mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-04-19 14:29:05 +00:00
simplify karg in device/grid of split-k op (#644)
* simplify karg in device/grid split-k op * fix mk_kn_mn instances * add more instances * use name from tensor layout
This commit is contained in:
carlushuang
@@ -73,157 +73,18 @@ struct DeviceGemmXdlSplitKCShuffle : public DeviceGemmSplitK<ALayout,
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static constexpr auto I2 = Number<2>{};
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static constexpr auto I3 = Number<3>{};
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static constexpr auto K1Number = Number<K1>{};
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static auto
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MakeAGridDescriptor_KBatch_K0_M_K1(index_t M, index_t K, index_t StrideA, int KBatch, int KPad)
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{
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assert(KPad % (K1 * KBatch) == 0);
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const index_t K0 = KPad / (K1 * KBatch);
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const auto a_grid_desc_m_k = [&]() {
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if constexpr(is_same<tensor_layout::gemm::RowMajor, ALayout>::value)
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{
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return make_naive_tensor_descriptor(make_tuple(M, K), make_tuple(StrideA, I1));
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}
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else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, ALayout>::value)
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{
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return make_naive_tensor_descriptor(make_tuple(M, K), make_tuple(I1, StrideA));
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}
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}();
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const auto a_grid_desc_m_kpad = transform_tensor_descriptor(
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a_grid_desc_m_k,
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make_tuple(make_pass_through_transform(M), make_right_pad_transform(K, KPad - K)),
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make_tuple(Sequence<0>{}, Sequence<1>{}),
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make_tuple(Sequence<0>{}, Sequence<1>{}));
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if constexpr(GemmSpec == GemmSpecialization::MNPadding)
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{
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const auto PadM = (MPerBlock - M % MPerBlock) % MPerBlock;
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return transform_tensor_descriptor(
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a_grid_desc_m_kpad,
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make_tuple(make_unmerge_transform(make_tuple(KBatch, K0, K1Number)),
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make_right_pad_transform(M, PadM)),
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make_tuple(Sequence<1>{}, Sequence<0>{}),
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make_tuple(Sequence<0, 1, 3>{}, Sequence<2>{}));
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}
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else
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{
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return transform_tensor_descriptor(
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a_grid_desc_m_kpad,
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make_tuple(make_unmerge_transform(make_tuple(KBatch, K0, K1Number)),
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make_pass_through_transform(M)),
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make_tuple(Sequence<1>{}, Sequence<0>{}),
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make_tuple(Sequence<0, 1, 3>{}, Sequence<2>{}));
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}
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}
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static auto
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MakeBGridDescriptor_KBatch_K0_N_K1(index_t K, index_t N, index_t StrideB, int KBatch, int KPad)
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{
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assert(KPad % (K1 * KBatch) == 0);
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const index_t K0 = KPad / (K1 * KBatch);
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const auto b_grid_desc_k_n = [&]() {
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if constexpr(is_same<tensor_layout::gemm::RowMajor, BLayout>::value)
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{
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return make_naive_tensor_descriptor(make_tuple(K, N), make_tuple(StrideB, I1));
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}
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else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, BLayout>::value)
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{
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return make_naive_tensor_descriptor(make_tuple(K, N), make_tuple(I1, StrideB));
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}
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}();
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const auto b_grid_desc_kpad_n = transform_tensor_descriptor(
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b_grid_desc_k_n,
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make_tuple(make_right_pad_transform(K, KPad - K), make_pass_through_transform(N)),
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make_tuple(Sequence<0>{}, Sequence<1>{}),
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make_tuple(Sequence<0>{}, Sequence<1>{}));
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if constexpr(GemmSpec == GemmSpecialization::MNPadding)
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{
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const auto PadN = (NPerBlock - N % NPerBlock) % NPerBlock;
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return transform_tensor_descriptor(
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b_grid_desc_kpad_n,
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make_tuple(make_unmerge_transform(make_tuple(KBatch, K0, K1Number)),
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make_right_pad_transform(N, PadN)),
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make_tuple(Sequence<0>{}, Sequence<1>{}),
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make_tuple(Sequence<0, 1, 3>{}, Sequence<2>{}));
