/****************************************************************************** * Copyright (c) 2011, Duane Merrill. All rights reserved. * Copyright (c) 2011-2022, NVIDIA CORPORATION. All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are met: * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of the NVIDIA CORPORATION nor the * names of its contributors may be used to endorse or promote products * derived from this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE * ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY * DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * ******************************************************************************/ /** * @file cub::DeviceScan provides device-wide, parallel operations for * computing a prefix scan across a sequence of data items residing * within device-accessible memory. */ #pragma once #include #include #include #include #include #include #include #include #include #include CUB_NAMESPACE_BEGIN /****************************************************************************** * Kernel entry points *****************************************************************************/ /** * @brief Initialization kernel for tile status initialization (multi-block) * * @tparam ScanTileStateT * Tile status interface type * * @param[in] tile_state * Tile status interface * * @param[in] num_tiles * Number of tiles */ template __global__ void DeviceScanInitKernel(ScanTileStateT tile_state, int num_tiles) { // Initialize tile status tile_state.InitializeStatus(num_tiles); } /** * Initialization kernel for tile status initialization (multi-block) * * @tparam ScanTileStateT * Tile status interface type * * @tparam NumSelectedIteratorT * Output iterator type for recording the number of items selected * * @param[in] tile_state * Tile status interface * * @param[in] num_tiles * Number of tiles * * @param[out] d_num_selected_out * Pointer to the total number of items selected * (i.e., length of `d_selected_out`) */ template __global__ void DeviceCompactInitKernel(ScanTileStateT tile_state, int num_tiles, NumSelectedIteratorT d_num_selected_out) { // Initialize tile status tile_state.InitializeStatus(num_tiles); // Initialize d_num_selected_out if ((blockIdx.x == 0) && (threadIdx.x == 0)) { *d_num_selected_out = 0; } } /** * @brief Scan kernel entry point (multi-block) * * * @tparam ChainedPolicyT * Chained tuning policy * * @tparam InputIteratorT * Random-access input iterator type for reading scan inputs \iterator * * @tparam OutputIteratorT * Random-access output iterator type for writing scan outputs \iterator * * @tparam ScanTileStateT * Tile status interface type * * @tparam ScanOpT * Binary scan functor type having member * `auto operator()(const T &a, const U &b)` * * @tparam InitValueT * Initial value to seed the exclusive scan * (cub::NullType for inclusive scans) * * @tparam OffsetT * Signed integer type for global offsets * * @paramInput d_in * data * * @paramOutput d_out * data * * @paramTile tile_state * status interface * * @paramThe start_tile * starting tile for the current grid * * @paramBinary scan_op * scan functor * * @paramInitial init_value * value to seed the exclusive scan * * @paramTotal num_items * number of scan items for the entire problem */ template __launch_bounds__(int(ChainedPolicyT::ActivePolicy::ScanPolicyT::BLOCK_THREADS)) __global__ void DeviceScanKernel(InputIteratorT d_in, OutputIteratorT d_out, ScanTileStateT tile_state, int start_tile, ScanOpT scan_op, InitValueT init_value, OffsetT num_items) { using RealInitValueT = typename InitValueT::value_type; typedef typename ChainedPolicyT::ActivePolicy::ScanPolicyT ScanPolicyT; // Thread block type for scanning input tiles typedef AgentScan AgentScanT; // Shared memory for AgentScan __shared__ typename AgentScanT::TempStorage temp_storage; RealInitValueT real_init_value = init_value; // Process tiles