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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 \brief Implements several possible threadblock-swizzling functions mapping blockIdx to GEMM problems. */ #pragma once #include "cutlass/cutlass.h" #include "cutlass/layout/matrix.h" #include "cutlass/platform/platform.h" #include "cutlass/gemm/gemm.h" #include "cutlass/conv/conv2d_problem_size.h" #include "cutlass/conv/conv3d_problem_size.h" ///////////////////////////////////////////////////////////////////////////////////////////////// namespace cutlass { namespace gemm { namespace threadblock { ///////////////////////////////////////////////////////////////////////////////////////////////// /// Helper to rematerialize block Idx. Reduces register liveness. CUTLASS_DEVICE int RematerializeThreadIdxX() { return threadIdx.x; } /// Helper to rematerialize block Idx. Reduces register liveness. CUTLASS_DEVICE int RematerializeThreadIdxY() { return threadIdx.y; } /// Helper to rematerialize block Idx. Reduces register liveness. CUTLASS_DEVICE int RematerializeThreadIdxZ() { return threadIdx.z; } /// Helper to rematerialize block Idx. Reduces register liveness. CUTLASS_DEVICE int RematerializeBlockIdxX() { return blockIdx.x; } /// Helper to rematerialize block Idx. Reduces register liveness. CUTLASS_DEVICE int RematerializeBlockIdxY() { return blockIdx.y; } /// Helper to rematerialize block Idx. Reduces register liveness. CUTLASS_DEVICE int RematerializeBlockIdxZ() { return blockIdx.z; } /// Helper to rematerialize block Dim. Reduces register liveness. CUTLASS_DEVICE int RematerializeBlockDimX() { return blockDim.x; } /// Helper to rematerialize block Dim. Reduces register liveness. CUTLASS_DEVICE int RematerializeBlockDimY() { return blockDim.y; } /// Helper to rematerialize block Dim. Reduces register liveness. CUTLASS_DEVICE int RematerializeBlockDimZ() { return blockDim.z; } ///////////////////////////////////////////////////////////////////////////////////////////////// /// Threadblock swizzling function for GEMMs template struct GemmIdentityThreadblockSwizzle { CUTLASS_HOST_DEVICE GemmIdentityThreadblockSwizzle() { } /// Returns the shape of the problem in units of logical tiles /// *Gemm* problem size: gemm(M, N, K) CUTLASS_HOST_DEVICE GemmCoord get_tiled_shape( GemmCoord problem_size, GemmCoord tile_size, int split_k_slices) const { return GemmCoord( (problem_size.m() + tile_size.m() - 1) / tile_size.m(), (problem_size.n() + tile_size.n() - 1) / tile_size.n(), split_k_slices); } /// Returns the shape of the problem in units of logical tiles /// *ImplicitGemm* Conv2d problem size: conv_operator(NPQK, NHWC, KRSC) CUTLASS_HOST_DEVICE GemmCoord get_tiled_shape( cutlass::conv::Operator conv_operator, cutlass::conv::Conv2dProblemSize const &problem_size, GemmCoord tile_size, int split_k_slices) const { gemm::GemmCoord implicit_gemm_problem_size = cutlass::conv::implicit_gemm_problem_size(conv_operator, problem_size); return get_tiled_shape( implicit_gemm_problem_size, tile_size, split_k_slices); } /// Returns the shape of the problem in units of logical tiles /// *ImplicitGemm* Conv3d problem size: conv_operator(NZPQK, NDHWC, KTRSC) CUTLASS_HOST_DEVICE GemmCoord get_tiled_shape( cutlass::conv::Operator conv_operator, cutlass::conv::Conv3dProblemSize