/****************************************************************************** * 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::WarpReduceShfl provides SHFL-based variants of parallel reduction of items partitioned across a CUDA thread warp. */ #pragma once #include "../../config.cuh" #include "../../thread/thread_operators.cuh" #include "../../util_ptx.cuh" #include "../../util_type.cuh" #include /// Optional outer namespace(s) CUB_NS_PREFIX /// CUB namespace namespace cub { /** * \brief WarpReduceShfl provides SHFL-based variants of parallel reduction of items partitioned across a CUDA thread warp. * * LOGICAL_WARP_THREADS must be a power-of-two */ template < typename T, ///< Data type being reduced int LOGICAL_WARP_THREADS, ///< Number of threads per logical warp int PTX_ARCH> ///< The PTX compute capability for which to to specialize this collective struct WarpReduceShfl { //--------------------------------------------------------------------- // Constants and type definitions //--------------------------------------------------------------------- enum { /// Whether the logical warp size and the PTX warp size coincide IS_ARCH_WARP = (LOGICAL_WARP_THREADS == CUB_WARP_THREADS(PTX_ARCH)), /// The number of warp reduction steps STEPS = Log2::VALUE, /// Number of logical warps in a PTX warp LOGICAL_WARPS = CUB_WARP_THREADS(PTX_ARCH) / LOGICAL_WARP_THREADS, /// The 5-bit SHFL mask for logically splitting warps into sub-segments starts 8-bits up SHFL_C = (CUB_WARP_THREADS(PTX_ARCH) - LOGICAL_WARP_THREADS) << 8 }; template struct IsInteger { enum { ///Whether the data type is a small (32b or less) integer for which we can use a single SFHL instruction per exchange IS_SMALL_UNSIGNED = (Traits::CATEGORY == UNSIGNED_INTEGER) && (sizeof(S) <= sizeof(unsigned int)) }; }; /// Shared memory storage layout type typedef NullType TempStorage; //--------------------------------------------------------------------- // Thread fields //--------------------------------------------------------------------- /// Lane index in logical warp int lane_id; /// Logical warp index in 32-thread physical warp int warp_id; /// 32-thread physical warp member mask of logical warp uint32_t member_mask; //--------------------------------------------------------------------- // Construction //--------------------------------------------------------------------- /// Constructor __device__ __forceinline__ WarpReduceShfl( TempStorage &/*temp_storage*/) { lane_id = static_cast(LaneId()); warp_id = 0; member_mask = 0xffffffffu >> (CUB_WARP_THREADS(PTX_ARCH) - LOGICAL_WARP_THREADS); if (!IS_ARCH_WARP) { warp_id = lane_id / LOGICAL_WARP_THREADS; lane_id = lane_id % LOGICAL_WARP_THREADS; member_mask = member_mask << (warp_id * LOGICAL_WARP_THREADS); } } //--------------------------------------------------------------------- // Reduction steps //--------------------------------------------------------------------- /// Reduction (specialized for summation across uint32 types) __device__ __forceinline__ unsigned int ReduceStep( unsigned int input, ///< [in] Calling thread's input item. cub::Sum /*reduction_op*/, ///< [in] Binary reduction operator int last_lane, ///< [in] Index of last lane in segment int offset) ///< [in] Up-offset to pull from { unsigned int output; int shfl_c = last_lane | SHFL_C; // Shuffle control (mask and last_lane) // Use predicate set from SHFL to guard against invalid peers #ifdef CUB_USE_COOPERATIVE_GROUPS asm volatile( "{" " .reg .u32 r0;" " .reg .pred p;" " shfl.sync.down.b32 r0|p, %1, %2, %3, %5;" " @p add.u32 r0, r0, %4;" " mov.u32 %0, r0;" "}" : "=r"(output) : "r"(input), "r"(offset), "r"(shfl_c), "r"(input), "r"(member_mask)); #else asm volatile( "{" " .reg .u32 r0;" " .reg .pred p;" " shfl.down.b32 r0|p, %1, %2, %3;" " @p add.u32 r0, r0, %4;" " mov.u32 %0, r0;" "}" : "=r"(output) : "r"(input), "r"(offset), "r"(shfl_c), "r"(input)); #endif return output; } /// Reduction (specialized for summation across fp32 types) __device__ __forceinline__ float ReduceStep( float input, ///< [in] Calling thread's input item. cub::Sum /*reduction_op*/, ///< [in] Binary reduction operator int last_lane, ///< [in] Index of last lane in segment int offset) ///< [in] Up-offset to pull from { float output; int shfl_c = last_lane | SHFL_C; // Shuffle control (mask and last_lane) // Use predicate set from SHFL to guard against invalid peers #ifdef CUB_USE_COOPERATIVE_GROUPS asm volatile( "{" " .reg .f32 r0;" " .reg .pred p;" " shfl.sync.down.b32 r0|p, %1, %2, %3, %5;" " @p add.f32 r0, r0, %4;" " mov.f32 %0, r0;" "}" : "=f"(output) : "f"(input), "r"(offset), "r"(shfl_c), "f"(input), "r"(member_mask)); #else asm volatile( "{" " .reg .f32 r0;" " .reg .pred p;" " shfl.down.b32 r0|p, %1, %2, %3;" " @p add.f32 r0, r0, %4;" " mov.f32 %0, r0;" "}" : "=f"(output) : "f"(input), "r"(offset), "r"(shfl_c), "f"(input)); #endif return output; } /// Reduction (specialized for summation across unsigned long long types) __device__ __forceinline__ unsigned long long ReduceStep( unsigned long long input, ///< [in] Calling thread's input item. cub::Sum /*reduction_op*/, ///< [in] Binary reduction operator int last_lane, ///< [in] Index of last lane in segment int offset) ///< [in] Up-offset to pull from { unsigned long long output; int shfl_c = last_lane | SHFL_C; // Shuffle control (mask and last_lane) #ifdef CUB_USE_COOPERATIVE_GROUPS asm volatile( "{" " .reg .u32 lo;" " .reg .u32 hi;" " .reg .pred p;" " mov.b64 {lo, hi}, %1;" " shfl.sync.down.b32 lo|p, lo, %2, %3, %4;" " shfl.sync.down.b32 hi|p, hi, %2, %3, %4;" " mov.b64 %0, {lo, hi};" " @p add.u64 %0, %0, %1;" "}" : "=l"(output) : "l"(input), "r"(offset), "r"(shfl_c), "r"(member_mask)); #else asm volatile( "{" " .reg .u32 lo;" " .reg .u32 hi;" " .reg .pred p;" " mov.b64 {lo, hi}, %1;" " shfl.down.b32 lo|p, lo, %2, %3;" " shfl.down.b32 hi|p, hi, %2, %3;" " mov.b64 %0, {lo, hi};" " @p add.u64 %0, %0, %1;" "}" : "=l"(output) : "l"(input), "r"(offset), "r"(shfl_c)); #endif return output; } /// Reduction (specialized for summation across long long types) __device__ __forceinline__ long long ReduceStep( long long input, ///< [in] Calling thread's input item. cub::Sum /*reduction_op*/, ///< [in] Binary reduction operator int last_lane, ///< [in] Index of last lane in segment int offset) ///< [in] Up-offset to pull from { long long output; int shfl_c = last_lane | SHFL_C; // Shuffle control (mask and last_lane) // Use predicate set from SHFL to guard against invalid peers #ifdef CUB_USE_COOPERATIVE_GROUPS asm volatile( "{" " .reg .u32 lo;" " .reg .u32 hi;" " .reg .pred p;" " mov.b64 {lo, hi}, %1;" " shfl.sync.down.b32 lo|p, lo, %2, %3, %4;" " shfl.sync.down.b32 hi|p, hi, %2, %3, %4;" " mov.b64 %0, {lo, hi};" " @p add.s64 %0, %0, %1;" "}" : "=l"(output) : "l"(input), "r"(offset), "r"(shfl_c), "r"(member_mask)); #else asm volatile( "{" " .reg .u32 lo;" " .reg .u32 hi;" " .reg .pred p;" " mov.b64 {lo, hi}, %1;" " shfl.down.b32 lo|p, lo, %2, %3;" " shfl.down.b32 hi|p, hi, %2, %3;" " mov.b64 %0, {lo, hi};" " @p add.s64 %0, %0, %1;" "}" : "=l"(output) : "l"(input), "r"(offset), "r"(shfl_c)); #endif return output; } /// Reduction (specialized