AgentScanT(temp_storage, d_in, d_out, scan_op, real_init_value) .ConsumeRange(num_items, tile_state, start_tile); } /****************************************************************************** * Policy ******************************************************************************/ namespace detail { namespace scan { template struct tuning { static constexpr int threads = Threads; static constexpr int items = Items; using delay_constructor = detail::fixed_delay_constructor_t; }; template ::PRIMITIVE, std::size_t AccumSize = sizeof(AccumT)> struct sm90_tuning { static constexpr int threads = 128; static constexpr int items = 15; using delay_constructor = detail::default_delay_constructor_t; }; // clang-format off template struct sm90_tuning : tuning<192, 22, 168, 1140> {}; template struct sm90_tuning : tuning<512, 12, 376, 1125> {}; template struct sm90_tuning : tuning<128, 24, 648, 1245> {}; template struct sm90_tuning : tuning<224, 24, 632, 1290> {}; template <> struct sm90_tuning : tuning<128, 24, 688, 1140> {}; template <> struct sm90_tuning : tuning<224, 24, 576, 1215> {}; #if CUB_IS_INT128_ENABLED template <> struct sm90_tuning< __int128_t, true, false, sizeof(__int128_t)> : tuning<576, 21, 860, 630> {}; template <> struct sm90_tuning<__uint128_t, true, false, sizeof(__uint128_t)> : tuning<576, 21, 860, 630> {}; #endif // clang-format on } // namespace scan } // namespace detail template struct DeviceScanPolicy { // For large values, use timesliced loads/stores to fit shared memory. static constexpr bool LargeValues = sizeof(AccumT) > 128; static constexpr BlockLoadAlgorithm ScanTransposedLoad = LargeValues ? BLOCK_LOAD_WARP_TRANSPOSE_TIMESLICED : BLOCK_LOAD_WARP_TRANSPOSE; static constexpr BlockStoreAlgorithm ScanTransposedStore = LargeValues ? BLOCK_STORE_WARP_TRANSPOSE_TIMESLICED : BLOCK_STORE_WARP_TRANSPOSE; template using policy_t = AgentScanPolicy, DelayConstructorT>; /// SM350 struct Policy350 : ChainedPolicy<350, Policy350, Policy350> { // GTX Titan: 29.5B items/s (232.4 GB/s) @ 48M 32-bit T using ScanPolicyT = policy_t<128, 12, ///< Threads per block, items per thread AccumT, BLOCK_LOAD_DIRECT, LOAD_CA, BLOCK_STORE_WARP_TRANSPOSE_TIMESLICED, BLOCK_SCAN_RAKING, detail::default_delay_constructor_t>; }; /// SM520 struct Policy520 : ChainedPolicy<520, Policy520, Policy350> { // Titan X: 32.47B items/s @ 48M 32-bit T using ScanPolicyT = policy_t<128, 12, ///< Threads per block, items per thread AccumT, BLOCK_LOAD_DIRECT, LOAD_CA, ScanTransposedStore, BLOCK_SCAN_WARP_SCANS, detail::default_delay_constructor_t>; }; /// SM600 struct Policy600 : ChainedPolicy<600, Policy600, Policy520> { using ScanPolicyT = policy_t<128, 15, ///< Threads per block, items per thread AccumT, ScanTransposedLoad, LOAD_DEFAULT, ScanTransposedStore, BLOCK_SCAN_WARP_SCANS, detail::default_delay_constructor_t>; }; /// SM900 struct Policy900 : ChainedPolicy<900, Policy900, Policy600> { using tuning = detail::scan::sm90_tuning::value>; using ScanPolicyT = policy_t; }; using MaxPolicy = Policy900; }; /****************************************************************************** * Dispatch ******************************************************************************/ /** * @brief Utility class for dispatching the appropriately-tuned kernels for * DeviceScan * * @tparam InputIteratorT * Random-access input iterator type for reading scan inputs \iterator * * @tparam OutputIteratorT * Random-access output iterator type for writing scan outputs \iterator * * @tparam ScanOpT * Binary scan functor type having member * `auto operator()(const T &a, const U &b)` * * @tparam InitValueT * The init_value element type for ScanOpT (cub::NullType for inclusive scans) * * @tparam OffsetT * Signed integer type for global offsets * */ template ::value, cub::detail::value_t, typename InitValueT::value_type>, cub::detail::value_t>, typename SelectedPolicy = DeviceScanPolicy> struct DispatchScan : SelectedPolicy { //--------------------------------------------------------------------- // Constants