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Composable Kernel: /home/docs/checkouts/readthedocs.org/user_builds/advanced-micro-devices-composable-kernel/checkouts/docs-6.4.3/include/ck_tile/ops/gemm/kernel/gemm_kernel.hpp Source File
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 // SPDX-License-Identifier: MIT
 // Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
  
 #pragma once
  
 #include <iostream>
 #include <string>
  
 #include "ck_tile/core.hpp"
 #include "ck_tile/ops/common.hpp"
  
 namespace ck_tile {
  
 struct GemmProblem
 {
     CK_TILE_HOST GemmProblem() = default;
     CK_TILE_HOST GemmProblem(
         index_t M_, index_t N_, index_t K_, index_t stride_A_, index_t stride_B_, index_t stride_C_)
         : M(M_), N(N_), K(K_), stride_A(stride_A_), stride_B(stride_B_), stride_C(stride_C_)
     {
     }
  
     index_t M;
     index_t N;
     index_t K;
     index_t stride_A;
     index_t stride_B;
     index_t stride_C;
 };
  
 struct GemmHostArgs : public GemmProblem
 {
     CK_TILE_HOST GemmHostArgs() = default;
     CK_TILE_HOST GemmHostArgs(const void* a_ptr_,
                               const void* b_ptr_,
                               void* c_ptr_,
                               index_t k_batch_,
                               index_t M_,
                               index_t N_,
                               index_t K_,
                               index_t stride_A_,
                               index_t stride_B_,
                               index_t stride_C_)
         : GemmProblem(M_, N_, K_, stride_A_, stride_B_, stride_C_),
           a_ptr(a_ptr_),
           b_ptr(b_ptr_),
           c_ptr(c_ptr_),
           k_batch(k_batch_)
     {
     }
  
     const void* a_ptr;
     const void* b_ptr;
     void* c_ptr;
     index_t k_batch;
 };
  
 template <typename TilePartitioner_, typename GemmPipeline_, typename EpiloguePipeline_>
 struct GemmKernel
 {
     using TilePartitioner                    = remove_cvref_t<TilePartitioner_>;
     using GemmPipeline                       = remove_cvref_t<GemmPipeline_>;
     using EpiloguePipeline                   = remove_cvref_t<EpiloguePipeline_>;
     using ALayout                            = remove_cvref_t<typename GemmPipeline::ALayout>;
     using BLayout                            = remove_cvref_t<typename GemmPipeline::BLayout>;
     using CLayout                            = remove_cvref_t<typename GemmPipeline::CLayout>;
     static constexpr index_t KernelBlockSize = GemmPipeline::BlockSize;
  
     using ADataType = remove_cvref_t<typename GemmPipeline::ADataType>;
     using BDataType = remove_cvref_t<typename GemmPipeline::BDataType>;
     // Below type is actually accumulation data type - the output of block GEMM.
     using CDataType = remove_cvref_t<typename EpiloguePipeline::ODataType>;
  
     static constexpr auto I0 = number<0>();
     static constexpr auto I1 = number<1>();
     static constexpr auto I2 = number<2>();
  
     CK_TILE_HOST static constexpr auto GridSize(index_t M, index_t N, index_t KBatch)
     {
         return dim3(TilePartitioner::GridSize(M, N), 1, KBatch);
     }
  
     CK_TILE_HOST static constexpr auto BlockSize() { return dim3(KernelBlockSize); }
  
     struct GemmKernelArgs
     {
         const void* a_ptr;
         const void* b_ptr;
         void* c_ptr;
         index_t M;
         index_t N;
         index_t K;
         index_t stride_A;
         index_t stride_B;
         index_t stride_C;
         index_t k_batch;
     };
  
     CK_TILE_HOST static constexpr GemmKernelArgs MakeKernelArgs(const GemmHostArgs& hostArgs)
     {
         return GemmKernelArgs{hostArgs.a_ptr,
                               hostArgs.b_ptr,
                               hostArgs.c_ptr,
                               hostArgs.M,
                               hostArgs.N,
                               hostArgs.K,
                               hostArgs.stride_A,
                               hostArgs.stride_B,
                               hostArgs.stride_C,
                               hostArgs.k_batch};
     }
  
     CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
     {
         return max(GemmPipeline::GetSmemSize(), EpiloguePipeline::GetSmemSize());
     }
  
     struct SplitKBatchOffset
     {
         __device__ SplitKBatchOffset(const GemmKernelArgs& kargs,
                                      const std::size_t k_id = blockIdx.z)
         {
             constexpr auto K1   = TilePartitioner::BlockGemmShape::WarpTile::at(number<2>{});
             const index_t K_t   = kargs.k_batch * K1;
             const index_t KRead = (kargs.K + K_t - 1) / K_t * K1;
  
             if constexpr(std::is_same_v<tensor_layout::gemm::RowMajor, ALayout>)
             {
                 a_k_split_offset = k_id * KRead;
             }
             else if constexpr(std::is_same_v<tensor_layout::gemm::ColumnMajor, ALayout>)
             {
                 a_k_split_offset = k_id * KRead * kargs.stride_A;
             }
  
             if constexpr(std::is_same_v<tensor_layout::gemm::RowMajor, BLayout>)
             {
                 b_k_split_offset = k_id * KRead * kargs.stride_B;
             }
             else if constexpr(std::is_same_v<tensor_layout::gemm::ColumnMajor, BLayout>)
             {
                 b_k_split_offset = k_id * KRead;
             }
  
             if(k_id < static_cast<uint32_t>(kargs.k_batch - 1))
             {
                 splitted_k = KRead;
             }
             else
             {
                 splitted_k = kargs.K - KRead * (kargs.k_batch - 1);
             }
         }
  
         index_t a_k_split_offset;
         index_t b_k_split_offset;
         index_t splitted_k;
     };
  
     CK_TILE_HOST static bool IsSupportedArgument(const GemmKernelArgs& kargs)
     {
         if constexpr(EpiloguePipeline::template GetVectorSizeC<CDataType>() % 2 != 0 &&
                      is_any_of<CDataType, fp16_t, bf16_t>::value)
         {
             if(kargs.k_batch != 1)
             {
                 std::cerr << "Conditions not met for Kbatch >1 !" << std::endl;
                 return false;
             }
         }
  
         if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
         {
             if(kargs.K % TilePartitioner::KPerBlock != 0 && GemmPipeline::kPadK == false)
             {
                 std::cerr << "Can't support K that is not a multiple of KPerBlock"
                              " without padding!"
                           << std::endl;
                 return false;
             }
             if(kargs.K % GemmPipeline::GetVectorSizeA() != 0)
             {
                 std::cerr << "K is not a multiple of vector load size for A tensor!" << std::endl;
                 return false;
             }
         }
         else
         {
             if(kargs.M % TilePartitioner::MPerBlock != 0 && GemmPipeline::kPadM == false)
             {
                 std::cerr << "Can't support M that is not a multiple of MPerBlock"
                              " without padding!"
                           << std::endl;
                 return false;
             }
             if(kargs.M % GemmPipeline::GetVectorSizeA() != 0)
             {
                 std::cerr << "M is not a multiple of vector load size for A tensor!" << std::endl;
                 return false;
             }
         }
  
         if constexpr(std::is_same_v<BLayout, tensor_layout::gemm::RowMajor>)
         {
             if(kargs.N % TilePartitioner::NPerBlock != 0 && GemmPipeline::kPadN == false)
             {
                 std::cerr << "Can't support N that is not a multiple of NPerBlock"
                              " without padding!"
                           << std::endl;
                 return false;
             }
             if(kargs.N % GemmPipeline::GetVectorSizeB() != 0)
             {
                 std::cerr << "N is not a multiple of vector load size for B tensor!" << std::endl;
                 return false;
             }
         }
         else
         {
             if(kargs.K % TilePartitioner::KPerBlock != 0 && GemmPipeline::kPadK == false)
             {
                 std::cerr << "Can't support K that is not a multiple of KPerBlock"
                              " without padding!"
                           << std::endl;
                 return false;
             }
             if(kargs.K % GemmPipeline::GetVectorSizeB() != 0)
             {
                 std::cerr << "K is not a multiple of vector load size for B tensor!" << std::endl;
                 return false;
             }
         }
  
