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https://github.com/ROCm/composable_kernel.git
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@@ -11,12 +11,97 @@
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#include "ck_tile/ops/gemm/pipeline/gemm_pipeline_ag_bg_cr_scheduler.hpp"
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namespace ck_tile {
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template <index_t NumDTensor = 0>
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struct FlatmmHostArgs
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struct FlatmmProblem
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{
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CK_TILE_HOST FlatmmHostArgs() = default;
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CK_TILE_HOST FlatmmHostArgs(const void* a_ptr_,
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CK_TILE_HOST FlatmmProblem() = default;
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CK_TILE_HOST FlatmmProblem(
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index_t M_, index_t N_, index_t K_, index_t stride_A_, index_t stride_B_, index_t stride_C_)
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: M(M_), N(N_), K(K_), stride_A(stride_A_), stride_B(stride_B_), stride_C(stride_C_)
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{
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}
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index_t M;
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index_t N;
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index_t K;
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index_t stride_A;
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index_t stride_B;
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index_t stride_C;
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};
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template <int SharedGranularity>
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struct FlatmmScalePointer
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{
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static constexpr int granularity = SharedGranularity;
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union
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{
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const float* ptr;
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float scalar; // if shared granularity is 0, all rows/columns use the same scale value
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};
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CK_TILE_HOST_DEVICE FlatmmScalePointer() = default;
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CK_TILE_HOST_DEVICE FlatmmScalePointer(float scalar_) : scalar(scalar_) {}
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CK_TILE_HOST_DEVICE FlatmmScalePointer(const float* ptr_) : ptr(ptr_) {}
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CK_TILE_HOST_DEVICE FlatmmScalePointer operator+(index_t offset) const
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{
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FlatmmScalePointer ret;
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if constexpr(granularity == 0)
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{
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ret.scalar = scalar;
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}
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else if constexpr(granularity == 1)
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{
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ret.ptr = ptr + offset;
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}
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else
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{
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ret.ptr = ptr + offset / granularity;
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}
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return ret;
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}
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CK_TILE_HOST_DEVICE float operator[](index_t i) const
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{
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if constexpr(granularity == 0)
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{
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return scalar;
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}
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else if constexpr(granularity == 1)
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{
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return ptr[i];
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}
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else
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{
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return ptr[i / granularity];
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}
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}
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};
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// shared granularity = -1 means no scale
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template <>
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struct FlatmmScalePointer<-1>
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{
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static constexpr int granularity = -1;
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CK_TILE_HOST_DEVICE constexpr FlatmmScalePointer() = default;
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CK_TILE_HOST_DEVICE constexpr FlatmmScalePointer(float scalar_) {}
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CK_TILE_HOST_DEVICE constexpr FlatmmScalePointer(const float* ptr_) {}
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CK_TILE_HOST_DEVICE constexpr FlatmmScalePointer operator+(index_t) const
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{
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return FlatmmScalePointer{};
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}
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CK_TILE_HOST_DEVICE constexpr float operator[](index_t) const
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{
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return 1; // alway return 1, it doesn't change the result
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}
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};
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template <>
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struct BaseFlatmmHostArgs
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{
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CK_TILE_HOST BaseFlatmmHostArgs() = default;
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CK_TILE_HOST BaseFlatmmHostArgs(const void* a_ptr_,
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const void* b_ptr_,
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const std::array<const void*, NumDTensor>& ds_ptr_,
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void* e_ptr_,
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@@ -66,7 +151,37 @@ struct FlatmmHostArgs
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index_t k_batch;
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};
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template <index_t NumDTensor = 0>
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template <class ScaleM = FlatmmScalePointer<-1>, class ScaleN = FlatmmScalePointer<-1>, index_t NumDTensor = 0>
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struct ScaleFlatmmHostArgs : public BaseFlatmmHostArgs<>
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{
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CK_TILE_HOST ScaleFlatmmHostArgs() = default;
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CK_TILE_HOST ScaleFlatmmHostArgs(const void* a_ptr_,
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const void* b_shuffle_ptr_,
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const std::array<const void*, NumDTensor>& ds_ptr_,
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void* c_ptr_,
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index_t k_batch_,
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index_t M_,
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index_t N_,
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index_t K_,
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index_t stride_A_,
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index_t stride_B_,
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const std::array<index_t, NumDTensor>& stride_Ds_,
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index_t stride_C_,
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ScaleM scale_m_ = nullptr,
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ScaleN scale_n_ = nullptr)
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: BaseFlatmmHostArgs(a_ptr_, b_shuffle_ptr_, ds_ptr_, c_ptr_, M_, N_, K_, stride_A_, stride_B_, stride_Ds_, stride_C_, k_batch_),
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scale_m(scale_m_),
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scale_n(scale_n_)
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{
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}
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ScaleM scale_m = nullptr;
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ScaleN scale_n = nullptr;
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};
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template <int NumberTensor=0>
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using FlatmmHostArgs = ScaleFlatmmHostArgs<FlatmmScalePointer<-1>, FlatmmScalePointer<-1>, NumberTensor>;
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template <class ScaleM, class ScaleN, index_t NumDTensor = 0>
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struct FlatmmKernelArgs
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{
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const void* a_ptr;
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@@ -82,6 +197,8 @@ struct FlatmmKernelArgs
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std::array<index_t, NumDTensor> stride_Ds;