and Types //--------------------------------------------------------------------- static constexpr int INIT_KERNEL_THREADS = 128; // The input value type using InputT = cub::detail::value_t; /// Device-accessible allocation of temporary storage. When NULL, the /// required allocation size is written to \p temp_storage_bytes and no work /// is done. void *d_temp_storage; /// Reference to size in bytes of \p d_temp_storage allocation size_t &temp_storage_bytes; /// Iterator to the input sequence of data items InputIteratorT d_in; /// Iterator to the output sequence of data items OutputIteratorT d_out; /// Binary scan functor ScanOpT scan_op; /// Initial value to seed the exclusive scan InitValueT init_value; /// Total number of input items (i.e., the length of \p d_in) OffsetT num_items; /// CUDA stream to launch kernels within. Default is stream0. cudaStream_t stream; int ptx_version; /** * * @param[in] d_temp_storage * Device-accessible allocation of temporary storage. When `nullptr`, the * required allocation size is written to `temp_storage_bytes` and no * work is done. * * @param[in,out] temp_storage_bytes * Reference to size in bytes of `d_temp_storage` allocation * * @param[in] d_in * Iterator to the input sequence of data items * * @param[out] d_out * Iterator to the output sequence of data items * * @param[in] num_items * Total number of input items (i.e., the length of `d_in`) * * @param[in] scan_op * Binary scan functor * * @param[in] init_value * Initial value to seed the exclusive scan * * @param[in] stream * **[optional]** CUDA stream to launch kernels within. * Default is stream0. */ CUB_RUNTIME_FUNCTION __forceinline__ DispatchScan(void *d_temp_storage, size_t &temp_storage_bytes, InputIteratorT d_in, OutputIteratorT d_out, OffsetT num_items, ScanOpT scan_op, InitValueT init_value, cudaStream_t stream, int ptx_version) : d_temp_storage(d_temp_storage) , temp_storage_bytes(temp_storage_bytes) , d_in(d_in) , d_out(d_out) , scan_op(scan_op) , init_value(init_value) , num_items(num_items) , stream(stream) , ptx_version(ptx_version) {} CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED CUB_RUNTIME_FUNCTION __forceinline__ DispatchScan(void *d_temp_storage, size_t &temp_storage_bytes, InputIteratorT d_in, OutputIteratorT d_out, OffsetT num_items, ScanOpT scan_op, InitValueT init_value, cudaStream_t stream, bool debug_synchronous, int ptx_version) : d_temp_storage(d_temp_storage) , temp_storage_bytes(temp_storage_bytes) , d_in(d_in) , d_out(d_out) , scan_op(scan_op) , init_value(init_value) , num_items(num_items) , stream(stream) , ptx_version(ptx_version) { CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG } template CUB_RUNTIME_FUNCTION __host__ __forceinline__ cudaError_t Invoke(InitKernel init_kernel, ScanKernel scan_kernel) { typedef typename ActivePolicyT::ScanPolicyT Policy; typedef typename cub::ScanTileState ScanTileStateT; // `LOAD_LDG` makes in-place execution UB and doesn't lead to better // performance. static_assert(Policy::LOAD_MODIFIER != CacheLoadModifier::LOAD_LDG, "The memory consistency model does not apply to texture " "accesses"); cudaError error = cudaSuccess; do { // Get device ordinal int device_ordinal; if (CubDebug(error = cudaGetDevice(&device_ordinal))) { break; } // Number of input tiles int tile_size = Policy::BLOCK_THREADS * Policy::ITEMS_PER_THREAD; int num_tiles = static_cast(cub::DivideAndRoundUp(num_items, 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; } // Return if empty problem if (num_items == 0) { break; } // Construct the tile status interface ScanTileStateT tile_state; if (CubDebug(error = tile_state.Init(num_tiles, allocations[0], allocation_sizes[0]))) { break; } // Log init_kernel configuration int init_grid_size = cub::DivideAndRoundUp(num_tiles, INIT_KERNEL_THREADS); #ifdef CUB_DETAIL_DEBUG_ENABLE_LOG _CubLog("Invoking init_kernel<<<%d, %d, 0, %lld>>>()\n", init_grid_size, INIT_KERNEL_THREADS, (long