const &problem_size, GemmCoord tile_size, int split_k_slices) const { gemm::GemmCoord implicit_gemm_problem_size = cutlass::conv::implicit_gemm_problem_size(conv_operator, problem_size); return get_tiled_shape( implicit_gemm_problem_size, tile_size, split_k_slices); } /// Computes CUDA grid dimensions given a size in units of logical tiles CUTLASS_HOST_DEVICE dim3 get_grid_shape(GemmCoord tiled_shape) const { int tile = 1 << get_log_tile(tiled_shape); return dim3(tiled_shape.m() * tile, (tiled_shape.n() + tile - 1) / tile, tiled_shape.k()); } /// Calculates optimal swizzle width CUTLASS_HOST_DEVICE int get_log_tile(GemmCoord tiled_shape) const { auto n = tiled_shape.n(); // Thresholds picked so that it doesn't cause too many no-op CTAs if (N >= 8 && n >= 6) return 3; else if (N >= 4 && n >= 3) return 2; else if (N >= 2 && n >= 2) return 1; else return 0; } /// Obtains the threadblock offset (in units of threadblock-scoped tiles) CUTLASS_DEVICE GemmCoord get_tile_offset(int log_tile) const { int block_idx_x = RematerializeBlockIdxX(); int block_idx_y = RematerializeBlockIdxY(); int block_idx_z = RematerializeBlockIdxZ(); return GemmCoord{(block_idx_x >> log_tile), // (block_idx_y << log_tile) + ((block_idx_x) & ((1 << (log_tile)) - 1)), block_idx_z}; } /// Obtains the threadblock offset (in units of threadblock-scoped tiles) CUTLASS_DEVICE GemmCoord get_tile_offset(GemmCoord tiled_shape) const { int const kTile = N; int block_idx_x = RematerializeBlockIdxX(); int block_idx_y = RematerializeBlockIdxY(); if ((tiled_shape.m() < kTile) || (tiled_shape.n() < kTile)) return GemmCoord{block_idx_x, block_idx_y, RematerializeBlockIdxZ()}; return GemmCoord{ (block_idx_x / kTile), (block_idx_y * kTile) + (block_idx_x % kTile), RematerializeBlockIdxZ() }; } }; ///////////////////////////////////////////////////////////////////////////////////////////////// /// Threadblock swizzling function for GEMMs struct GemmHorizontalThreadblockSwizzle { CUTLASS_HOST_DEVICE GemmHorizontalThreadblockSwizzle() { } /// Returns the shape of the problem in units of logical tiles CUTLASS_HOST_DEVICE GemmCoord get_tiled_shape( GemmCoord problem_size, GemmCoord tile_size, int split_k_slices) const { return GemmCoord( (problem_size.m() + tile_size.m() - 1) / tile_size.m(), (problem_size.n() + tile_size.n() - 1) / tile_size.n(), split_k_slices); } /// Computes CUDA grid dimensions given a size in units of logical tiles CUTLASS_HOST_DEVICE dim3 get_grid_shape(GemmCoord tiled_shape) const { return dim3(tiled_shape.n(), tiled_shape.m(), tiled_shape.k()); } /// Calculates optimal swizzle width CUTLASS_HOST_DEVICE int get_log_tile(GemmCoord tiled_shape) const { return 0; } /// Obtains the threadblock offset (in units of threadblock-scoped tiles) CUTLASS_DEVICE GemmCoord get_tile_offset(GemmCoord tiled_shape) const { return GemmCoord{ RematerializeBlockIdxY(), RematerializeBlockIdxX(), RematerializeBlockIdxZ() }; } }; ///////////////////////////////////////////////////////////////////////////////////////////////// /// Threadblock swizzling function for batched GEMMs struct GemmBatchedIdentityThreadblockSwizzle { /// Returns the shape of the problem in units of logical tiles CUTLASS_HOST_DEVICE GemmCoord get_tiled_shape( GemmCoord problem_size, GemmCoord tile_size, int