Merge remote-tracking branch 'origin/develop' into miopen_downstream-dynamic_reduction_pr

composable_kernel/include/problem_transform/transform_backward_weight_convolution_into_gemm_v4r4r2_nchw_kcyx_nkhw.hpp

+#ifndef CK_TRANSFORM_BACKWARD_WEIGHT_CONVOLUTION_INTO_GEMM_V4R4R2_NCHW_KCYX_NKHW_HPP
+#define CK_TRANSFORM_BACKWARD_WEIGHT_CONVOLUTION_INTO_GEMM_V4R4R2_NCHW_KCYX_NKHW_HPP
+
+#include "common_header.hpp"
+#include "tensor_descriptor.hpp"
+#include "tensor_descriptor_helper.hpp"
+
+namespace ck {
+
+// GemmM = K
+// GemmK = N * Ho * Wo
+// GemmN = C * Y * X
+template <typename... Wei,
+          typename... In,
+          typename... Out,
+          typename ConvStrides,
+          typename ConvDilations,
+          typename InLeftPads,
+          typename InRightPads,
+          index_t GemmK1Value>
+__host__ __device__ constexpr auto
+transform_backward_weight_convolution_into_gemm_v4r4r2_nchw_kcyx_nkhw_pad(
+    const TensorDescriptor<Wei...>& wei_k_c_y_x_grid_desc,
+    const TensorDescriptor<In...>& in_n_c_hi_wi_grid_desc,
+    const TensorDescriptor<Out...>& out_n_k_ho_wo_grid_desc,
+    const ConvStrides& conv_strides,
+    const ConvDilations& conv_dilations,
+    const InLeftPads& in_left_pads,
+    const InRightPads& in_right_pads,
+    Number<GemmK1Value>)
+{
+    constexpr auto I0 = Number<0>{};
+    constexpr auto I1 = Number<1>{};
+    constexpr auto I2 = Number<2>{};
+    constexpr auto I3 = Number<3>{};
+
+    constexpr auto GemmK1 = Number<GemmK1Value>{};
+
+    const auto N = in_n_c_hi_wi_grid_desc.GetLength(I0);
+    const auto C = in_n_c_hi_wi_grid_desc.GetLength(I1);
+    const auto K = out_n_k_ho_wo_grid_desc.GetLength(I1);
+
+    const auto Hi = in_n_c_hi_wi_grid_desc.GetLength(I2);
+    const auto Wi = in_n_c_hi_wi_grid_desc.GetLength(I3);
+
+    const auto Ho = out_n_k_ho_wo_grid_desc.GetLength(I2);
+    const auto Wo = out_n_k_ho_wo_grid_desc.GetLength(I3);
+
+    const auto Y = wei_k_c_y_x_grid_desc.GetLength(I2);
+    const auto X = wei_k_c_y_x_grid_desc.GetLength(I3);
+
+    const auto ConvStrideH = conv_strides[I0];
+    const auto ConvStrideW = conv_strides[I1];
+
+    const auto ConvDilationH = conv_dilations[I0];
+    const auto ConvDilationW = conv_dilations[I1];
+
+    const auto InLeftPadH = in_left_pads[I0];
+    const auto InLeftPadW = in_left_pads[I1];
+
+    const auto InRightPadH = in_right_pads[I0];
+    const auto InRightPadW = in_right_pads[I1];
+
+    const auto GemmM  = K;
+    const auto GemmN  = C * Y * X;
+    const auto GemmK  = N * Ho * Wo;
+    const auto GemmK0 = GemmK / GemmK1;
+
+    // weight tensor
+    const auto wei_gemmm_gemmn_grid_desc = transform_tensor_descriptor(
+        make_naive_tensor_descriptor_packed(make_tuple(K, C * Y * X)),
+        make_tuple(make_pass_through_transform(K), make_pass_through_transform(C * Y * X)),
+        make_tuple(Sequence<0>{}, Sequence<1>{}),
+        make_tuple(Sequence<0>{}, Sequence<1>{}));
+
+    // input tensor
+    const auto in_n_c_hip_wip_grid_desc = transform_tensor_descriptor(
+        in_n_c_hi_wi_grid_desc,
+        make_tuple(make_pass_through_transform(N),
+                   make_pass_through_transform(C),
+                   make_pad_transform(Hi, InLeftPadH, InRightPadH),
+                   make_pad_transform(Wi, InLeftPadW, InRightPadW)),
+        make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
+        make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}));
+
+    const auto in_n_c_y_ho_x_wo_grid_desc = transform_tensor_descriptor(
+        in_n_c_hip_wip_grid_desc,
+        make_tuple(make_pass_through_transform(N),
+                   make_pass_through_transform(C),
+                   make_embed_transform(make_tuple(Y, Ho), make_tuple(ConvDilationH, ConvStrideH)),
+                   make_embed_transform(make_tuple(X, Wo), make_tuple(ConvDilationW, ConvStrideW))),
+        make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
+        make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}, Sequence<4, 5>{}));
+
+    const auto in_gemmk_gemmn_grid_desc =
+        transform_tensor_descriptor(in_n_c_y_ho_x_wo_grid_desc,
+                                    make_tuple(make_merge_transform(make_tuple(C, Y, X)),
+                                               make_merge_transform(make_tuple(N, Ho, Wo))),
+                                    make_tuple(Sequence<1, 2, 4>{}, Sequence<0, 3, 5>{}),
+                                    make_tuple(Sequence<1>{}, Sequence<0>{}));
+
+    const auto in_gemmk0_gemmn_gemmk1_grid_desc =
+        transform_tensor_descriptor(in_gemmk_gemmn_grid_desc,
+                                    make_tuple(make_unmerge_transform(make_tuple(GemmK0, GemmK1)),
+                                               make_pass_through_transform(GemmN)),
+                                    make_tuple(Sequence<0>{}, Sequence<1>{}),
+                                    make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+
+    // output tensor
+    const auto out_gemmk_gemmm_grid_desc = transform_tensor_descriptor(
+        make_naive_tensor_descriptor_packed(make_tuple(N, K, Ho * Wo)),
+        make_tuple(make_pass_through_transform(K), make_merge_transform(make_tuple(N, Ho * Wo))),
+        make_tuple(Sequence<1>{}, Sequence<0, 2>{}),
+        make_tuple(Sequence<1>{}, Sequence<0>{}));
+
+    const auto out_gemmk0_gemmm_gemmk1_grid_desc =
+        transform_tensor_descriptor(out_gemmk_gemmm_grid_desc,
+                                    make_tuple(make_unmerge_transform(make_tuple(GemmK0, GemmK1)),
+                                               make_pass_through_transform(GemmM)),
+                                    make_tuple(Sequence<0>{}, Sequence<1>{}),
+                                    make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+
+    return make_tuple(out_gemmk0_gemmm_gemmk1_grid_desc,
+                      in_gemmk0_gemmn_gemmk1_grid_desc,
+                      wei_gemmm_gemmn_grid_desc);
+}
+
+} // namespace ck
+#endif

composable_kernel/include/tensor_description/multi_index_transform.hpp

@@ -1327,6 +1327,129 @@ struct Merge_v2r2_magic_division
     }
 };
 
+// Implementation of "Merge" transformation primitive that uses division and mod. It is supposed to
+// be used for low_lengths that are known at compile time and are power of 2, otherwise performance
+// will be very bad
+template <typename LowLengths>
+struct Merge_v3_division_mod
+{
+    static constexpr index_t NDimLow = LowLengths::Size();
+
+    using LowerIndex = MultiIndex<NDimLow>;
+    using UpperIndex = MultiIndex<1>;
+
+    using LowLengthsScan =
+        decltype(container_reverse_exclusive_scan(LowLengths{}, math::multiplies{}, Number<1>{}));
+
+    using UpLengths =
+        decltype(make_tuple(container_reduce(LowLengths{}, math::multiplies{}, Number<1>{})));
+
+    LowLengths low_lengths_;
+    LowLengthsScan low_lengths_scan_;
+    UpLengths up_lengths_;
+
+    __host__ __device__ constexpr Merge_v3_division_mod() = default;
+
+    __host__ __device__ constexpr Merge_v3_division_mod(const LowLengths& low_lengths)
+        : low_lengths_{low_lengths},
+          low_lengths_scan_{
+              container_reverse_exclusive_scan(low_lengths, math::multiplies{}, Number<1>{})},
+          up_lengths_{make_tuple(container_reduce(low_lengths, math::multiplies{}, Number<1>{}))}
+    {
+        static_assert(LowerIndex::Size() == NDimLow, "wrong!");
+    }
+
+    __host__ __device__ static constexpr index_t GetNumOfLowerDimension() { return NDimLow; }
+
+    __host__ __device__ static constexpr index_t GetNumOfUpperDimension() { return 1; }
+
+    __host__ __device__ constexpr const auto& GetUpperLengths() const { return up_lengths_; }
+
+    template <typename LowIdx, typename UpIdx>
+    __host__ __device__ constexpr void CalculateLowerIndex(LowIdx& idx_low,
+                                                           const UpIdx& idx_up) const
+    {
+        static_assert(LowIdx::Size() == NDimLow && UpIdx::Size() == 1,
+                      "wrong! inconsistent # of dimension");
+
+        index_t tmp = idx_up[Number<0>{}];
+
+        // division and mod
+        static_for<0, NDimLow - 1, 1>{}([&](auto i) {
+            idx_low(i) = tmp / this->low_lengths_scan_[i];
+            tmp %= this->low_lengths_scan_[i];
+        });
+
+        idx_low(Number<NDimLow - 1>{}) = tmp;
+    }
+
+    template <typename LowIdxDiff,
+              typename UpIdxDiff,
+              typename LowIdx,
+              typename UpIdx,
+              index_t Hack>
+    __host__ __device__ void UpdateLowerIndex(LowIdxDiff& idx_diff_low,
+                                              const UpIdxDiff&,
+                                              LowIdx& idx_low,
+                                              const UpIdx& idx_up_new,
+                                              Number<Hack>) const
+    {
+        static_assert(LowIdxDiff::Size() == NDimLow && UpIdxDiff::Size() == 1 &&
+                          LowIdx::Size() == NDimLow && UpIdx::Size() == 1,
+                      "wrong! inconsistent # of dimension");
+
+        constexpr auto I0   = Number<0>{};
+        constexpr auto INm1 = Number<NDimLow - 1>{};
+
+        index_t tmp = idx_up_new[I0];
+
+        static_for<0, NDimLow - 1, 1>{}([&](auto i) {
+            const index_t tmp2 = idx_low[i];
+            idx_low(i)         = tmp / this->low_lengths_scan_[i];
+            idx_diff_low(i)    = idx_low[i] - tmp2;
+            tmp %= this->low_lengths_scan_[i];
+        });
+
+        const index_t tmp2 = idx_low[INm1];
+        idx_low(INm1)      = tmp;
+        idx_diff_low(INm1) = idx_low[INm1] - tmp2;
+    }
+
+    __host__ __device__ static constexpr bool IsLinearTransform() { return false; }
+
+    __host__ __device__ static constexpr bool IsValidUpperIndexAlwaysMappedToValidLowerIndex()
+    {
+        return true;
+    }
+
+    __host__ __device__ static constexpr bool IsKnownAtCompileTime()
+    {
+        return is_known_at_compile_time<LowLengths>::value &&
+               is_known_at_compile_time<LowLengthsScan>::value &&
+               is_known_at_compile_time<UpLengths>::value;
+    }
+
+    template <typename UpIdx>
+    __host__ __device__ static constexpr bool
+    IsValidUpperIndexMappedToValidLowerIndex(const UpIdx& /* idx_up */)
+    {
+        return true;
+    }
+
+    __host__ __device__ void Print() const
+    {
+        printf("{");
+        printf("Merge_v3_direct_division_mod, ");
+        printf("low_lengths_ ");
+        print_multi_index(low_lengths_);
+        printf("low_lengths_scan_ ");
+        print_multi_index(low_lengths_scan_);
+        printf("up_lengths_ ");
+        print_multi_index(up_lengths_);
+        printf("}");
+    }
+};
+
 template <typename UpLengths, bool Use24BitIntegerCalculation>
 struct UnMerge
 {

composable_kernel/include/tensor_description/multi_index_transform_helper.hpp

@@ -52,22 +52,36 @@ __host__ __device__ constexpr auto make_embed_transform(const UpLengths& up_leng
 template <typename LowLengths>
 __host__ __device__ constexpr auto make_merge_transform(const LowLengths& low_lengths)
 {
-#if !CK_EXPERIMENTAL_MERGE_USE_MAGIC_DIVISION
-    return Merge_v1_carry_check<LowLengths>{low_lengths};
+#if CK_EXPERIMENTAL_MERGE_USE_MAGIC_DIVISION
+    return make_merge_transform_v2_magic_division(low_lengths);
 #else
+    return make_merge_transform_v1_carry_check(low_lengths);
+#endif
+}
+
+template <typename LowLengths>
+__host__ __device__ constexpr auto
+make_merge_transform_v1_carry_check(const LowLengths& low_lengths)
+{
+    return Merge_v1_carry_check<LowLengths>{low_lengths};
+}
+
+template <typename LowLengths>
+__host__ __device__ constexpr auto
+make_merge_transform_v2_magic_division(const LowLengths& low_lengths)
+{
 #if 1
     return Merge_v2_magic_division<LowLengths>{low_lengths};
 #else
     return Merge_v2r2_magic_division<LowLengths>{low_lengths};
 #endif
-#endif
 }
 
 template <typename LowLengths>
 __host__ __device__ constexpr auto
-make_merge_transform_v2_magic_division(const LowLengths& low_lengths)
+make_merge_transform_v3_division_mod(const LowLengths& low_lengths)
 {
-    return Merge_v2_magic_division<LowLengths>{low_lengths};
+    return Merge_v3_division_mod<LowLengths>{low_lengths};
 }
 
 template <typename UpLengths, bool Use24BitIntegerCalculation = false>

composable_kernel/include/tensor_description/tensor_adaptor.hpp

@@ -189,8 +189,7 @@ struct TensorAdaptor
         bool is_known = true;
 
         static_for<0, Transforms::Size(), 1>{}([&](auto i) {
-            is_known &=
-                remove_cv_t<remove_reference_t<decltype(Transforms{}[i])>>::IsKnownAtCompileTime();
+            is_known &= remove_cvref_t<decltype(Transforms{}[i])>::IsKnownAtCompileTime();
         });
 
         return is_known && is_known_at_compile_time<ElementSize>::value;

composable_kernel/include/tensor_description/tensor_descriptor.hpp

@@ -185,8 +185,7 @@ struct TensorDescriptor
         bool is_known = true;
 
         static_for<0, Transforms::Size(), 1>{}([&](auto i) {
-            is_known &=
-                remove_cv_t<remove_reference_t<decltype(Transforms{}[i])>>::IsKnownAtCompileTime();
+            is_known &= remove_cvref_t<decltype(Transforms{}[i])>::IsKnownAtCompileTime();
         });
 
         return is_known && is_known_at_compile_time<ElementSize>::value &&
@@ -587,11 +586,11 @@ __host__ __device__ constexpr bool coordinate_has_valid_offset(const TensorDesc&
 
 template <typename TensorDesc>
 using TensorCoordinate_t = decltype(make_tensor_coordinate(
-    TensorDesc{}, MultiIndex<remove_cv_t<remove_reference_t<TensorDesc>>::GetNumOfDimension()>{}));
+    TensorDesc{}, MultiIndex<remove_cvref_t<TensorDesc>::GetNumOfDimension()>{}));
 
 template <typename TensorDesc>
 using TensorCoordinateStep_t = decltype(make_tensor_coordinate_step(
-    TensorDesc{}, MultiIndex<remove_cv_t<remove_reference_t<TensorDesc>>::GetNumOfDimension()>{}));
+    TensorDesc{}, MultiIndex<remove_cvref_t<TensorDesc>::GetNumOfDimension()>{}));
 
 } // namespace ck
 #endif

composable_kernel/include/tensor_operation/blockwise_gemm_dlops_v3.hpp

@@ -110,12 +110,10 @@ struct BlockwiseGemmDlops_km_kn_m0m1n0n1_v3
                         const BThreadBuffer& b_thread_buf,
                         CThreadBuffer& c_thread_buf) const
     {
-        static_assert(is_same<remove_cv_t<remove_reference_t<typename ABlockBuffer::type>>,
-                              remove_cv_t<remove_reference_t<FloatA>>>::value &&
-                      is_same<remove_cv_t<remove_reference_t<typename BThreadBuffer::type>>,
-                              remove_cv_t<remove_reference_t<FloatB>>>::value &&
-                      is_same<remove_cv_t<remove_reference_t<typename CThreadBuffer::type>>,
-                              remove_cv_t<remove_reference_t<FloatC>>>::value &&
+        static_assert(
+            is_same<remove_cvref_t<typename ABlockBuffer::type>, remove_cvref_t<FloatA>>::value &&
+            is_same<remove_cvref_t<typename BThreadBuffer::type>, remove_cvref_t<FloatB>>::value &&
+            is_same<remove_cvref_t<typename CThreadBuffer::type>, remove_cvref_t<FloatC>>::value &&
             "wrong! inconsistent type");
 
         constexpr auto I0 = Number<0>{};

composable_kernel/include/tensor_operation/blockwise_gemm_xdlops.hpp

@@ -4,21 +4,21 @@
 #include "common_header.hpp"
 #include "threadwise_tensor_slice_transfer.hpp"
 #include "xdlops_gemm.hpp"
+#include "tensor_adaptor.hpp"
 
 namespace ck {
 
 template <index_t BlockSize,
           typename FloatAB,
-          class ABlockDesc,
-          class BBlockDesc,
-          index_t MPerWave,
-          index_t NPerWave,
+          typename AK0MK1BlockDesc,
+          typename BK0NK1BlockDesc,
+          index_t MPerXDL,
+          index_t NPerXDL,
+          index_t MRepeat,
+          index_t NRepeat,
           index_t K1>
-struct BlockwiseGemmXdlops_km_kn_m0m1m2n_v1
+struct BlockwiseGemmXdlops_k0mk1_k0nk1_m0n0m1n1m2m3m4n2_v1
 {
-
-    using CIndex = MultiIndex<2>;
-
     static constexpr auto I0 = Number<0>{};
     static constexpr auto I1 = Number<1>{};
     static constexpr auto I2 = Number<2>{};
@@ -26,329 +26,165 @@ struct BlockwiseGemmXdlops_km_kn_m0m1m2n_v1
 
     static constexpr index_t WaveSize = 64;
 
-    static constexpr index_t M0 = ABlockDesc{}.GetLength(I1);
-    static constexpr index_t M1 = ABlockDesc{}.GetLength(I2);
-
-    static constexpr index_t N0 = BBlockDesc{}.GetLength(I1);
-    static constexpr index_t N1 = BBlockDesc{}.GetLength(I2);
+    static constexpr index_t MPerBlock = AK0MK1BlockDesc{}.GetLength(I1);
+    static constexpr index_t NPerBlock = BK0NK1BlockDesc{}.GetLength(I1);
 
-    static constexpr auto xdlops_gemm = XdlopsGemm<FloatAB, MPerWave, NPerWave, K1>{};
+    static constexpr index_t K0        = BK0NK1BlockDesc{}.GetLength(I0);
+    static constexpr index_t KPerBlock = K0;
 
-    static constexpr index_t MWaves = M1 / MPerWave;
-    static constexpr index_t NWaves = N1 / NPerWave;
+    static constexpr auto xdlops_gemm = XdlopsGemm<FloatAB, MPerXDL, NPerXDL, K1>{};
 
-    static constexpr index_t MRepeat = M0;
-    static constexpr index_t NRepeat = N0;
+    static constexpr index_t MWaves = MPerBlock / (MRepeat * MPerXDL);
+    static constexpr index_t NWaves = NPerBlock / (NRepeat * NPerXDL);
 
-    __device__ constexpr auto GetCLayout() const { return xdlops_gemm.GetCLayout(); }
+    __device__ static auto GetWaveIdx()
+    {
+        const index_t thread_id = get_thread_local_1d_id();
 
-    __device__ constexpr auto GetNumBlks() const { return xdlops_gemm.GetCLayout().GetNumBlks(); }
+        constexpr auto threadid_to_wave_idx_adaptor = make_single_stage_tensor_adaptor(
+            make_tuple(make_merge_transform(make_tuple(MWaves, NWaves, WaveSize))),
+            make_tuple(Sequence<0, 1, 2>{}),
+            make_tuple(Sequence<0>{}));
 
-    __device__ constexpr auto GetBlkSize() const { return xdlops_gemm.GetCLayout().GetBlkSize(); }
+        return threadid_to_wave_idx_adaptor.CalculateBottomIndex(make_multi_index(thread_id));
+    }
 