long)stream); #endif // Invoke init_kernel to initialize tile descriptors THRUST_NS_QUALIFIER::cuda_cub::launcher::triple_chevron( init_grid_size, INIT_KERNEL_THREADS, 0, stream) .doit(init_kernel, tile_state, num_tiles); // Check for failure to launch if (CubDebug(error = cudaPeekAtLastError())) { break; } // Sync the stream if specified to flush runtime errors error = detail::DebugSyncStream(stream); if (CubDebug(error)) { break; } // Get SM occupancy for scan_kernel int scan_sm_occupancy; if (CubDebug(error = MaxSmOccupancy(scan_sm_occupancy, // out scan_kernel, Policy::BLOCK_THREADS))) { break; } // Get max x-dimension of grid int max_dim_x; if (CubDebug(error = cudaDeviceGetAttribute(&max_dim_x, cudaDevAttrMaxGridDimX, device_ordinal))) { break; } // Run grids in epochs (in case number of tiles exceeds max x-dimension int scan_grid_size = CUB_MIN(num_tiles, max_dim_x); for (int start_tile = 0; start_tile < num_tiles; start_tile += scan_grid_size) { // Log scan_kernel configuration #ifdef CUB_DETAIL_DEBUG_ENABLE_LOG _CubLog("Invoking %d scan_kernel<<<%d, %d, 0, %lld>>>(), %d items " "per thread, %d SM occupancy\n", start_tile, scan_grid_size, Policy::BLOCK_THREADS, (long long)stream, Policy::ITEMS_PER_THREAD, scan_sm_occupancy); #endif // Invoke scan_kernel THRUST_NS_QUALIFIER::cuda_cub::launcher::triple_chevron( scan_grid_size, Policy::BLOCK_THREADS, 0, stream) .doit(scan_kernel, d_in, d_out, tile_state, start_tile, scan_op, init_value, num_items); // Check for failure to launch if (CubDebug(error = cudaPeekAtLastError())) { break; } // Sync the stream if specified to flush runtime errors error = detail::DebugSyncStream(stream); if (CubDebug(error)) { break; } } } while (0); return error; } template CUB_RUNTIME_FUNCTION __host__ __forceinline__ cudaError_t Invoke() { typedef typename DispatchScan::MaxPolicy MaxPolicyT; typedef typename cub::ScanTileState ScanTileStateT; // Ensure kernels are instantiated. return Invoke(DeviceScanInitKernel, DeviceScanKernel); } /** * @brief Internal dispatch routine * * @param[in] d_temp_storage * Device-accessible allocation of temporary storage. When `nullptr`, the * required allocation size is written to `temp_storage_bytes` and no * work is done. * * @param[in,out] temp_storage_bytes * Reference to size in bytes of `d_temp_storage` allocation * * @param[in] d_in * Iterator to the input sequence of data items * * @param[out] d_out * Iterator to the output sequence of data items * * @param[in] scan_op * Binary scan functor * * @param[in] init_value * Initial value to seed the exclusive scan * * @param[in] num_items * Total number of input items (i.e., the length of `d_in`) * * @param[in] stream * **[optional]** CUDA stream to launch kernels within. * Default is stream0. * */ CUB_RUNTIME_FUNCTION __forceinline__ static cudaError_t Dispatch(void *d_temp_storage, size_t &temp_storage_bytes, InputIteratorT d_in, OutputIteratorT d_out, ScanOpT scan_op, InitValueT init_value, OffsetT num_items, cudaStream_t stream) { typedef typename DispatchScan::MaxPolicy MaxPolicyT; cudaError_t error; do { // Get PTX version int ptx_version = 0; if (CubDebug(error = PtxVersion(ptx_version))) { break; } // Create dispatch functor DispatchScan dispatch(d_temp_storage, temp_storage_bytes, d_in, d_out, num_items, scan_op, init_value, stream, ptx_version); // Dispatch to chained policy if (CubDebug(error = MaxPolicyT::Invoke(ptx_version, dispatch))) { break; } } while (0); return error; } CUB_DETAIL_RUNTIME_DEBUG_SYNC_IS_NOT_SUPPORTED CUB_RUNTIME_FUNCTION __forceinline__ static cudaError_t Dispatch(void *d_temp_storage, size_t &temp_storage_bytes, InputIteratorT d_in, OutputIteratorT d_out, ScanOpT scan_op, InitValueT init_value, OffsetT num_items, cudaStream_t stream, bool debug_synchronous) { CUB_DETAIL_RUNTIME_DEBUG_SYNC_USAGE_LOG return Dispatch(d_temp_storage, temp_storage_bytes, d_in, d_out, scan_op, init_value, num_items, stream); } }; CUB_NAMESPACE_END