// SPDX-License-Identifier: MIT // Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved. #include #include #include #include #include "profiler/profile_gemm_b_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 F16_I4_F16, // 8 }; enum struct BScaleBlockTile { K_64, // 0 K_128, // 1 }; #define OP_NAME "gemm_b_scale" #define OP_DESC "Int4-dequant GEMM" int profile_gemm_b_scale(int argc, char* argv[]) { if(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; 8: f16@i4)\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: B scale block tile (0: 64, 1: 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, StrideC\n"); printf("arg15: split k into mulitiple batch\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); } printf("Start profiling\n"); const auto data_type = static_cast(std::stoi(argv[2])); const auto layout = static_cast(std::stoi(argv[3])); const auto B_scale_block = static_cast(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 StrideC = std::stoi(argv[14]); const int KBatch = std::stoi(argv[15]); printf("M:%d, N:%d, K:%d, StrideA:%d, StrideB:%d, StrideC:%d, KBatch:%d\n", M, N, K, StrideA, StrideB, StrideC, KBatch); 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; printf("n_warmup:%d, n_iter:%d, rotating:%lu\n", n_warmup, n_iter, rotating); } using F32 = float; using F16 = ck::half_t; using I4 = ck::pk_i4_t; using Row = ck::tensor_layout::gemm::RowMajor; using Col = ck::tensor_layout::gemm::ColumnMajor; auto profile = [&](auto a_type, auto b_type, auto b_scale_type, auto comp_type, auto acc_type, auto c_type, auto scale_block_k, auto a_layout, auto b_layout, auto c_layout) { using ADataType = decltype(a_type); using BDataType = decltype(b_type); using BScaleDataType = decltype(b_scale_type); using ComputeDataType = decltype(comp_type); using AccDataType = decltype(acc_type); using CDataType = decltype(c_type); using ALayout = decltype(a_layout); using BLayout = decltype(b_layout); using CLayout = decltype(c_layout); const int DefaultStrideA = ck::is_same_v ? K : M; const int DefaultStrideB = ck::is_same_v ? N : K; const int DefaultStrideC = ck::is_same_v ? N : M; bool pass = ck::profiler::profile_gemm_b_scale_impl( do_verification, init_method, do_log, time_kernel, M, N, K, (StrideA < 0) ? DefaultStrideA : StrideA, (StrideB < 0) ? DefaultStrideB : StrideB, (StrideC < 0) ? DefaultStrideC : StrideC, KBatch, n_warmup, n_iter, rotating); return pass ? 0 : 1; }; if(data_type == GemmDataType::F16_I4_F16 && layout == GemmMatrixLayout::MK_NK_MN && B_scale_block == BScaleBlockTile::K_128) { printf("F16_I4_F16 MK_NK_MN K_128\n"); return profile( F16{}, I4{}, F16{}, F16{}, F32{}, F16{}, ck::Number<128>{}, Row{}, Col{}, Row{}); } else { std::cout << "this data_type & layout is not implemented" << std::endl; return 1; } } REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_gemm_b_scale);