     __device__ static auto CalculateAThreadOriginDataIndex()
     {
-        const index_t thread_id = get_thread_local_1d_id();
-        const index_t waveId    = thread_id / WaveSize;
-        const index_t laneId    = thread_id % WaveSize;
-        const index_t waveId_m  = waveId / NWaves;
+        const auto wave_idx = GetWaveIdx();
 
-        if constexpr(xdlops_gemm.IsKReduction)
-        {
-            const index_t m_offset = waveId_m * MPerWave + xdlops_gemm.GetBlkTd(laneId);
-            const index_t k_offset = xdlops_gemm.GetBlkId(laneId);
-            return make_tuple(k_offset, 0, m_offset, 0);
-        }
-        else
-        {
-            const index_t m_offset = waveId_m * MPerWave + laneId;
-            const index_t k_offset = 0;
-            return make_tuple(k_offset, 0, m_offset, 0);
-        }
+        const auto waveId_m = wave_idx[I0];
+
+        const auto xdlops_a_idx = xdlops_gemm.CalculateAThreadOriginDataIndex();
+
+        return make_tuple(xdlops_a_idx[I0], 0, waveId_m, xdlops_a_idx[I1], 0);
     }
 
     __device__ static auto CalculateBThreadOriginDataIndex()
     {
-        const index_t thread_id = get_thread_local_1d_id();
-        const index_t waveId    = thread_id / WaveSize;
-        const index_t laneId    = thread_id % WaveSize;
-        const index_t waveId_n  = waveId % NWaves;
+        const auto wave_idx = GetWaveIdx();
 
-        if constexpr(xdlops_gemm.IsKReduction)
-        {
-            const index_t n_offset = waveId_n * NPerWave + xdlops_gemm.GetBlkTd(laneId);
-            const index_t k_offset = xdlops_gemm.GetBlkId(laneId);
-            return make_tuple(k_offset, 0, n_offset, 0);
-        }
-        else
-        {
-            const index_t n_offset = waveId_n * NPerWave + laneId;
-            const index_t k_offset = 0;
-            return make_tuple(k_offset, 0, n_offset, 0);
-        }
+        const auto waveId_n = wave_idx[I1];
+
+        const auto xdlops_b_idx = xdlops_gemm.CalculateBThreadOriginDataIndex();
+
+        return make_tuple(xdlops_b_idx[I0], 0, waveId_n, xdlops_b_idx[I1], 0);
     }
 
     template <index_t m0, index_t n0, index_t xdlops_i, index_t blk_i>
-    __device__ static CIndex
+    __device__ static auto
         CalculateCThreadOriginDataIndex(Number<m0>, Number<n0>, Number<xdlops_i>, Number<blk_i>)
     {
+        const auto wave_idx = GetWaveIdx();
 
-        const index_t waveId = get_thread_local_1d_id() / WaveSize;
+        const auto waveId_m = wave_idx[I0];
+        const auto waveId_n = wave_idx[I1];
 
-        const auto thread_mtx_on_blk = xdlops_gemm.GetBeginOfThreadBlk(xdlops_i, blk_i);
+        const auto blk_idx = xdlops_gemm.GetBeginOfThreadBlk(xdlops_i, blk_i);
 
-        const index_t waveId_m = waveId / NWaves;
-        const index_t waveId_n = waveId % NWaves;
+        constexpr auto mrepeat_mwave_mperxdl_to_m_adaptor = make_single_stage_tensor_adaptor(
+            make_tuple(make_unmerge_transform(make_tuple(MRepeat, MWaves, MPerXDL))),
+            make_tuple(Sequence<0>{}),
+            make_tuple(Sequence<0, 1, 2>{}));
 
-        const index_t m_offset = m0 * M1 + waveId_m * MPerWave + thread_mtx_on_blk[I0];
-        const index_t n_offset = n0 * N1 + waveId_n * NPerWave + thread_mtx_on_blk[I1];
+        constexpr auto nrepeat_nwave_nperxdl_to_n_adaptor = make_single_stage_tensor_adaptor(
+            make_tuple(make_unmerge_transform(make_tuple(NRepeat, NWaves, NPerXDL))),
+            make_tuple(Sequence<0>{}),
+            make_tuple(Sequence<0, 1, 2>{}));
 
-        return CIndex{m_offset, n_offset};
+        const index_t c_thread_m = mrepeat_mwave_mperxdl_to_m_adaptor.CalculateBottomIndex(
+            make_tuple(m0, waveId_m, blk_idx[I0]))[I0];
+        const index_t c_thread_n = nrepeat_nwave_nperxdl_to_n_adaptor.CalculateBottomIndex(
+            make_tuple(n0, waveId_n, blk_idx[I1]))[I0];
+
+        return make_tuple(c_thread_m, c_thread_n);
     }
 
-    __device__ BlockwiseGemmXdlops_km_kn_m0m1m2n_v1()
-        : a_thread_copy_{CalculateAThreadOriginDataIndex()},
-          b_thread_copy_{CalculateBThreadOriginDataIndex()}
+    __host__ __device__ BlockwiseGemmXdlops_k0mk1_k0nk1_m0n0m1n1m2m3m4n2_v1()
     {
-        static_assert(ABlockDesc::IsKnownAtCompileTime() && BBlockDesc::IsKnownAtCompileTime(),
+        static_assert(AK0MK1BlockDesc::IsKnownAtCompileTime() &&
+                          BK0NK1BlockDesc::IsKnownAtCompileTime(),
                       "wrong! Desc should be known at compile-time");
 
-        static_assert(ABlockDesc{}.GetLength(I0) == BBlockDesc{}.GetLength(I0),
-                      "wrong! K dimension not consistent");
+        static_assert(AK0MK1BlockDesc{}.GetLength(I0) == BK0NK1BlockDesc{}.GetLength(I0),
+                      "wrong! K0 dimension not consistent");
 
-        static_assert(ABlockDesc{}.GetLength(I3) == BBlockDesc{}.GetLength(I3),
+        static_assert(AK0MK1BlockDesc{}.GetLength(I2) == BK0NK1BlockDesc{}.GetLength(I2),
                       "wrong! K1 dimension not consistent");
 
         static_assert(BlockSize == MWaves * NWaves * WaveSize,
                       "BlockSize != MWaves * NWaves * WaveSize\n");
 
-        static_assert(K1 == BBlockDesc{}.GetLength(I3), "K1 is wrong!");
-
-        constexpr index_t KPerBlock = ABlockDesc{}.GetLength(I0);
-
-        static_assert(KPerBlock % xdlops_gemm.KPerXdlops == 0, "KPerBlock is wrong!");
-
-        static_assert(K1 % xdlops_gemm.mfma_type.k_base == 0, "K1 is wrong!");
+        static_assert(MPerBlock % (MPerXDL * MRepeat) == 0 && NPerBlock % (NPerXDL * NRepeat) == 0,
+                      "wrong!");
     }
 
-    template <typename ABlockBuffer, typename BBlockBuffer, typename CThreadBuffer>
-    __device__ void Run(const ABlockBuffer& a_block_buf,
-                        const BBlockBuffer& b_block_buf,
-                        CThreadBuffer& c_thread_buf) const
+    __host__ __device__ static constexpr auto GetCM0N0M1N1M2M3M4N2ThreadDescriptor()
     {
-        auto a_thread_buf = make_static_buffer<AddressSpaceEnum_t::Vgpr, FloatAB>(
-            a_thread_desc_.GetElementSpaceSize());
-        auto b_thread_buf = make_static_buffer<AddressSpaceEnum_t::Vgpr, FloatAB>(
-            b_thread_desc_.GetElementSpaceSize());
-
-        constexpr index_t KPerBlock = ABlockDesc{}.GetLength(I0);
-
-        vector_type<FloatAB, a_thread_desc_.GetElementSpaceSize()> a_thread_vec;
-
-        vector_type<FloatAB, b_thread_desc_.GetElementSpaceSize()> b_thread_vec;
-
-        static_for<0, KPerBlock, xdlops_gemm.KPerXdlops>{}([&](auto k) {
-            // read A
-            a_thread_copy_.Run(ABlockDesc{},
-                               make_tuple(k, I0, I0, I0),
-                               a_block_buf,
-                               a_thread_desc_,
-                               make_tuple(I0, I0, I0, I0),
-                               a_thread_buf);
-
-            // read B
-            b_thread_copy_.Run(BBlockDesc{},
-                               make_tuple(k, I0, I0, I0),
-                               b_block_buf,
-                               b_thread_desc_,
-                               make_tuple(I0, I0, I0, I0),
-                               b_thread_buf);
-
-            using mfma_input_type =
-                typename vector_type<FloatAB, xdlops_gemm.mfma_type.k_base>::type;
-
-            static_for<0, a_thread_desc_.GetElementSpaceSize(), 1>{}([&](auto i) {
-                a_thread_vec.template AsType<FloatAB>()(Number<i>{}) = a_thread_buf[Number<i>{}];
-            });
+        constexpr auto c_m0_m1_m2_n_tblk_lens = xdlops_gemm.GetCM0M1M2NThreadBlkLengths();
 
-            static_for<0, b_thread_desc_.GetElementSpaceSize(), 1>{}([&](auto i) {
-                b_thread_vec.template AsType<FloatAB>()(Number<i>{}) = b_thread_buf[Number<i>{}];
-            });
+        constexpr auto M0 = c_m0_m1_m2_n_tblk_lens[I0];
+        constexpr auto M1 = c_m0_m1_m2_n_tblk_lens[I1];
+        constexpr auto M2 = c_m0_m1_m2_n_tblk_lens[I2];
+        constexpr auto N  = c_m0_m1_m2_n_tblk_lens[I3];
 
-            static_for<0, MRepeat, 1>{}([&](auto m0) {
-                static_for<0, NRepeat, 1>{}([&](auto n0) {
-                    xdlops_gemm.template Run<decltype(a_thread_desc_),
-                                             decltype(b_thread_desc_),
-                                             decltype(c_thread_desc_),
-                                             m0,
-                                             n0>(a_thread_vec.template AsType<mfma_input_type>(),
-                                                 b_thread_vec.template AsType<mfma_input_type>(),
-                                                 c_thread_buf);
-                });
-            });
-        });
+        return make_naive_tensor_descriptor_packed(make_tuple(I1, I1, I1, I1, M0, M1, M2, N));
     }
 
-    private:
-    // A[K, M]
-    static constexpr auto a_thread_desc_ =
-        make_naive_tensor_descriptor_packed(make_tuple(I1, Number<MRepeat>{}, I1, Number<K1>{}));
-
-    // B[K, N]
-    static constexpr auto b_thread_desc_ =
-        make_naive_tensor_descriptor_packed(make_tuple(I1, Number<NRepeat>{}, I1, Number<K1>{}));
-
-    static constexpr auto c_thread_desc_ =
-        make_naive_tensor_descriptor_packed(make_tuple(Number<MRepeat>{}, Number<NRepeat>{}));
-
-    using AThreadCopy = ThreadwiseTensorSliceTransfer_v4<FloatAB,
-                                                         FloatAB,
-                                                         ABlockDesc,
-                                                         decltype(a_thread_desc_),
-                                                         Sequence<1, MRepeat, 1, K1>,
-                                                         Sequence<0, 1, 2, 3>,
-                                                         3,
-                                                         K1,
-                                                         1>;
-
-    using BThreadCopy = ThreadwiseTensorSliceTransfer_v4<FloatAB,
-                                                         FloatAB,
-                                                         BBlockDesc,
-                                                         decltype(b_thread_desc_),
-                                                         Sequence<1, NRepeat, 1, K1>,
-                                                         Sequence<0, 1, 2, 3>,
-                                                         3,
-                                                         K1,
-                                                         1>;
-
-    AThreadCopy a_thread_copy_;
-    BThreadCopy b_thread_copy_;
-};
-
-template <index_t BlockSize,
-          typename FloatAB,
-          class ABlockDesc,
-          class BBlockDesc,
-          index_t MPerWave,
-          index_t NPerWave,
-          index_t K1>
-struct BlockwiseGemmXdlops_km_kn_m0m1m2n_v1_2x2pipeline
-{
-
-    using CIndex = MultiIndex<2>;
-
-    static constexpr auto I0 = Number<0>{};
-    static constexpr auto I1 = Number<1>{};
-    static constexpr auto I2 = Number<2>{};
-    static constexpr auto I3 = Number<3>{};
-
-    static constexpr auto xdlops_gemm = XdlopsGemm<float, MPerWave, NPerWave, K1>{};
-
-    static constexpr index_t WaveSize = 64;
-
-    static constexpr index_t M0 = ABlockDesc{}.GetLength(I1);
-    static constexpr index_t M1 = ABlockDesc{}.GetLength(I2);
-
-    static constexpr index_t N0 = BBlockDesc{}.GetLength(I1);
-    static constexpr index_t N1 = BBlockDesc{}.GetLength(I2);
-
-    static constexpr index_t MWaves = M1 / MPerWave;
-    static constexpr index_t NWaves = N1 / NPerWave;
-
-    static constexpr index_t MRepeat = M0;
-    static constexpr index_t NRepeat = N0;
-
-    __device__ constexpr auto GetCLayout() const { return xdlops_gemm.GetCLayout(); }
-
-    __device__ constexpr auto GetNumBlks() const { return xdlops_gemm.GetCLayout().GetNumBlks(); }
-
-    __device__ constexpr auto GetBlkSize() const { return xdlops_gemm.GetCLayout().GetBlkSize(); }
-
-    __device__ static auto CalculateAThreadOriginDataIndex()
+    __host__ __device__ static constexpr auto GetCM0N0M1N1M2M3M4N2BlockDescriptor()
     {
-        const index_t thread_id = get_thread_local_1d_id();
-        const index_t waveId    = thread_id / WaveSize;
-        const index_t laneId    = thread_id % WaveSize;
-        const index_t waveId_m  = waveId / NWaves;
-
-        if constexpr(xdlops_gemm.IsKReduction)
-        {
-            const index_t m_offset = waveId_m * MPerWave + xdlops_gemm.GetBlkTd(laneId);
-            const index_t k_offset = xdlops_gemm.GetBlkId(laneId);
-            return make_tuple(k_offset, 0, m_offset, 0);
-        }
-        else
-        {
-            const index_t m_offset = waveId_m * MPerWave + laneId;
-            const index_t k_offset = 0;
-            return make_tuple(k_offset, 0, m_offset, 0);
-        }
+        constexpr auto c_m0_n0_m1_n1_m2_n2_block_desc =
+            make_naive_tensor_descriptor_packed(make_tuple(Number<MRepeat>{},
+                                                           Number<NRepeat>{},
+                                                           Number<MWaves>{},
+                                                           Number<NWaves>{},
+                                                           Number<MPerXDL>{},
+                                                           Number<NPerXDL>{}));
+
+        return xdlops_gemm.MakeCM0N0M1N1M2M3M4N2Descriptor(c_m0_n0_m1_n1_m2_n2_block_desc);
     }
 
-    __device__ static auto CalculateBThreadOriginDataIndex()
-    {
-        const index_t thread_id = get_thread_local_1d_id();
-        const index_t waveId    = thread_id / WaveSize;
-        const index_t laneId    = thread_id % WaveSize;
-        const index_t waveId_n  = waveId % NWaves;
-
-        if constexpr(xdlops_gemm.IsKReduction)
-        {
-            const index_t n_offset = waveId_n * NPerWave + xdlops_gemm.GetBlkTd(laneId);
-            const index_t k_offset = xdlops_gemm.GetBlkId(laneId);
-            return make_tuple(k_offset, 0, n_offset, 0);
-        }
-        else
+    template <typename CMNGridDesc>
+    __host__ __device__ static constexpr auto
+    MakeCM0N0M1N1M2M3M4N2GridDescriptor(const CMNGridDesc& c_m_n_grid_desc)
     {
-            const index_t n_offset = waveId_n * NPerWave + laneId;
-            const index_t k_offset = 0;
-            return make_tuple(k_offset, 0, n_offset, 0);
-        }
+        const auto c_m0_n0_m1_n1_m2_n2_grid_desc = transform_tensor_descriptor(
+            c_m_n_grid_desc,
+            make_tuple(make_unmerge_transform(make_tuple(MRepeat, MWaves, MPerXDL)),
+                       make_unmerge_transform(make_tuple(NRepeat, NWaves, NPerXDL))),
+            make_tuple(Sequence<0>{}, Sequence<1>{}),
+            make_tuple(Sequence<0, 2, 4>{}, Sequence<1, 3, 5>{}));
+
+        return xdlops_gemm.MakeCM0N0M1N1M2M3M4N2Descriptor(c_m0_n0_m1_n1_m2_n2_grid_desc);
     }
 
-    template <index_t m0, index_t n0, index_t xdlops_i, index_t blk_i>
-    __device__ static CIndex
-        CalculateCThreadOriginDataIndex(Number<m0>, Number<n0>, Number<xdlops_i>, Number<blk_i>)
+    __host__ __device__ static constexpr auto MakeAK0M0M1M2K1BlockDescriptor()
     {
-
-        const index_t waveId = get_thread_local_1d_id() / WaveSize;
-
-        const auto thread_mtx_on_blk = xdlops_gemm.GetBeginOfThreadBlk(xdlops_i, blk_i);
-
-        const index_t waveId_m = waveId / NWaves;
-        const index_t waveId_n = waveId % NWaves;
-
-        const index_t m_offset = m0 * M1 + waveId_m * MPerWave + thread_mtx_on_blk[I0];
-        const index_t n_offset = n0 * N1 + waveId_n * NPerWave + thread_mtx_on_blk[I1];
-
-        return CIndex{m_offset, n_offset};
+        return transform_tensor_descriptor(
+            AK0MK1BlockDesc{},
+            make_tuple(make_pass_through_transform(Number<KPerBlock>{}),
+                       make_unmerge_transform(
+                           make_tuple(Number<MRepeat>{}, Number<MWaves>{}, Number<MPerXDL>{})),
+                       make_pass_through_transform(Number<K1>{})),
+            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}),
+            make_tuple(Sequence<0>{}, Sequence<1, 2, 3>{}, Sequence<4>{}));
     }
 
-    __device__ BlockwiseGemmXdlops_km_kn_m0m1m2n_v1_2x2pipeline()
-        : a_thread_copy_{CalculateAThreadOriginDataIndex()},
-          b_thread_copy_{CalculateBThreadOriginDataIndex()}
+    __host__ __device__ static constexpr auto MakeBK0N0N1N2K1BlockDescriptor()
     {
-        static_assert(ABlockDesc::IsKnownAtCompileTime() && BBlockDesc::IsKnownAtCompileTime(),
-                      "wrong! Desc should be known at compile-time");
-
-        static_assert(ABlockDesc{}.GetLength(I0) == BBlockDesc{}.GetLength(I0),
-                      "wrong! K dimension not consistent");
-
-        static_assert(ABlockDesc{}.GetLength(I3) == BBlockDesc{}.GetLength(I3),
-                      "wrong! K1 dimension not consistent");
-
-        static_assert(BlockSize == MWaves * NWaves * WaveSize,
-                      "BlockSize != MWaves * NWaves * WaveSize\n");
-
-        static_assert(K1 == BBlockDesc{}.GetLength(I3), "K1 is wrong!");
-
-        constexpr index_t KPerBlock = ABlockDesc{}.GetLength(I0);
-
-        static_assert(KPerBlock % xdlops_gemm.KPerXdlops == 0, "KPerBlock is wrong!");
-
-        static_assert(K1 % xdlops_gemm.mfma_type.k_base == 0, "K1 is wrong!");
+        return transform_tensor_descriptor(
+            BK0NK1BlockDesc{},
+            make_tuple(make_pass_through_transform(Number<KPerBlock>{}),
+                       make_unmerge_transform(
+                           make_tuple(Number<NRepeat>{}, Number<NWaves>{}, Number<NPerXDL>{})),
+                       make_pass_through_transform(Number<K1>{})),
+            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}),
+            make_tuple(Sequence<0>{}, Sequence<1, 2, 3>{}, Sequence<4>{}));
     }
 
+    static constexpr auto a_k0_m0_m1_m2_k1_block_desc = MakeAK0M0M1M2K1BlockDescriptor();
+    static constexpr auto b_k0_n0_n1_n2_k1_block_desc = MakeBK0N0N1N2K1BlockDescriptor();
+
     template <typename ABlockBuffer, typename BBlockBuffer, typename CThreadBuffer>
     __device__ void Run(const ABlockBuffer& a_block_buf,
                         const BBlockBuffer& b_block_buf,
@@ -359,165 +195,87 @@ struct BlockwiseGemmXdlops_km_kn_m0m1m2n_v1_2x2pipeline
         auto b_thread_buf = make_static_buffer<AddressSpaceEnum_t::Vgpr, FloatAB>(
             b_thread_desc_.GetElementSpaceSize());
 