for summation across double types) __device__ __forceinline__ double ReduceStep( double input, ///< [in] Calling thread's input item. cub::Sum /*reduction_op*/, ///< [in] Binary reduction operator int last_lane, ///< [in] Index of last lane in segment int offset) ///< [in] Up-offset to pull from { double output; int shfl_c = last_lane | SHFL_C; // Shuffle control (mask and last_lane) // Use predicate set from SHFL to guard against invalid peers #ifdef CUB_USE_COOPERATIVE_GROUPS asm volatile( "{" " .reg .u32 lo;" " .reg .u32 hi;" " .reg .pred p;" " .reg .f64 r0;" " mov.b64 %0, %1;" " mov.b64 {lo, hi}, %1;" " shfl.sync.down.b32 lo|p, lo, %2, %3, %4;" " shfl.sync.down.b32 hi|p, hi, %2, %3, %4;" " mov.b64 r0, {lo, hi};" " @p add.f64 %0, %0, r0;" "}" : "=d"(output) : "d"(input), "r"(offset), "r"(shfl_c), "r"(member_mask)); #else asm volatile( "{" " .reg .u32 lo;" " .reg .u32 hi;" " .reg .pred p;" " .reg .f64 r0;" " mov.b64 %0, %1;" " mov.b64 {lo, hi}, %1;" " shfl.down.b32 lo|p, lo, %2, %3;" " shfl.down.b32 hi|p, hi, %2, %3;" " mov.b64 r0, {lo, hi};" " @p add.f64 %0, %0, r0;" "}" : "=d"(output) : "d"(input), "r"(offset), "r"(shfl_c)); #endif return output; } /// Reduction (specialized for swizzled ReduceByKeyOp across KeyValuePair types) template __device__ __forceinline__ KeyValuePair ReduceStep( KeyValuePair input, ///< [in] Calling thread's input item. SwizzleScanOp > /*reduction_op*/, ///< [in] Binary reduction operator int last_lane, ///< [in] Index of last lane in segment int offset) ///< [in] Up-offset to pull from { KeyValuePair output; KeyT other_key = ShuffleDown(input.key, offset, last_lane, member_mask); output.key = input.key; output.value = ReduceStep( input.value, cub::Sum(), last_lane, offset, Int2Type::IS_SMALL_UNSIGNED>()); if (input.key != other_key) output.value = input.value; return output; } /// Reduction (specialized for swizzled ReduceBySegmentOp across KeyValuePair types) template __device__ __forceinline__ KeyValuePair ReduceStep( KeyValuePair input, ///< [in] Calling thread's input item. SwizzleScanOp > /*reduction_op*/, ///< [in] Binary reduction operator int last_lane, ///< [in] Index of last lane in segment int offset) ///< [in] Up-offset to pull from { KeyValuePair output; output.value = ReduceStep(input.value, cub::Sum(), last_lane, offset, Int2Type::IS_SMALL_UNSIGNED>()); output.key = ReduceStep(input.key, cub::Sum(), last_lane, offset, Int2Type::IS_SMALL_UNSIGNED>()); if (input.key > 0) output.value = input.value; return output; } /// Reduction step (generic) template __device__ __forceinline__ _T ReduceStep( _T input, ///< [in] Calling thread's input item. ReductionOp reduction_op, ///< [in] Binary reduction operator int last_lane, ///< [in] Index of last lane in segment int offset) ///< [in] Up-offset to pull from { _T output = input; _T temp = ShuffleDown(output, offset, last_lane, member_mask); // Perform reduction op if valid if (offset + lane_id <= last_lane) output = reduction_op(input, temp); return output; } /// Reduction step (specialized for small unsigned integers size 32b or less) template __device__ __forceinline__ _T ReduceStep( _T input, ///< [in] Calling thread's input item. ReductionOp reduction_op, ///< [in] Binary reduction operator int last_lane, ///< [in] Index of last lane in segment int offset, ///< [in] Up-offset to pull from Int2Type /*is_small_unsigned*/) ///< [in] Marker type indicating whether T is a small unsigned integer { return ReduceStep(input, reduction_op, last_lane, offset); } /// Reduction step (specialized for types other than small unsigned integers size 