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}
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else
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{
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return transform_tensor_descriptor(
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b_grid_desc_kpad_n,
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make_tuple(make_unmerge_transform(make_tuple(KBatch, K0, K1Number)),
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make_pass_through_transform(N)),
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make_tuple(Sequence<0>{}, Sequence<1>{}),
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make_tuple(Sequence<0, 1, 3>{}, Sequence<2>{}));
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}
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}
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static auto MakeCGridDescriptor_M_N(index_t M, index_t N, index_t StrideC)
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{
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const auto c_grid_desc_m_n = [&]() {
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if constexpr(is_same<tensor_layout::gemm::RowMajor, CLayout>::value)
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{
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return make_naive_tensor_descriptor(make_tuple(M, N), make_tuple(StrideC, I1));
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}
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else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, CLayout>::value)
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{
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return make_naive_tensor_descriptor(make_tuple(M, N), make_tuple(I1, StrideC));
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}
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}();
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if constexpr(GemmSpec == GemmSpecialization::MNPadding)
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{
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const auto PadM = (MPerBlock - M % MPerBlock) % MPerBlock;
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const auto PadN = (NPerBlock - N % NPerBlock) % NPerBlock;
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return transform_tensor_descriptor(
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c_grid_desc_m_n,
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make_tuple(make_right_pad_transform(M, PadM), make_right_pad_transform(N, PadN)),
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make_tuple(Sequence<0>{}, Sequence<1>{}),
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make_tuple(Sequence<0>{}, Sequence<1>{}));
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}
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else
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{
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return transform_tensor_descriptor(
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c_grid_desc_m_n,
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make_tuple(make_pass_through_transform(M), make_pass_through_transform(N)),
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make_tuple(Sequence<0>{}, Sequence<1>{}),
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make_tuple(Sequence<0>{}, Sequence<1>{}));
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}
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}
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static auto GetKPad(index_t K, index_t KBatch)
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{
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const index_t K0 = math::integer_divide_ceil(K, K1 * K0PerBlock * KBatch) * K0PerBlock;
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const index_t KPad = KBatch * K0 * K1;
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return KPad;
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}
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using AGridDesc_K0_M_K1 = decltype(MakeAGridDescriptor_KBatch_K0_M_K1(1, 1, 1, 1, 1));
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using BGridDesc_K0_N_K1 = decltype(MakeBGridDescriptor_KBatch_K0_N_K1(1, 1, 1, 1, 1));
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using CGridDesc_M_N = decltype(MakeCGridDescriptor_M_N(1, 1, 1));
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// GridwiseGemm
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using GridwiseGemm = GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2<
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BlockSize,
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ADataType, // TODO: distinguish A/B datatype
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AccDataType,
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CDataType,
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InMemoryDataOperationEnum::Set,
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AGridDesc_K0_M_K1,
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BGridDesc_K0_N_K1,
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CGridDesc_M_N,
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ALayout,
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BLayout,
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CLayout,
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AElementwiseOperation,
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BElementwiseOperation,
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CElementwiseOperation,
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GemmSpec,
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MPerBlock,
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NPerBlock,
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K0PerBlock,
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@@ -253,236 +114,64 @@ struct DeviceGemmXdlSplitKCShuffle : public DeviceGemmSplitK<ALayout,
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CBlockTransferScalarPerVector_NWaveNPerXDL,
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CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock>;
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// GridwiseGemm
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using GridwiseGemmAtomicAdd = GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2<
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BlockSize,
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ADataType, // TODO: distinguish A/B datatype
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AccDataType,
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CDataType,
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InMemoryDataOperationEnum::AtomicAdd,
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AGridDesc_K0_M_K1,