-        constexpr index_t KPerBlock = ABlockDesc{}.GetLength(I0);
-
-        // read A_sub_0
-        a_thread_copy_.Run(ABlockDesc{},
-                           make_tuple(I0, I0, I0, I0),
-                           a_block_buf,
-                           a_thread_desc_,
-                           make_tuple(I0, I0, I0, I0),
-                           a_thread_buf);
-
-        // read B_sub_0
-        b_thread_copy_.Run(BBlockDesc{},
-                           make_tuple(I0, I0, I0, I0),
-                           b_block_buf,
-                           b_thread_desc_,
-                           make_tuple(I0, I0, I0, I0),
-                           b_thread_buf);
-
-        // read B_sub_1
-        b_thread_copy_.Run(BBlockDesc{},
-                           make_tuple(I0, I1, I0, I0),
-                           b_block_buf,
-                           b_thread_desc_,
-                           make_tuple(I0, I1, I0, I0),
-                           b_thread_buf);
+        vector_type<FloatAB, K1> a_thread_vec;
 
-        // read A_sub_1
-        a_thread_copy_.Run(ABlockDesc{},
-                           make_tuple(I0, I1, I0, I0),
-                           a_block_buf,
-                           a_thread_desc_,
-                           make_tuple(I0, I1, I0, I0),
-                           a_thread_buf);
+        vector_type<FloatAB, K1> b_thread_vec;
 
-        // C_sub_00 += transpose(A_sub_0) * B_sub_0
-        xdlops_gemm.template Run<decltype(a_thread_desc_),
-                                 decltype(b_thread_desc_),
-                                 decltype(c_thread_desc_),
-                                 0,
-                                 0>(a_thread_buf, b_thread_buf, c_thread_buf);
-
-        // C_sub_01 += transpose(A_sub_0) * B_sub_1
-        xdlops_gemm.template Run<decltype(a_thread_desc_),
-                                 decltype(b_thread_desc_),
-                                 decltype(c_thread_desc_),
-                                 0,
-                                 1>(a_thread_buf, b_thread_buf, c_thread_buf);
-
-        static_for<xdlops_gemm.KPerXdlops, KPerBlock, xdlops_gemm.KPerXdlops>{}([&](auto k) {
-            // read A_sub_0
-            a_thread_copy_.Run(ABlockDesc{},
-                               make_tuple(k, I0, I0, I0),
+        static_for<0, KPerBlock, xdlops_gemm.KPerXdlops / xdlops_gemm.KPerThread>{}([&](auto k0) {
+            // read A
+            a_thread_copy_.Run(a_k0_m0_m1_m2_k1_block_desc,
+                               make_tuple(k0, I0, I0, I0, I0),
                                a_block_buf,
                                a_thread_desc_,
-                               make_tuple(I0, I0, I0, I0),
+                               make_tuple(I0, I0, I0, I0, I0),
                                a_thread_buf);
 
-            // C_sub_10 += transpose(A_sub_1) * B_sub_0
-            xdlops_gemm.template Run<decltype(a_thread_desc_),
-                                     decltype(b_thread_desc_),
-                                     decltype(c_thread_desc_),
-                                     1,
-                                     0>(a_thread_buf, b_thread_buf, c_thread_buf);
-
-            // read B_sub_0
-            b_thread_copy_.Run(BBlockDesc{},
-                               make_tuple(k, I0, I0, I0),
-                               b_block_buf,
-                               b_thread_desc_,
-                               make_tuple(I0, I0, I0, I0),
-                               b_thread_buf);
-
-            // C_sub_11 += transpose(A_sub_1) * B_sub_1
-            xdlops_gemm.template Run<decltype(a_thread_desc_),
-                                     decltype(b_thread_desc_),
-                                     decltype(c_thread_desc_),
-                                     1,
-                                     1>(a_thread_buf, b_thread_buf, c_thread_buf);
-
-            // read B_sub_1
-            b_thread_copy_.Run(BBlockDesc{},
-                               make_tuple(k, I1, I0, I0),
+            // read B
+            b_thread_copy_.Run(b_k0_n0_n1_n2_k1_block_desc,
+                               make_tuple(k0, I0, I0, I0, I0),
                                b_block_buf,
                                b_thread_desc_,
-                               make_tuple(I0, I1, I0, I0),
+                               make_tuple(I0, I0, I0, I0, I0),
                                b_thread_buf);
 
-            // read A_sub_1
-            a_thread_copy_.Run(ABlockDesc{},
-                               make_tuple(k, I1, I0, I0),
-                               a_block_buf,
-                               a_thread_desc_,
-                               make_tuple(I0, I1, I0, I0),
-                               a_thread_buf);
+            using mfma_input_type = typename vector_type<FloatAB, xdlops_gemm.KPerThread>::type;
 
-            // C_sub_00 += transpose(A_sub_0) * B_sub_0
-            xdlops_gemm.template Run<decltype(a_thread_desc_),
-                                     decltype(b_thread_desc_),
-                                     decltype(c_thread_desc_),
-                                     0,
-                                     0>(a_thread_buf, b_thread_buf, c_thread_buf);
+            static_for<0, MRepeat, 1>{}([&](auto m0) {
+                static_for<0, NRepeat, 1>{}([&](auto n0) {
+                    static_for<0, K1, 1>{}([&](auto i) {
+                        a_thread_vec.template AsType<FloatAB>()(i) = a_thread_buf
+                            [Number<a_thread_desc_.CalculateOffset(make_tuple(0, m0, 0, 0, i))>{}];
+                    });
 
-            // C_sub_01 += transpose(A_sub_0) * B_sub_1
-            xdlops_gemm.template Run<decltype(a_thread_desc_),
-                                     decltype(b_thread_desc_),
-                                     decltype(c_thread_desc_),
-                                     0,
-                                     1>(a_thread_buf, b_thread_buf, c_thread_buf);
+                    static_for<0, K1, 1>{}([&](auto i) {
+                        b_thread_vec.template AsType<FloatAB>()(i) = b_thread_buf
+                            [Number<b_thread_desc_.CalculateOffset(make_tuple(0, n0, 0, 0, i))>{}];
                     });
 
-        // C_sub_10 += transpose(A_sub_1) * B_sub_0
-        xdlops_gemm.template Run<decltype(a_thread_desc_),
-                                 decltype(b_thread_desc_),
-                                 decltype(c_thread_desc_),
-                                 1,
-                                 0>(a_thread_buf, b_thread_buf, c_thread_buf);
+                    constexpr index_t c_offset =
+                        c_thread_desc_.CalculateOffset(make_tuple(m0, n0, 0));
 
-        // C_sub_11 += transpose(A_sub_1) * B_sub_1
-        xdlops_gemm.template Run<decltype(a_thread_desc_),
-                                 decltype(b_thread_desc_),
-                                 decltype(c_thread_desc_),
-                                 1,
-                                 1>(a_thread_buf, b_thread_buf, c_thread_buf);
+                    xdlops_gemm.template Run<c_offset>(
+                        a_thread_vec.template AsType<mfma_input_type>(),
+                        b_thread_vec.template AsType<mfma_input_type>(),
+                        c_thread_buf);
+                });
+            });
+        });
     }
 
     private:
     // A[K, M]
-    static constexpr auto a_thread_desc_ =
-        make_naive_tensor_descriptor_packed(make_tuple(I1, Number<MRepeat>{}, I1, Number<K1>{}));
+    static constexpr auto a_thread_desc_ = make_naive_tensor_descriptor_packed(
+        make_tuple(I1, Number<MRepeat>{}, I1, I1, Number<K1>{}));
 
     // B[K, N]
-    static constexpr auto b_thread_desc_ =
-        make_naive_tensor_descriptor_packed(make_tuple(I1, Number<NRepeat>{}, I1, Number<K1>{}));
+    static constexpr auto b_thread_desc_ = make_naive_tensor_descriptor_packed(
+        make_tuple(I1, Number<NRepeat>{}, I1, I1, Number<K1>{}));
 
-    static constexpr auto c_thread_desc_ =
-        make_naive_tensor_descriptor_packed(make_tuple(Number<MRepeat>{}, Number<NRepeat>{}));
+    static constexpr auto c_thread_desc_ = make_naive_tensor_descriptor_packed(
+        make_tuple(Number<MRepeat>{}, Number<NRepeat>{}, Number<xdlops_gemm.GetNumXdlops()>{}));
 
     using AThreadCopy = ThreadwiseTensorSliceTransfer_v4<FloatAB,
                                                          FloatAB,
-                                                         ABlockDesc,
+                                                         decltype(a_k0_m0_m1_m2_k1_block_desc),
                                                          decltype(a_thread_desc_),
-                                                         Sequence<1, 1, 1, K1>,
-                                                         Sequence<0, 1, 2, 3>,
-                                                         3,
-                                                         1, // K1,
+                                                         Sequence<1, MRepeat, 1, 1, K1>,
+                                                         Sequence<0, 1, 2, 3, 4>,
+                                                         4,
+                                                         K1,
                                                          1>;
 
     using BThreadCopy = ThreadwiseTensorSliceTransfer_v4<FloatAB,
                                                          FloatAB,
-                                                         BBlockDesc,
+                                                         decltype(b_k0_n0_n1_n2_k1_block_desc),
                                                          decltype(b_thread_desc_),
-                                                         Sequence<1, 1, 1, K1>,
-                                                         Sequence<0, 1, 2, 3>,
-                                                         3,
-                                                         1, // K1,
+                                                         Sequence<1, NRepeat, 1, 1, K1>,
+                                                         Sequence<0, 1, 2, 3, 4>,
+                                                         4,
+                                                         K1,
                                                          1>;
 
-    AThreadCopy a_thread_copy_;
-    BThreadCopy b_thread_copy_;
+    AThreadCopy a_thread_copy_{CalculateAThreadOriginDataIndex()};
+    BThreadCopy b_thread_copy_{CalculateBThreadOriginDataIndex()};
 };
 
 } // namespace ck

composable_kernel/include/tensor_operation/gridwise_gemm_xdlops_v2r3.hpp

@@ -18,7 +18,7 @@ template <typename GridwiseGemm,
           typename FloatC,
           typename AK0MK1GridDesc,
           typename BK0NK1GridDesc,
-          typename CM0M1M2NGridDesc,
+          typename CM0N0M1N1M2M3M4N2GridDesc,
           typename CBlockClusterAdaptor>
 __global__ void
 #if CK_USE_LAUNCH_BOUNDS
@@ -29,7 +29,7 @@ __global__ void
                                 FloatC* __restrict__ p_c_grid,
                                 const AK0MK1GridDesc a_k0_m_k1_grid_desc,
                                 const BK0NK1GridDesc b_k0_n_k1_grid_desc,
-                                const CM0M1M2NGridDesc c_m0_m1_m2_n_grid_desc,
+                                const CM0N0M1N1M2M3M4N2GridDesc c_m0_m1_m2_n_grid_desc,
                                 const CBlockClusterAdaptor c_block_cluster_adaptor)
 {
     constexpr index_t shared_block_size =
@@ -43,7 +43,7 @@ __global__ void
                       p_shared_block,
                       a_k0_m_k1_grid_desc,
                       b_k0_n_k1_grid_desc,
-                      c_m0_m1_m2_n_grid_desc,
+                      c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc,
                       c_block_cluster_adaptor);
 }
 #elif CK_EXPERIMENTAL_PASS_TENSOR_DESCRIPTOR_BY_VOID_POINTER
@@ -52,7 +52,7 @@ template <typename GridwiseGemm,
           typename FloatC,
           typename AK0MK1GridDesc,
           typename BK0NK1GridDesc,
-          typename CM0M1M2NGridDesc,
+          typename CM0N0M1N1M2M3M4N2GridDesc,
           typename CBlockClusterAdaptor>
 __global__ void
 #if CK_USE_LAUNCH_BOUNDS
@@ -63,7 +63,7 @@ __global__ void
                                 FloatC* __restrict__ p_c_grid,
                                 const void CONSTANT* p_a_k0_m_k1_grid_desc,
                                 const void CONSTANT* p_b_k0_n_k1_grid_desc,
-                                const void CONSTANT* p_c_m0_m1_m2_n_grid_desc,
+                                const void CONSTANT* p_c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc,
                                 const void CONSTANT* p_c_block_cluster_adaptor)
 {
     constexpr index_t shared_block_size =
@@ -73,8 +73,9 @@ __global__ void
         cast_pointer_to_generic_address_space(p_a_k0_m_k1_grid_desc));
     const auto b_k0_n_k1_grid_desc = *reinterpret_cast<const BK0NK1GridDesc*>(
         cast_pointer_to_generic_address_space(p_b_k0_n_k1_grid_desc));
-    const auto c_m0_m1_m2_n_grid_desc = *reinterpret_cast<const CM0M1M2NGridDesc*>(
-        cast_pointer_to_generic_address_space(p_c_m0_m1_m2_n_grid_desc));
+    const auto c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc =
+        *reinterpret_cast<const CM0N0M1N1M2M3M4N2GridDesc*>(
+            cast_pointer_to_generic_address_space(p_c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc));
     const auto c_block_cluster_adaptor = *reinterpret_cast<const CBlockClusterAdaptor*>(
         cast_pointer_to_generic_address_space(p_c_block_cluster_adaptor));
 
@@ -86,7 +87,7 @@ __global__ void
                       p_shared_block,
                       a_k0_m_k1_grid_desc,
                       b_k0_n_k1_grid_desc,
-                      c_m0_m1_m2_n_grid_desc,
+                      c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc,
                       c_block_cluster_adaptor);
 }
 #endif
@@ -102,8 +103,8 @@ template <index_t BlockSize,
           index_t MPerBlock,
           index_t NPerBlock,
           index_t KPerBlock,
-          index_t MPerWave,
-          index_t NPerWave,
+          index_t MPerXDL,
+          index_t NPerXDL,
           index_t K1Value,
           index_t MRepeat,
           index_t NRepeat,
@@ -138,6 +139,9 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3
     static constexpr auto I1 = Number<1>{};
     static constexpr auto I2 = Number<2>{};
     static constexpr auto I3 = Number<3>{};
+    static constexpr auto I4 = Number<4>{};
+    static constexpr auto I5 = Number<5>{};
+    static constexpr auto I6 = Number<6>{};
 
     // K1 should be Number<...>
     static constexpr auto K1 = Number<K1Value>{};
@@ -179,14 +183,16 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3
         const auto N  = b_k0_n_k1_grid_desc.GetLength(I1);
         const auto K0 = a_k0_m_k1_grid_desc.GetLength(I0);
 
-        // TODO: also check validity of all components (blockwise-copy, threadwise-copy, etc)
+        static_assert((MPerBlock % (MPerXDL * MRepeat) == 0) &&
+                          (NPerBlock % (NRepeat * NPerXDL)) == 0,
+                      "Invalid tuning param!");
 
+        // TODO: also check validity of all components (blockwise-copy, threadwise-copy, etc)
         return (M == c_m_n_grid_desc.GetLength(I0) && N == c_m_n_grid_desc.GetLength(I1) &&
                 K0 == b_k0_n_k1_grid_desc.GetLength(I0) &&
                 K1 == a_k0_m_k1_grid_desc.GetLength(I2) &&
                 K1 == b_k0_n_k1_grid_desc.GetLength(I2)) &&
-               (M % MPerBlock == 0 && N % NPerBlock == 0 && K0 % KPerBlock == 0) &&
-               (MPerBlock % MPerWave == 0 && NPerBlock % NPerWave == 0);
+               (M % MPerBlock == 0 && N % NPerBlock == 0 && K0 % KPerBlock == 0);
     }
 
     __host__ __device__ static constexpr index_t
@@ -201,29 +207,28 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3
     }
 
     __host__ __device__ static constexpr auto
-    MakeCM0M1M2NGridDescriptor(const CMNGridDesc& c_m_n_grid_desc)
+    MakeCM0N0M1N1M2M3M4N2GridDescriptor(const CMNGridDesc& c_m_n_grid_desc)
     {
-        constexpr auto xdlops_gemm = XdlopsGemm<FloatAB, MPerWave, NPerWave, K1>{};
-
-        constexpr auto CLayout = xdlops_gemm.GetCLayout();
-
-        constexpr auto M0 = Number<CLayout.M1()>{};
-        constexpr auto M1 = Number<CLayout.N1()>{};
-        constexpr auto M2 = Number<CLayout.M0()>{};
+        constexpr auto max_lds_align = K1;
 
-        constexpr index_t MWaves = MPerBlock / (MPerWave * MRepeat);
-        constexpr index_t NWaves = NPerBlock / (NPerWave * NRepeat);
+        constexpr auto a_k0_m_k1_block_desc = make_naive_tensor_descriptor_aligned(
+            make_tuple(Number<KPerBlock>{}, Number<MPerBlock>{}, K1), max_lds_align);
 
-        constexpr auto N1 = Number<CLayout.N0()>{};
+        constexpr auto b_k0_n_k1_block_desc = make_naive_tensor_descriptor_aligned(
+            make_tuple(Number<KPerBlock>{}, Number<NPerBlock>{}, K1), max_lds_align);
 
-        const auto c_m0_m1_m2_n_grid_desc = transform_tensor_descriptor(
-            c_m_n_grid_desc,
-            make_tuple(make_unmerge_transform(make_tuple(MRepeat, MWaves, M0, M1, M2)),
-                       make_unmerge_transform(make_tuple(NRepeat, NWaves, N1))),
-            make_tuple(Sequence<0>{}, Sequence<1>{}),
-            make_tuple(Sequence<0, 2, 4, 5, 6>{}, Sequence<1, 3, 7>{}));
+        using BlockwiseGemm =
+            BlockwiseGemmXdlops_k0mk1_k0nk1_m0n0m1n1m2m3m4n2_v1<BlockSize,
+                                                                FloatAB,
+                                                                decltype(a_k0_m_k1_block_desc),
+                                                                decltype(b_k0_n_k1_block_desc),
+                                                                MPerXDL,
+                                                                NPerXDL,
+                                                                MRepeat,
+                                                                NRepeat,
+                                                                K1>;
 
-        return c_m0_m1_m2_n_grid_desc;
+        return BlockwiseGemm::MakeCM0N0M1N1M2M3M4N2GridDescriptor(c_m_n_grid_desc);
     }
 
     __host__ __device__ static constexpr auto
@@ -253,7 +258,7 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3
         return c_blockid_to_m0_n0_block_cluster_adaptor;
     }
 
-    using CM0M1M2NGridDesc     = decltype(MakeCM0M1M2NGridDescriptor(CMNGridDesc{}));
+    using CM0N0M1N1M2M3M4N2GridDesc = decltype(MakeCM0N0M1N1M2M3M4N2GridDescriptor(CMNGridDesc{}));
     using CBlockClusterAdaptor      = decltype(MakeCBlockClusterAdaptor(CMNGridDesc{}));
 
     __device__ static void Run(const FloatAB* __restrict__ p_a_grid,
@@ -262,7 +267,7 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3
                                FloatAB* __restrict__ p_shared_block,
                                const AK0MK1GridDesc& a_k0_m_k1_grid_desc,
                                const BK0NK1GridDesc& b_k0_n_k1_grid_desc,
-                               const CM0M1M2NGridDesc& c_m0_m1_m2_n_grid_desc,
+                               const CM0N0M1N1M2M3M4N2GridDesc& c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc,
                                const CBlockClusterAdaptor& c_block_cluster_adaptor)
     {
         const auto a_grid_buf = make_dynamic_buffer<AddressSpaceEnum_t::Global>(
@@ -270,7 +275,7 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3
         const auto b_grid_buf = make_dynamic_buffer<AddressSpaceEnum_t::Global>(
             p_b_grid, b_k0_n_k1_grid_desc.GetElementSpaceSize());
         auto c_grid_buf = make_dynamic_buffer<AddressSpaceEnum_t::Global>(
-            p_c_grid, c_m0_m1_m2_n_grid_desc.GetElementSpaceSize());
+            p_c_grid, c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc.GetElementSpaceSize());
 
         const auto K0 = a_k0_m_k1_grid_desc.GetLength(I0);
 
@@ -358,50 +363,26 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3
         //       register
         // sanity check
 
