mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-03 05:01:25 +00:00
243118c275
The following changes were made: - Clean-up of variable namings - Addition of README - Removal of num_cu and occupancy args; such options are meant for testing purposes and should not be exposed to the user - Removal of CK_TILE_PIPELINE_MEMORY macro and PipelineTypeTraits class since we only support one pipeline at the moment.
107 lines
3.7 KiB
C++
107 lines
3.7 KiB
C++
// Copyright © Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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#pragma once
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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/epilogue.hpp"
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#include "ck_tile/ops/gemm.hpp"
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struct GemmConfigBase
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{
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static constexpr bool kPadM = true;
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static constexpr bool kPadN = true;
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static constexpr bool kPadK = true;
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static constexpr bool PermuteA = false;
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static constexpr bool PermuteB = false;
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static constexpr bool TransposeC = false;
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static constexpr bool UseStructuredSparsity = false;
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static constexpr bool Persistent = false;
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static constexpr int kBlockPerCu = 1;
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static constexpr auto Scheduler = ck_tile::GemmPipelineScheduler::Intrawave;
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static constexpr ck_tile::index_t NumWaveGroups = 1;
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static constexpr bool Preshuffle = false;
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static constexpr bool DoubleSmemBuffer = false;
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};
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template <typename PrecType>
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struct GemmConfigMemoryInterwave : public GemmConfigBase
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{
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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 = 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 = sizeof(PrecType) == 2 ? 8 : 16;
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static constexpr auto Scheduler = ck_tile::GemmPipelineScheduler::Intrawave;
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};
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template <typename ADataType_, typename BDataType_ = ADataType_, typename CDataType_ = ADataType_>
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struct StreamKGemmTypeConfig
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{
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using ADataType = ADataType_;
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using BDataType = BDataType_;
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using AccDataType = float;
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using CDataType = CDataType_;
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};
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template <typename T>
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struct DataTypeTraits;
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template <>
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struct DataTypeTraits<float>
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{
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static constexpr const char* name = "fp32";
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};
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template <>
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struct DataTypeTraits<ck_tile::half_t>
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{
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static constexpr const char* name = "fp16";
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};
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template <>
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struct DataTypeTraits<ck_tile::bf16_t>
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{
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static constexpr const char* name = "bf16";
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};
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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", "512", "n dimension")
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.insert("k", "512", "k dimension")
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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 - Column by default")
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.insert("c_layout", "R", "C tensor data layout - Row by default")
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.insert("num_sk_blocks",
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"-1",
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"number of Stream-K blocks. -1: chosen by algorithm, or user selected")
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.insert("reduction_strategy",
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"atomic",
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"strategy for storing results in C tensor - atomic/reduction")
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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("v", "2", "0. No validation, 1. Validation on CPU, 2. Validation on GPU")
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.insert("prec", "fp16", "data type. fp16/bf16")
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.insert("warmup", "50", "number of iterations before benchmarking 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("init", "0", "0:random, 1:linear, 2:constant(1)")
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.insert("flush_cache", "true", "flush cache before running the kernel, defaults to true");
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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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