         if constexpr(std::is_same_v<CLayout, tensor_layout::gemm::RowMajor>)
         {
             if(kargs.N % TilePartitioner::NPerBlock != 0 && GemmPipeline::kPadN == false)
             {
                 std::cerr << "Can't support N that is not a multiple of NPerBlock"
                              " without padding!"
                           << std::endl;
                 return false;
             }
             if(kargs.N % EpiloguePipeline::template GetVectorSizeC<CDataType>() != 0)
             {
                 std::cerr << "N is not a multiple of vector load size for C tensor!" << std::endl;
                 return false;
             }
         }
         else
         {
             if(kargs.M % TilePartitioner::MPerBlock != 0 && GemmPipeline::kPadM == false)
             {
                 std::cerr << "Can't support M that is not a multiple of MPerBlock"
                              " without padding!"
                           << std::endl;
                 return false;
             }
             if(kargs.M % EpiloguePipeline::template GetVectorSizeC<CDataType>() != 0)
             {
                 std::cerr << "M is not a multiple of vector load size for C tensor!" << std::endl;
                 return false;
             }
         }
         return true;
     }
  
     template <memory_operation_enum DstInMemOp = memory_operation_enum::set>
     CK_TILE_DEVICE static auto MakeGemmTensorViews(const ADataType* a_ptr,
                                                    const BDataType* b_ptr,
                                                    CDataType* c_ptr,
                                                    const GemmKernelArgs& kargs,
                                                    const SplitKBatchOffset& splitk_batch_offset)
     {
         const auto& a_tensor_view = [&]() {
             if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
             {
                 return make_naive_tensor_view<address_space_enum::global>(
                     a_ptr,
                     make_tuple(kargs.M, splitk_batch_offset.splitted_k),
                     make_tuple(kargs.stride_A, 1),
                     number<GemmPipeline::GetVectorSizeA()>{},
                     number<1>{});
             }
             else
             {
                 return make_naive_tensor_view<address_space_enum::global>(
                     a_ptr,
                     make_tuple(splitk_batch_offset.splitted_k, kargs.M),
                     make_tuple(kargs.stride_A, 1),
                     number<GemmPipeline::GetVectorSizeA()>{},
                     number<1>{});
             }
         }();
  
         const auto& b_tensor_view = [&]() {
             if constexpr(std::is_same_v<BLayout, tensor_layout::gemm::RowMajor>)
             {
                 return make_naive_tensor_view<address_space_enum::global>(
                     b_ptr,
                     make_tuple(splitk_batch_offset.splitted_k, kargs.N),
                     make_tuple(kargs.stride_B, 1),
                     number<GemmPipeline::GetVectorSizeB()>{},
                     number<1>{});
             }
             else
             {
                 return make_naive_tensor_view<address_space_enum::global>(
                     b_ptr,
                     make_tuple(kargs.N, splitk_batch_offset.splitted_k),
                     make_tuple(kargs.stride_B, 1),
                     number<GemmPipeline::GetVectorSizeB()>{},
                     number<1>{});
             }
         }();
  
         // TODO: enable vector write for C in ColMajor
         const auto& c_tensor_view = [&]() {
             if constexpr(std::is_same_v<CLayout, tensor_layout::gemm::RowMajor>)
             {
                 return make_naive_tensor_view<address_space_enum::global, DstInMemOp>(
                     c_ptr,
                     make_tuple(kargs.M, kargs.N),
                     make_tuple(kargs.stride_C, 1),
                     number<EpiloguePipeline::template GetVectorSizeC<CDataType>()>{},
                     number<1>{});
             }
             else
             {
                 return make_naive_tensor_view<address_space_enum::global, DstInMemOp>(
                     c_ptr,
                     make_tuple(kargs.M, kargs.N),
                     make_tuple(1, kargs.stride_C),
                     number<1>{},
                     number<1>{});
             }
         }();
  