-        static_assert(MPerBlock % (MPerWave * MRepeat) == 0 &&
-                          NPerBlock % (NPerWave * NRepeat) == 0,
-                      "wrong!");
-
-        constexpr auto a_k0_m0_m1_k1_block_desc = transform_tensor_descriptor(
-            a_k0_m_k1_block_desc,
-            make_tuple(make_pass_through_transform(Number<KPerBlock>{}),
-                       make_unmerge_transform(
-                           make_tuple(Number<MRepeat>{}, Number<MPerBlock / MRepeat>{})),
-                       make_pass_through_transform(K1)),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}),
-            make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<3>{}));
-
-        constexpr auto b_k0_n0_n1_k1_block_desc = transform_tensor_descriptor(
-            b_k0_n_k1_block_desc,
-            make_tuple(make_pass_through_transform(Number<KPerBlock>{}),
-                       make_unmerge_transform(
-                           make_tuple(Number<NRepeat>{}, Number<NPerBlock / NRepeat>{})),
-                       make_pass_through_transform(K1)),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}),
-            make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<3>{}));
-
         const auto blockwise_gemm =
-            BlockwiseGemmXdlops_km_kn_m0m1m2n_v1<BlockSize,
+            BlockwiseGemmXdlops_k0mk1_k0nk1_m0n0m1n1m2m3m4n2_v1<BlockSize,
                                                                 FloatAB,
-                                                 decltype(a_k0_m0_m1_k1_block_desc),
-                                                 decltype(b_k0_n0_n1_k1_block_desc),
-                                                 MPerWave,
-                                                 NPerWave,
+                                                                decltype(a_k0_m_k1_block_desc),
+                                                                decltype(b_k0_n_k1_block_desc),
+                                                                MPerXDL,
+                                                                NPerXDL,
+                                                                MRepeat,
+                                                                NRepeat,
                                                                 K1>{};
 
-        constexpr auto CLayout = blockwise_gemm.GetCLayout();
-
-        constexpr index_t BlkSize   = CLayout.GetBlkSize();
-        constexpr index_t NumBlks   = CLayout.GetNumBlks();
-        constexpr index_t NumXdlops = CLayout.GetNumXdlops();
-
-        static_assert(NumBlks == 1 && NumXdlops == 1, "K Reduction Mfma only");
-
         constexpr auto c_mr_nr_blk_desc =
             make_naive_tensor_descriptor_packed(make_tuple(Number<MRepeat>{}, Number<NRepeat>{}));
 
+        constexpr auto c_m0_n0_m1_n1_m2_m3_m4_n2_thread_desc =
+            blockwise_gemm.GetCM0N0M1N1M2M3M4N2ThreadDescriptor();
+        constexpr auto CBlkSize = c_m0_n0_m1_n1_m2_m3_m4_n2_thread_desc.GetElementSpaceSize();
+
         StaticBuffer<AddressSpaceEnum_t::Vgpr,
-                     vector_type<FloatAcc, BlkSize>,
+                     vector_type<FloatAcc, CBlkSize>,
                      c_mr_nr_blk_desc.GetElementSpaceSize(),
                      true>
             c_thread_buf;
@@ -474,94 +455,14 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3
             blockwise_gemm.Run(a_block_buf, b_block_buf, c_thread_buf);
         }
 
-#if 0
         // output: register to global memory
         {
-            constexpr index_t M0 = CLayout.M1();
-            constexpr index_t M1 = CLayout.N1();
-            constexpr index_t M2 = CLayout.M0();
-
-            constexpr index_t N0 = CLayout.N1();
-            constexpr index_t N1 = CLayout.N0();
-
-            constexpr auto c_m0_m1_m2_n_thread_desc =
-                make_naive_tensor_descriptor_packed(make_tuple(Number<MRepeat>{},
-                                                                          Number<NRepeat>{},
-                                                                          Number<1>{},
-                                                                          Number<1>{},
-                                                                          Number<M0>{},
-                                                                          Number<1>{},
-                                                                          Number<M2>{},
-                                                                          Number<1>{}));
-
-            StaticBuffer<AddressSpaceEnum_t::Vgpr, FloatC, c_m0_m1_m2_n_thread_desc.GetElementSpaceSize(), true>
-                c_blk_buf_;
-
-            static_for<0, MRepeat, 1>{}([&](auto mr_i) {
-                static_for<0, NRepeat, 1>{}([&](auto nr_i) {
-                    constexpr auto blk_off =
-                        c_mr_nr_blk_desc.CalculateOffset(make_tuple(mr_i, nr_i));
-
-                    static_for<0, BlkSize, 1>{}([&](auto j) {
-                        c_blk_buf_(Number<blk_off * BlkSize + j>{}) =
-                            c_thread_buf[Number<blk_off>{}]
-                                .template AsType<FloatAcc>()[Number<j>{}];
-                    });
-                });
-            });
+            constexpr auto c_m0_n0_m1_n1_m2_m3_m4_n2_block_desc =
+                blockwise_gemm.GetCM0N0M1N1M2M3M4N2BlockDescriptor();
 
-            // calculate origin of thread output tensor on global memory
-            //     blockwise GEMM c matrix starting index
-            const auto c_thread_mtx_on_block =
-                blockwise_gemm.CalculateCThreadOriginDataIndex(I0, I0, I0, I0);
-
-            const index_t m_thread_data_on_grid =
-                m_block_data_idx_on_grid + c_thread_mtx_on_block[I0];
-
-            const index_t n_thread_data_on_grid =
-                n_block_data_idx_on_grid + c_thread_mtx_on_block[I1];
-
-            constexpr auto c_m0_m1_m2_n_grid_tensor_step_hacks = CGridStepHacks{};
-
-            constexpr index_t MWaves = MPerBlock / (MPerWave * MRepeat);
-            constexpr index_t NWaves = NPerBlock / (NPerWave * NRepeat);
-
-            ThreadwiseTensorSliceTransfer_v1r3<
-                FloatC,
-                FloatC,
-                decltype(c_m0_m1_m2_n_thread_desc),
-                decltype(c_m0_m1_m2_n_grid_desc),
-                Sequence<MRepeat, NRepeat, 1, 1, M0, 1, M2, 1>,
-                CThreadTransferSrcDstAccessOrder,
-                CThreadTransferSrcDstVectorDim,
-                CThreadTransferDstScalarPerVector,
-                CGlobalMemoryDataOperation,
-                1,
-                true>{
-                c_m0_m1_m2_n_grid_desc,
-                make_multi_index(m_thread_data_on_grid / (M2 * M1 * M0 * MWaves),
-                                 n_thread_data_on_grid / (N1 * NWaves),
-                                 m_thread_data_on_grid % (M2 * M1 * M0 * MWaves) / (M2 * M1 * M0),
-                                 n_thread_data_on_grid % (N1 * NWaves) / N1,
-                                 m_thread_data_on_grid % (M2 * M1 * M0) / (M2 * M1),
-                                 m_thread_data_on_grid % (M2 * M1) / M2,
-                                 m_thread_data_on_grid % M2,
-                                 n_thread_data_on_grid % N1)}
-                .Run(c_m0_m1_m2_n_thread_desc,
-                     make_tuple(I0, I0, I0, I0, I0, I0, I0, I0),
-                     c_blk_buf_,
-                     c_m0_m1_m2_n_grid_desc,
-                     c_grid_buf,
-                     c_m0_m1_m2_n_grid_tensor_step_hacks);
-        }
-#else
-        {
-            constexpr index_t M0 = CLayout.M1();
-            constexpr index_t M1 = CLayout.N1();
-            constexpr index_t M2 = CLayout.M0();
-
-            constexpr auto c_m0_m1_m2_n_thread_desc = make_naive_tensor_descriptor_packed(
-                make_tuple(I1, I1, I1, I1, Number<M0>{}, Number<1>{}, Number<M2>{}, Number<1>{}));
+            constexpr auto M2 = c_m0_n0_m1_n1_m2_m3_m4_n2_block_desc.GetLength(I4);
+            constexpr auto M3 = c_m0_n0_m1_n1_m2_m3_m4_n2_block_desc.GetLength(I5);
+            constexpr auto M4 = c_m0_n0_m1_n1_m2_m3_m4_n2_block_desc.GetLength(I6);
 
             // calculate origin of thread output tensor on global memory
             //     blockwise GEMM c matrix starting index
@@ -574,92 +475,96 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3
             const index_t n_thread_data_on_grid =
                 n_block_data_idx_on_grid + c_thread_mtx_on_block[I1];
 
-            constexpr auto c_m0_m1_m2_n_grid_tensor_step_hacks = CGridStepHacks{};
+            constexpr auto c_m0_n0_m1_n1_m2_m3_m4_n2_grid_tensor_step_hacks = CGridStepHacks{};
 
             auto c_thread_copy =
                 ThreadwiseTensorSliceTransfer_v1r3<FloatC,
                                                    FloatC,
-                                                   decltype(c_m0_m1_m2_n_thread_desc),
-                                                   decltype(c_m0_m1_m2_n_grid_desc),
-                                                   Sequence<1, 1, 1, 1, M0, 1, M2, 1>,
+                                                   decltype(c_m0_n0_m1_n1_m2_m3_m4_n2_thread_desc),
+                                                   decltype(c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc),
+                                                   Sequence<I1, I1, I1, I1, M2, I1, M4, I1>,
                                                    CThreadTransferSrcDstAccessOrder,
                                                    CThreadTransferSrcDstVectorDim,
                                                    CThreadTransferDstScalarPerVector,
                                                    CGlobalMemoryDataOperation,
                                                    1,
                                                    true>{
-                    c_m0_m1_m2_n_grid_desc,
+                    c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc,
                     make_multi_index(0,
                                      0,
                                      0,
                                      0,
-                                     m_thread_data_on_grid / (M2 * M1),
-                                     m_thread_data_on_grid % (M2 * M1) / M2,
-                                     m_thread_data_on_grid % M2,
+                                     m_thread_data_on_grid / (M3 * M4),
+                                     m_thread_data_on_grid % (M3 * M4) / M4,
+                                     m_thread_data_on_grid % M4,
                                      n_thread_data_on_grid)};
 
             auto init_copy = [&](auto c_thread_idx_) {
                 constexpr auto blk_off = c_mr_nr_blk_desc.CalculateOffset(c_thread_idx_);
-                c_thread_copy.Run(c_m0_m1_m2_n_thread_desc,
+                c_thread_copy.Run(c_m0_n0_m1_n1_m2_m3_m4_n2_thread_desc,
                                   make_tuple(I0, I0, I0, I0, I0, I0, I0, I0),
                                   c_thread_buf[Number<blk_off>{}].template AsType<FloatAcc>(),
-                                  c_m0_m1_m2_n_grid_desc,
+                                  c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc,
                                   c_grid_buf,
-                                  c_m0_m1_m2_n_grid_tensor_step_hacks);
+                                  c_m0_n0_m1_n1_m2_m3_m4_n2_grid_tensor_step_hacks);
 
                 return c_thread_idx_;
             };
 
             auto mrepeat_plus_copy = [&](auto c_thread_idx_) {
                 constexpr auto mrepeat_step_plus = make_multi_index(1, 0, 0, 0, 0, 0, 0, 0);
-                c_thread_copy.MoveDstSliceWindow(c_m0_m1_m2_n_grid_desc, mrepeat_step_plus);
+                c_thread_copy.MoveDstSliceWindow(c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc,
+                                                 mrepeat_step_plus);
 
                 constexpr auto blk_off = c_mr_nr_blk_desc.CalculateOffset(c_thread_idx_);
-                c_thread_copy.Run(c_m0_m1_m2_n_thread_desc,
+                c_thread_copy.Run(c_m0_n0_m1_n1_m2_m3_m4_n2_thread_desc,
                                   make_tuple(I0, I0, I0, I0, I0, I0, I0, I0),
                                   c_thread_buf[Number<blk_off>{}].template AsType<FloatAcc>(),
-                                  c_m0_m1_m2_n_grid_desc,
+                                  c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc,
                                   c_grid_buf,
-                                  c_m0_m1_m2_n_grid_tensor_step_hacks);
+                                  c_m0_n0_m1_n1_m2_m3_m4_n2_grid_tensor_step_hacks);
             };
 
             auto nrepeat_plus_copy = [&](auto c_thread_idx_) {
                 constexpr auto nrepeat_step_plus = make_multi_index(0, 1, 0, 0, 0, 0, 0, 0);
-                c_thread_copy.MoveDstSliceWindow(c_m0_m1_m2_n_grid_desc, nrepeat_step_plus);
+                c_thread_copy.MoveDstSliceWindow(c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc,
+                                                 nrepeat_step_plus);
 
                 constexpr auto blk_off = c_mr_nr_blk_desc.CalculateOffset(c_thread_idx_);
-                c_thread_copy.Run(c_m0_m1_m2_n_thread_desc,
+                c_thread_copy.Run(c_m0_n0_m1_n1_m2_m3_m4_n2_thread_desc,
                                   make_tuple(I0, I0, I0, I0, I0, I0, I0, I0),
                                   c_thread_buf[Number<blk_off>{}].template AsType<FloatAcc>(),
-                                  c_m0_m1_m2_n_grid_desc,
+                                  c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc,
                                   c_grid_buf,
-                                  c_m0_m1_m2_n_grid_tensor_step_hacks);
+                                  c_m0_n0_m1_n1_m2_m3_m4_n2_grid_tensor_step_hacks);
             };
 
             auto mrepeat_minus_copy = [&](auto c_thread_idx_) {
                 constexpr auto mrepeat_step_plus = make_multi_index(-1, 0, 0, 0, 0, 0, 0, 0);
-                c_thread_copy.MoveDstSliceWindow(c_m0_m1_m2_n_grid_desc, mrepeat_step_plus);
+                c_thread_copy.MoveDstSliceWindow(c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc,
+                                                 mrepeat_step_plus);
 
                 constexpr auto blk_off = c_mr_nr_blk_desc.CalculateOffset(c_thread_idx_);
-                c_thread_copy.Run(c_m0_m1_m2_n_thread_desc,
+                c_thread_copy.Run(c_m0_n0_m1_n1_m2_m3_m4_n2_thread_desc,
                                   make_tuple(I0, I0, I0, I0, I0, I0, I0, I0),
                                   c_thread_buf[Number<blk_off>{}].template AsType<FloatAcc>(),
-                                  c_m0_m1_m2_n_grid_desc,
+                                  c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc,
                                   c_grid_buf,
-                                  c_m0_m1_m2_n_grid_tensor_step_hacks);
+                                  c_m0_n0_m1_n1_m2_m3_m4_n2_grid_tensor_step_hacks);
             };
 
             auto nrepeat_minus_copy = [&](auto c_thread_idx_) {
                 constexpr auto nrepeat_step_minus = make_multi_index(0, -1, 0, 0, 0, 0, 0, 0);
-                c_thread_copy.MoveDstSliceWindow(c_m0_m1_m2_n_grid_desc, nrepeat_step_minus);
+                c_thread_copy.MoveDstSliceWindow(c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc,
+                                                 nrepeat_step_minus);
 
                 constexpr auto blk_off = c_mr_nr_blk_desc.CalculateOffset(c_thread_idx_);
-                c_thread_copy.Run(c_m0_m1_m2_n_thread_desc,
+                c_thread_copy.Run(c_m0_n0_m1_n1_m2_m3_m4_n2_thread_desc,
                                   make_tuple(I0, I0, I0, I0, I0, I0, I0, I0),
                                   c_thread_buf[Number<blk_off>{}].template AsType<FloatAcc>(),
-                                  c_m0_m1_m2_n_grid_desc,
+                                  c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc,
                                   c_grid_buf,
-                                  c_m0_m1_m2_n_grid_tensor_step_hacks);
+                                  c_m0_n0_m1_n1_m2_m3_m4_n2_grid_tensor_step_hacks);
             };
 
             static_assert((MRepeat == 4 && NRepeat == 4) or (MRepeat == 4 && NRepeat == 2) or
@@ -791,7 +696,6 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3
                 init_copy(make_tuple(I0, I0));
             }
         }
-#endif
     }
 }; // namespace ck
 

composable_kernel/include/tensor_operation/threadwise_contraction_dlops.hpp

@@ -55,18 +55,15 @@ struct ThreadwiseGemmDlops_km0m1_kn0n1_m0m1n0n1
                                CBuffer& c_buf,
                                COriginIdx)
     {
-        static_assert(
-            is_known_at_compile_time<remove_cv_t<remove_reference_t<AOriginIdx>>>::value &&
-                is_known_at_compile_time<remove_cv_t<remove_reference_t<BOriginIdx>>>::value &&
-                is_known_at_compile_time<remove_cv_t<remove_reference_t<COriginIdx>>>::value,
+        static_assert(is_known_at_compile_time<remove_cvref_t<AOriginIdx>>::value &&
+                          is_known_at_compile_time<remove_cvref_t<BOriginIdx>>::value &&
+                          is_known_at_compile_time<remove_cvref_t<COriginIdx>>::value,
                       "wrong! AOriginIdx, BOriginIdx, COringinIdx should be known at compile-time");
 
-        static_assert(is_same<remove_cv_t<remove_reference_t<typename ABuffer::type>>,
-                              remove_cv_t<remove_reference_t<FloatA>>>::value &&
-                      is_same<remove_cv_t<remove_reference_t<typename BBuffer::type>>,
-                              remove_cv_t<remove_reference_t<FloatB>>>::value &&
-                      is_same<remove_cv_t<remove_reference_t<typename CBuffer::type>>,
-                              remove_cv_t<remove_reference_t<FloatC>>>::value &&
+        static_assert(
+            is_same<remove_cvref_t<typename ABuffer::type>, remove_cvref_t<FloatA>>::value &&
+            is_same<remove_cvref_t<typename BBuffer::type>, remove_cvref_t<FloatB>>::value &&
+            is_same<remove_cvref_t<typename CBuffer::type>, remove_cvref_t<FloatC>>::value &&
             "wrong! inconsistent type");
 
         constexpr auto I0 = Number<0>{};
@@ -157,18 +154,15 @@ struct ThreadwiseContractionDlops_A_TK0_TM0_TM1_TK1_B_TK0_TN0_TN1_TK1_C_TM0_TM1_
                                CBuffer& c_buf,
                                COriginIdx)
     {
-        static_assert(
-            is_known_at_compile_time<remove_cv_t<remove_reference_t<AOriginIdx>>>::value &&
-                is_known_at_compile_time<remove_cv_t<remove_reference_t<BOriginIdx>>>::value &&
-                is_known_at_compile_time<remove_cv_t<remove_reference_t<COriginIdx>>>::value,
+        static_assert(is_known_at_compile_time<remove_cvref_t<AOriginIdx>>::value &&
+                          is_known_at_compile_time<remove_cvref_t<BOriginIdx>>::value &&
+                          is_known_at_compile_time<remove_cvref_t<COriginIdx>>::value,
                       "wrong! AOriginIdx, BOriginIdx, COringinIdx should be known at compile-time");
 
-        static_assert(is_same<remove_cv_t<remove_reference_t<typename ABuffer::type>>,
-                              remove_cv_t<remove_reference_t<FloatA>>>::value &&
-                      is_same<remove_cv_t<remove_reference_t<typename BBuffer::type>>,
-                              remove_cv_t<remove_reference_t<FloatB>>>::value &&
-                      is_same<remove_cv_t<remove_reference_t<typename CBuffer::type>>,
-                              remove_cv_t<remove_reference_t<FloatC>>>::value &&
+        static_assert(
+            is_same<remove_cvref_t<typename ABuffer::type>, remove_cvref_t<FloatA>>::value &&
+            is_same<remove_cvref_t<typename BBuffer::type>, remove_cvref_t<FloatB>>::value &&
+            is_same<remove_cvref_t<typename CBuffer::type>, remove_cvref_t<FloatC>>::value &&
             "wrong! inconsistent type");
 
         constexpr auto I0 = Number<0>{};

composable_kernel/include/tensor_operation/threadwise_gemm_dlops_v3.hpp

@@ -41,18 +41,15 @@ struct ThreadwiseGemmDlops_km_kn_mn_v3
                           CDesc::IsKnownAtCompileTime(),
                       "wrong! Desc should be known at compile-time");
 
-        static_assert(
-            is_known_at_compile_time<remove_cv_t<remove_reference_t<AOriginIdx>>>::value &&
-                is_known_at_compile_time<remove_cv_t<remove_reference_t<BOriginIdx>>>::value &&
-                is_known_at_compile_time<remove_cv_t<remove_reference_t<COriginIdx>>>::value,
+        static_assert(is_known_at_compile_time<remove_cvref_t<AOriginIdx>>::value &&
+                          is_known_at_compile_time<remove_cvref_t<BOriginIdx>>::value &&
+                          is_known_at_compile_time<remove_cvref_t<COriginIdx>>::value,
                       "wrong! AOriginIdx, BOriginIdx, COringinIdx should be known at compile-time");
 