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BGridDesc_K0_N_K1,
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CGridDesc_M_N,
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AElementwiseOperation,
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BElementwiseOperation,
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CElementwiseOperation,
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MPerBlock,
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NPerBlock,
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K0PerBlock,
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MPerXDL,
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NPerXDL,
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K1,
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MXdlPerWave,
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NXdlPerWave,
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ABlockTransferThreadClusterLengths_K0_M_K1,
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ABlockTransferThreadClusterArrangeOrder,
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ABlockTransferSrcAccessOrder,
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ABlockTransferSrcVectorDim,
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ABlockTransferSrcScalarPerVector,
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ABlockTransferDstScalarPerVector_K1,
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false, // AThreadTransferSrcResetCoordinateAfterRun,
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ABlockLdsAddExtraM,
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BBlockTransferThreadClusterLengths_K0_N_K1,
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BBlockTransferThreadClusterArrangeOrder,
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BBlockTransferSrcAccessOrder,
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BBlockTransferSrcVectorDim,
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BBlockTransferSrcScalarPerVector,
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BBlockTransferDstScalarPerVector_K1,
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false, // BThreadTransferSrcResetCoordinateAfterRun,
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BBlockLdsAddExtraN,
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CShuffleMRepeatPerShuffle,
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CShuffleNRepeatPerShuffle,
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CBlockTransferScalarPerVector_NWaveNPerXDL,
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CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock>;
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using CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock =
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decltype(GridwiseGemm::MakeCGridDesc_MBlock_MPerBlock_NBlock_NPerBlock(CGridDesc_M_N{}));
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using Block2CTileMap = typename GridwiseGemm::CBlockClusterAdaptor;
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// Argument
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struct Argument : public BaseArgument
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{
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Argument(const ADataType* p_a_grid,
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const BDataType* p_b_grid,
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CDataType* p_c_grid,
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index_t M,
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index_t N,
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index_t K,
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index_t StrideA,
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index_t StrideB,
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index_t StrideC,
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index_t M01,
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index_t N01,
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AElementwiseOperation a_element_op,
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BElementwiseOperation b_element_op,
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CElementwiseOperation c_element_op,
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index_t k_batch)
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: p_a_grid_{p_a_grid},
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p_b_grid_{p_b_grid},
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p_c_grid_{p_c_grid},
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a_grid_desc_kbatch_k0_m_k1_{},
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b_grid_desc_kbatch_k0_n_k1_{},
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c_grid_desc_m_n_{},
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c_grid_desc_mblock_mperblock_nblock_nperblock_{},
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block_2_ctile_map_{},
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M01_{M01},
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N01_{N01},
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a_element_op_{a_element_op},
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b_element_op_{b_element_op},
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c_element_op_{c_element_op},
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k_batch_{k_batch}
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{
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int KPad = DeviceGemmXdlSplitKCShuffle::GetKPad(K, k_batch_);
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a_grid_desc_kbatch_k0_m_k1_ =
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DeviceGemmXdlSplitKCShuffle::MakeAGridDescriptor_KBatch_K0_M_K1(
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M, K, StrideA, k_batch_, KPad);
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b_grid_desc_kbatch_k0_n_k1_ =
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DeviceGemmXdlSplitKCShuffle::MakeBGridDescriptor_KBatch_K0_N_K1(
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K, N, StrideB, k_batch_, KPad);
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c_grid_desc_m_n_ = DeviceGemmXdlSplitKCShuffle::MakeCGridDescriptor_M_N(M, N, StrideC);
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block_2_ctile_map_ =
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GridwiseGemm::MakeCBlockClusterAdaptor(c_grid_desc_m_n_, M01, N01, k_batch_);
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if(GridwiseGemm::CheckValidity(a_grid_desc_kbatch_k0_m_k1_,
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b_grid_desc_kbatch_k0_n_k1_,
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c_grid_desc_m_n_,
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block_2_ctile_map_))
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{