batch_count) const { return GemmCoord( (problem_size.m() + tile_size.m() - 1) / tile_size.m(), (problem_size.n() + tile_size.n() - 1) / tile_size.n(), batch_count % (1 << 16)); } /// Computes CUDA grid dimensions given a size in units of logical tiles CUTLASS_HOST_DEVICE dim3 get_grid_shape(GemmCoord tiled_shape) const { return dim3(tiled_shape.m(), tiled_shape.n(), tiled_shape.k()); } /// Calculates optimal swizzle width CUTLASS_HOST_DEVICE int get_log_tile(GemmCoord tiled_shape) const { return 0; } /// Obtains the threadblock offset (in units of threadblock-scoped tiles) CUTLASS_DEVICE GemmCoord get_tile_offset(GemmCoord tiled_shape) const { return GemmCoord{ RematerializeBlockIdxX(), RematerializeBlockIdxY(), RematerializeBlockIdxZ() }; } /// Obtains the threadblock offset (in units of threadblock-scoped tiles) CUTLASS_DEVICE GemmCoord get_tile_offset(int log_tile) const { int block_idx_x = RematerializeBlockIdxX(); int block_idx_y = RematerializeBlockIdxY(); int block_idx_z = RematerializeBlockIdxZ(); return GemmCoord{(block_idx_x >> log_tile), // (block_idx_y << log_tile) + ((block_idx_x) & ((1 << (log_tile)) - 1)), block_idx_z}; } /// Gets the batch index CUTLASS_DEVICE int get_batch_idx() const { return RematerializeBlockIdxZ(); } }; ///////////////////////////////////////////////////////////////////////////////////////////////// /// Threadblock swizzling function for split-K GEMMs template struct GemmSplitKIdentityThreadblockSwizzle { int const kTile = N; /// Returns the shape of the problem in units of logical tiles CUTLASS_HOST_DEVICE GemmCoord get_tiled_shape( GemmCoord problem_size, GemmCoord tile_size, int partitions) const { return GemmCoord( (problem_size.m() + tile_size.m() - 1) / tile_size.m(), (problem_size.n() + tile_size.n() - 1) / tile_size.n(), partitions); } /// Calculates optimal swizzle width CUTLASS_HOST_DEVICE int get_log_tile(GemmCoord tiled_shape) const { auto n = tiled_shape.n(); // Thresholds picked so that it doesn't cause too many no-op CTAs if (N >= 8 && n >= 6) return 3; else if (N >= 4 && n >= 3) return 2; else if (N >= 2 && n >= 2) return 1; else return 0; } /// Computes CUDA grid dimensions given a size in units of logical tiles CUTLASS_HOST_DEVICE dim3 get_grid_shape(GemmCoord tiled_shape) const { int tile = 1 << get_log_tile(tiled_shape); return dim3(tiled_shape.m() * tile, (tiled_shape.n() + tile - 1) / tile, tiled_shape.k()); } /// Obtains the threadblock offset (in units of threadblock-scoped tiles) CUTLASS_DEVICE GemmCoord get_tile_offset(int log_tile) const { int block_idx_x = RematerializeBlockIdxX(); int block_idx_y = RematerializeBlockIdxY(); int block_idx_z = RematerializeBlockIdxZ(); return GemmCoord{(block_idx_x >> log_tile), // (block_idx_y << log_tile) + ((block_idx_x) & ((1 << (log_tile)) - 1)), block_idx_z}; } /// Obtains the threadblock offset (in units of threadblock-scoped tiles) CUTLASS_DEVICE GemmCoord get_tile_offset(GemmCoord tiled_shape) const { int const kTile = N; int block_idx_x = RematerializeBlockIdxX(); int block_idx_y = RematerializeBlockIdxY(); if ((tiled_shape.m() < kTile) || (tiled_shape.n() < kTile)) return GemmCoord{block_idx_x, block_idx_y, RematerializeBlockIdxZ()}; return GemmCoord{ (block_idx_x / kTile), (block_idx_y * kTile) + (block_idx_x % kTile), RematerializeBlockIdxZ() }; } }; ///////////////////////////////////////////////////////////////////////////////////////////////// /// Threadblock swizzling function for split-K GEMMs struct GemmSplitKHorizontalThreadblockSwizzle { /// Returns the shape of the problem in units of logical tiles CUTLASS_HOST_DEVICE GemmCoord get_tiled_shape( GemmCoord problem_size, GemmCoord tile_size, int partitions) const { return GemmCoord( (problem_size.m() + tile_size.m() - 1) / tile_size.m(), (problem_size.n() + tile_size.n() - 1) / tile_size.n(), partitions); } /// Computes CUDA grid dimensions given a size in units of logical tiles CUTLASS_HOST_DEVICE dim3 get_grid_shape(GemmCoord tiled_shape) const { return dim3(tiled_shape.n(), tiled_shape.m(), tiled_shape.k()); } /// Calculates optimal swizzle width CUTLASS_HOST_DEVICE int get_log_tile(GemmCoord tiled_shape) const { return 0; } /// Obtains the threadblock offset (in units of threadblock-scoped tiles) CUTLASS_DEVICE GemmCoord get_tile_offset(int log_tile) const { return GemmCoord{ RematerializeBlockIdxY(), RematerializeBlockIdxX(), RematerializeBlockIdxZ() }; } /// Obtains the threadblock offset (in units of threadblock-scoped tiles) CUTLASS_DEVICE GemmCoord get_tile_offset(GemmCoord tiled_shape) const { return GemmCoord{ RematerializeBlockIdxY(), RematerializeBlockIdxX(), RematerializeBlockIdxZ() }; } }; ///////////////////////////////////////////////////////////////////////////////////////////////// /// Threadblock swizzling function for batched GEMVs struct GemvBatchedStridedThreadblockDefaultSwizzle { /// Returns the shape of the problem in units of logical tiles CUTLASS_HOST_DEVICE BatchedGemmCoord get_tiled_shape( BatchedGemmCoord problem_size, BatchedGemmCoord tile_size) const { return BatchedGemmCoord( 1, // M is always 1 (problem_size.n() + tile_size.n() - 1) / tile_size.n(), (problem_size.k() + tile_size.k() - 1) / tile_size.k(), (problem_size.batch() + tile_size.batch() - 1) / tile_size.batch()); } /// Computes CUDA grid dimensions given a size in units of logical tiles CUTLASS_HOST_DEVICE dim3 get_grid_shape(BatchedGemmCoord tiled_shape) const { return dim3(tiled_shape.n(), tiled_shape.batch(), tiled_shape.k()); } /// Calculates optimal swizzle width CUTLASS_HOST_DEVICE int get_log_tile(GemmCoord tiled_shape) const { return 0; } /// Obtains the threadblock offset (in units of threadblock-scoped tiles) CUTLASS_DEVICE BatchedGemmCoord get_tile_offset(int log_tile) const { return BatchedGemmCoord{ 0, // M is always 1 RematerializeBlockIdxX(), RematerializeBlockIdxZ(), RematerializeBlockIdxY(), }; } /// Obtains the threadblock offset (in units of threadblock-scoped tiles) CUTLASS_DEVICE BatchedGemmCoord get_tile_offset() const { return BatchedGemmCoord{ 0, // M is always 1 RematerializeBlockIdxX(), RematerializeBlockIdxZ(), RematerializeBlockIdxY(), }; } /// Gets the batch tile index CUTLASS_DEVICE int get_batch_tile_idx() const { return RematerializeBlockIdxY(); } /// Gets the absolute batch index CUTLASS_DEVICE int get_batch_idx() const { return RematerializeBlockDimY()*RematerializeBlockIdxY() + RematerializeThreadIdxY(); } }; ///////////////////////////////////////////////////////////////////////////////////////////////// } // namespace threadblock } // namespace gemm } // namespace cutlass