-        static_assert(is_same<remove_cv_t<remove_reference_t<typename ABuffer::type>>,
-                              remove_cv_t<remove_reference_t<FloatA>>>::value &&
-                      is_same<remove_cv_t<remove_reference_t<typename BBuffer::type>>,
-                              remove_cv_t<remove_reference_t<FloatB>>>::value &&
-                      is_same<remove_cv_t<remove_reference_t<typename CBuffer::type>>,
-                              remove_cv_t<remove_reference_t<FloatC>>>::value &&
+        static_assert(
+            is_same<remove_cvref_t<typename ABuffer::type>, remove_cvref_t<FloatA>>::value &&
+            is_same<remove_cvref_t<typename BBuffer::type>, remove_cvref_t<FloatB>>::value &&
+            is_same<remove_cvref_t<typename CBuffer::type>, remove_cvref_t<FloatC>>::value &&
             "wrong! inconsistent type");
 
         constexpr auto I0 = Number<0>{};

composable_kernel/include/tensor_operation/threadwise_tensor_slice_set.hpp

@@ -30,11 +30,11 @@ struct ThreadwiseTensorSliceSet_v1
 
         static_assert(Buffer::IsStaticBuffer(), "wrong! DstBuffer need to be StaticBuffer");
 
-        static_assert(is_known_at_compile_time<remove_cv_t<remove_reference_t<OriginIdx>>>::value,
+        static_assert(is_known_at_compile_time<remove_cvref_t<OriginIdx>>::value,
                       "wrong! OriginIdx need to be known at compile-time");
 
         // Desc is known at compile-time
-        constexpr auto desc = remove_cv_t<remove_reference_t<Desc>>{};
+        constexpr auto desc = remove_cvref_t<Desc>{};
 
         // OriginIdx is known at compile-time
         constexpr auto origin_idx = to_multi_index(OriginIdx{});

composable_kernel/include/tensor_operation/threadwise_tensor_slice_transfer.hpp

@@ -95,18 +95,13 @@ struct ThreadwiseTensorSliceTransfer_v1r3
         static_assert(SrcDesc::IsKnownAtCompileTime(),
                       "wrong! SrcDesc need to known at compile-time");
 
-        static_assert(
-            is_known_at_compile_time<remove_cv_t<remove_reference_t<SrcSliceOriginIdx>>>::value,
+        static_assert(is_known_at_compile_time<remove_cvref_t<SrcSliceOriginIdx>>::value,
                       "wrong! SrcSliceOrigin need to known at compile-time");
 
         static_assert(SrcBuffer::IsStaticBuffer(), "wrong! SrcBuffer need to be StaticBuffer");
 
-        // static_assert(is_same<remove_cv_t<remove_reference_t<typename SrcBuffer::type>>,
-        // remove_cv_t<remove_reference_t<SrcData>>>::value,
-        //"wrong! SrcBuffer data type is wrong");
-
         // SrcDesc and src_slice_origin_idx are known at compile-time
-        constexpr auto src_desc             = remove_cv_t<remove_reference_t<SrcDesc>>{};
+        constexpr auto src_desc             = remove_cvref_t<SrcDesc>{};
         constexpr auto src_slice_origin_idx = to_multi_index(SrcSliceOriginIdx{});
 
         constexpr auto I0 = Number<0>{};
@@ -208,10 +203,20 @@ struct ThreadwiseTensorSliceTransfer_v1r3
                 coordinate_has_valid_offset_assuming_visible_index_is_valid(dst_desc, dst_coord_);
 
             // copy data from dst_vector into dst_buf
+            if constexpr(DstInMemOp == InMemoryDataOperationEnum_t::Set)
+            {
                 dst_buf.template Set<dst_vector_t>(
                     dst_coord_.GetOffset(),
                     is_dst_valid,
                     dst_vector.template AsType<dst_vector_t>()[Number<0>{}]);
+            }
+            else if constexpr(DstInMemOp == InMemoryDataOperationEnum_t::AtomicAdd)
+            {
+                dst_buf.template AtomicAdd<dst_vector_t>(
+                    dst_coord_.GetOffset(),
+                    is_dst_valid,
+                    dst_vector.template AsType<dst_vector_t>()[Number<0>{}]);
+            }
 
             constexpr auto move_on_dim = [&]() constexpr
             {
@@ -411,16 +416,15 @@ struct ThreadwiseTensorSliceTransfer_v2
         static_assert(DstDesc::IsKnownAtCompileTime(),
                       "wrong! DstDesc need to known at compile-time");
 
-        static_assert(
-            is_known_at_compile_time<remove_cv_t<remove_reference_t<DstSliceOriginIdx>>>::value,
+        static_assert(is_known_at_compile_time<remove_cvref_t<DstSliceOriginIdx>>::value,
                       "wrong! DstSliceOrigin need to known at compile-time");
 
-        static_assert(is_same<remove_cv_t<remove_reference_t<typename DstBuffer::type>>,
-                              remove_cv_t<remove_reference_t<DstData>>>::value &&
+        static_assert(
+            is_same<remove_cvref_t<typename DstBuffer::type>, remove_cvref_t<DstData>>::value &&
             "wrong! inconsistent type");
 
         // DstDesc and dst_slice_origin_idx are known at compile-time
-        constexpr auto dst_desc             = remove_cv_t<remove_reference_t<DstDesc>>{};
+        constexpr auto dst_desc             = remove_cvref_t<DstDesc>{};
         constexpr auto dst_slice_origin_idx = DstSliceOriginIdx{};
 
         constexpr auto I0 = Number<0>{};
@@ -729,8 +733,8 @@ struct ThreadwiseTensorSliceTransfer_v3
                           SrcBuffer::GetAddressSpace() == AddressSpaceEnum_t::Lds,
                       "wrong!");
 
-        static_assert(is_same<remove_cv_t<remove_reference_t<typename SrcBuffer::type>>,
-                              remove_cv_t<remove_reference_t<SrcData>>>::value,
+        static_assert(
+            is_same<remove_cvref_t<typename SrcBuffer::type>, remove_cvref_t<SrcData>>::value,
             "wrong! SrcBuffer and SrcData data type are inconsistent");
 
         constexpr auto I0 = Number<0>{};
@@ -886,8 +890,8 @@ struct ThreadwiseTensorSliceTransfer_v3
                           DstBuffer::GetAddressSpace() == AddressSpaceEnum_t::Lds,
                       "wrong!");
 
-        static_assert(is_same<remove_cv_t<remove_reference_t<typename DstBuffer::type>>,
-                              remove_cv_t<remove_reference_t<DstData>>>::value,
+        static_assert(
+            is_same<remove_cvref_t<typename DstBuffer::type>, remove_cvref_t<DstData>>::value,
             "wrong! SrcBuffer or DstBuffer data type is wrong");
 
         constexpr auto I0 = Number<0>{};
@@ -1303,24 +1307,21 @@ struct ThreadwiseTensorSliceTransfer_v4
         static_assert(SrcDesc::IsKnownAtCompileTime() && DstDesc::IsKnownAtCompileTime(),
                       "wrong! SrcDesc and DstDesc need to known at compile-time");
 
-        static_assert(is_same<remove_cv_t<remove_reference_t<typename SrcBuffer::type>>,
-                              remove_cv_t<remove_reference_t<SrcData>>>::value &&
-                          is_same<remove_cv_t<remove_reference_t<typename DstBuffer::type>>,
-                                  remove_cv_t<remove_reference_t<DstData>>>::value,
+        static_assert(
+            is_same<remove_cvref_t<typename SrcBuffer::type>, remove_cvref_t<SrcData>>::value &&
+                is_same<remove_cvref_t<typename DstBuffer::type>, remove_cvref_t<DstData>>::value,
             "wrong! SrcBuffer or DstBuffer data type is wrong");
 
         static_assert(DstBuffer::IsStaticBuffer(), "wrong! DstBuffer need to be StaticBuffer");
 
-        static_assert(
-            is_known_at_compile_time<
-                remove_cv_t<remove_reference_t<SrcRefToOriginDisplacement>>>::value &&
-                is_known_at_compile_time<remove_cv_t<remove_reference_t<DstOriginIdx>>>::value,
+        static_assert(is_known_at_compile_time<remove_cvref_t<SrcRefToOriginDisplacement>>::value &&
+                          is_known_at_compile_time<remove_cvref_t<DstOriginIdx>>::value,
                       "wrong! SrcOriginToRefDistance and DstOriginToRefDistance need to be known "
                       "at compile-time");
 
         // SrcDesc and DstDesc are known at compile-time
-        constexpr auto src_desc = remove_cv_t<remove_reference_t<SrcDesc>>{};
-        constexpr auto dst_desc = remove_cv_t<remove_reference_t<DstDesc>>{};
+        constexpr auto src_desc = remove_cvref_t<SrcDesc>{};
+        constexpr auto dst_desc = remove_cvref_t<DstDesc>{};
 
         // SrcOriginToRefDisttance and DstOriginToRefDistance are known at compile-time
         constexpr auto src_ref_to_origin_disp_idx = to_multi_index(SrcRefToOriginDisplacement{});

composable_kernel/include/tensor_operation/threadwise_tensor_slice_transfer_v2.hpp

@@ -80,8 +80,8 @@ struct ThreadwiseTensorSliceTransfer_v3r1
                           SrcBuffer::GetAddressSpace() == AddressSpaceEnum_t::Lds,
                       "wrong!");
 
-        static_assert(is_same<remove_cv_t<remove_reference_t<typename SrcBuffer::type>>,
-                              remove_cv_t<remove_reference_t<SrcData>>>::value,
+        static_assert(
+            is_same<remove_cvref_t<typename SrcBuffer::type>, remove_cvref_t<SrcData>>::value,
             "wrong! SrcBuffer and SrcData data type are inconsistent");
 
         // tensor descriptor for src_vector
@@ -248,8 +248,8 @@ struct ThreadwiseTensorSliceTransfer_v3r1
                           DstBuffer::GetAddressSpace() == AddressSpaceEnum_t::Lds,
                       "wrong!");
 
-        static_assert(is_same<remove_cv_t<remove_reference_t<typename DstBuffer::type>>,
-                              remove_cv_t<remove_reference_t<DstData>>>::value,
+        static_assert(
+            is_same<remove_cvref_t<typename DstBuffer::type>, remove_cvref_t<DstData>>::value,
             "wrong! SrcBuffer or DstBuffer data type is wrong");
 
         // tensor descriptor for dst_vector
@@ -669,24 +669,21 @@ struct ThreadwiseTensorSliceTransfer_v4r1
         static_assert(SrcDesc::IsKnownAtCompileTime() && DstDesc::IsKnownAtCompileTime(),
                       "wrong! SrcDesc and DstDesc need to known at compile-time");
 
-        static_assert(is_same<remove_cv_t<remove_reference_t<typename SrcBuffer::type>>,
-                              remove_cv_t<remove_reference_t<SrcData>>>::value &&
-                          is_same<remove_cv_t<remove_reference_t<typename DstBuffer::type>>,
-                                  remove_cv_t<remove_reference_t<DstData>>>::value,
+        static_assert(
+            is_same<remove_cvref_t<typename SrcBuffer::type>, remove_cvref_t<SrcData>>::value &&
+                is_same<remove_cvref_t<typename DstBuffer::type>, remove_cvref_t<DstData>>::value,
             "wrong! SrcBuffer or DstBuffer data type is wrong");
 
         static_assert(DstBuffer::IsStaticBuffer(), "wrong! DstBuffer need to be StaticBuffer");
 
-        static_assert(
-            is_known_at_compile_time<
-                remove_cv_t<remove_reference_t<SrcRefToOriginDisplacement>>>::value &&
-                is_known_at_compile_time<remove_cv_t<remove_reference_t<DstOriginIdx>>>::value,
+        static_assert(is_known_at_compile_time<remove_cvref_t<SrcRefToOriginDisplacement>>::value &&
+                          is_known_at_compile_time<remove_cvref_t<DstOriginIdx>>::value,
                       "wrong! SrcOriginToRefDistance and DstOriginToRefDistance need to be known "
                       "at compile-time");
 
         // SrcDesc and DstDesc are known at compile-time
-        constexpr auto src_desc = remove_cv_t<remove_reference_t<SrcDesc>>{};
-        constexpr auto dst_desc = remove_cv_t<remove_reference_t<DstDesc>>{};
+        constexpr auto src_desc = remove_cvref_t<SrcDesc>{};
+        constexpr auto dst_desc = remove_cvref_t<DstDesc>{};
 
         // SrcOriginToRefDisttance and DstOriginToRefDistance are known at compile-time
         constexpr auto src_ref_to_origin_disp_idx = to_multi_index(SrcRefToOriginDisplacement{});

composable_kernel/include/tensor_operation/xdlops_gemm.hpp

@@ -7,21 +7,18 @@
 
 namespace ck {
 
-enum struct mfma_instr
+enum struct MfmaInstr
 {
-    /// fp32
     mfma_f32_32x32x1xf32 = 0,
     mfma_f32_16x16x1xf32,
     mfma_f32_4x4x1xf32,
     mfma_f32_32x32x2xf32, // k reduction
     mfma_f32_16x16x4xf32, // k reduction
-                          /// fp16
     mfma_f32_32x32x4f16,
     mfma_f32_16x16x4f16,
     mfma_f32_4x4x4f16,
     mfma_f32_32x32x8f16,  // k reduction
     mfma_f32_16x16x16f16, // k reduction
-                          /// bfp16
     mfma_f32_32x32x2bf16,
     mfma_f32_16x16x2bf16,
     mfma_f32_4x4x2bf16,
@@ -29,25 +26,23 @@ enum struct mfma_instr
     mfma_f32_16x16x8bf16, // k reduction
 };
 
-template <mfma_instr instr>
-struct mfma_info;
+template <MfmaInstr instr>
+struct mfma_type;
 
 template <>
-struct mfma_info<mfma_instr::mfma_f32_32x32x1xf32>
+struct mfma_type<MfmaInstr::mfma_f32_32x32x1xf32>
 {
     static constexpr index_t group_size          = 4;
-    static constexpr index_t num_groups_blk  = 4;
-    static constexpr index_t num_regs_blk    = group_size * num_groups_blk;
-    static constexpr index_t num_threads_blk = 32;
+    static constexpr index_t num_groups_per_blk  = 4;
+    static constexpr index_t num_regs_per_blk    = 16;
+    static constexpr index_t num_threads_per_blk = 32;
     static constexpr index_t wave_size           = 64;
-    static constexpr index_t num_input_blks  = wave_size / num_threads_blk;
+    static constexpr index_t num_input_blks      = 2;
     static constexpr index_t num_output_blks     = 2;
-    static constexpr index_t num_regs_xdlops = num_regs_blk * num_output_blks;
-    static constexpr index_t m               = 32;
-    static constexpr index_t n               = 32;
-    static constexpr index_t k               = 1;
-    static constexpr index_t cycles          = 64;
-    static constexpr index_t k_base          = 1;
+    static constexpr index_t m_per_blk           = 32;
+    static constexpr index_t n_per_blk           = 32;
+    static constexpr index_t k_per_blk           = 1;
+    static constexpr bool is_k_reduction         = false;
 
     template <index_t MPerXdlops,
               index_t NPerXdlops,
@@ -62,21 +57,19 @@ struct mfma_info<mfma_instr::mfma_f32_32x32x1xf32>
 };
 
 template <>
-struct mfma_info<mfma_instr::mfma_f32_32x32x2xf32>
+struct mfma_type<MfmaInstr::mfma_f32_32x32x2xf32>
 {
     static constexpr index_t group_size          = 4;
-    static constexpr index_t num_groups_blk  = 4;
-    static constexpr index_t num_regs_blk    = group_size * num_groups_blk;
-    static constexpr index_t num_threads_blk = 32;
+    static constexpr index_t num_groups_per_blk  = 4;
+    static constexpr index_t num_regs_per_blk    = 16;
+    static constexpr index_t num_threads_per_blk = 32;
     static constexpr index_t wave_size           = 64;
-    static constexpr index_t num_input_blks  = wave_size / num_threads_blk;
+    static constexpr index_t num_input_blks      = 2;
     static constexpr index_t num_output_blks     = 1;
-    static constexpr index_t num_regs_xdlops = num_regs_blk * num_output_blks;
-    static constexpr index_t m               = 32;
-    static constexpr index_t n               = 32;
-    static constexpr index_t k               = 2;
-    static constexpr index_t cycles          = 64;
-    static constexpr index_t k_base          = 1;
+    static constexpr index_t m_per_blk           = 32;
+    static constexpr index_t n_per_blk           = 32;
+    static constexpr index_t k_per_blk           = 1;
+    static constexpr bool is_k_reduction         = true;
 
     template <index_t MPerXdlops,
               index_t NPerXdlops,
@@ -91,21 +84,19 @@ struct mfma_info<mfma_instr::mfma_f32_32x32x2xf32>
 };
 
 template <>
-struct mfma_info<mfma_instr::mfma_f32_16x16x4xf32>
+struct mfma_type<MfmaInstr::mfma_f32_16x16x4xf32>
 {
     static constexpr index_t group_size          = 4;
-    static constexpr index_t num_groups_blk  = 1;
-    static constexpr index_t num_regs_blk    = group_size * num_groups_blk;
-    static constexpr index_t num_threads_blk = 16;
+    static constexpr index_t num_groups_per_blk  = 1;
+    static constexpr index_t num_regs_per_blk    = 4;
+    static constexpr index_t num_threads_per_blk = 16;
     static constexpr index_t wave_size           = 64;
-    static constexpr index_t num_input_blks  = wave_size / num_threads_blk;
+    static constexpr index_t num_input_blks      = 4;
     static constexpr index_t num_output_blks     = 1;
-    static constexpr index_t num_regs_xdlops = num_regs_blk * num_output_blks;
-    static constexpr index_t m               = 16;
-    static constexpr index_t n               = 16;
-    static constexpr index_t k               = 4;
-    static constexpr index_t cycles          = 32;
-    static constexpr index_t k_base          = 1;
+    static constexpr index_t m_per_blk           = 16;
+    static constexpr index_t n_per_blk           = 16;
+    static constexpr index_t k_per_blk           = 1;
+    static constexpr bool is_k_reduction         = true;
 
     template <index_t MPerXdlops,
               index_t NPerXdlops,
@@ -120,21 +111,19 @@ struct mfma_info<mfma_instr::mfma_f32_16x16x4xf32>
 };
 
 template <>
-struct mfma_info<mfma_instr::mfma_f32_16x16x1xf32>
+struct mfma_type<MfmaInstr::mfma_f32_16x16x1xf32>
 {
     static constexpr index_t group_size          = 4;
-    static constexpr index_t num_groups_blk  = 1;
-    static constexpr index_t num_regs_blk    = group_size * num_groups_blk;
-    static constexpr index_t num_threads_blk = 16;
+    static constexpr index_t num_groups_per_blk  = 1;
+    static constexpr index_t num_regs_per_blk    = 4;
+    static constexpr index_t num_threads_per_blk = 16;
     static constexpr index_t wave_size           = 64;
-    static constexpr index_t num_input_blks  = wave_size / num_threads_blk;
+    static constexpr index_t num_input_blks      = 4;
     static constexpr index_t num_output_blks     = 4;
-    static constexpr index_t num_regs_xdlops = num_regs_blk * num_output_blks;
-    static constexpr index_t m               = 16;
-    static constexpr index_t n               = 16;
-    static constexpr index_t k               = 1;
-    static constexpr index_t cycles          = 32;
-    static constexpr index_t k_base          = 1;
+    static constexpr index_t m_per_blk           = 16;
+    static constexpr index_t n_per_blk           = 16;
+    static constexpr index_t k_per_blk           = 1;
+    static constexpr bool is_k_reduction         = false;
 
     template <index_t MPerXdlops,
               index_t NPerXdlops,
@@ -150,21 +139,19 @@ struct mfma_info<mfma_instr::mfma_f32_16x16x1xf32>
 
