mirror of
https://github.com/ROCm/composable_kernel.git
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2ec57a8e70
This change replaces pipeline macros like CK_TILE_PIPELINE_COMPUTE_V3, CK_TILE_PIPELINE_MEMORY, etc in the CK Tile examples with a common enum called GemmPipeline to reduce code duplication.
176 lines
6.7 KiB
C++
176 lines
6.7 KiB
C++
// SPDX-License-Identifier: MIT
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// Copyright (c) 2024-2025, Advanced Micro Devices, Inc. All rights reserved.
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#pragma once
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#include <string>
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#include "ck_tile/core.hpp"
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#include "ck_tile/host/kernel_launch.hpp"
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#include "ck_tile/ops/gemm/kernel/batched_gemm_kernel.hpp"
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#include "ck_tile/ops/elementwise/unary_element_wise_operation.hpp"
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#include "ck_tile/utility/json_dump.hpp"
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struct GemmConfigMemory
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{
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// Memory friendly for Interwave scheduler
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static constexpr ck_tile::index_t M_Tile = 128;
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static constexpr ck_tile::index_t N_Tile = 32;
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static constexpr ck_tile::index_t K_Tile = 64;
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static constexpr ck_tile::index_t M_Warp = 4;
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static constexpr ck_tile::index_t N_Warp = 1;
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static constexpr ck_tile::index_t K_Warp = 1;
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static constexpr ck_tile::index_t M_Warp_Tile = 32;
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static constexpr ck_tile::index_t N_Warp_Tile = 32;
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static constexpr ck_tile::index_t K_Warp_Tile = 8;
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static constexpr bool DoubleSmemBuffer = false;
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static constexpr ck_tile::GemmPipeline Pipeline = ck_tile::GemmPipeline::MEMORY;
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static constexpr auto Scheduler = ck_tile::GemmPipelineScheduler::Interwave;
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};
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struct GemmConfigV3
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{
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// Compute friendly for Intrawave scheduler
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static constexpr ck_tile::index_t M_Tile = 256;
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static constexpr ck_tile::index_t N_Tile = 256;
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static constexpr ck_tile::index_t K_Tile = 64;
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static constexpr ck_tile::index_t M_Warp = 2;
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static constexpr ck_tile::index_t N_Warp = 2;
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static constexpr ck_tile::index_t K_Warp = 1;
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static constexpr ck_tile::index_t M_Warp_Tile = 32;
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static constexpr ck_tile::index_t N_Warp_Tile = 32;
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static constexpr ck_tile::index_t K_Warp_Tile = 16;
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static constexpr bool DoubleSmemBuffer = false;
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static constexpr ck_tile::GemmPipeline Pipeline = ck_tile::GemmPipeline::COMPUTE_V3;
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static constexpr auto Scheduler = ck_tile::GemmPipelineScheduler::Intrawave;
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};
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struct GemmConfigV4
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{
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// Compute friendly for Intrawave scheduler
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// Using the ping pong reader in the lds level
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static constexpr ck_tile::index_t M_Tile = 256;
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static constexpr ck_tile::index_t N_Tile = 256;
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static constexpr ck_tile::index_t K_Tile = 32;
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static constexpr ck_tile::index_t M_Warp = 2;
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static constexpr ck_tile::index_t N_Warp = 2;
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static constexpr ck_tile::index_t K_Warp = 1;
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static constexpr ck_tile::index_t M_Warp_Tile = 32;
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static constexpr ck_tile::index_t N_Warp_Tile = 32;
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static constexpr ck_tile::index_t K_Warp_Tile = 16;
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static constexpr bool DoubleSmemBuffer = true;
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static constexpr ck_tile::GemmPipeline Pipeline = ck_tile::GemmPipeline::COMPUTE_V4;
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static constexpr auto Scheduler = ck_tile::GemmPipelineScheduler::Intrawave;
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};
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struct GemmConfigV3_Wmma
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{
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// Compute friendly for Intrawave scheduler
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static constexpr ck_tile::index_t M_Tile = 128;
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static constexpr ck_tile::index_t N_Tile = 128;
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static constexpr ck_tile::index_t K_Tile = 64;
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static constexpr ck_tile::index_t M_Warp = 2;
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static constexpr ck_tile::index_t N_Warp = 2;
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static constexpr ck_tile::index_t K_Warp = 1;
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static constexpr ck_tile::index_t M_Warp_Tile = 16;
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static constexpr ck_tile::index_t N_Warp_Tile = 16;
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static constexpr ck_tile::index_t K_Warp_Tile = 16;