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c_grid_desc_mblock_mperblock_nblock_nperblock_ =
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GridwiseGemm::MakeCGridDesc_MBlock_MPerBlock_NBlock_NPerBlock(c_grid_desc_m_n_);
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}
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}
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// private:
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const ADataType* p_a_grid_;
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const BDataType* p_b_grid_;
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CDataType* p_c_grid_;
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AGridDesc_K0_M_K1 a_grid_desc_kbatch_k0_m_k1_;
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BGridDesc_K0_N_K1 b_grid_desc_kbatch_k0_n_k1_;
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CGridDesc_M_N c_grid_desc_m_n_;
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CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock c_grid_desc_mblock_mperblock_nblock_nperblock_;
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Block2CTileMap block_2_ctile_map_;
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index_t M01_;
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index_t N01_;
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AElementwiseOperation a_element_op_;
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BElementwiseOperation b_element_op_;
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CElementwiseOperation c_element_op_;
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index_t k_batch_;
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};
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using Argument = typename GridwiseGemm::Argument;
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// Invoker
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struct Invoker : public BaseInvoker
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{
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using Argument = DeviceGemmXdlSplitKCShuffle::Argument;
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void Print(const Argument& arg)
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{
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std::cout << "arg.a_grid_desc_kbatch_k0_m_k1_{"
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<< arg.a_grid_desc_kbatch_k0_m_k1_.GetLength(I0) << ", "
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<< arg.a_grid_desc_kbatch_k0_m_k1_.GetLength(I1) << ", "
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<< arg.a_grid_desc_kbatch_k0_m_k1_.GetLength(I2) << ", "
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<< arg.a_grid_desc_kbatch_k0_m_k1_.GetLength(I3) << "}" << std::endl;
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void Print(const Argument& karg) { karg.Print(); }
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std::cout << "arg.b_grid_desc_kbatch_k0_n_k1_{"
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<< arg.b_grid_desc_kbatch_k0_n_k1_.GetLength(I0) << ", "
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<< arg.b_grid_desc_kbatch_k0_n_k1_.GetLength(I1) << ", "
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<< arg.b_grid_desc_kbatch_k0_n_k1_.GetLength(I2) << ", "
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<< arg.b_grid_desc_kbatch_k0_n_k1_.GetLength(I3) << "}" << std::endl;
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std::cout << "arg.c_grid_desc_m_n_{ " << arg.c_grid_desc_m_n_.GetLength(I0) << ", "
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<< arg.c_grid_desc_m_n_.GetLength(I1) << "}" << std::endl;
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}
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float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
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float Run(const Argument& karg, const StreamConfig& stream_config = StreamConfig{})
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{
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if(stream_config.log_level_ > 0)
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{
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Print(arg);
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Print(karg);
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}
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const auto kbatch = arg.a_grid_desc_kbatch_k0_m_k1_.GetLength(I0);
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const auto kbatch = karg.k_batch;
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if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_kbatch_k0_m_k1_,
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arg.b_grid_desc_kbatch_k0_n_k1_,
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arg.c_grid_desc_m_n_,
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arg.block_2_ctile_map_))
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if(!GridwiseGemm::CheckValidity(karg))
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{
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throw std::runtime_error(
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"wrong! GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2 has invalid setting");
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"wrong! GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2 has invalid "
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"setting");
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}
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const index_t grid_size =
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arg.block_2_ctile_map_.CalculateGridSize(arg.c_grid_desc_m_n_);
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const auto K0 = arg.a_grid_desc_kbatch_k0_m_k1_.GetLength(I1);
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index_t gdx, gdy, gdz;
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std::tie(gdx, gdy, gdz) = GridwiseGemm::CalculateGridSize(karg);
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const auto K0 = karg.K0;
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const bool has_main_k0_block_loop = GridwiseGemm::CalculateHasMainK0BlockLoop(K0);
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float ave_time = 0;
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const auto Run = [&](const auto& kernel) {
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hipGetErrorString(hipMemset(
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arg.p_c_grid_,
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0,
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arg.c_grid_desc_mblock_mperblock_nblock_nperblock_.GetElementSpaceSize() *
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sizeof(CDataType)));