 // treat 4x4x1 as a single-blk 4x64 mfma
 template <>
-struct mfma_info<mfma_instr::mfma_f32_4x4x1xf32>
+struct mfma_type<MfmaInstr::mfma_f32_4x4x1xf32>
 {
     static constexpr index_t group_size          = 4;
-    static constexpr index_t num_groups_blk  = 1;
-    static constexpr index_t num_regs_blk    = group_size * num_groups_blk;
-    static constexpr index_t num_threads_blk = 64;
+    static constexpr index_t num_groups_per_blk  = 1;
+    static constexpr index_t num_regs_per_blk    = 4;
+    static constexpr index_t num_threads_per_blk = 64;
     static constexpr index_t wave_size           = 64;
     static constexpr index_t num_input_blks      = 1;
     static constexpr index_t num_output_blks     = 1;
-    static constexpr index_t num_regs_xdlops = 4;
-    static constexpr index_t m               = 4;
-    static constexpr index_t n               = 64;
-    static constexpr index_t k               = 1;
-    static constexpr index_t cycles          = 8;
-    static constexpr index_t k_base          = 1;
+    static constexpr index_t m_per_blk           = 4;
+    static constexpr index_t n_per_blk           = 64;
+    static constexpr index_t k_per_blk           = 1;
+    static constexpr bool is_k_reduction         = false;
 
     template <index_t MPerXdlops,
               index_t NPerXdlops,
@@ -179,21 +166,19 @@ struct mfma_info<mfma_instr::mfma_f32_4x4x1xf32>
 };
 
 template <>
-struct mfma_info<mfma_instr::mfma_f32_32x32x4f16>
+struct mfma_type<MfmaInstr::mfma_f32_32x32x4f16>
 {
     static constexpr index_t group_size          = 4;
-    static constexpr index_t num_groups_blk  = 4;
-    static constexpr index_t num_regs_blk    = group_size * num_groups_blk;
-    static constexpr index_t num_threads_blk = 32;
+    static constexpr index_t num_groups_per_blk  = 4;
+    static constexpr index_t num_regs_per_blk    = 16;
+    static constexpr index_t num_threads_per_blk = 32;
     static constexpr index_t wave_size           = 64;
-    static constexpr index_t num_input_blks  = wave_size / num_threads_blk;
+    static constexpr index_t num_input_blks      = 2;
     static constexpr index_t num_output_blks     = 2;
-    static constexpr index_t num_regs_xdlops = num_regs_blk * num_output_blks;
-    static constexpr index_t m               = 32;
-    static constexpr index_t n               = 32;
-    static constexpr index_t k               = 4;
-    static constexpr index_t cycles          = 64;
-    static constexpr index_t k_base          = 4;
+    static constexpr index_t m_per_blk           = 32;
+    static constexpr index_t n_per_blk           = 32;
+    static constexpr index_t k_per_blk           = 4;
+    static constexpr bool is_k_reduction         = false;
 
     template <index_t MPerXdlops,
               index_t NPerXdlops,
@@ -208,21 +193,19 @@ struct mfma_info<mfma_instr::mfma_f32_32x32x4f16>
 };
 
 template <>
-struct mfma_info<mfma_instr::mfma_f32_32x32x8f16>
+struct mfma_type<MfmaInstr::mfma_f32_32x32x8f16>
 {
     static constexpr index_t group_size          = 4;
-    static constexpr index_t num_groups_blk  = 4;
-    static constexpr index_t num_regs_blk    = group_size * num_groups_blk;
-    static constexpr index_t num_threads_blk = 32;
+    static constexpr index_t num_groups_per_blk  = 4;
+    static constexpr index_t num_regs_per_blk    = 16;
+    static constexpr index_t num_threads_per_blk = 32;
     static constexpr index_t wave_size           = 64;
-    static constexpr index_t num_input_blks  = wave_size / num_threads_blk;
+    static constexpr index_t num_input_blks      = 2;
     static constexpr index_t num_output_blks     = 1;
-    static constexpr index_t num_regs_xdlops = num_regs_blk * num_output_blks;
-    static constexpr index_t m               = 32;
-    static constexpr index_t n               = 32;
-    static constexpr index_t k               = 8;
-    static constexpr index_t cycles          = 64;
-    static constexpr index_t k_base          = 4;
+    static constexpr index_t m_per_blk           = 32;
+    static constexpr index_t n_per_blk           = 32;
+    static constexpr index_t k_per_blk           = 4;
+    static constexpr bool is_k_reduction         = true;
 
     template <index_t MPerXdlops,
               index_t NPerXdlops,
@@ -237,21 +220,19 @@ struct mfma_info<mfma_instr::mfma_f32_32x32x8f16>
 };
 
 template <>
-struct mfma_info<mfma_instr::mfma_f32_16x16x16f16>
+struct mfma_type<MfmaInstr::mfma_f32_16x16x16f16>
 {
     static constexpr index_t group_size          = 4;
-    static constexpr index_t num_groups_blk  = 1;
-    static constexpr index_t num_regs_blk    = group_size * num_groups_blk;
-    static constexpr index_t num_threads_blk = 16;
+    static constexpr index_t num_groups_per_blk  = 1;
+    static constexpr index_t num_regs_per_blk    = 4;
+    static constexpr index_t num_threads_per_blk = 16;
     static constexpr index_t wave_size           = 64;
-    static constexpr index_t num_input_blks  = wave_size / num_threads_blk;
+    static constexpr index_t num_input_blks      = 4;
     static constexpr index_t num_output_blks     = 1;
-    static constexpr index_t num_regs_xdlops = num_regs_blk * num_output_blks;
-    static constexpr index_t m               = 16;
-    static constexpr index_t n               = 16;
-    static constexpr index_t k               = 16;
-    static constexpr index_t cycles          = 32;
-    static constexpr index_t k_base          = 4;
+    static constexpr index_t m_per_blk           = 16;
+    static constexpr index_t n_per_blk           = 16;
+    static constexpr index_t k_per_blk           = 4;
+    static constexpr bool is_k_reduction         = true;
 
     template <index_t MPerXdlops,
               index_t NPerXdlops,
@@ -266,21 +247,19 @@ struct mfma_info<mfma_instr::mfma_f32_16x16x16f16>
 };
 
 template <>
-struct mfma_info<mfma_instr::mfma_f32_16x16x4f16>
+struct mfma_type<MfmaInstr::mfma_f32_16x16x4f16>
 {
     static constexpr index_t group_size          = 4;
-    static constexpr index_t num_groups_blk  = 1;
-    static constexpr index_t num_regs_blk    = group_size * num_groups_blk;
-    static constexpr index_t num_threads_blk = 16;
+    static constexpr index_t num_groups_per_blk  = 1;
+    static constexpr index_t num_regs_per_blk    = 4;
+    static constexpr index_t num_threads_per_blk = 16;
     static constexpr index_t wave_size           = 64;
-    static constexpr index_t num_input_blks  = wave_size / num_threads_blk;
+    static constexpr index_t num_input_blks      = 4;
     static constexpr index_t num_output_blks     = 4;
-    static constexpr index_t num_regs_xdlops = num_regs_blk * num_output_blks;
-    static constexpr index_t m               = 16;
-    static constexpr index_t n               = 16;
-    static constexpr index_t k               = 4;
-    static constexpr index_t cycles          = 32;
-    static constexpr index_t k_base          = 4;
+    static constexpr index_t m_per_blk           = 16;
+    static constexpr index_t n_per_blk           = 16;
+    static constexpr index_t k_per_blk           = 4;
+    static constexpr bool is_k_reduction         = false;
 
     template <index_t MPerXdlops,
               index_t NPerXdlops,
@@ -295,21 +274,19 @@ struct mfma_info<mfma_instr::mfma_f32_16x16x4f16>
 };
 
 template <>
-struct mfma_info<mfma_instr::mfma_f32_4x4x4f16>
+struct mfma_type<MfmaInstr::mfma_f32_4x4x4f16>
 {
     static constexpr index_t group_size          = 4;
-    static constexpr index_t num_groups_blk  = 1;
-    static constexpr index_t num_regs_blk    = group_size * num_groups_blk;
-    static constexpr index_t num_threads_blk = 64;
+    static constexpr index_t num_groups_per_blk  = 1;
+    static constexpr index_t num_regs_per_blk    = 4;
+    static constexpr index_t num_threads_per_blk = 64;
     static constexpr index_t wave_size           = 64;
     static constexpr index_t num_input_blks      = 1;
     static constexpr index_t num_output_blks     = 1;
-    static constexpr index_t num_regs_xdlops = 4;
-    static constexpr index_t m               = 4;
-    static constexpr index_t n               = 64;
-    static constexpr index_t k               = 4;
-    static constexpr index_t cycles          = 8;
-    static constexpr index_t k_base          = 4;
+    static constexpr index_t m_per_blk           = 4;
+    static constexpr index_t n_per_blk           = 64;
+    static constexpr index_t k_per_blk           = 4;
+    static constexpr bool is_k_reduction         = false;
 
     template <index_t MPerXdlops,
               index_t NPerXdlops,
@@ -325,21 +302,19 @@ struct mfma_info<mfma_instr::mfma_f32_4x4x4f16>
 
 #if 0
 template <>
-struct mfma_info<mfma_instr::mfma_f32_32x32x2bf16>
+struct mfma_type<MfmaInstr::mfma_f32_32x32x2bf16>
 {
     static constexpr index_t group_size          = 4;
-    static constexpr index_t num_groups_blk  = 4;
-    static constexpr index_t num_regs_blk    = group_size * num_groups_blk;
-    static constexpr index_t num_threads_blk = 32;
+    static constexpr index_t num_groups_per_blk  = 4;
+    static constexpr index_t num_regs_per_blk    = 16;
+    static constexpr index_t num_threads_per_blk = 32;
     static constexpr index_t wave_size           = 64;
-    static constexpr index_t num_input_blks  = wave_size / num_threads_blk;
+    static constexpr index_t num_input_blks      = 2;
     static constexpr index_t num_output_blks     = 2;
-    static constexpr index_t num_regs_xdlops = num_regs_blk * num_output_blks;
-    static constexpr index_t m               = 32;
-    static constexpr index_t n               = 32;
-    static constexpr index_t k               = 2;
-    static constexpr index_t cycles          = 64;
-    static constexpr index_t k_base          = 2;
+    static constexpr index_t m_per_blk           = 32;
+    static constexpr index_t n_per_blk           = 32;
+    static constexpr index_t k_per_blk           = 2;
+    static constexpr bool is_k_reduction         = false;
 
     template <index_t MPerXdlops,
               index_t NPerXdlops,
@@ -359,21 +334,19 @@ struct mfma_info<mfma_instr::mfma_f32_32x32x2bf16>
 };
 
 template <>
-struct mfma_info<mfma_instr::mfma_f32_32x32x4bf16>
+struct mfma_type<MfmaInstr::mfma_f32_32x32x4bf16>
 {
     static constexpr index_t group_size          = 4;
-    static constexpr index_t num_groups_blk  = 4;
-    static constexpr index_t num_regs_blk    = group_size * num_groups_blk;
-    static constexpr index_t num_threads_blk = 32;
+    static constexpr index_t num_groups_per_blk  = 4;
+    static constexpr index_t num_regs_per_blk    = 16;
+    static constexpr index_t num_threads_per_blk = 32;
     static constexpr index_t wave_size           = 64;
-    static constexpr index_t num_input_blks  = wave_size / num_threads_blk;
+    static constexpr index_t num_input_blks      = 2;
     static constexpr index_t num_output_blks     = 1;
-    static constexpr index_t num_regs_xdlops = num_regs_blk * num_output_blks;
-    static constexpr index_t m               = 32;
-    static constexpr index_t n               = 32;
-    static constexpr index_t k               = 4;
-    static constexpr index_t cycles          = 64;
-    static constexpr index_t k_base          = 2;
+    static constexpr index_t m_per_blk           = 32;
+    static constexpr index_t n_per_blk           = 32;
+    static constexpr index_t k_per_blk           = 2;
+    static constexpr bool is_k_reduction         = true;
 
     template <index_t MPerXdlops,
               index_t NPerXdlops,
@@ -392,21 +365,19 @@ struct mfma_info<mfma_instr::mfma_f32_32x32x4bf16>
 };
 
 template <>
-struct mfma_info<mfma_instr::mfma_f32_16x16x8bf16>
+struct mfma_type<MfmaInstr::mfma_f32_16x16x8bf16>
 {
     static constexpr index_t group_size          = 4;
-    static constexpr index_t num_groups_blk  = 1;
-    static constexpr index_t num_regs_blk    = group_size * num_groups_blk;
-    static constexpr index_t num_threads_blk = 16;
+    static constexpr index_t num_groups_per_blk  = 1;
+    static constexpr index_t num_regs_per_blk    = 4;
+    static constexpr index_t num_threads_per_blk = 16;
     static constexpr index_t wave_size           = 64;
-    static constexpr index_t num_input_blks  = wave_size / num_threads_blk;
+    static constexpr index_t num_input_blks      = 4;
     static constexpr index_t num_output_blks     = 1;
-    static constexpr index_t num_regs_xdlops = num_regs_blk * num_output_blks;
-    static constexpr index_t m               = 16;
-    static constexpr index_t n               = 16;
-    static constexpr index_t k               = 8;
-    static constexpr index_t cycles          = 32;
-    static constexpr index_t k_base          = 2;
+    static constexpr index_t m_per_blk           = 16;
+    static constexpr index_t n_per_blk           = 16;
+    static constexpr index_t k_per_blk           = 2;
+    static constexpr bool is_k_reduction         = true;
 
     template <index_t MPerXdlops,
               index_t NPerXdlops,
@@ -425,21 +396,19 @@ struct mfma_info<mfma_instr::mfma_f32_16x16x8bf16>
 };
 
 template <>
-struct mfma_info<mfma_instr::mfma_f32_16x16x2bf16>
+struct mfma_type<MfmaInstr::mfma_f32_16x16x2bf16>
 {
     static constexpr index_t group_size          = 4;
-    static constexpr index_t num_groups_blk  = 1;
-    static constexpr index_t num_regs_blk    = group_size * num_groups_blk;
-    static constexpr index_t num_threads_blk = 16;
+    static constexpr index_t num_groups_per_blk  = 1;
+    static constexpr index_t num_regs_per_blk    = 4;
+    static constexpr index_t num_threads_per_blk = 16;
     static constexpr index_t wave_size           = 64;
-    static constexpr index_t num_input_blks  = wave_size / num_threads_blk;
+    static constexpr index_t num_input_blks      = 4;
     static constexpr index_t num_output_blks     = 4;
-    static constexpr index_t num_regs_xdlops = num_regs_blk * num_output_blks;
-    static constexpr index_t m               = 16;
-    static constexpr index_t n               = 16;
-    static constexpr index_t k               = 2;
-    static constexpr index_t cycles          = 32;
-    static constexpr index_t k_base          = 2;
+    static constexpr index_t m_per_blk           = 16;
+    static constexpr index_t n_per_blk           = 16;
+    static constexpr index_t k_per_blk           = 2;
+    static constexpr bool is_k_reduction         = false;
 
     template <index_t MPerXdlops,
               index_t NPerXdlops,
@@ -458,21 +427,19 @@ struct mfma_info<mfma_instr::mfma_f32_16x16x2bf16>
 };
 
 template <>
-struct mfma_info<mfma_instr::mfma_f32_4x4x2bf16>
+struct mfma_type<MfmaInstr::mfma_f32_4x4x2bf16>
 {
     static constexpr index_t group_size          = 4;
-    static constexpr index_t num_groups_blk  = 1;
-    static constexpr index_t num_regs_blk    = group_size * num_groups_blk;
-    static constexpr index_t num_threads_blk = 64;
+    static constexpr index_t num_groups_per_blk  = 1;
+    static constexpr index_t num_regs_per_blk    = 4;
+    static constexpr index_t num_threads_per_blk = 64;
     static constexpr index_t wave_size           = 64;
     static constexpr index_t num_input_blks      = 1;
     static constexpr index_t num_output_blks     = 1;
-    static constexpr index_t num_regs_xdlops = 4;
-    static constexpr index_t m               = 4;
-    static constexpr index_t n               = 64;
-    static constexpr index_t k               = 2;
-    static constexpr index_t cycles          = 8;
-    static constexpr index_t k_base          = 2;
+    static constexpr index_t m_per_blk           = 4;
+    static constexpr index_t n_per_blk           = 64;
+    static constexpr index_t k_per_blk           = 2;
+    static constexpr bool is_k_reduction         = false;
 
     template <index_t MPerXdlops,
               index_t NPerXdlops,
@@ -491,200 +458,227 @@ struct mfma_info<mfma_instr::mfma_f32_4x4x2bf16>
 };
 #endif
 
-template <mfma_instr instr, index_t MPerXdlops_, index_t NPerXdlops_>
-struct xdlops_info
+template <typename base_type, index_t MPerXdlops, index_t NPerXdlops>
+struct MfmaSelector
 {
-    static constexpr auto mfma_type = mfma_info<instr>{};
+    template <typename base_type_, index_t MPerXdlops_, index_t NPerXdlops_>
+    static constexpr auto GetMfma();
 
-    static constexpr index_t MPerXdlops = MPerXdlops_;
-    static constexpr index_t NPerXdlops = NPerXdlops_;
-
-    static constexpr bool IsABroadcast()
+    template <>
+    static constexpr auto GetMfma<float, 64, 64>()
     {
-        static_assert(NPerXdlops >= MPerXdlops, "only support ABroadcast");
-        return true;
+        return MfmaInstr::mfma_f32_32x32x1xf32;
     }
 
-    static constexpr bool IsKReduction()
+    template <>
+    static constexpr auto GetMfma<float, 32, 64>()
     {
-        return (mfma_type.num_output_blks == 1) && (mfma_type.num_input_blks > 1);
+        return MfmaInstr::mfma_f32_32x32x1xf32;
     }
 
-    static constexpr index_t GetKPerXdlops()
+    template <>
+    static constexpr auto GetMfma<float, 16, 64>()
     {
-        return IsKReduction() ? mfma_type.num_input_blks : 1;
+        return MfmaInstr::mfma_f32_16x16x1xf32;
     }
 
-    static constexpr index_t GetNumCRegs() { return MPerXdlops * NPerXdlops / mfma_type.wave_size; }
-};
-
-template <class base_type, index_t MPerWave, index_t NPerWave, index_t KPack>
-struct XdlopsGemm
-{
-    template <class base_type_  = base_type,
-              index_t MPerWave_ = MPerWave,
-              index_t NPerWave_ = NPerWave>
-    static constexpr auto GetXdlopsInfo();
-
     template <>
-    static constexpr auto GetXdlopsInfo<float, 64, 64>()
+    static constexpr auto GetMfma<float, 8, 64>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_32x32x1xf32, 64, 64>{};
+        return MfmaInstr::mfma_f32_4x4x1xf32;
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<float, 32, 64>()
+    static constexpr auto GetMfma<float, 4, 64>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_32x32x1xf32, 32, 64>{};
+        return MfmaInstr::mfma_f32_4x4x1xf32;
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<float, 16, 64>()
+    static constexpr auto GetMfma<float, 32, 32>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_16x16x1xf32, 16, 64>{};
+        return MfmaInstr::mfma_f32_32x32x2xf32;
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<float, 8, 64>()
+    static constexpr auto GetMfma<float, 16, 16>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_4x4x1xf32, 8, 64>{};
+        return MfmaInstr::mfma_f32_16x16x4xf32;
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<float, 4, 64>()
+    static constexpr auto GetMfma<half_t, 64, 64>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_4x4x1xf32, 4, 64>{};
+        return MfmaInstr::mfma_f32_32x32x4f16;
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<float, 32, 32>()
+    static constexpr auto GetMfma<half_t, 32, 64>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_32x32x2xf32, 32, 32>{};
+        return MfmaInstr::mfma_f32_32x32x4f16;
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<float, 16, 16>()
+    static constexpr auto GetMfma<half_t, 32, 32>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_16x16x4xf32, 16, 16>{};
+        return MfmaInstr::mfma_f32_32x32x8f16;
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<half_t, 64, 64>()
+    static constexpr auto GetMfma<half_t, 16, 16>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_32x32x4f16, 64, 64>{};
+        return MfmaInstr::mfma_f32_16x16x16f16;
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<half_t, 32, 64>()
+    static constexpr auto GetMfma<half_t, 16, 64>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_32x32x4f16, 32, 64>{};
+        return MfmaInstr::mfma_f32_16x16x4f16;
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<half_t, 32, 32>()
+    static constexpr auto GetMfma<half_t, 8, 64>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_32x32x8f16, 32, 32>{};
+        return MfmaInstr::mfma_f32_4x4x4f16;
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<half_t, 16, 16>()
+    static constexpr auto GetMfma<half_t, 4, 64>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_16x16x16f16, 16, 16>{};
+        return MfmaInstr::mfma_f32_4x4x4f16;
     }
 
+#if 0
     template <>
-    static constexpr auto GetXdlopsInfo<half_t, 16, 64>()
+    static constexpr auto GetMfma<ushort, 128, 64>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_16x16x4f16, 16, 64>{};
+        return xdlops_info<MfmaInstr::mfma_f32_32x32x2bf16, 64, 64, 2, 1, c_vec32_4_t>{};
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<half_t, 8, 64>()
+    static constexpr auto GetMfma<ushort, 64, 128>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_4x4x4f16, 8, 64>{};
+        return xdlops_info<MfmaInstr::mfma_f32_32x32x2bf16, 64, 64, 1, 2, c_vec32_4_t>{};
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<half_t, 4, 64>()
+    static constexpr auto GetMfma<ushort, 64, 64>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_4x4x4f16, 4, 64>{};
+        return xdlops_info<MfmaInstr::mfma_f32_32x32x2bf16, 64, 64, 1, 1, c_vec32_2_t>{};
     }
 
