Batched GEMM Multiple D based on Universal GEMM (#1655)

* Batched GEMM Multiple D based on Universal GEMM
Co-authored-by: Jing Zhang <jizhan@fb.com>

* CI fixes
Co-authored-by: Jing Zhang <jizhan@fb.com>

---------
Co-authored-by: Jing Zhang <jizhan@fb.com>

profiler/src/profile_gemm_universal_batched.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <cstdint>
+#include <iostream>
+#include <numeric>
+#include <initializer_list>
+#include <cstdlib>
+
+#include "profiler/profile_gemm_universal_batched_impl.hpp"
+#include "profiler_operation_registry.hpp"
+
+#include "ck/library/tensor_operation_instance/gpu/gemm_universal_batched.hpp"
+
+enum struct GemmMatrixLayout
+{
+    MK_KN_MN, // 0
+    MK_NK_MN, // 1
+    KM_KN_MN, // 2
+    KM_NK_MN, // 3
+};
+
+enum struct GemmDataType
+{
+    BF16_BF16_BF16, // 0
+    F8_F8_BF16,     // 1
+};
+
+#define OP_NAME "gemm_universal_batched"
+#define OP_DESC "Batched GEMM Universal"
+
+int profile_batched_gemm_universal(int argc, char* argv[])
+{
+    if(argc != 18 && argc != 21)
+    {
+        // clang-format off
+        printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
+        printf("arg2: data type (0: bf16, 1: fp8->bf16)\n");
+        printf("arg3: matrix layout (0: A[g, m, k] * B[g, k, n] = C[g, m, n];\n");
+        printf("                     1: A[g, m, k] * B[g, n, k] = C[g, m, n];\n");
+        printf("                     2: A[g, k, m] * B[g, k, n] = C[g, m, n];\n");
+        printf("                     3: A[g, k, m] * B[g, n, k] = C[g, m, n])\n");
+        printf("arg4: verification (0: no; 1: yes)\n");
+        printf("arg5: initialization (0: no init; 1: integer value; 2: decimal value)\n");
+        printf("arg6: print tensor value (0: no; 1: yes)\n");
+        printf("arg7: time kernel (0=n0, 1=yes)\n");
+        printf("arg8 to 17: M, N, K, StrideA, StrideB, StrideC, BatchStrideA, BatchStrideB, BatchStrideC, BatchCount\n");
+        printf("optional:\n");
+        printf("arg18: number of warm-up cycles (default 1)\n");
+        printf("arg19: number of iterations (default 10)\n");
+        printf("arg20: memory for rotating buffer (default 0, size in MB)\n");
+        // clang-format on
+        exit(1);
+    }
+
+    int n_warmup      = 1;
+    int n_iter        = 10;
+    uint64_t rotating = 0;
+    if(argc == 21)
+    {
+        n_warmup = std::stoi(argv[18]);
+        n_iter   = std::stoi(argv[19]);
+        rotating = std::stoull(argv[20]) * 1024 * 1024;
+    }
+
+    const auto data_type       = static_cast<GemmDataType>(std::stoi(argv[2]));
+    const auto layout          = static_cast<GemmMatrixLayout>(std::stoi(argv[3]));
+    const bool do_verification = std::stoi(argv[4]);
+    const int init_method      = std::stoi(argv[5]);
+    const bool do_log          = std::stoi(argv[6]);
+    const bool time_kernel     = std::stoi(argv[7]);
+
+    const int M = std::stoi(argv[8]);
+    const int N = std::stoi(argv[9]);
+    const int K = std::stoi(argv[10]);
+
+    const int StrideA = std::stoi(argv[11]);
+    const int StrideB = std::stoi(argv[12]);
+    const int StrideC = std::stoi(argv[13]);
+
+    const int BatchStrideA = std::stoi(argv[14]);
+    const int BatchStrideB = std::stoi(argv[15]);
+    const int BatchStrideC = std::stoi(argv[16]);
+
+    const int BatchCount = std::stoi(argv[17]);
+
+#if defined(CK_USE_FP8_ON_UNSUPPORTED_ARCH) || defined(CK_USE_GFX94)
+    using F8 = ck::f8_t;
+#endif
+    using BF16 = ck::bhalf_t;
+
+    using Row = ck::tensor_layout::gemm::RowMajor;
+    using Col = ck::tensor_layout::gemm::ColumnMajor;
+
+    auto profile =
+        [&](auto a_type, auto b_type, auto c_type, auto a_layout, auto b_layout, auto c_layout) {
+            using ADataType  = decltype(a_type);
+            using BDataType  = decltype(b_type);
+            using DsDataType = ck::Tuple<>;
+            using CDataType  = decltype(c_type);
+
+            using ALayout  = decltype(a_layout);
+            using BLayout  = decltype(b_layout);
+            using DsLayout = ck::Tuple<>;
+            using CLayout  = decltype(c_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 DefaultStrideC = ck::is_same_v<CLayout, Row> ? N : M;
+
+            const int StrideA_ = (StrideA < 0) ? DefaultStrideA : StrideA;
+            const int StrideB_ = (StrideB < 0) ? DefaultStrideB : StrideB;
+            const int StrideC_ = (StrideC < 0) ? DefaultStrideC : StrideC;
+
+            const int DefaultBatchStrideA = (ck::is_same_v<ALayout, Row> ? M : K) * StrideA_;
+            const int DefaultBatchStrideB = (ck::is_same_v<BLayout, Row> ? K : N) * StrideB_;
+            const int DefaultBatchStrideC = (ck::is_same_v<CLayout, Row> ? M : N) * StrideC_;