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if(kbatch > 1)
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hipGetErrorString(
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hipMemset(karg.p_c_grid, 0, karg.M * karg.N * sizeof(CDataType)));
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ave_time =
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launch_and_time_kernel(stream_config,
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kernel,
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dim3(grid_size),
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dim3(BlockSize),
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0,
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arg.p_a_grid_,
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arg.p_b_grid_,
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arg.p_c_grid_,
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arg.a_grid_desc_kbatch_k0_m_k1_,
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arg.b_grid_desc_kbatch_k0_n_k1_,
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arg.c_grid_desc_mblock_mperblock_nblock_nperblock_,
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arg.a_element_op_,
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arg.b_element_op_,
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arg.c_element_op_,
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arg.block_2_ctile_map_);
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ave_time = launch_and_time_kernel(
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stream_config, kernel, dim3(gdx, gdy, gdz), dim3(BlockSize), 0, karg);
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};
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if(has_main_k0_block_loop)
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{
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if(kbatch == 1)
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{
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const auto kernel = kernel_gemm_xdlops_v2r4r2<
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GridwiseGemm,
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ADataType, // TODO: distiguish A/B datatype
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CDataType,
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remove_reference_t<DeviceGemmXdlSplitKCShuffle::AGridDesc_K0_M_K1>,
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remove_reference_t<DeviceGemmXdlSplitKCShuffle::BGridDesc_K0_N_K1>,
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remove_reference_t<DeviceGemmXdlSplitKCShuffle::
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CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock>,
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AElementwiseOperation,
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BElementwiseOperation,
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CElementwiseOperation,
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remove_reference_t<DeviceGemmXdlSplitKCShuffle::Block2CTileMap>,
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true>;
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const auto kernel =
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kernel_gemm_xdlops_v2r4r2_simplified<GridwiseGemm,
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true,
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InMemoryDataOperationEnum::Set>;
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|
||||
Run(kernel);
|
||||
}
|
||||
else
|
||||
{
|
||||
const auto kernel = kernel_gemm_xdlops_v2r4r2<
|
||||
GridwiseGemmAtomicAdd,
|
||||
ADataType, // TODO: distiguish A/B datatype
|
||||
CDataType,
|
||||
remove_reference_t<DeviceGemmXdlSplitKCShuffle::AGridDesc_K0_M_K1>,
|
||||
remove_reference_t<DeviceGemmXdlSplitKCShuffle::BGridDesc_K0_N_K1>,
|
||||
remove_reference_t<DeviceGemmXdlSplitKCShuffle::
|
||||
CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock>,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation,
|
||||
remove_reference_t<DeviceGemmXdlSplitKCShuffle::Block2CTileMap>,
|
||||
true>;
|
||||
const auto kernel =
|
||||
kernel_gemm_xdlops_v2r4r2_simplified<GridwiseGemm,
|
||||
true,
|
||||
InMemoryDataOperationEnum::AtomicAdd>;
|
||||
|
||||
Run(kernel);
|
||||
}
|
||||
@@ -491,37 +180,19 @@ struct DeviceGemmXdlSplitKCShuffle : public DeviceGemmSplitK<ALayout,
|
||||
{
|
||||
if(kbatch == 1)
|
||||
{
|
||||
const auto kernel = kernel_gemm_xdlops_v2r4r2<
|
||||
GridwiseGemm,
|
||||
ADataType, // TODO: distiguish A/B datatype
|
||||
CDataType,
|
||||
remove_reference_t<DeviceGemmXdlSplitKCShuffle::AGridDesc_K0_M_K1>,
|
||||
remove_reference_t<DeviceGemmXdlSplitKCShuffle::BGridDesc_K0_N_K1>,
|
||||
remove_reference_t<DeviceGemmXdlSplitKCShuffle::
|
||||
CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock>,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation,
|
||||
remove_reference_t<DeviceGemmXdlSplitKCShuffle::Block2CTileMap>,
|
||||
false>;
|
||||
const auto kernel =
|
||||
kernel_gemm_xdlops_v2r4r2_simplified<GridwiseGemm,
|
||||
false,
|
||||
InMemoryDataOperationEnum::Set>;
|
||||
|
||||
Run(kernel);
|
||||
}
|
||||
else
|
||||
{
|
||||
const auto kernel = kernel_gemm_xdlops_v2r4r2<
|
||||
GridwiseGemmAtomicAdd,
|
||||
ADataType, // TODO: distiguish A/B datatype
|
||||
CDataType,
|
||||
remove_reference_t<DeviceGemmXdlSplitKCShuffle::AGridDesc_K0_M_K1>,
|
||||
remove_reference_t<DeviceGemmXdlSplitKCShuffle::BGridDesc_K0_N_K1>,
|
||||
remove_reference_t<DeviceGemmXdlSplitKCShuffle::
|
||||
CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock>,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation,
|
||||
remove_reference_t<DeviceGemmXdlSplitKCShuffle::Block2CTileMap>,
|
||||
false>;
|
||||
const auto kernel =
|
||||
kernel_gemm_xdlops_v2r4r2_simplified<GridwiseGemm,
|
||||
false,
|
||||
InMemoryDataOperationEnum::AtomicAdd>;
|
||||
|
||||
Run(kernel);
|
||||
}
|
||||
@@ -544,12 +215,9 @@ struct DeviceGemmXdlSplitKCShuffle : public DeviceGemmSplitK<ALayout,
|
||||
return true;
|
||||
}
|
||||
|
||||
static bool IsSupportedArgument(const Argument& arg)
|
||||
static bool IsSupportedArgument(const Argument& karg)
|
||||
{
|
||||
return GridwiseGemm::CheckValidity(arg.a_grid_desc_kbatch_k0_m_k1_,
|
||||
arg.b_grid_desc_kbatch_k0_n_k1_,
|
||||
arg.c_grid_desc_m_n_,
|
||||
arg.block_2_ctile_map_);
|
||||
return GridwiseGemm::CheckValidity(karg);
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
@@ -567,9 +235,9 @@ struct DeviceGemmXdlSplitKCShuffle : public DeviceGemmSplitK<ALayout,
|
||||
index_t StrideA,
|
||||
index_t StrideB,
|
||||
index_t StrideC,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CElementwiseOperation c_element_op,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation,
|
||||
index_t KBatch)
|
||||
{
|
||||
return Argument{p_a,
