We're on the host, so lookup and initialize the kernel dispatch configurations with the policies that match the device's PTX version if (ptx_version >= 350) { device_rle_config.template Init(); } else if (ptx_version >= 300) { device_rle_config.template Init(); } else if (ptx_version >= 200) { device_rle_config.template Init(); } else if (ptx_version >= 130) { device_rle_config.template Init(); } else { device_rle_config.template Init(); } #endif } /** * Kernel kernel dispatch configuration. Mirrors the constants within AgentRlePolicyT. */ struct KernelConfig { int block_threads; int items_per_thread; BlockLoadAlgorithm load_policy; bool store_warp_time_slicing; BlockScanAlgorithm scan_algorithm; template CUB_RUNTIME_FUNCTION __forceinline__ void Init() { block_threads = AgentRlePolicyT::BLOCK_THREADS; items_per_thread = AgentRlePolicyT::ITEMS_PER_THREAD; load_policy = AgentRlePolicyT::LOAD_ALGORITHM; store_warp_time_slicing = AgentRlePolicyT::STORE_WARP_TIME_SLICING; scan_algorithm = AgentRlePolicyT::SCAN_ALGORITHM; } CUB_RUNTIME_FUNCTION __forceinline__ void Print() { printf("%d, %d, %d, %d, %d", block_threads, items_per_thread, load_policy, store_warp_time_slicing, scan_algorithm); } }; /****************************************************************************** * Dispatch entrypoints ******************************************************************************/ /** * Internal dispatch routine for computing a device-wide run-length-encode using the * specified kernel functions. */ template < typename DeviceScanInitKernelPtr, ///< Function type of cub::DeviceScanInitKernel typename DeviceRleSweepKernelPtr> ///< Function type of cub::DeviceRleSweepKernelPtr CUB_RUNTIME_FUNCTION __forceinline__ static cudaError_t Dispatch( void* d_temp_storage, ///< [in] %Device-accessible allocation of temporary storage. When NULL, the required allocation size is written to \p temp_storage_bytes and no work is done. size_t& temp_storage_bytes, ///< [in,out] Reference to size in bytes of \p d_temp_storage allocation InputIteratorT d_in, ///< [in] Pointer to the input sequence of data items OffsetsOutputIteratorT d_offsets_out, ///< [out] Pointer to the output sequence of run-offsets LengthsOutputIteratorT d_lengths_out, ///< [out] Pointer to the output sequence of run-lengths NumRunsOutputIteratorT d_num_runs_out, ///< [out] Pointer to the total number of runs encountered (i.e., length of \p d_offsets_out) EqualityOpT equality_op, ///< [in] Equality operator for input items OffsetT num_items, ///< [in] Total number of input items (i.e., length of \p d_in) cudaStream_t stream, ///< [in] CUDA stream to launch kernels within. Default is stream0. bool debug_synchronous, ///< [in] Whether or not to synchronize the stream after every kernel launch to check for errors. Also causes launch configurations to be printed to the console. Default is \p false. int ptx_version, ///< [in] PTX version of dispatch kernels DeviceScanInitKernelPtr device_scan_init_kernel, ///< [in] Kernel function pointer to parameterization of cub::DeviceScanInitKernel DeviceRleSweepKernelPtr device_rle_sweep_kernel, ///< [in] Kernel function pointer to parameterization of cub::DeviceRleSweepKernel KernelConfig device_rle_config) ///< [in] Dispatch parameters that match the policy that \p device_rle_sweep_kernel was compiled for { #ifndef CUB_RUNTIME_ENABLED // Kernel launch not supported from this device return CubDebug(cudaErrorNotSupported); #else cudaError error = cudaSuccess; do { // Get device ordinal int device_ordinal; if (CubDebug(error = cudaGetDevice(&device_ordinal))) break; // Get SM count int sm_count; if (CubDebug(error = cudaDeviceGetAttribute (&sm_count, cudaDevAttrMultiProcessorCount, device_ordinal))) break; // Number of input tiles int tile_size = device_rle_config.block_threads * device_rle_config.items_per_thread; int num_tiles = (num_items + tile_size - 1) / tile_size; // Specify temporary storage allocation requirements size_t allocation_sizes[1]; if (CubDebug(error = ScanTileStateT::AllocationSize(num_tiles, allocation_sizes[0]))) break; // bytes needed for tile status descriptors // Compute allocation pointers into the single storage blob (or compute the necessary size of the blob) void* allocations[1]; if (CubDebug(error = AliasTemporaries(d_temp_storage, temp_storage_bytes, allocations, allocation_sizes))) break; if (d_temp_storage == NULL) { // Return if the caller is simply requesting the size of the storage allocation break; } // Construct the tile status interface ScanTileStateT tile_status; if (CubDebug(error = tile_status.Init(num_tiles, allocations[0], allocation_sizes[0]))) break; // Log device_scan_init_kernel configuration int init_grid_size = CUB_MAX(1, (num_tiles + INIT_KERNEL_THREADS - 1) / INIT_KERNEL_THREADS); if (debug_synchronous) _CubLog("Invoking device_scan_init_kernel<<<%d, %d, 0, %lld>>>()\n", init_grid_size, INIT_KERNEL_THREADS, (long long) stream); // Invoke device_scan_init_kernel to initialize tile descriptors and queue descriptors device_scan_init_kernel<<>>( tile_status, num_tiles, d_num_runs_out); // Check for failure to launch if (CubDebug(error = cudaPeekAtLastError())) break; // Sync the stream if specified to flush runtime errors if (debug_synchronous && (CubDebug(error = SyncStream(stream)))) break; // Return if empty problem if (num_items == 0) break; // Get SM occupancy for device_rle_sweep_kernel int device_rle_kernel_sm_occupancy; if (CubDebug(error = MaxSmOccupancy( device_rle_kernel_sm_occupancy, // out device_rle_sweep_kernel, device_rle_config.block_threads))) break; // Get max x-dimension of grid int max_dim_x; if (CubDebug(error = cudaDeviceGetAttribute(&max_dim_x, cudaDevAttrMaxGridDimX, device_ordinal))) break;; // Get grid size for scanning tiles dim3 scan_grid_size; scan_grid_size.z = 1; scan_grid_size.y = ((unsigned int) num_tiles + max_dim_x - 1) / max_dim_x; scan_grid_size.x = CUB_MIN(num_tiles, max_dim_x); // Log device_rle_sweep_kernel configuration if (debug_synchronous) _CubLog("Invoking device_rle_sweep_kernel<<<{%d,%d,%d}, %d, 0, %lld>>>(), %d items per thread, %d SM occupancy\n", scan_grid_size.x, scan_grid_size.y, scan_grid_size.z, device_rle_config.block_threads, (long long) stream, device_rle_config.items_per_thread, device_rle_kernel_sm_occupancy); // Invoke device_rle_sweep_kernel device_rle_sweep_kernel<<>>( d_in, d_offsets_out, d_lengths_out, d_num_runs_out, tile_status, equality_op, num_items, num_tiles); // Check for failure to launch if (CubDebug(error = cudaPeekAtLastError())) break; // Sync the stream if specified to flush runtime errors if (debug_synchronous && (CubDebug(error = SyncStream(stream)))) break; } while (0); return error; #endif // CUB_RUNTIME_ENABLED } /** * Internal dispatch routine */ CUB_RUNTIME_FUNCTION __forceinline__ static cudaError_t Dispatch( void* d_temp_storage, ///< [in] %Device-accessible allocation of temporary storage. When NULL, the required allocation size is written to \p temp_storage_bytes and no work is done. size_t& temp_storage_bytes, ///< [in,out] Reference to size in bytes of \p d_temp_storage allocation InputIteratorT d_in, ///< [in] Pointer to input sequence of data items OffsetsOutputIteratorT d_offsets_out, ///< [out] Pointer to output sequence of run-offsets LengthsOutputIteratorT d_lengths_out, ///< [out] Pointer to output sequence of run-lengths NumRunsOutputIteratorT d_num_runs_out, ///< [out] Pointer to total number of runs (i.e., length of \p d_offsets_out) EqualityOpT equality_op, ///< [in] Equality operator for input items OffsetT num_items, ///< [in] Total number of input items (i.e., length of \p d_in) cudaStream_t stream, ///< [in] [optional] CUDA stream to launch kernels within. Default is stream0. bool debug_synchronous) ///< [in] [optional] Whether or not to synchronize the stream after every kernel launch to check for errors. Also causes launch configurations to be printed to the console. Default is \p false. { cudaError error = cudaSuccess; do { // Get PTX version int ptx_version; #if (CUB_PTX_ARCH == 0) if (CubDebug(error = PtxVersion(ptx_version))) break; #else ptx_version = CUB_PTX_ARCH; #endif // Get kernel kernel dispatch configurations KernelConfig device_rle_config; InitConfigs(ptx_version, device_rle_config); // Dispatch if (CubDebug(error = Dispatch( d_temp_storage, temp_storage_bytes, d_in, d_offsets_out, d_lengths_out, d_num_runs_out, equality_op, num_items, stream, debug_synchronous, ptx_version, DeviceCompactInitKernel, DeviceRleSweepKernel, device_rle_config))) break; } while (0); return error; } }; } // CUB namespace CUB_NS_POSTFIX // Optional outer namespace(s)