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static constexpr bool DoubleSmemBuffer = false;
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static constexpr ck_tile::GemmPipeline Pipeline = ck_tile::GemmPipeline::COMPUTE_V3;
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static constexpr auto Scheduler = ck_tile::GemmPipelineScheduler::Intrawave;
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};
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template <ck_tile::GemmPipeline PipelineId>
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struct PipelineTypeTraits;
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template <>
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struct PipelineTypeTraits<ck_tile::GemmPipeline::MEMORY>
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{
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template <typename PipelineProblem>
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using GemmPipeline = ck_tile::GemmPipelineAgBgCrMem<PipelineProblem>;
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template <typename PipelineProblem>
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using UniversalGemmPipeline = ck_tile::BaseGemmPipelineAgBgCrMem<PipelineProblem>;
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};
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template <>
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struct PipelineTypeTraits<ck_tile::GemmPipeline::COMPUTE_V3>
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{
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template <typename PipelineProblem>
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using GemmPipeline = ck_tile::GemmPipelineAgBgCrCompV3<PipelineProblem>;
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template <typename PipelineProblem>
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using UniversalGemmPipeline = ck_tile::BaseGemmPipelineAgBgCrCompV3<PipelineProblem>;
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};
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template <>
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struct PipelineTypeTraits<ck_tile::GemmPipeline::COMPUTE_V4>
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{
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template <typename PipelineProblem>
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using GemmPipeline = ck_tile::GemmPipelineAgBgCrCompV4<PipelineProblem>;
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template <typename PipelineProblem>
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using UniversalGemmPipeline = ck_tile::BaseGemmPipelineAgBgCrCompV4<PipelineProblem>;
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};
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template <typename DataType>
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struct BatchedGemmTypeConfig;
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template <>
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struct BatchedGemmTypeConfig<ck_tile::half_t>
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{
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using ADataType = ck_tile::half_t;
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using BDataType = ck_tile::half_t;
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using AccDataType = float;
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using CDataType = ck_tile::half_t;
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};
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using Types = BatchedGemmTypeConfig<ck_tile::half_t>;
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// Specific type aliases for easy access
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using ADataType = Types::ADataType;
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using BDataType = Types::BDataType;
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using AccDataType = Types::AccDataType;
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using CDataType = Types::CDataType;
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auto create_args(int argc, char* argv[])
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{
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ck_tile::ArgParser arg_parser;
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arg_parser.insert("m", "512", "m dimension")
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.insert("n", "1024", "n dimension")
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.insert("k", "2048", "k dimension")
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.insert("stride_a", "0", "Tensor A stride")
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.insert("stride_b", "0", "Tensor B stride")
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.insert("stride_c", "0", "Tensor C stride")
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.insert("a_layout", "R", "A tensor data layout - Row by default")
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.insert("b_layout", "C", "B tensor data layout - Row by default")
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.insert("c_layout", "R", "C tensor data layout - Row by default")
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.insert("batch_stride_a", "1048576", "Batch A stride")
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.insert("batch_stride_b", "2097152", "Batch B stride")
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.insert("batch_stride_c", "524288", "Batch C stride")
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.insert("batch_count", "8", "Batch count")
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.insert("v", "1", "0. No validation, 1. Validation on CPU, 2. Validation on GPU")
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.insert("prec", "fp16", "data type. fp16/bf16/fp8/bf8")
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.insert("warmup", "50", "number of iterations before benchmark the kernel")
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.insert("repeat", "100", "number of iterations to benchmark the kernel")
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.insert("timer", "gpu", "gpu:gpu timer, cpu:cpu timer")
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.insert("split_k", "1", "splitK value")
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.insert("json", "0", "0: No Json, 1: Dump Results in Json format")
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.insert("jsonfile", "cktile_batched_gemm.json", "json file name to dump results");
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bool result = arg_parser.parse(argc, argv);
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return std::make_tuple(result, arg_parser);
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}
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// host API
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float batched_gemm(const ck_tile::BatchedGemmHostArgs& args, const ck_tile::stream_config& s);
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