         return make_tuple(a_tensor_view, b_tensor_view, c_tensor_view);
     }
  
     template <typename TensorView>
     CK_TILE_DEVICE static auto MakeGemmPadViews(const TensorView& views)
     {
         const auto& a_pad_view = [&]() {
             const auto& a_tensor_view = views.at(I0);
             if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
             {
                 return pad_tensor_view(a_tensor_view,
                                        make_tuple(number<TilePartitioner::MPerBlock>{},
                                                   number<TilePartitioner::KPerBlock>{}),
                                        sequence<false, GemmPipeline::kPadK>{});
             }
             else
             {
                 return pad_tensor_view(a_tensor_view,
                                        make_tuple(number<TilePartitioner::KPerBlock>{},
                                                   number<TilePartitioner::MPerBlock>{}),
                                        sequence<false, GemmPipeline::kPadM>{});
             }
         }();
  
         const auto& b_pad_view = [&]() {
             const auto& b_tensor_view = views.at(I1);
             if constexpr(std::is_same_v<BLayout, tensor_layout::gemm::ColumnMajor>)
             {
                 return pad_tensor_view(b_tensor_view,
                                        make_tuple(number<TilePartitioner::NPerBlock>{},
                                                   number<TilePartitioner::KPerBlock>{}),
                                        sequence<false, GemmPipeline::kPadK>{});
             }
             else
             {
                 return pad_tensor_view(b_tensor_view,
                                        make_tuple(number<TilePartitioner::KPerBlock>{},
                                                   number<TilePartitioner::NPerBlock>{}),
                                        sequence<false, GemmPipeline::kPadN>{});
             }
         }();
  
         // TODO vector write in for C in ColMajor
         const auto& c_pad_view = [&]() {
             const auto& c_tensor_view = views.at(I2);
             if constexpr(std::is_same_v<CLayout, tensor_layout::gemm::RowMajor>)
             {
                 return pad_tensor_view(c_tensor_view,
                                        make_tuple(number<TilePartitioner::MPerBlock>{},
                                                   number<TilePartitioner::NPerBlock>{}),
                                        sequence<false, GemmPipeline::kPadN>{});
             }
             else
             {
                 return pad_tensor_view(c_tensor_view,
                                        make_tuple(number<TilePartitioner::MPerBlock>{},
                                                   number<TilePartitioner::NPerBlock>{}),
                                        sequence<GemmPipeline::kPadM, false>{});
             }
         }();
  
         return make_tuple(a_pad_view, b_pad_view, c_pad_view);
     }
  
     template <typename PadView>
     CK_TILE_DEVICE static auto
     MakeGemmTileWindows(const PadView& views, const index_t i_m, const index_t i_n)
     {
         const auto& a_pad_view = views.at(I0);
         const auto& b_pad_view = views.at(I1);
         const auto& c_pad_view = views.at(I2);
  
         const auto& a_block_window = [&]() {
             if constexpr(std::is_same_v<ALayout, tensor_layout::gemm::RowMajor>)
             {
                 return make_tile_window(a_pad_view,
                                         make_tuple(number<TilePartitioner::MPerBlock>{},
                                                    number<TilePartitioner::KPerBlock>{}),
                                         {i_m, 0});
             }
             else
             {
                 return make_tile_window(a_pad_view,
                                         make_tuple(number<TilePartitioner::KPerBlock>{},
                                                    number<TilePartitioner::MPerBlock>{}),
                                         {0, i_m});
             }
         }();
  
         const auto& b_block_window = [&]() {
             if constexpr(std::is_same_v<BLayout, tensor_layout::gemm::ColumnMajor>)
             {
                 return make_tile_window(b_pad_view,
                                         make_tuple(number<TilePartitioner::NPerBlock>{},
                                                    number<TilePartitioner::KPerBlock>{}),
                                         {i_n, 0});
             }
             else
             {
                 return make_tile_window(b_pad_view,
                                         make_tuple(number<TilePartitioner::KPerBlock>{},
                                                    number<TilePartitioner::NPerBlock>{}),
                                         {0, i_n});
             }
         }();
  