|
||||
@@ -581,11 +249,10 @@ struct DeviceGemmXdlSplitKCShuffle : public DeviceGemmSplitK<ALayout,
|
||||
StrideA,
|
||||
StrideB,
|
||||
StrideC,
|
||||
1,
|
||||
1,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
c_element_op,
|
||||
GridwiseGemm::CalculateMPadded(M),
|
||||
GridwiseGemm::CalculateNPadded(N),
|
||||
GridwiseGemm::CalculateKPadded(K),
|
||||
GridwiseGemm::CalculateK0(K, KBatch),
|
||||
KBatch};
|
||||
}
|
||||
|
||||
@@ -601,9 +268,9 @@ struct DeviceGemmXdlSplitKCShuffle : public DeviceGemmSplitK<ALayout,
|
||||
index_t StrideA,
|
||||
index_t StrideB,
|
||||
index_t StrideC,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CElementwiseOperation c_element_op,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation,
|
||||
ck::index_t KBatch = 1) override
|
||||
{
|
||||
return std::make_unique<Argument>(static_cast<const ADataType*>(p_a),
|
||||
@@ -615,11 +282,10 @@ struct DeviceGemmXdlSplitKCShuffle : public DeviceGemmSplitK<ALayout,
|
||||
StrideA,
|
||||
StrideB,
|
||||
StrideC,
|
||||
1,
|
||||
1,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
c_element_op,
|
||||
GridwiseGemm::CalculateMPadded(M),
|
||||
GridwiseGemm::CalculateNPadded(N),
|
||||
GridwiseGemm::CalculateKPadded(K),
|
||||
GridwiseGemm::CalculateK0(K, KBatch),
|
||||
KBatch);
|
||||
}
|
||||
|
||||
@@ -630,31 +296,7 @@ struct DeviceGemmXdlSplitKCShuffle : public DeviceGemmSplitK<ALayout,
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
std::string GetTypeString() const override
|
||||
{
|
||||
auto str = std::stringstream();
|
||||
|
||||
// clang-format off
|
||||
str << "DeviceGemmXdlSplitKCShuffle"
|
||||
<< "<"
|
||||
<< BlockSize << ", "
|
||||
<< MPerBlock << ", "
|
||||
<< NPerBlock << ", "
|
||||
<< K0PerBlock << ", "
|
||||
<< K1 << ", "
|
||||
<< MPerXDL << ", "
|
||||
<< NPerXDL << ", "
|
||||
<< MXdlPerWave << ", "
|
||||
<< NXdlPerWave << ", "
|
||||
<< ABlockTransferSrcScalarPerVector << ", "
|
||||
<< ABlockTransferDstScalarPerVector_K1 << ", "
|
||||
<< BBlockTransferSrcScalarPerVector << ", "
|
||||
<< BBlockTransferDstScalarPerVector_K1
|
||||
<< ">";
|
||||
// clang-format on
|
||||
|
||||
return str.str();
|
||||
}
|
||||
std::string GetTypeString() const override { return GridwiseGemm::GetTypeString(); }
|
||||
};
|
||||
|
||||
} // namespace device
|
||||
|
||||
@@ -18,60 +18,23 @@
|
||||
namespace ck {
|
||||
|
||||
template <typename GridwiseGemm,
|
||||
typename FloatAB,
|
||||
typename FloatC,
|
||||
typename AGridDesc_B_K0_M_K1,
|
||||
typename BGridDesc_B_K0_N_K1,
|
||||
typename CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CElementwiseOperation,
|
||||
typename CBlockClusterAdaptor,
|
||||
bool HasMainKBlockLoop>
|
||||
bool HasMainKBlockLoop,
|
||||
InMemoryDataOperationEnum CGlobalMemoryDataOperation>
|
||||
__global__ void
|
||||
#if CK_USE_LAUNCH_BOUNDS
|
||||
__launch_bounds__(CK_MAX_THREAD_PER_BLOCK, CK_MIN_BLOCK_PER_CU)
|
||||
#endif
|
||||
kernel_gemm_xdlops_v2r4r2(const FloatAB* __restrict__ p_a_grid,
|
||||
const FloatAB* __restrict__ p_b_grid,
|
||||
FloatC* __restrict__ p_c_grid,
|
||||
const AGridDesc_B_K0_M_K1 a_b_k0_m_k1_grid_desc,
|
||||
const BGridDesc_B_K0_N_K1 b_b_k0_n_k1_grid_desc,
|
||||
const CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
const AElementwiseOperation a_element_op,
|
||||
const BElementwiseOperation b_element_op,
|
||||
const CElementwiseOperation c_element_op,
|
||||
const CBlockClusterAdaptor c_block_cluster_adaptor)
|
||||
kernel_gemm_xdlops_v2r4r2_simplified(typename GridwiseGemm::Argument karg)
|
||||
{
|
||||
#if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__))
|
||||
constexpr index_t shared_block_size =
|
||||
GridwiseGemm::GetSharedMemoryNumberOfByte() / sizeof(FloatAB);
|
||||
constexpr index_t shared_size = GridwiseGemm::GetSharedMemoryNumberOfByte();
|
||||
|
||||
__shared__ FloatAB p_shared_block[shared_block_size];
|
||||
__shared__ uint8_t p_shared[shared_size];
|
||||
|
||||
GridwiseGemm::template Run<HasMainKBlockLoop>(p_a_grid,
|
||||
p_b_grid,
|
||||
p_c_grid,
|
||||
static_cast<void*>(p_shared_block),
|
||||
a_b_k0_m_k1_grid_desc,
|
||||
b_b_k0_n_k1_grid_desc,
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
c_element_op,
|
||||
c_block_cluster_adaptor);
|
||||
GridwiseGemm::template Run<HasMainKBlockLoop, CGlobalMemoryDataOperation>(
|
||||
karg, static_cast<void*>(p_shared));
|
||||
#else
|
||||
ignore = p_a_grid;
|
||||
ignore = p_b_grid;
|
||||
ignore = p_c_grid;
|
||||
ignore = a_b_k0_m_k1_grid_desc;
|
||||
ignore = b_b_k0_n_k1_grid_desc;
|
||||
ignore = c_grid_desc_mblock_mperblock_nblock_nperblock;
|
||||
ignore = a_element_op;
|
||||
ignore = b_element_op;
|
||||
ignore = c_element_op;
|
||||
ignore = c_block_cluster_adaptor;
|
||||
ignore = karg;
|
||||
#endif // end of if (defined(__gfx908__) || defined(__gfx90a__))
|
||||
}
|
||||
|
||||
@@ -79,13 +42,13 @@ template <index_t BlockSize,
|
||||
typename FloatAB,
|
||||
typename FloatAcc,
|
||||
typename FloatC,
|
||||
InMemoryDataOperationEnum CGlobalMemoryDataOperation,
|
||||
typename AGridDesc_B_K0_M_K1,
|
||||
typename BGridDesc_B_K0_N_K1,
|
||||
typename CMNGridDesc,
|
||||
typename ALayout,
|
||||
typename BLayout,
|
||||
typename CLayout,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CElementwiseOperation,
|
||||
tensor_operation::device::GemmSpecialization GemmSpec,
|
||||
index_t MPerBlock,
|
||||
index_t NPerBlock,
|
||||
index_t K0PerBlock,
|
||||
@@ -126,10 +89,238 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
|
||||
static constexpr auto I7 = Number<7>{};
|
||||
|
||||
// K1 should be Number<...>
|
||||
static constexpr auto K1 = Number<K1Value>{};
|
||||
static constexpr auto K1 = Number<K1Value>{};
|
||||
static constexpr auto M01 = 1;
|
||||
static constexpr auto N01 = 1;
|
||||
|
||||
using ThisThreadBlock = ThisThreadBlock<BlockSize>;
|
||||
|
||||
struct Argument : public ck::tensor_operation::device::BaseArgument
|
||||
{
|
||||
const FloatAB* p_a_grid;
|
||||
const FloatAB* p_b_grid;
|
||||
FloatC* p_c_grid;
|
||||
index_t M;
|
||||
index_t N;
|
||||
index_t K;
|
||||
index_t StrideA;
|
||||
index_t StrideB;
|
||||
index_t StrideC;
|
||||
index_t MPadded;
|
||||
index_t NPadded;
|
||||
index_t KPadded;
|
||||
index_t K0;
|
||||
index_t k_batch;
|
||||
|
||||
Argument(const FloatAB* p_a_grid_,
|
||||
const FloatAB* p_b_grid_,
|
||||
FloatC* p_c_grid_,
|
||||
index_t M_,
|
||||
index_t N_,
|
||||
index_t K_,
|
||||
index_t StrideA_,
|
||||
index_t StrideB_,
|
||||
index_t StrideC_,
|
||||
index_t MPadded_,
|
||||
index_t NPadded_,
|
||||
index_t KPadded_,
|
||||
index_t K0_,
|
||||
index_t k_batch_)
|
||||
: p_a_grid(p_a_grid_),
|
||||
p_b_grid(p_b_grid_),
|
||||
p_c_grid(p_c_grid_),
|
||||
M(M_),
|
||||
N(N_),
|
||||
K(K_),
|
||||
StrideA(StrideA_),
|
||||
StrideB(StrideB_),
|
||||
StrideC(StrideC_),
|
||||
MPadded(MPadded_),
|
||||
NPadded(NPadded_),
|
||||
