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composable_kernel/profiler/src/profile_gemm_ab_scale.cpp
Aviral Goel 0aadb4b2c4 chore(copyright): update copyright header for profiler directory (#3205)
* chore(copyright): update copyright header for tile_engine directory

* chore(copyright): update copyright header for script directory

* chore(copyright): update copyright header for test_data directory

* chore(copyright): update copyright header for python directory

* chore(copyright): update copyright header for profiler directory
2025-11-14 11:19:25 -08:00

222 lines
7.8 KiB
C++

// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT
#include <iostream>
#include <numeric>
#include <initializer_list>
#include <cstdlib>
#include "profiler/profile_gemm_ab_scale_impl.hpp"
#include "profiler_operation_registry.hpp"
enum struct GemmMatrixLayout
{
MK_KN_MN, // 0
MK_NK_MN, // 1
KM_KN_MN, // 2
KM_NK_MN, // 3
};
enum struct GemmDataType
{
F32_F32_F32, // 0
F16_F16_F16, // 1
BF16_BF16_BF16, // 2
INT8_INT8_INT8, // 3
F8_F16_F16, // 4
F16_F8_F16, // 5
F16_F16_F16_F8, // 6
F8_F8_BF16, // 7
};
enum struct ScaleBlockTile
{
Tile_128_128_128, // 0
Tile_1_128_128, // 1
};
#define OP_NAME "gemm_ab_scale"
#define OP_DESC "GEMM_AB_Scale"
int profile_gemm_ab_scale(int argc, char* argv[])
{
if(argc != 15 && argc != 16 && argc != 19)
{
printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
printf("arg2: data type (0: fp32; 1: fp16; 2: bf16; 3: int8; 4: f8@f16; 5: f16@f8; 6: "
"f16->f8; 7: f8->bf16, "
"comp f8)\n");
printf("arg3: matrix layout (0: A[m, k] * B[k, n] = C[m, n];\n");
printf(" 1: A[m, k] * B[n, k] = C[m, n];\n");
printf(" 2: A[k, m] * B[k, n] = C[m, n];\n");
printf(" 3: A[k, m] * B[n, k] = C[m, n])\n");
printf("arg4: scale block tile (0: ScaleBlockM/N/K = [128, 128, 128]; 1: ScaleBlockM/N/K = "
"[1, 128, 128];\n");
printf("arg5: verification (0: no; 1: yes)\n");
printf("arg6: initialization (0: no init; 1: integer value; 2: decimal value)\n");
printf("arg7: print tensor value (0: no; 1: yes)\n");
printf("arg8: time kernel (0=no, 1=yes)\n");
printf("arg9 to 14: M, N, K, StrideA, StrideB, StrideE\n");
printf("arg15: KBatch (default: 1)\n");
printf("optional:\n");
printf("arg16: number of warm-up cycles (default 1)\n");
printf("arg17: number of iterations (default 10)\n");
printf("arg18: memory for rotating buffer (default 0, size in MB)\n");
exit(1);
}
const auto data_type = static_cast<GemmDataType>(std::stoi(argv[2]));
const auto layout = static_cast<GemmMatrixLayout>(std::stoi(argv[3]));
const auto scale_block_tile = static_cast<ScaleBlockTile>(std::stoi(argv[4]));
const bool do_verification = std::stoi(argv[5]);
const int init_method = std::stoi(argv[6]);
const bool do_log = std::stoi(argv[7]);
const bool time_kernel = std::stoi(argv[8]);
const int M = std::stoi(argv[9]);
const int N = std::stoi(argv[10]);
const int K = std::stoi(argv[11]);
const int StrideA = std::stoi(argv[12]);
const int StrideB = std::stoi(argv[13]);
const int StrideE = std::stoi(argv[14]);
const int KBatch = (argc > 15) ? std::stoi(argv[15]) : 1;
int n_warmup = 1;
int n_iter = 10;
uint64_t rotating = 0;
if(argc == 19)
{
n_warmup = std::stoi(argv[16]);
n_iter = std::stoi(argv[17]);
rotating = std::stoull(argv[18]) * 1024 * 1024;
}
using F32 = float;
using BF16 = ck::bhalf_t;
using F8 = ck::f8_t;
using Row = ck::tensor_layout::gemm::RowMajor;
using Col = ck::tensor_layout::gemm::ColumnMajor;
auto profile = [&](auto a0_type,
auto a1_type,
auto b0_type,
auto b1_type,
auto comp_type,
auto acc_type,
auto c_type,
auto scale_block_m,
auto scale_block_n,
auto scale_block_k,
auto a_layout,
auto b_layout,
auto e_layout) {
using A0DataType = decltype(a0_type);
using A1DataType = decltype(a1_type);
using B0DataType = decltype(b0_type);
using B1DataType = decltype(b1_type);
using ComputeDataType = decltype(comp_type);
using AccDataType = decltype(acc_type);
using EDataType = decltype(c_type);
using ALayout = decltype(a_layout);
using BLayout = decltype(b_layout);
using ELayout = decltype(e_layout);
const int DefaultStrideA = ck::is_same_v<ALayout, Row> ? K : M;
const int DefaultStrideB = ck::is_same_v<BLayout, Row> ? N : K;
const int DefaultStrideE = ck::is_same_v<ELayout, Row> ? N : M;
bool pass = ck::profiler::profile_gemm_ab_scale_impl<A0DataType,
A1DataType,
B0DataType,
B1DataType,
ComputeDataType,
AccDataType,
EDataType,
scale_block_m,
scale_block_n,
scale_block_k,
ALayout,
BLayout,
ELayout>(
do_verification,
init_method,
do_log,
time_kernel,
M,
N,
K,
(StrideA < 0) ? DefaultStrideA : StrideA,
(StrideB < 0) ? DefaultStrideB : StrideB,
(StrideE < 0) ? DefaultStrideE : StrideE,
KBatch,
n_warmup,
n_iter,
rotating);
return pass ? 0 : 1;
};
if(data_type == GemmDataType::F8_F8_BF16 && layout == GemmMatrixLayout::MK_NK_MN &&
scale_block_tile == ScaleBlockTile::Tile_1_128_128)
{
return profile(F8{},
F32{},
F8{},
F32{},
F8{},
F32{},
BF16{},
ck::Number<1>{},
ck::Number<128>{},
ck::Number<128>{},
Row{},
Col{},
Row{});
}
else if(data_type == GemmDataType::F8_F8_BF16 && layout == GemmMatrixLayout::MK_KN_MN &&
scale_block_tile == ScaleBlockTile::Tile_1_128_128)
{
return profile(F8{},
F32{},
F8{},
F32{},
F8{},
F32{},
BF16{},
ck::Number<1>{},
ck::Number<128>{},
ck::Number<128>{},
Row{},
Row{},
Row{});
}
else if(data_type == GemmDataType::F8_F8_BF16 && layout == GemmMatrixLayout::KM_KN_MN &&
scale_block_tile == ScaleBlockTile::Tile_1_128_128)
{
return profile(F8{},
F32{},
F8{},
F32{},
F8{},
F32{},
BF16{},
ck::Number<1>{},
ck::Number<128>{},
ck::Number<128>{},
Col{},
Row{},
Row{});
}
else
{
std::cout << "this data_type & layout is not implemented" << std::endl;
return 1;
}
}
REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_gemm_ab_scale);