/******************************************************************************* * * MIT License * * Copyright 2024-2025 AMD ROCm(TM) Software * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to deal * in the Software without restriction, including without limitation the rights * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell * copies of the Software, and to permit persons to whom the Software is * furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in * all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. * *******************************************************************************/ #pragma once #include #include #include #include namespace rocRoller { namespace KernelGraph { /** * @brief Flatten tile space and stream accumulation tiles. * * See `StreamKCoordinatetransformDesign`. * * The AddStreamK transformation is typically applied in * matrix-matrix multiply problems of the form D = A B where A * and B have been tiled with A: M x K tiles, and B: K x N * tiles. Here the K tiles are the accumulation tiles. * * The `dims` parameter selects the free (M and N) dimensions. * The `topLoop` parameter selects the accumulation loop * (which was most likely created during the * LowerTensorContraction transformation). * * The AddStreamK transform creates a flattened "global tile * space" from all of the M/N/K tiles. The flattened M/N/K * global tile-space is distributed evenly among the WGs. * Each WG iterates over its portion of the flattened global * tile-space; with the K tiles iterated over in the * inner-most "streaming" loop. * * The transformation is parameterised by: * * @param dims The sub-dimensions of dangling * `MacroTileNumber`s that should be included in the streaming * construct. * * @param tileNumberCoordSizes Sizes of `MacroTileNumber`s * matched by `dims`. * * @param topLoop Which loop to insert the local tile-loop * above. * * @param accmulatorLoop Which accumulation loop to stream. * * @param numWGs How many workgroups will be launched. */ class AddStreamK : public GraphTransform { public: AddStreamK() = delete; AddStreamK(AddStreamK const&) = delete; AddStreamK(ContextPtr context, CommandParametersPtr params, std::string const& topLoop, std::string const& accumulatorLoop, Expression::ExpressionPtr numWGs); KernelGraph apply(KernelGraph const& original) override; std::string name() const override; private: CommandParametersPtr m_params; ContextPtr m_context; /** * The sub-dimensions of dangling `MacroTileNumber`s that * should be included in the streaming construct. */ std::vector m_dimensionIndices; /** * Name of the loop to insert the local tile-loop above. */ std::string m_topLoop; /** * Name of the accumulator (K) loop. */ std::string m_accumulatorLoop; /** * Use two-tile SK + DP variant? */ bool m_twoTile; /** * Number of Workgroups. * * An Expression that either: * 1. Pulls a value from a CommandArgument * 2. Is a literal (for testing) */ Expression::ExpressionPtr m_numWGs; }; } }