KPadded(KPadded_),
|
||||
K0(K0_),
|
||||
k_batch(k_batch_)
|
||||
{
|
||||
}
|
||||
|
||||
void Print() const
|
||||
{
|
||||
std::cout << "arg {"
|
||||
<< "M:" << M << ", "
|
||||
<< "N:" << N << ", "
|
||||
<< "K:" << K << ", "
|
||||
<< "SA:" << StrideA << ", "
|
||||
<< "SB:" << StrideB << ", "
|
||||
<< "SC:" << StrideC << ", "
|
||||
<< "MP:" << MPadded << ", "
|
||||
<< "NP:" << NPadded << ", "
|
||||
<< "KP:" << KPadded << ", "
|
||||
<< "K0:" << K0 << ", "
|
||||
<< "KB:" << k_batch << "}" << std::endl;
|
||||
}
|
||||
};
|
||||
|
||||
__host__ __device__ static auto CalculateGridSize(const Argument& karg)
|
||||
{
|
||||
return std::make_tuple(math::integer_divide_ceil(karg.N, NPerBlock),
|
||||
math::integer_divide_ceil(karg.M, MPerBlock),
|
||||
karg.k_batch);
|
||||
}
|
||||
|
||||
// prefer this to be called on host
|
||||
__host__ __device__ static auto CalculateMPadded(index_t M)
|
||||
{
|
||||
return (M + MPerBlock - 1) / MPerBlock * MPerBlock;
|
||||
}
|
||||
|
||||
__host__ __device__ static auto CalculateNPadded(index_t N)
|
||||
{
|
||||
return (N + NPerBlock - 1) / NPerBlock * NPerBlock;
|
||||
}
|
||||
|
||||
__host__ __device__ static auto CalculateK0(index_t K, index_t K_Batch = 1)
|
||||
{
|
||||
// k_batch * k0 * k0_per_block * k1
|
||||
auto K_t = K_Batch * K0PerBlock * K1;
|
||||
return (K + K_t - 1) / K_t * K0PerBlock;
|
||||
}
|
||||
|
||||
__host__ __device__ static auto CalculateKPadded(index_t K, index_t K_Batch = 1)
|
||||
{
|
||||
auto K0 = CalculateK0(K, K_Batch);
|
||||
return K_Batch * K0 * K1;
|
||||
}
|
||||
|
||||
__host__ __device__ static auto MakeAGridDescriptor_KBatch_K0_M_K1(index_t M,
|
||||
index_t MPad,
|
||||
index_t K,
|
||||
index_t StrideA,
|
||||
index_t KBatch,
|
||||
index_t K0,
|
||||
index_t KPad)
|
||||
{
|
||||
const auto a_grid_desc_m_k = [&]() {
|
||||
if constexpr(is_same<tensor_layout::gemm::RowMajor, ALayout>::value)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(M, K), make_tuple(StrideA, I1));
|
||||
}
|
||||
else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, ALayout>::value)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(M, K), make_tuple(I1, StrideA));
|
||||
}
|
||||
}();
|
||||
|
||||
const auto a_grid_desc_m_kpad = transform_tensor_descriptor(
|
||||
a_grid_desc_m_k,
|
||||
make_tuple(make_pass_through_transform(M), make_right_pad_transform(K, KPad - K)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}));
|
||||
|
||||
if constexpr(GemmSpec == tensor_operation::device::GemmSpecialization::MPadding ||
|
||||
GemmSpec == tensor_operation::device::GemmSpecialization::MNPadding ||
|
||||
GemmSpec == tensor_operation::device::GemmSpecialization::MKPadding ||
|
||||
GemmSpec == tensor_operation::device::GemmSpecialization::MNKPadding)
|
||||
{
|
||||
// const auto PadM = (MPerBlock - M % MPerBlock) % MPerBlock;
|
||||
return transform_tensor_descriptor(
|
||||
a_grid_desc_m_kpad,
|
||||
make_tuple(make_unmerge_transform(make_tuple(KBatch, K0, K1)),
|
||||
make_right_pad_transform(M, MPad - M)),
|
||||
make_tuple(Sequence<1>{}, Sequence<0>{}),
|
||||
make_tuple(Sequence<0, 1, 3>{}, Sequence<2>{}));
|
||||
}
|
||||
else
|
||||
{
|
||||
return transform_tensor_descriptor(
|
||||
a_grid_desc_m_kpad,
|
||||
make_tuple(make_unmerge_transform(make_tuple(KBatch, K0, K1)),
|
||||
make_pass_through_transform(M)),
|
||||
make_tuple(Sequence<1>{}, Sequence<0>{}),
|
||||
make_tuple(Sequence<0, 1, 3>{}, Sequence<2>{}));
|
||||
}
|
||||
}
|
||||
|
||||
__host__ __device__ static auto MakeBGridDescriptor_KBatch_K0_N_K1(index_t K,
|
||||
index_t NPad,
|
||||
index_t N,
|
||||
index_t StrideB,
|
||||
index_t KBatch,
|
||||
index_t K0,
|
||||
index_t KPad)
|
||||
{
|
||||
const auto b_grid_desc_k_n = [&]() {
|
||||
if constexpr(is_same<tensor_layout::gemm::RowMajor, BLayout>::value)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(K, N), make_tuple(StrideB, I1));
|
||||
}
|
||||
else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, BLayout>::value)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(K, N), make_tuple(I1, StrideB));
|
||||
}
|
||||
}();
|
||||
|
||||
const auto b_grid_desc_kpad_n = transform_tensor_descriptor(
|
||||
b_grid_desc_k_n,
|
||||
make_tuple(make_right_pad_transform(K, KPad - K), make_pass_through_transform(N)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}));
|
||||
|
||||
if constexpr(GemmSpec == tensor_operation::device::GemmSpecialization::NPadding ||
|
||||
GemmSpec == tensor_operation::device::GemmSpecialization::MNPadding ||
|
||||
GemmSpec == tensor_operation::device::GemmSpecialization::NKPadding ||
|
||||
GemmSpec == tensor_operation::device::GemmSpecialization::MNKPadding)
|
||||
{
|
||||
// const auto PadN = (NPerBlock - N % NPerBlock) % NPerBlock;
|
||||
return transform_tensor_descriptor(
|
||||
b_grid_desc_kpad_n,
|
||||
make_tuple(make_unmerge_transform(make_tuple(KBatch, K0, K1)),
|
||||
make_right_pad_transform(N, NPad - N)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0, 1, 3>{}, Sequence<2>{}));
|
||||
}
|
||||
else
|
||||
{
|
||||
return transform_tensor_descriptor(
|
||||
b_grid_desc_kpad_n,
|
||||
make_tuple(make_unmerge_transform(make_tuple(KBatch, K0, K1)),
|
||||
make_pass_through_transform(N)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0, 1, 3>{}, Sequence<2>{}));
|
||||
}
|
||||
}
|
||||
|
||||
__host__ __device__ static auto
|
||||
MakeCGridDescriptor_M_N(index_t M, index_t N, index_t MPad, index_t NPad, index_t StrideC)
|
||||
{
|
||||
const auto c_grid_desc_m_n = [&]() {
|
||||
if constexpr(is_same<tensor_layout::gemm::RowMajor, CLayout>::value)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(M, N), make_tuple(StrideC, I1));
|
||||
}
|
||||
else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, CLayout>::value)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(M, N), make_tuple(I1, StrideC));
|
||||
}
|
||||
}();
|
||||
|
||||
if constexpr(GemmSpec == tensor_operation::device::GemmSpecialization::MNPadding)
|
||||
{
|
||||
return transform_tensor_descriptor(c_grid_desc_m_n,
|
||||
make_tuple(make_right_pad_transform(M, MPad - M),
|
||||
make_right_pad_transform(N, NPad - N)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}));
|
||||
}
|
||||
else
|
||||
{
|
||||
return transform_tensor_descriptor(
|
||||
c_grid_desc_m_n,
|
||||
make_tuple(make_pass_through_transform(M), make_pass_through_transform(N)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}));
|
||||
}
|
||||
}
|
||||
|
||||
__host__ __device__ static constexpr index_t GetSharedMemoryNumberOfByte()
|
||||
{
|
||||
constexpr auto max_lds_align = K1;
|
||||
@@ -178,45 +369,68 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
|
||||
c_block_size * sizeof(FloatC));
|
||||
}
|
||||
|
||||
// block_id to matrix tile idx (m0, n0) mapping are controlled by {M01, N01}
|
||||
template <typename Block2CTileMap>
|
||||
__host__ __device__ static constexpr bool
|