-#if 0
     template <>
-    static constexpr auto GetXdlopsInfo<ushort, 128, 64>()
+    static constexpr auto GetMfma<ushort, 64, 32>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_32x32x2bf16, 64, 64, 2, 1, c_vec32_4_t>{};
+        return xdlops_info<MfmaInstr::mfma_f32_32x32x2bf16, 64, 32, 1, 1, c_vec32_1_t>{};
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<ushort, 64, 128>()
+    static constexpr auto GetMfma<ushort, 32, 64>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_32x32x2bf16, 64, 64, 1, 2, c_vec32_4_t>{};
+        return xdlops_info<MfmaInstr::mfma_f32_32x32x2bf16, 32, 64, 1, 1, c_vec32_1_t>{};
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<ushort, 64, 64>()
+    static constexpr auto GetMfma<ushort, 64, 16>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_32x32x2bf16, 64, 64, 1, 1, c_vec32_2_t>{};
+        return xdlops_info<MfmaInstr::mfma_f32_16x16x2bf16, 64, 16, 1, 1, c_vec16_1_t>{};
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<ushort, 64, 32>()
+    static constexpr auto GetMfma<ushort, 16, 64>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_32x32x2bf16, 64, 32, 1, 1, c_vec32_1_t>{};
+        return xdlops_info<MfmaInstr::mfma_f32_16x16x2bf16, 16, 64, 1, 1, c_vec16_1_t>{};
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<ushort, 32, 64>()
+    static constexpr auto GetMfma<ushort, 8, 64>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_32x32x2bf16, 32, 64, 1, 1, c_vec32_1_t>{};
+        return xdlops_info<MfmaInstr::mfma_f32_4x4x2bf16, 8, 64, 1, 1, c_vec4_2_t>{};
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<ushort, 64, 16>()
+    static constexpr auto GetMfma<ushort, 4, 64>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_16x16x2bf16, 64, 16, 1, 1, c_vec16_1_t>{};
+        return xdlops_info<MfmaInstr::mfma_f32_4x4x2bf16, 4, 64, 1, 1, c_vec4_1_t>{};
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<ushort, 16, 64>()
+    static constexpr auto GetMfma<ushort, 32, 32>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_16x16x2bf16, 16, 64, 1, 1, c_vec16_1_t>{};
+        return xdlops_info<MfmaInstr::mfma_f32_32x32x4bf16, 32, 32, 1, 1, c_vec16_1_t>{};
     }
 
     template <>
-    static constexpr auto GetXdlopsInfo<ushort, 8, 64>()
+    static constexpr auto GetMfma<ushort, 16, 16>()
     {
-        return xdlops_info<mfma_instr::mfma_f32_4x4x2bf16, 8, 64, 1, 1, c_vec4_2_t>{};
+        return xdlops_info<MfmaInstr::mfma_f32_16x16x8bf16, 16, 16, 1, 1, c_vec4_1_t>{};
     }
+#endif
 
-    template <>
-    static constexpr auto GetXdlopsInfo<ushort, 4, 64>()
+    static constexpr auto selected_mfma = mfma_type<GetMfma<base_type, MPerXdlops, NPerXdlops>()>{};
+
+    __host__ __device__ static constexpr void mfma_check()
     {
-        return xdlops_info<mfma_instr::mfma_f32_4x4x2bf16, 4, 64, 1, 1, c_vec4_1_t>{};
+        static_assert(selected_mfma.group_size * selected_mfma.num_groups_per_blk ==
+                          selected_mfma.num_regs_per_blk,
+                      "wrong! num_regs_per_blk");
+
+        static_assert(selected_mfma.num_threads_per_blk == selected_mfma.n_per_blk,
+                      "n_per_blk != num_threads_per_blk");
+
+        static_assert(selected_mfma.num_regs_per_blk * selected_mfma.num_input_blks ==
+                          selected_mfma.m_per_blk,
+                      "m_per_blk != num_input_blks * num_regs_per_blk");
+
+        static_assert(selected_mfma.num_output_blks == selected_mfma.num_input_blks ||
+                          selected_mfma.num_output_blks == 1,
+                      "incorrect num_output_blks");
+
+        static_assert(selected_mfma.num_regs_per_blk * selected_mfma.wave_size ==
+                          selected_mfma.m_per_blk * selected_mfma.n_per_blk,
+                      "num_regs_per_blk incorrect");
+
+        static_assert(selected_mfma.is_k_reduction ||
+                          (selected_mfma.num_input_blks == selected_mfma.num_output_blks),
+                      "is_k_reduction wrong!");
     }
 
-    template <>
-    static constexpr auto GetXdlopsInfo<ushort, 32, 32>()
+    __host__ __device__ constexpr MfmaSelector() { mfma_check(); }
+
+    static constexpr bool IsABroadcast()
     {
-        return xdlops_info<mfma_instr::mfma_f32_32x32x4bf16, 32, 32, 1, 1, c_vec16_1_t>{};
+        static_assert(NPerXdlops >= MPerXdlops, "only support ABroadcast");
+        return true;
     }
 
-    template <>
-    static constexpr auto GetXdlopsInfo<ushort, 16, 16>()
+    static constexpr index_t GetKPerXdlops()
     {
-        return xdlops_info<mfma_instr::mfma_f32_16x16x8bf16, 16, 16, 1, 1, c_vec4_1_t>{};
+        return (selected_mfma.is_k_reduction ? selected_mfma.num_input_blks : 1) *
+               selected_mfma.k_per_blk;
     }
-#endif
+
+    static constexpr index_t GetKPerThread() { return selected_mfma.k_per_blk; }
+};
+
+template <typename base_type, index_t MPerXdlops, index_t NPerXdlops, index_t KPack>
+struct XdlopsGemm
+{
+    static constexpr auto I0 = Number<0>{};
+    static constexpr auto I1 = Number<1>{};
+    static constexpr auto I2 = Number<2>{};
+    static constexpr auto I3 = Number<3>{};
+    static constexpr auto I4 = Number<4>{};
+    static constexpr auto I5 = Number<5>{};
 
     using CIndex = MultiIndex<2>;
 
-    __device__ static constexpr index_t GetNumBlks() { return mfma_type.num_output_blks; }
+    __device__ static constexpr index_t GetNumBlks() { return mfma_instr.num_output_blks; }
 
     __device__ static constexpr index_t GetNumXdlops()
     {
-        return MPerXdlops * NPerXdlops / (mfma_type.m * mfma_type.n * mfma_type.num_output_blks);
+        return MPerXdlops * NPerXdlops /
+               (mfma_instr.m_per_blk * mfma_instr.n_per_blk * mfma_instr.num_output_blks);
     }
 
     __host__ __device__ constexpr XdlopsGemm()
@@ -697,104 +691,142 @@ struct XdlopsGemm
                           MPerXdlops == 64,
                       "Only support GemmMPerXdlops == 4, 8, 16, 32 or 64 for xdlops");
 
-        static_assert(mfma_type.num_threads_blk == mfma_type.n, "n != num_threads_blk");
-        static_assert(mfma_type.num_regs_blk * mfma_type.num_input_blks == mfma_type.m,
-                      "m != num_input_blks * num_regs_blk");
-        static_assert(mfma_type.num_output_blks == mfma_type.num_input_blks ||
-                          mfma_type.num_output_blks == 1,
-                      "incorrect num_output_blks");
-        static_assert(mfma_type.num_regs_blk * mfma_type.wave_size == mfma_type.m * mfma_type.n,
-                      "num_regs_blk incorrect");
-
-        static_assert(mfma_type.k % mfma_type.k_base == 0, "k % kbase != 0!");
+        static_assert(KPack % mfma_instr.k_per_blk == 0, "KPack cannot be divided by k_per_blk");
+    }
+
+    template <typename CM0N0M1N1M2N2Desc>
+    __host__ __device__ static constexpr auto
+    MakeCM0N0M1N1M2M3M4N2Descriptor(const CM0N0M1N1M2N2Desc& c_m0_n0_m1_n1_m2_n2_desc)
+    {
+        const auto M0 = c_m0_n0_m1_n1_m2_n2_desc.GetLength(I0);
+        const auto N0 = c_m0_n0_m1_n1_m2_n2_desc.GetLength(I1);
+        const auto M1 = c_m0_n0_m1_n1_m2_n2_desc.GetLength(I2);
+        const auto N1 = c_m0_n0_m1_n1_m2_n2_desc.GetLength(I3);
+
+        return transform_tensor_descriptor(
+            c_m0_n0_m1_n1_m2_n2_desc,
+            make_tuple(make_pass_through_transform(M0),
+                       make_pass_through_transform(N0),
+                       make_pass_through_transform(M1),
+                       make_pass_through_transform(N1),
+                       make_unmerge_transform(make_tuple(mfma_instr.num_groups_per_blk,
+                                                         mfma_instr.num_input_blks,
+                                                         mfma_instr.group_size)),
+                       make_pass_through_transform(mfma_instr.num_threads_per_blk)),
+            make_tuple(Sequence<0>{},
+                       Sequence<1>{},
+                       Sequence<2>{},
+                       Sequence<3>{},
+                       Sequence<4>{},
+                       Sequence<5>{}),
+            make_tuple(Sequence<0>{},
+                       Sequence<1>{},
+                       Sequence<2>{},
+                       Sequence<3>{},
+                       Sequence<4, 5, 6>{},
+                       Sequence<7>{}));
     }
 
     __device__ static constexpr index_t GetRegSizePerXdlops()
     {
-        return MPerXdlops * NPerXdlops / mfma_type.wave_size;
+        return MPerXdlops * NPerXdlops / mfma_instr.wave_size;
     }
 
-    template <class ADesc,
-              class BDesc,
-              class CDesc,
-              index_t m0,
-              index_t n0,
-              class FloatA,
-              class FloatB,
-              class FloatC>
+    template <index_t c_offset, class FloatA, class FloatB, class FloatC>
     __device__ void Run(const FloatA& p_a_wave, const FloatB& p_b_wave, FloatC& p_c_thread) const
     {
         static_assert(is_same<base_type, float>::value || is_same<base_type, half_t>::value ||
                           is_same<base_type, ushort>::value,
                       "base base_type must be float, half, ushort!");
 
-        static_assert(KPack % mfma_type.k_base == 0, "KPack cannot be divided by k_base");
+        static_for<0, KPack / mfma_instr.k_per_blk, 1>{}([&](auto k) {
+            mfma_instr.template run<MPerXdlops, NPerXdlops, c_offset>(
+                p_a_wave[k], p_b_wave[k], p_c_thread);
+        });
+    }
+
+    __device__ static auto GetLaneId() { return get_thread_local_1d_id() % mfma_instr.wave_size; }
 
-        constexpr index_t c_offset = CDesc{}.CalculateOffset(make_tuple(m0, n0)) * GetNumXdlops();
+    __device__ static auto GetBlkIdx()
+    {
+        const auto laneId = GetLaneId();
 
-        static_for<0, KPack, mfma_type.k_base>{}([&](auto k) {
-            constexpr index_t a_offset = ADesc{}.CalculateOffset(make_tuple(0, m0, 0, k));
-            constexpr index_t b_offset = BDesc{}.CalculateOffset(make_tuple(0, n0, 0, k));
+        constexpr auto threadidx_to_blk_idx_adaptor = make_single_stage_tensor_adaptor(
+            make_tuple(make_merge_transform(
+                make_tuple(1, mfma_instr.num_input_blks, mfma_instr.num_threads_per_blk))),
+            make_tuple(Sequence<0, 1, 2>{}),
+            make_tuple(Sequence<0>{}));
 
-            mfma_type.template run<MPerXdlops, NPerXdlops, c_offset>(
-                p_a_wave[Number<a_offset / mfma_type.k_base>{}],
-                p_b_wave[Number<b_offset / mfma_type.k_base>{}],
-                p_c_thread);
-        });
+        const auto blk_idx =
+            threadidx_to_blk_idx_adaptor.CalculateBottomIndex(make_multi_index(laneId));
+
+        const auto blk_id = blk_idx[I1];
+        const auto blk_td = blk_idx[I2];
+
+        return make_tuple(blk_id, blk_td);
     }
 
-    __device__ static CIndex GetBeginOfThreadBlk(index_t xdlops_i, index_t blk_i)
+    __host__ __device__ static auto CalculateAThreadOriginDataIndex()
     {
-        const index_t laneId = get_thread_local_1d_id() % mfma_type.wave_size;
-        const index_t blk_id = laneId / mfma_type.num_threads_blk;
-        const index_t blk_td = laneId % mfma_type.num_threads_blk;
+        const auto laneId  = GetLaneId();
+        const auto blk_idx = GetBlkIdx();
 
-        index_t n_offset = blk_i * mfma_type.n + blk_td;
-        index_t m_offset = xdlops_i * mfma_type.m + blk_id * mfma_type.group_size;
+        const auto blk_id = blk_idx[I0];
+        const auto blk_td = blk_idx[I1];
 
-        return CIndex{m_offset, n_offset};
+        if constexpr(mfma_instr.is_k_reduction)
+        {
+            return make_tuple(blk_id, blk_td);
+        }
+        else
+        {
+            return make_tuple(0, laneId);
+        }
     }
 
-    static constexpr index_t MRepeats   = GetXdlopsInfo().MRepeats;
-    static constexpr index_t NRepeats   = GetXdlopsInfo().NRepeats;
-    static constexpr index_t MPerXdlops = GetXdlopsInfo().MPerXdlops;
-    static constexpr index_t NPerXdlops = GetXdlopsInfo().NPerXdlops;
+    __host__ __device__ static auto CalculateBThreadOriginDataIndex()
+    {
+        const auto laneId  = GetLaneId();
+        const auto blk_idx = GetBlkIdx();
 
-    static constexpr bool IsKReduction  = GetXdlopsInfo().IsKReduction();
-    static constexpr bool IsABroadcast  = GetXdlopsInfo().IsABroadcast();
-    static constexpr index_t KPerXdlops = GetXdlopsInfo().GetKPerXdlops();
+        const auto blk_id = blk_idx[I0];
+        const auto blk_td = blk_idx[I1];
 
-    static constexpr auto GetBlkId(const index_t lane_id)
+        if constexpr(mfma_instr.is_k_reduction)
         {
-        return lane_id / mfma_type.num_threads_blk;
+            return make_tuple(blk_id, blk_td);
         }
-
-    static constexpr auto GetBlkTd(const index_t lane_id)
+        else
         {
-        return lane_id % mfma_type.num_threads_blk;
+            return make_tuple(0, laneId);
+        }
     }
 
-    static constexpr auto mfma_type = GetXdlopsInfo().mfma_type;
-
-    struct CLayout
+    __device__ static CIndex GetBeginOfThreadBlk(index_t xdlops_i, index_t blk_i)
     {
-        __host__ __device__ static constexpr index_t M1() { return mfma_type.num_groups_blk; }
-        __host__ __device__ static constexpr index_t M0() { return mfma_type.group_size; }
-        __host__ __device__ static constexpr index_t N1() { return mfma_type.num_input_blks; }
-        __host__ __device__ static constexpr index_t N0() { return mfma_type.num_threads_blk; }
+        const auto blk_idx = GetBlkIdx();
 
-        __device__ static constexpr index_t GetBlkSize() { return mfma_type.num_regs_blk; }
+        const auto blk_id = blk_idx[I0];
+        const auto blk_td = blk_idx[I1];
 
-        __device__ static constexpr index_t GetNumBlks() { return mfma_type.num_output_blks; }
+        index_t n_offset = blk_i * mfma_instr.n_per_blk + blk_td;
+        index_t m_offset = xdlops_i * mfma_instr.m_per_blk + blk_id * mfma_instr.group_size;
 
-        __device__ static constexpr index_t GetNumXdlops()
-        {
-            return MPerXdlops * NPerXdlops /
-                   (mfma_type.m * mfma_type.n * mfma_type.num_output_blks);
+        return CIndex{m_offset, n_offset};
     }
-    };
 
-    __host__ __device__ static constexpr auto GetCLayout() { return CLayout{}; }
+    static constexpr auto mfma = MfmaSelector<base_type, MPerXdlops, NPerXdlops>{};
+
+    static constexpr auto mfma_instr = mfma.selected_mfma;
+
+    static constexpr auto KPerXdlops = mfma.GetKPerXdlops();
+    static constexpr auto KPerThread = mfma.GetKPerThread();
+
+    __host__ __device__ static constexpr auto GetCM0M1M2NThreadBlkLengths()
+    {
+        return make_tuple(
+            Number<mfma_instr.num_groups_per_blk>{}, I1, Number<mfma_instr.group_size>{}, I1);
+    }
 };
 
 } // namespace ck

composable_kernel/include/utility/amd_buffer_addressing.hpp

@@ -202,6 +202,22 @@ llvm_amdgcn_raw_buffer_store_fp32x4(float4_t vdata,
                                     index_t voffset,
                                     index_t soffset,
                                     index_t glc_slc) __asm("llvm.amdgcn.raw.buffer.store.v4f32");
+// atomic add
+// int
+__device__ int32_t llvm_amdgcn_raw_buffer_atomic_add_i32(
+    int32_t vdata,
+    int32x4_t rsrc,
+    index_t voffset,
+    index_t soffset,
+    index_t glc_slc) __asm("llvm.amdgcn.raw.buffer.atomic.add.i32");
+
+// float
+__device__ float llvm_amdgcn_raw_buffer_atomic_add_fp32(
+    float vdata,
+    int32x4_t rsrc,
+    index_t voffset,
+    index_t soffset,
+    index_t glc_slc) __asm("llvm.amdgcn.raw.buffer.atomic.fadd.f32");
 
 template <typename T, index_t N>
 __device__ typename vector_type<T, N>::type amd_buffer_load_impl(int32x4_t src_wave_buffer_resource,
@@ -624,8 +640,130 @@ __device__ void amd_buffer_store_impl(const typename vector_type<T, N>::type src
     }
 }
 
+template <typename T, index_t N>
+__device__ void amd_buffer_atomic_add_impl(const typename vector_type<T, N>::type src_thread_data,
+                                           int32x4_t dst_wave_buffer_resource,
+                                           index_t dst_thread_addr_offset,
+                                           index_t dst_wave_addr_offset)
+{
+    static_assert((is_same<T, float>::value && (N == 1 || N == 2 || N == 4)) ||
+                      (is_same<T, int32_t>::value && (N == 1 || N == 2 || N == 4)),
+                  "wrong! not implemented");
+
+    if constexpr(is_same<T, float>::value)
+    {
+        if constexpr(N == 1)
+        {
+            llvm_amdgcn_raw_buffer_atomic_add_fp32(src_thread_data,
+                                                   dst_wave_buffer_resource,
+                                                   dst_thread_addr_offset,
+                                                   dst_wave_addr_offset,
+                                                   0);
+        }
+        else if constexpr(N == 2)
+        {
+            vector_type<float, 2> tmp{src_thread_data};
+
+            llvm_amdgcn_raw_buffer_atomic_add_fp32(tmp.AsType<float>()[Number<0>{}],
+                                                   dst_wave_buffer_resource,
+                                                   dst_thread_addr_offset,
+                                                   dst_wave_addr_offset,
+                                                   0);
+
+            llvm_amdgcn_raw_buffer_atomic_add_fp32(tmp.AsType<float>()[Number<1>{}],
+                                                   dst_wave_buffer_resource,
+                                                   dst_thread_addr_offset,
+                                                   dst_wave_addr_offset + sizeof(float),
+                                                   0);
+        }
+        else if constexpr(N == 4)
+        {
+            vector_type<float, 4> tmp{src_thread_data};
+
+            llvm_amdgcn_raw_buffer_atomic_add_fp32(tmp.AsType<float>()[Number<0>{}],
+                                                   dst_wave_buffer_resource,
+                                                   dst_thread_addr_offset,
+                                                   dst_wave_addr_offset,
+                                                   0);
+
+            llvm_amdgcn_raw_buffer_atomic_add_fp32(tmp.AsType<float>()[Number<1>{}],
+                                                   dst_wave_buffer_resource,
+                                                   dst_thread_addr_offset,
+                                                   dst_wave_addr_offset + sizeof(float),
+                                                   0);
+
+            llvm_amdgcn_raw_buffer_atomic_add_fp32(tmp.AsType<float>()[Number<2>{}],
+                                                   dst_wave_buffer_resource,
+                                                   dst_thread_addr_offset,
+                                                   dst_wave_addr_offset + 2 * sizeof(float),
+                                                   0);
+
+            llvm_amdgcn_raw_buffer_atomic_add_fp32(tmp.AsType<float>()[Number<3>{}],
+                                                   dst_wave_buffer_resource,
+                                                   dst_thread_addr_offset,
+                                                   dst_wave_addr_offset + 3 * sizeof(float),
+                                                   0);
+        }
+    }
+    else if constexpr(is_same<T, int32_t>::value)
+    {
+        if constexpr(N == 1)
+        {
+            llvm_amdgcn_raw_buffer_atomic_add_i32(src_thread_data,
+                                                  dst_wave_buffer_resource,
+                                                  dst_thread_addr_offset,
+                                                  dst_wave_addr_offset,
+                                                  0);
+        }
+        else if constexpr(N == 2)
+        {
+            vector_type<int32_t, 2> tmp{src_thread_data};
+
+            llvm_amdgcn_raw_buffer_atomic_add_i32(tmp.AsType<int32_t>()[Number<0>{}],
+                                                  dst_wave_buffer_resource,
+                                                  dst_thread_addr_offset,
+                                                  dst_wave_addr_offset,
+                                                  0);
+
+            llvm_amdgcn_raw_buffer_atomic_add_i32(tmp.AsType<int32_t>()[Number<1>{}],
+                                                  dst_wave_buffer_resource,
+                                                  dst_thread_addr_offset,
+                                                  dst_wave_addr_offset + sizeof(int32_t),
+                                                  0);
+        }
+        else if constexpr(N == 4)
+        {
+            vector_type<int32_t, 4> tmp{src_thread_data};
+
+            llvm_amdgcn_raw_buffer_atomic_add_i32(tmp.AsType<int32_t>()[Number<0>{}],
+                                                  dst_wave_buffer_resource,
+                                                  dst_thread_addr_offset,
+                                                  dst_wave_addr_offset,
+                                                  0);
+
+            llvm_amdgcn_raw_buffer_atomic_add_i32(tmp.AsType<int32_t>()[Number<1>{}],
+                                                  dst_wave_buffer_resource,
+                                                  dst_thread_addr_offset,
+                                                  dst_wave_addr_offset + sizeof(int32_t),
+                                                  0);
+
+            llvm_amdgcn_raw_buffer_atomic_add_i32(tmp.AsType<int32_t>()[Number<2>{}],
+                                                  dst_wave_buffer_resource,
+                                                  dst_thread_addr_offset,
+                                                  dst_wave_addr_offset + 2 * sizeof(int32_t),
+                                                  0);
+
+            llvm_amdgcn_raw_buffer_atomic_add_i32(tmp.AsType<int32_t>()[Number<3>{}],
+                                                  dst_wave_buffer_resource,
+                                                  dst_thread_addr_offset,
+                                                  dst_wave_addr_offset + 3 * sizeof(int32_t),
+                                                  0);
+        }
+    }
+}
+
 // buffer_load requires:
-//   1) p_src_wave must be in global memory space
+//   1) p_src_wave must point to global memory space
 //   2) p_src_wave must be a wavewise pointer.
 // It is user's responsibility to make sure that is true.
 template <typename T, index_t N>
@@ -659,7 +797,7 @@ amd_buffer_load_invalid_element_return_return_zero(const T* p_src_wave,
 }
 