32b or less) template __device__ __forceinline__ _T ReduceStep( _T input, ///< [in] Calling thread's input item. ReductionOp reduction_op, ///< [in] Binary reduction operator int last_lane, ///< [in] Index of last lane in segment int offset, ///< [in] Up-offset to pull from Int2Type /*is_small_unsigned*/) ///< [in] Marker type indicating whether T is a small unsigned integer { return ReduceStep(input, reduction_op, last_lane, offset); } //--------------------------------------------------------------------- // Templated inclusive scan iteration //--------------------------------------------------------------------- template __device__ __forceinline__ void ReduceStep( T& input, ///< [in] Calling thread's input item. ReductionOp reduction_op, ///< [in] Binary reduction operator int last_lane, ///< [in] Index of last lane in segment Int2Type /*step*/) { input = ReduceStep(input, reduction_op, last_lane, 1 << STEP, Int2Type::IS_SMALL_UNSIGNED>()); ReduceStep(input, reduction_op, last_lane, Int2Type()); } template __device__ __forceinline__ void ReduceStep( T& /*input*/, ///< [in] Calling thread's input item. ReductionOp /*reduction_op*/, ///< [in] Binary reduction operator int /*last_lane*/, ///< [in] Index of last lane in segment Int2Type /*step*/) {} //--------------------------------------------------------------------- // Reduction operations //--------------------------------------------------------------------- /// Reduction template < bool ALL_LANES_VALID, ///< Whether all lanes in each warp are contributing a valid fold of items typename ReductionOp> __device__ __forceinline__ T Reduce( T input, ///< [in] Calling thread's input int valid_items, ///< [in] Total number of valid items across the logical warp ReductionOp reduction_op) ///< [in] Binary reduction operator { int last_lane = (ALL_LANES_VALID) ? LOGICAL_WARP_THREADS - 1 : valid_items - 1; T output = input; // // Iterate reduction steps // #pragma unroll // for (int STEP = 0; STEP < STEPS; STEP++) // { // output = ReduceStep(output, reduction_op, last_lane, 1 << STEP, Int2Type::IS_SMALL_UNSIGNED>()); // } // Template-iterate reduction steps ReduceStep(output, reduction_op, last_lane, Int2Type<0>()); return output; } /// Segmented reduction template < bool HEAD_SEGMENTED, ///< Whether flags indicate a segment-head or a segment-tail typename FlagT, typename ReductionOp> __device__ __forceinline__ T SegmentedReduce( T input, ///< [in] Calling thread's input FlagT flag, ///< [in] Whether or not the current lane is a segment head/tail ReductionOp reduction_op) ///< [in] Binary reduction operator { // Get the start flags for each thread in the warp. int warp_flags = WARP_BALLOT(flag, member_mask); // Convert to tail-segmented if (HEAD_SEGMENTED) warp_flags >>= 1; // Mask out the bits below the current thread warp_flags &= LaneMaskGe(); // Mask of physical lanes outside the logical warp and convert to logical lanemask if (!IS_ARCH_WARP) { warp_flags = (warp_flags & member_mask) >> (warp_id * LOGICAL_WARP_THREADS); } // Mask in the last lane of logical warp warp_flags |= 1u << (LOGICAL_WARP_THREADS - 1); // Find the next set flag int last_lane = __clz(__brev(warp_flags)); T output = input; // // Iterate reduction steps // #pragma unroll // for (int STEP = 0; STEP < STEPS; STEP++) // { // output = ReduceStep(output, reduction_op, last_lane, 1 << STEP, Int2Type::IS_SMALL_UNSIGNED>()); // } // Template-iterate reduction steps ReduceStep(output, reduction_op, last_lane, Int2Type<0>()); return output; } }; } // CUB namespace CUB_NS_POSTFIX // Optional outer namespace(s)