         auto c_block_window = make_tile_window(
             c_pad_view,
             make_tuple(number<TilePartitioner::MPerBlock>{}, number<TilePartitioner::NPerBlock>{}),
             {i_m, i_n});
  
         return make_tuple(a_block_window, b_block_window, c_block_window);
     }
  
     template <memory_operation_enum DstInMemOp = memory_operation_enum::set>
     CK_TILE_DEVICE static void RunGemm(const ADataType* a_ptr,
                                        const BDataType* b_ptr,
                                        CDataType* c_ptr,
                                        void* smem_ptr,
                                        const GemmKernelArgs& kargs,
                                        const SplitKBatchOffset& splitk_batch_offset,
                                        const index_t block_idx_m,
                                        const index_t block_idx_n)
     {
         // Create Gemm tensor views, pad views and tile windows
         const auto& gemm_tensor_views_tuple =
             MakeGemmTensorViews<DstInMemOp>(a_ptr, b_ptr, c_ptr, kargs, splitk_batch_offset);
  
         const auto& gemm_pad_views = MakeGemmPadViews(gemm_tensor_views_tuple);
         auto gemm_tile_windows     = MakeGemmTileWindows(gemm_pad_views, block_idx_m, block_idx_n);
  
         const index_t num_loop = TilePartitioner::GetLoopNum(splitk_batch_offset.splitted_k);
  
         // Run GEMM cooperatively by whole workgroup.
         const auto& a_block_window = gemm_tile_windows.at(I0);
         const auto& b_block_window = gemm_tile_windows.at(I1);
         const auto& c_block_tile =
             GemmPipeline{}.template operator()(a_block_window, b_block_window, num_loop, smem_ptr);
  
         // Run Epilogue Pipeline
         auto& c_block_window = gemm_tile_windows.at(I2);
  
         EpiloguePipeline{}
             .template operator()<decltype(c_block_window), decltype(c_block_tile), DstInMemOp>(
                 c_block_window, c_block_tile, smem_ptr);
     }
  
     CK_TILE_DEVICE void operator()(GemmKernelArgs kargs) const
     {
         const auto [iM, iN] = TilePartitioner{kargs.M, kargs.N}.GetOutputTileIndex(blockIdx.x);
         const index_t i_m   = __builtin_amdgcn_readfirstlane(iM * TilePartitioner::MPerBlock);
         const index_t i_n   = __builtin_amdgcn_readfirstlane(iN * TilePartitioner::NPerBlock);
  
         const SplitKBatchOffset splitk_batch_offset(kargs);
         // options
         const ADataType* a_ptr =
             static_cast<const ADataType*>(kargs.a_ptr) + splitk_batch_offset.a_k_split_offset;
         const BDataType* b_ptr =
             static_cast<const BDataType*>(kargs.b_ptr) + splitk_batch_offset.b_k_split_offset;
         CDataType* c_ptr = static_cast<CDataType*>(kargs.c_ptr);
  
         // allocate LDS
         __shared__ char smem_ptr[GetSmemSize()];
  
         if(kargs.k_batch == 1)
         {
             RunGemm(a_ptr, b_ptr, c_ptr, smem_ptr, kargs, splitk_batch_offset, i_m, i_n);
         }
         else
         {
             // Do not compile in case where we have unsupported
             // VectorSizeC & data type configuration.
             if constexpr(!(EpiloguePipeline::template GetVectorSizeC<CDataType>() % 2 != 0 &&
                            is_any_of<CDataType, fp16_t, bf16_t>::value))
             {
                 RunGemm<memory_operation_enum::atomic_add>(
                     a_ptr, b_ptr, c_ptr, smem_ptr, kargs, splitk_batch_offset, i_m, i_n);
             }
         }
     }
 };
  
 } // namespace ck_tile