 // buffer_load requires:
-//   1) p_src_wave must be in global memory space
+//   1) p_src_wave must point to global memory space
 //   2) p_src_wave must be a wavewise pointer.
 // It is user's responsibility to make sure that is true.
 template <typename T, index_t N>
@@ -687,8 +825,8 @@ amd_buffer_load_invalid_element_return_customized_value(const T* p_src_wave,
 }
 
 // buffer_store requires:
-//   1) p_dst_wave must be global memory
-//   2) p_dst_wave to be a wavewise pointer.
+//   1) p_dst_wave must point to global memory
+//   2) p_dst_wave must be a wavewise pointer.
 // It is user's responsibility to make sure that is true.
 template <typename T, index_t N>
 __device__ void amd_buffer_store(const typename vector_type_maker<T, N>::type::type src_thread_data,
@@ -720,5 +858,40 @@ __device__ void amd_buffer_store(const typename vector_type_maker<T, N>::type::t
 #endif
 }
 
+// buffer_atomic_add requires:
+//   1) p_dst_wave must point to global memory
+//   2) p_dst_wave must be a wavewise pointer.
+// It is user's responsibility to make sure that is true.
+template <typename T, index_t N>
+__device__ void
+amd_buffer_atomic_add(const typename vector_type_maker<T, N>::type::type src_thread_data,
+                      T* p_dst_wave,
+                      const index_t dst_thread_element_offset,
+                      const bool dst_thread_element_valid,
+                      const index_t dst_element_space_size)
+{
+    const int32x4_t dst_wave_buffer_resource =
+        make_wave_buffer_resource(p_dst_wave, dst_element_space_size);
+
+    index_t dst_thread_addr_offset = dst_thread_element_offset * sizeof(T);
+
+    using vector_t                = typename vector_type_maker<T, N>::type::type;
+    using scalar_t                = typename scalar_type<vector_t>::type;
+    constexpr index_t vector_size = scalar_type<vector_t>::vector_size;
+
+#if CK_EXPERIMENTAL_USE_BUFFER_ATOMIC_ADD_OOB_CHECK_OFFSET_TRICK
+    uint32_t dst_addr_shift = dst_thread_element_valid ? 0 : 0x7fffffff;
+
+    amd_buffer_atomic_add_impl<scalar_t, vector_size>(
+        src_thread_data, dst_wave_buffer_resource, dst_addr_shift + dst_thread_addr_offset, 0);
+#else
+    if(dst_thread_element_valid)
+    {
+        amd_buffer_atomic_add_impl<scalar_t, vector_size>(
+            src_thread_data, dst_wave_buffer_resource, dst_thread_addr_offset, 0);
+    }
+#endif
+}
+
 } // namespace ck
 #endif

composable_kernel/include/utility/array.hpp

@@ -48,7 +48,7 @@ struct Array<TData, 0>
 template <typename X, typename... Xs>
 __host__ __device__ constexpr auto make_array(X&& x, Xs&&... xs)
 {
-    using data_type = remove_cv_t<remove_reference_t<X>>;
+    using data_type = remove_cvref_t<X>;
     return Array<data_type, sizeof...(Xs) + 1>{{std::forward<X>(x), std::forward<Xs>(xs)...}};
 }
 

composable_kernel/include/utility/config.hpp

@@ -85,8 +85,8 @@
 #define CK_EXPERIMENTAL_USE_BUFFER_STORE_OOB_CHECK_OFFSET_TRICK 1
 #endif
 
-#ifndef CK_EXPERIMENTAL_USE_BUFFER_ATOMIC_OOB_CHECK_OFFSET_TRICK
-#define CK_EXPERIMENTAL_USE_BUFFER_ATOMIC_OOB_CHECK_OFFSET_TRICK 1
+#ifndef CK_EXPERIMENTAL_USE_BUFFER_ATOMIC_ADD_OOB_CHECK_OFFSET_TRICK
+#define CK_EXPERIMENTAL_USE_BUFFER_ATOMIC_ADD_OOB_CHECK_OFFSET_TRICK 1
 #endif
 
 // pass tensor descriptor by value or void*

composable_kernel/include/utility/dynamic_buffer.hpp

@@ -43,18 +43,15 @@ struct DynamicBuffer
     __host__ __device__ constexpr T& operator()(index_t i) { return p_data_[i]; }
 
     template <typename X,
-              typename enable_if<
-                  is_same<typename scalar_type<remove_cv_t<remove_reference_t<X>>>::type,
-                          typename scalar_type<remove_cv_t<remove_reference_t<T>>>::type>::value,
+              typename enable_if<is_same<typename scalar_type<remove_cvref_t<X>>::type,
+                                         typename scalar_type<remove_cvref_t<T>>::type>::value,
                                  bool>::type = false>
     __host__ __device__ constexpr auto Get(index_t i, bool is_valid_element) const
     {
         // X contains multiple T
-        constexpr index_t scalar_per_t_vector =
-            scalar_type<remove_cv_t<remove_reference_t<T>>>::vector_size;
+        constexpr index_t scalar_per_t_vector = scalar_type<remove_cvref_t<T>>::vector_size;
 
-        constexpr index_t scalar_per_x_vector =
-            scalar_type<remove_cv_t<remove_reference_t<X>>>::vector_size;
+        constexpr index_t scalar_per_x_vector = scalar_type<remove_cvref_t<X>>::vector_size;
 
         static_assert(scalar_per_x_vector % scalar_per_t_vector == 0,
                       "wrong! X need to be multiple T");
@@ -71,14 +68,13 @@ struct DynamicBuffer
 
             if constexpr(InvalidElementUseNumericalZeroValue)
             {
-                return amd_buffer_load_invalid_element_return_return_zero<
-                    remove_cv_t<remove_reference_t<T>>,
-                    t_per_x>(p_data_, i, is_valid_element, element_space_size_);
+                return amd_buffer_load_invalid_element_return_return_zero<remove_cvref_t<T>,
+                                                                          t_per_x>(
+                    p_data_, i, is_valid_element, element_space_size_);
             }
             else
             {
-                return amd_buffer_load_invalid_element_return_customized_value<
-                    remove_cv_t<remove_reference_t<T>>,
+                return amd_buffer_load_invalid_element_return_customized_value<remove_cvref_t<T>,
                                                                                t_per_x>(
                     p_data_, i, is_valid_element, element_space_size_, invalid_element_value_);
             }
@@ -98,18 +94,15 @@ struct DynamicBuffer
     }
 
     template <typename X,
-              typename enable_if<
-                  is_same<typename scalar_type<remove_cv_t<remove_reference_t<X>>>::type,
-                          typename scalar_type<remove_cv_t<remove_reference_t<T>>>::type>::value,
+              typename enable_if<is_same<typename scalar_type<remove_cvref_t<X>>::type,
+                                         typename scalar_type<remove_cvref_t<T>>::type>::value,
                                  bool>::type = false>
     __host__ __device__ void Set(index_t i, bool is_valid_element, const X& x)
     {
         // X contains multiple T
-        constexpr index_t scalar_per_t_vector =
-            scalar_type<remove_cv_t<remove_reference_t<T>>>::vector_size;
+        constexpr index_t scalar_per_t_vector = scalar_type<remove_cvref_t<T>>::vector_size;
 
-        constexpr index_t scalar_per_x_vector =
-            scalar_type<remove_cv_t<remove_reference_t<X>>>::vector_size;
+        constexpr index_t scalar_per_x_vector = scalar_type<remove_cvref_t<X>>::vector_size;
 
         static_assert(scalar_per_x_vector % scalar_per_t_vector == 0,
                       "wrong! X need to be multiple T");
@@ -119,7 +112,7 @@ struct DynamicBuffer
 #if CK_USE_AMD_BUFFER_ADDRESSING
             constexpr index_t t_per_x = scalar_per_x_vector / scalar_per_t_vector;
 
-            amd_buffer_store<remove_cv_t<remove_reference_t<T>>, t_per_x>(
+            amd_buffer_store<remove_cvref_t<T>, t_per_x>(
                 x, p_data_, i, is_valid_element, element_space_size_);
 #else
             if(is_valid_element)
@@ -140,70 +133,65 @@ struct DynamicBuffer
                 // ISA, so I try to let compiler emit IR "store<i32, 4>" which would be lower to
                 // ds_write_b128
                 // TODO: remove this after compiler fix
-                if constexpr(is_same<typename scalar_type<remove_cv_t<remove_reference_t<T>>>::type,
-                                     int8_t>::value)
-                {
-                    static_assert(
-                        (is_same<remove_cv_t<remove_reference_t<T>>, int8_t>::value &&
-                         is_same<remove_cv_t<remove_reference_t<X>>, int8_t>::value) ||
-                            (is_same<remove_cv_t<remove_reference_t<T>>, int8_t>::value &&
-                             is_same<remove_cv_t<remove_reference_t<X>>, int8x2_t>::value) ||
-                            (is_same<remove_cv_t<remove_reference_t<T>>, int8_t>::value &&
-                             is_same<remove_cv_t<remove_reference_t<X>>, int8x4_t>::value) ||
-                            (is_same<remove_cv_t<remove_reference_t<T>>, int8x4_t>::value &&
-                             is_same<remove_cv_t<remove_reference_t<X>>, int8x4_t>::value) ||
-                            (is_same<remove_cv_t<remove_reference_t<T>>, int8x8_t>::value &&
-                             is_same<remove_cv_t<remove_reference_t<X>>, int8x8_t>::value) ||
-                            (is_same<remove_cv_t<remove_reference_t<T>>, int8x16_t>::value &&
-                             is_same<remove_cv_t<remove_reference_t<X>>, int8x16_t>::value),
+                if constexpr(is_same<typename scalar_type<remove_cvref_t<T>>::type, int8_t>::value)
+                {
+                    static_assert((is_same<remove_cvref_t<T>, int8_t>::value &&
+                                   is_same<remove_cvref_t<X>, int8_t>::value) ||
+                                      (is_same<remove_cvref_t<T>, int8_t>::value &&
+                                       is_same<remove_cvref_t<X>, int8x2_t>::value) ||
+                                      (is_same<remove_cvref_t<T>, int8_t>::value &&
+                                       is_same<remove_cvref_t<X>, int8x4_t>::value) ||
+                                      (is_same<remove_cvref_t<T>, int8x4_t>::value &&
+                                       is_same<remove_cvref_t<X>, int8x4_t>::value) ||
+                                      (is_same<remove_cvref_t<T>, int8x8_t>::value &&
+                                       is_same<remove_cvref_t<X>, int8x8_t>::value) ||
+                                      (is_same<remove_cvref_t<T>, int8x16_t>::value &&
+                                       is_same<remove_cvref_t<X>, int8x16_t>::value),
                                   "wrong! not implemented for this combination, please add "
                                   "implementation");
 
-                    if constexpr(is_same<remove_cv_t<remove_reference_t<T>>, int8_t>::value &&
-                                 is_same<remove_cv_t<remove_reference_t<X>>, int8_t>::value)
+                    if constexpr(is_same<remove_cvref_t<T>, int8_t>::value &&
+                                 is_same<remove_cvref_t<X>, int8_t>::value)
                     {
                         // HACK: cast pointer of x is bad
                         // TODO: remove this after compiler fix
                         *c_style_pointer_cast<int8_t*>(&p_data_[i]) =
                             *c_style_pointer_cast<const int8_t*>(&x);
                     }
-                    else if constexpr(is_same<remove_cv_t<remove_reference_t<T>>, int8_t>::value &&
-                                      is_same<remove_cv_t<remove_reference_t<X>>, int8x2_t>::value)
+                    else if constexpr(is_same<remove_cvref_t<T>, int8_t>::value &&
+                                      is_same<remove_cvref_t<X>, int8x2_t>::value)
                     {
                         // HACK: cast pointer of x is bad
                         // TODO: remove this after compiler fix
                         *c_style_pointer_cast<int16_t*>(&p_data_[i]) =
                             *c_style_pointer_cast<const int16_t*>(&x);
                     }
-                    else if constexpr(is_same<remove_cv_t<remove_reference_t<T>>, int8_t>::value &&
-                                      is_same<remove_cv_t<remove_reference_t<X>>, int8x4_t>::value)
+                    else if constexpr(is_same<remove_cvref_t<T>, int8_t>::value &&
+                                      is_same<remove_cvref_t<X>, int8x4_t>::value)
                     {
                         // HACK: cast pointer of x is bad
                         // TODO: remove this after compiler fix
                         *c_style_pointer_cast<int32_t*>(&p_data_[i]) =
                             *c_style_pointer_cast<const int32_t*>(&x);
                     }
-                    else if constexpr(is_same<remove_cv_t<remove_reference_t<T>>,
-                                              int8x4_t>::value &&
-                                      is_same<remove_cv_t<remove_reference_t<X>>, int8x4_t>::value)
+                    else if constexpr(is_same<remove_cvref_t<T>, int8x4_t>::value &&
+                                      is_same<remove_cvref_t<X>, int8x4_t>::value)
                     {
                         // HACK: cast pointer of x is bad
                         // TODO: remove this after compiler fix
                         *c_style_pointer_cast<int32_t*>(&p_data_[i]) =
                             *c_style_pointer_cast<const int32_t*>(&x);
                     }
-                    else if constexpr(is_same<remove_cv_t<remove_reference_t<T>>,
-                                              int8x8_t>::value &&
-                                      is_same<remove_cv_t<remove_reference_t<X>>, int8x8_t>::value)
+                    else if constexpr(is_same<remove_cvref_t<T>, int8x8_t>::value &&
+                                      is_same<remove_cvref_t<X>, int8x8_t>::value)
                     {
                         // HACK: cast pointer of x is bad
                         // TODO: remove this after compiler fix
                         *c_style_pointer_cast<int32x2_t*>(&p_data_[i]) =
                             *c_style_pointer_cast<const int32x2_t*>(&x);
                     }
-                    else if constexpr(is_same<remove_cv_t<remove_reference_t<T>>,
-                                              int8x16_t>::value &&
-                                      is_same<remove_cv_t<remove_reference_t<X>>, int8x16_t>::value)
+                    else if constexpr(is_same<remove_cvref_t<T>, int8x16_t>::value &&
+                                      is_same<remove_cvref_t<X>, int8x16_t>::value)
                     {
                         // HACK: cast pointer of x is bad
                         // TODO: remove this after compiler fix
@@ -227,6 +215,35 @@ struct DynamicBuffer
         }
     }
 
+    template <typename X,
+              typename enable_if<is_same<typename scalar_type<remove_cvref_t<X>>::type,
+                                         typename scalar_type<remove_cvref_t<T>>::type>::value,
+                                 bool>::type = false>
+    __host__ __device__ void AtomicAdd(index_t i, bool is_valid_element, const X& x)
+    {
+        // X contains multiple T
+        constexpr index_t scalar_per_t_vector = scalar_type<remove_cvref_t<T>>::vector_size;
+
+        constexpr index_t scalar_per_x_vector = scalar_type<remove_cvref_t<X>>::vector_size;
+
+        static_assert(scalar_per_x_vector % scalar_per_t_vector == 0,
+                      "wrong! X need to be multiple T");
+
+        static_assert(GetAddressSpace() == AddressSpaceEnum_t::Global, "only support global mem");
+
+#if CK_USE_AMD_BUFFER_ADDRESSING
+        constexpr index_t t_per_x = scalar_per_x_vector / scalar_per_t_vector;
+
+        amd_buffer_atomic_add<remove_cvref_t<T>, t_per_x>(
+            x, p_data_, i, is_valid_element, element_space_size_);
+#else
+        if(is_valid_element)
+        {
+            atomicAdd(&p_data_[i], x);
+        }
+#endif
+    }
+
     __host__ __device__ static constexpr bool IsStaticBuffer() { return false; }
 
     __host__ __device__ static constexpr bool IsDynamicBuffer() { return true; }

composable_kernel/include/utility/magic_division.hpp

@@ -114,12 +114,11 @@ struct MagicDivision
     __host__ __device__ static constexpr uint32_t
     DoMagicDivision(uint32_t dividend, uint32_t multiplier, uint32_t shift)
     {
-        uint32_t tmp = (uint64_t(dividend) * uint64_t(multiplier)) >> 32;
+        uint32_t tmp = __umulhi(dividend, multiplier);
         return (tmp + dividend) >> shift;
     }
 
-#if 1 // debug
-    // HACK: magic division for int32_t
+    // magic division for int32_t
     // HACK: use dividend_i32 as if it's uint32_t, dividend_i32 need to be
     // non-negative for result to be correct
     // TODO: figure out how to do magic number divison for int32_t as dividended
@@ -127,27 +126,9 @@ struct MagicDivision
     DoMagicDivision(int32_t dividend_i32, uint32_t multiplier, uint32_t shift)
     {
         uint32_t dividend_u32 = as_type<uint32_t>(dividend_i32);
-        uint32_t tmp =
-            (static_cast<uint64_t>(dividend_u32) * static_cast<uint64_t>(multiplier)) >> 32;
+        uint32_t tmp          = __umulhi(dividend_u32, multiplier);
         return (tmp + dividend_u32) >> shift;
     }
-#else
-    // the inline ASM is producing wrong result
-    __host__ __device__ static int32_t
-    DoMagicDivision(int32_t dividend_i32, uint32_t multiplier, uint32_t shift)
-    {
-        uint32_t r;
-        asm volatile("\n \
-                v_mul_hi_u32 %0, %1, %2 \n \
-                v_add_u32_e32 %0, %1, %0 \n \
-                v_lshrrev_b32_e32 %0, %3, %0 \n \
-                "
-                     : "=v"(r)
-                     : "v"(as_type<uint32_t>(dividend_i32)), "s"(multiplier), "s"(shift));
-
-        return as_type<int32_t>(r);
-    }
-#endif
 };
 
 } // namespace ck

composable_kernel/include/utility/tuple.hpp

@@ -159,7 +159,7 @@ struct Tuple : detail::TupleImpl<typename arithmetic_sequence_gen<0, sizeof...(X
 template <typename... Xs>
 __host__ __device__ constexpr auto make_tuple(Xs&&... xs)
 {
-    return Tuple<remove_cv_t<remove_reference_t<Xs>>...>(std::forward<Xs>(xs)...);
+    return Tuple<remove_cvref_t<Xs>...>(std::forward<Xs>(xs)...);
 }
 
 } // namespace ck