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index_t stride_E;
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index_t k_batch;
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ScaleM scale_m_ptr = nullptr;
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ScaleN scale_n_ptr = nullptr;
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};
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template <typename TilePartitioner_, typename FlatmmPipeline_, typename EpiloguePipeline_>
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@@ -113,7 +230,7 @@ struct FlatmmKernel
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static_assert(DsLayout::size() == DsDataType::size(),
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"The size of DsLayout and DsDataType should be the same");
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using KernelArgs = FlatmmKernelArgs<DsLayout::size()>;
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// using KernelArgs = FlatmmKernelArgs<DsLayout::size()>;
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[[nodiscard]] CK_TILE_HOST static const std::string GetName()
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{
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@@ -129,21 +246,24 @@ struct FlatmmKernel
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CK_TILE_HOST static constexpr auto BlockSize() { return dim3(KernelBlockSize); }
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CK_TILE_HOST static constexpr KernelArgs
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MakeKernelArgs(const FlatmmHostArgs<NumDTensor>& hostArgs)
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template <class ScaleM, class ScaleN>
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CK_TILE_HOST static constexpr FlatmmKernelArgs<ScaleM, ScaleN, DsDataType::size()>
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MakeKernelArgs(const FlatmmHostArgs<ScaleM, ScaleN, DsDataType::size()>& hostArgs)
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{
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return KernelArgs{hostArgs.a_ptr,
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hostArgs.b_ptr,
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hostArgs.ds_ptr,
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hostArgs.e_ptr,
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hostArgs.M,
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hostArgs.N,
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hostArgs.K,
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hostArgs.stride_A,
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hostArgs.stride_B,
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hostArgs.stride_Ds,
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hostArgs.stride_E,
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hostArgs.k_batch};
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return {hostArgs.a_ptr,
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hostArgs.b_ptr,
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hostArgs.ds_ptr,
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hostArgs.e_ptr,
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hostArgs.M,
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hostArgs.N,
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hostArgs.K,
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hostArgs.stride_A,
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hostArgs.stride_B,
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hostArgs.stride_Ds,
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hostArgs.stride_E,
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hostArgs.k_batch,
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hostArgs.scale_m,
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hostArgs.scale_n};
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}
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CK_TILE_HOST_DEVICE static constexpr index_t GetSmemPingSize()
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@@ -157,8 +277,8 @@ struct FlatmmKernel
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struct SplitKBatchOffset
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{
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__device__ SplitKBatchOffset(const KernelArgs& kargs, const std::size_t k_id = blockIdx.z)
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{
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template <class KernelArgs>
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__device__ SplitKBatchOffset(const KernelArgs& kargs, const std::size_t k_id = blockIdx.z) {
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constexpr auto K1 = TilePartitioner::BlockGemmShape::WarpTile::at(number<2>{});
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const index_t K_t = kargs.k_batch * K1;
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const index_t KRead = (kargs.K + K_t - 1) / K_t * K1;
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@@ -196,6 +316,7 @@ struct FlatmmKernel
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index_t splitted_k;
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};
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template <class KernelArgs>
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CK_TILE_HOST static bool IsSupportedArgument(const KernelArgs& kargs)
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{
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if constexpr(EpiloguePipeline::GetVectorSizeC() % 2 != 0 &&
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@@ -341,7 +462,7 @@ struct FlatmmKernel
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return DTesnorIsValid;
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}
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template <memory_operation_enum DstInMemOp = memory_operation_enum::set>
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template <memory_operation_enum DstInMemOp = memory_operation_enum::set, class KernelArgs>
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CK_TILE_DEVICE static auto
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MakeGemmTensorViews(const ADataType* a_ptr,
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const BDataType* b_flat_ptr,
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@@ -559,14 +680,14 @@ struct FlatmmKernel
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return make_tuple(a_block_window, b_flat_block_window, ds_block_window, e_block_window);
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}
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template <bool UseDefaultScheduler = true>
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template <class ScaleM, class ScaleN, bool UseDefaultScheduler = true>
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CK_TILE_DEVICE static void RunFlatmm(const ADataType* a_ptr,
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const BDataType* b_flat_ptr,
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const std::array<const void*, NumDTensor>& ds_ptr,
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EDataType* e_ptr,
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void* smem_ptr_ping,
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void* smem_ptr_pong,
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const KernelArgs& kargs,
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const FlatmmKernelArgs<ScaleM, ScaleN, DsDataType::size()>& kargs,
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const SplitKBatchOffset& splitk_batch_offset,
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const index_t block_idx_m,
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const index_t block_idx_n)
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@@ -588,8 +709,18 @@ struct FlatmmKernel
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a_block_window, b_flat_block_window, num_loop, smem_ptr_ping, smem_ptr_pong);
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// Run Epilogue Pipeline
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if(UseDefaultScheduler || (get_warp_id() == 0))
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if constexpr(ScaleM::granularity != -1 || ScaleN::granularity != -1)
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{
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auto& c_block_window = gemm_tile_windows.at(I3);
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EpiloguePipeline{}.template operator()<decltype(c_block_window), decltype(c_block_tile), decltype(d_block_window)>(
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c_block_window,
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c_block_tile,
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d_block_window,
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smem_ptr_ping,
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kargs.scale_m_ptr + block_idx_m,
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kargs.scale_n_ptr + block_idx_n);
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}
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else if(UseDefaultScheduler || (get_warp_id() == 0))
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{
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// Run Epilogue Pipeline
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auto& c_block_window = gemm_tile_windows.at(I3);
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@@ -598,7 +729,9 @@ struct FlatmmKernel
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}
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}
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CK_TILE_DEVICE void operator()(KernelArgs kargs) const
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template <class ScaleM, class ScaleN>
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CK_TILE_DEVICE void operator()(FlatmmKernelArgs<ScaleM, ScaleN, DsDataType::size()> kargs,
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int partition_idx = blockIdx.x) const
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{
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const auto [iM, iN] = TilePartitioner{kargs.M, kargs.N}.GetOutputTileIndex(blockIdx.x);
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const index_t i_m = __builtin_amdgcn_readfirstlane(iM * TilePartitioner::MPerBlock);
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