+
+            const int BatchStrideA_ = (BatchStrideA < 0) ? DefaultBatchStrideA : BatchStrideA;
+            const int BatchStrideB_ = (BatchStrideB < 0) ? DefaultBatchStrideB : BatchStrideB;
+            const int BatchStrideC_ = (BatchStrideC < 0) ? DefaultBatchStrideC : BatchStrideC;
+
+            using AElementOp = ck::tensor_operation::element_wise::PassThrough;
+            using BElementOp = ck::tensor_operation::element_wise::PassThrough;
+            using CElementOp = ck::tensor_operation::element_wise::PassThrough;
+
+            using DeviceOp = ck::tensor_operation::device::DeviceBatchedGemmV2MultiD<ALayout,
+                                                                                     BLayout,
+                                                                                     DsLayout,
+                                                                                     CLayout,
+                                                                                     ADataType,
+                                                                                     BDataType,
+                                                                                     DsDataType,
+                                                                                     CDataType,
+                                                                                     AElementOp,
+                                                                                     BElementOp,
+                                                                                     CElementOp>;
+
+            bool pass = ck::profiler::profile_gemm_universal_batched_impl<ADataType,
+                                                                          BDataType,
+                                                                          CDataType,
+                                                                          ALayout,
+                                                                          BLayout,
+                                                                          CLayout,
+                                                                          AElementOp,
+                                                                          BElementOp,
+                                                                          CElementOp,
+                                                                          DeviceOp>(do_verification,
+                                                                                    init_method,
+                                                                                    do_log,
+                                                                                    time_kernel,
+                                                                                    M,
+                                                                                    N,
+                                                                                    K,
+                                                                                    BatchStrideA_,
+                                                                                    BatchStrideB_,
+                                                                                    BatchStrideC_,
+                                                                                    StrideA_,
+                                                                                    StrideB_,
+                                                                                    StrideC_,
+                                                                                    BatchCount,
+                                                                                    n_warmup,
+                                                                                    n_iter,
+                                                                                    rotating);
+
+            return pass ? 0 : 1;
+        };
+
+    if(data_type == GemmDataType::BF16_BF16_BF16 && layout == GemmMatrixLayout::MK_NK_MN)
+    {
+        return profile(BF16{}, BF16{}, BF16{}, Row{}, Col{}, Row{});
+    }
+#if defined(CK_USE_FP8_ON_UNSUPPORTED_ARCH) || defined(CK_USE_GFX94)
+    else if(data_type == GemmDataType::F8_F8_BF16 && layout == GemmMatrixLayout::MK_NK_MN)
+    {
+        return profile(F8{}, F8{}, BF16{}, Row{}, Col{}, Row{});
+    }
+#endif
+    else
+    {
+        std::cout << "this data_type & layout is not implemented" << std::endl;
+
+        return 1;
+    }
+}
+
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_batched_gemm_universal);