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batched_gemm.hpp
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169 lines (139 loc) · 6.28 KB
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// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT
#pragma once
#include <string>
#include "ck_tile/core.hpp"
#include "ck_tile/host/kernel_launch.hpp"
#include "ck_tile/ops/gemm/kernel/batched_gemm_kernel.hpp"
#include "ck_tile/ops/elementwise/unary_element_wise_operation.hpp"
#include "ck_tile/utility/json_dump.hpp"
struct GemmConfigMemory
{
// Memory friendly for Interwave scheduler
static constexpr ck_tile::index_t M_Tile = 128;
static constexpr ck_tile::index_t N_Tile = 32;
static constexpr ck_tile::index_t K_Tile = 64;
static constexpr ck_tile::index_t M_Warp = 4;
static constexpr ck_tile::index_t N_Warp = 1;
static constexpr ck_tile::index_t K_Warp = 1;
static constexpr ck_tile::index_t M_Warp_Tile = 32;
static constexpr ck_tile::index_t N_Warp_Tile = 32;
static constexpr ck_tile::index_t K_Warp_Tile = 8;
static constexpr bool DoubleSmemBuffer = false;
static constexpr ck_tile::GemmPipeline Pipeline = ck_tile::GemmPipeline::MEMORY;
static constexpr auto Scheduler = ck_tile::GemmPipelineScheduler::Interwave;
};
struct GemmConfigV3
{
// Compute friendly for Intrawave scheduler
static constexpr ck_tile::index_t M_Tile = 256;
static constexpr ck_tile::index_t N_Tile = 256;
static constexpr ck_tile::index_t K_Tile = 64;
static constexpr ck_tile::index_t M_Warp = 2;
static constexpr ck_tile::index_t N_Warp = 2;
static constexpr ck_tile::index_t K_Warp = 1;
static constexpr ck_tile::index_t M_Warp_Tile = 32;
static constexpr ck_tile::index_t N_Warp_Tile = 32;
static constexpr ck_tile::index_t K_Warp_Tile = 16;
static constexpr bool DoubleSmemBuffer = false;
static constexpr ck_tile::GemmPipeline Pipeline = ck_tile::GemmPipeline::COMPUTE_V3;
static constexpr auto Scheduler = ck_tile::GemmPipelineScheduler::Intrawave;
};
struct GemmConfigV4
{
// Compute friendly for Intrawave scheduler
// Using the ping pong reader in the lds level
static constexpr ck_tile::index_t M_Tile = 256;
static constexpr ck_tile::index_t N_Tile = 256;
static constexpr ck_tile::index_t K_Tile = 32;
static constexpr ck_tile::index_t M_Warp = 2;
static constexpr ck_tile::index_t N_Warp = 2;
static constexpr ck_tile::index_t K_Warp = 1;
static constexpr ck_tile::index_t M_Warp_Tile = 32;
static constexpr ck_tile::index_t N_Warp_Tile = 32;
static constexpr ck_tile::index_t K_Warp_Tile = 16;
static constexpr bool DoubleSmemBuffer = true;
static constexpr ck_tile::GemmPipeline Pipeline = ck_tile::GemmPipeline::COMPUTE_V4;
static constexpr auto Scheduler = ck_tile::GemmPipelineScheduler::Intrawave;
};
struct GemmConfigV3_Wmma
{
// Compute friendly for Intrawave scheduler
static constexpr ck_tile::index_t M_Tile = 128;
static constexpr ck_tile::index_t N_Tile = 128;
static constexpr ck_tile::index_t K_Tile = 64;
static constexpr ck_tile::index_t M_Warp = 2;
static constexpr ck_tile::index_t N_Warp = 2;
static constexpr ck_tile::index_t K_Warp = 1;
static constexpr ck_tile::index_t M_Warp_Tile = 16;
static constexpr ck_tile::index_t N_Warp_Tile = 16;
static constexpr ck_tile::index_t K_Warp_Tile = 16;
static constexpr bool DoubleSmemBuffer = false;
static constexpr ck_tile::GemmPipeline Pipeline = ck_tile::GemmPipeline::COMPUTE_V3;
static constexpr auto Scheduler = ck_tile::GemmPipelineScheduler::Intrawave;
};
template <ck_tile::GemmPipeline PipelineId>
struct PipelineTypeTraits;
template <>
struct PipelineTypeTraits<ck_tile::GemmPipeline::MEMORY>
{
template <typename PipelineProblem>
using GemmPipeline = ck_tile::GemmPipelineAgBgCrMem<PipelineProblem>;
};
template <>
struct PipelineTypeTraits<ck_tile::GemmPipeline::COMPUTE_V3>
{
template <typename PipelineProblem>
using GemmPipeline = ck_tile::GemmPipelineAgBgCrCompV3<PipelineProblem>;
};
template <>
struct PipelineTypeTraits<ck_tile::GemmPipeline::COMPUTE_V4>
{
template <typename PipelineProblem>
using GemmPipeline = ck_tile::GemmPipelineAgBgCrCompV4<PipelineProblem>;
};
template <typename DataType>
struct BatchedGemmTypeConfig;
template <>
struct BatchedGemmTypeConfig<ck_tile::half_t>
{
using ADataType = ck_tile::half_t;
using BDataType = ck_tile::half_t;
using AccDataType = float;
using CDataType = ck_tile::half_t;
};
using Types = BatchedGemmTypeConfig<ck_tile::half_t>;
// Specific type aliases for easy access
using ADataType = Types::ADataType;
using BDataType = Types::BDataType;
using AccDataType = Types::AccDataType;
using CDataType = Types::CDataType;
auto create_args(int argc, char* argv[])
{
ck_tile::ArgParser arg_parser;
arg_parser.insert("m", "512", "m dimension")
.insert("n", "1024", "n dimension")
.insert("k", "2048", "k dimension")
.insert("stride_a", "0", "Tensor A stride")
.insert("stride_b", "0", "Tensor B stride")
.insert("stride_c", "0", "Tensor C stride")
.insert("a_layout", "R", "A tensor data layout - Row by default")
.insert("b_layout", "C", "B tensor data layout - Row by default")
.insert("c_layout", "R", "C tensor data layout - Row by default")
.insert("batch_stride_a", "1048576", "Batch A stride")
.insert("batch_stride_b", "2097152", "Batch B stride")
.insert("batch_stride_c", "524288", "Batch C stride")
.insert("batch_count", "8", "Batch count")
.insert("v", "1", "0. No validation, 1. Validation on CPU, 2. Validation on GPU")
.insert("prec", "fp16", "data type. fp16/bf16/fp8/bf8")
.insert("warmup", "50", "number of iterations before benchmark the kernel")
.insert("repeat", "100", "number of iterations to benchmark the kernel")
.insert("timer", "gpu", "gpu:gpu timer, cpu:cpu timer")
.insert("split_k", "1", "splitK value")
.insert("json", "0", "0: No Json, 1: Dump Results in Json format")
.insert("jsonfile", "cktile_batched_gemm.json", "json file name to dump results");
bool result = arg_parser.parse(argc, argv);
return std::make_tuple(result, arg_parser);
}
// host API
float batched_gemm(const ck_tile::BatchedGemmHostArgs& args, const ck_tile::stream_config& s);