||||
CheckValidity(const AGridDesc_B_K0_M_K1& a_b_k0_m_k1_grid_desc,
|
||||
const BGridDesc_B_K0_N_K1& b_b_k0_n_k1_grid_desc,
|
||||
const CMNGridDesc& c_m_n_grid_desc,
|
||||
const Block2CTileMap& block_2_ctile_map)
|
||||
__host__ __device__ static constexpr bool CheckValidity(const Argument& karg)
|
||||
{
|
||||
static_assert(is_known_at_compile_time<remove_cv_t<decltype(K1)>>::value,
|
||||
"wrong! K1 need to be known at compile-time");
|
||||
|
||||
static_assert((MPerBlock % (MPerXDL * MRepeat) == 0) &&
|
||||
(NPerBlock % (NRepeat * NPerXDL)) == 0,
|
||||
"Invalid tuning param!");
|
||||
|
||||
const auto M = a_b_k0_m_k1_grid_desc.GetLength(I2);
|
||||
const auto N = b_b_k0_n_k1_grid_desc.GetLength(I2);
|
||||
const auto K0 = a_b_k0_m_k1_grid_desc.GetLength(I1);
|
||||
const auto KBatch = a_b_k0_m_k1_grid_desc.GetLength(I0);
|
||||
|
||||
if(!(M == c_m_n_grid_desc.GetLength(I0) && N == c_m_n_grid_desc.GetLength(I1) &&
|
||||
K0 == b_b_k0_n_k1_grid_desc.GetLength(I1) &&
|
||||
K1 == a_b_k0_m_k1_grid_desc.GetLength(I3) &&
|
||||
K1 == b_b_k0_n_k1_grid_desc.GetLength(I3) &&
|
||||
KBatch == b_b_k0_n_k1_grid_desc.GetLength(I0)))
|
||||
return false;
|
||||
|
||||
if(!(M % MPerBlock == 0 && N % NPerBlock == 0 && K0 % K0PerBlock == 0))
|
||||
return false;
|
||||
|
||||
if(!block_2_ctile_map.CheckValidity(c_m_n_grid_desc))
|
||||
if constexpr(!(GemmSpec == tensor_operation::device::GemmSpecialization::MPadding ||
|
||||
GemmSpec == tensor_operation::device::GemmSpecialization::MNPadding ||
|
||||
GemmSpec == tensor_operation::device::GemmSpecialization::MKPadding ||
|
||||
GemmSpec == tensor_operation::device::GemmSpecialization::MNKPadding))
|
||||
{
|
||||
return false;
|
||||
if(!(karg.M % MPerBlock == 0))
|
||||
return false;
|
||||
}
|
||||
if constexpr(!(GemmSpec == tensor_operation::device::GemmSpecialization::NPadding ||
|
||||
GemmSpec == tensor_operation::device::GemmSpecialization::MNPadding ||
|
||||
GemmSpec == tensor_operation::device::GemmSpecialization::NKPadding ||
|
||||
GemmSpec == tensor_operation::device::GemmSpecialization::MNKPadding))
|
||||
{
|
||||
if(!(karg.N % NPerBlock == 0))
|
||||
return false;
|
||||
}
|
||||
|
||||
if constexpr(is_same<tensor_layout::gemm::RowMajor, ALayout>::value)
|
||||
{
|
||||
if(karg.K % ABlockTransferSrcScalarPerVector != 0)
|
||||
return false;
|
||||
}
|
||||
else
|
||||
{
|
||||
if(karg.M % ABlockTransferSrcScalarPerVector != 0)
|
||||
return false;
|
||||
}
|
||||
|
||||
if constexpr(is_same<tensor_layout::gemm::RowMajor, BLayout>::value)
|
||||
{
|
||||
if(karg.N % BBlockTransferSrcScalarPerVector != 0)
|
||||
return false;
|
||||
}
|
||||
else
|
||||
{
|
||||
if(karg.K % BBlockTransferSrcScalarPerVector != 0)
|
||||
return false;
|
||||
}
|
||||
|
||||
if constexpr(is_same<tensor_layout::gemm::RowMajor, CLayout>::value)
|
||||
{
|
||||
if(karg.N % CBlockTransferScalarPerVector_NWaveNPerXDL != 0)
|
||||
return false;
|
||||
}
|
||||
else
|
||||
{
|
||||
if(karg.M % CBlockTransferScalarPerVector_NWaveNPerXDL != 0)
|
||||
return false;
|
||||
}
|
||||
|
||||
// TODO: also check validity of all components (blockwise-copy, threadwise-copy, etc)
|
||||
return true;
|
||||
}
|
||||
|
||||
__host__ __device__ static auto GetKPad(index_t K, index_t KBatch)
|
||||
{
|
||||
const index_t K0 = math::integer_divide_ceil(K, K1 * K0PerBlock * KBatch) * K0PerBlock;
|
||||
const index_t KPad = KBatch * K0 * K1;
|
||||
return KPad;
|
||||
}
|
||||
|
||||
__host__ __device__ static constexpr bool CalculateHasMainK0BlockLoop(index_t K0)
|
||||
{
|
||||
const bool has_main_k0_block_loop = K0 > K0PerBlock;
|
||||
@@ -224,8 +438,9 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
|
||||
return has_main_k0_block_loop;
|
||||
}
|
||||
|
||||
template <typename CGridDesc>
|
||||
__host__ __device__ static constexpr auto
|
||||
MakeCGridDesc_MBlock_MPerBlock_NBlock_NPerBlock(const CMNGridDesc& c_m_n_grid_desc)
|
||||
MakeCGridDesc_MBlock_MPerBlock_NBlock_NPerBlock(const CGridDesc& c_m_n_grid_desc)
|
||||
{
|
||||
const auto M = c_m_n_grid_desc.GetLength(I0);
|
||||
const auto N = c_m_n_grid_desc.GetLength(I1);
|
||||
@@ -242,10 +457,11 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
|
||||
}
|
||||
|
||||
// return block_id to C matrix tile idx (m0, n0) mapping
|
||||
template <typename CGridDesc>
|
||||
__host__ __device__ static constexpr auto MakeCBlockClusterAdaptor(
|
||||
const CMNGridDesc& c_m_n_grid_desc, index_t /* M01 */, index_t /* N01 */, index_t KBatch)
|
||||
const CGridDesc& c_m_n_grid_desc, index_t /* M01 */, index_t /* N01 */, index_t KBatch)
|
||||
{
|
||||
return BlockToCTileMap_KSplit_M00_N0_M01Adapt<MPerBlock, NPerBlock, CMNGridDesc>(
|
||||
return BlockToCTileMap_KSplit_M00_N0_M01Adapt<MPerBlock, NPerBlock, CGridDesc>(
|
||||
c_m_n_grid_desc, 8, KBatch);
|
||||
}
|
||||
|
||||
@@ -262,24 +478,25 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
|
||||
Number<CShuffleNRepeatPerShuffle * NWave * NPerXDL>{}));
|
||||
}
|
||||
|
||||
using CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock =
|
||||
decltype(MakeCGridDesc_MBlock_MPerBlock_NBlock_NPerBlock(CMNGridDesc{}));
|
||||
using CBlockClusterAdaptor = decltype(MakeCBlockClusterAdaptor(CMNGridDesc{}, 1, 1, 1));
|
||||
|
||||
template <bool HasMainKBlockLoop>
|
||||
__device__ static void Run(const FloatAB* __restrict__ p_a_grid,
|
||||
const FloatAB* __restrict__ p_b_grid,
|
||||
FloatC* __restrict__ p_c_grid,
|
||||
void* __restrict__ p_shared_block,
|
||||
const AGridDesc_B_K0_M_K1& a_b_k0_m_k1_grid_desc,
|
||||
const BGridDesc_B_K0_N_K1& b_b_k0_n_k1_grid_desc,
|
||||
const CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock&
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
const AElementwiseOperation& a_element_op,
|
||||
const BElementwiseOperation& b_element_op,
|
||||
const CElementwiseOperation& c_element_op,
|
||||
const CBlockClusterAdaptor& c_block_cluster_adaptor)
|
||||
template <bool HasMainKBlockLoop, InMemoryDataOperationEnum CGlobalMemoryDataOperation>
|
||||
__device__ static void Run(const Argument& karg, void* __restrict__ p_shared_block)
|
||||
{
|
||||
const FloatAB* p_a_grid = karg.p_a_grid;
|
||||
const FloatAB* p_b_grid = karg.p_b_grid;
|
||||
FloatC* p_c_grid = karg.p_c_grid;
|
||||
const auto a_b_k0_m_k1_grid_desc = MakeAGridDescriptor_KBatch_K0_M_K1(
|
||||
karg.M, karg.MPadded, karg.K, karg.StrideA, karg.k_batch, karg.K0, karg.KPadded);
|
||||
const auto b_b_k0_n_k1_grid_desc = MakeBGridDescriptor_KBatch_K0_N_K1(
|
||||
karg.K, karg.NPadded, karg.N, karg.StrideB, karg.k_batch, karg.K0, karg.KPadded);
|
||||
const auto c_grid_desc_m_n =
|
||||
MakeCGridDescriptor_M_N(karg.M, karg.N, karg.MPadded, karg.NPadded, karg.StrideC);
|
||||
|
||||
const auto c_grid_desc_mblock_mperblock_nblock_nperblock =
|
||||
MakeCGridDesc_MBlock_MPerBlock_NBlock_NPerBlock(c_grid_desc_m_n);
|
||||
const AElementwiseOperation a_element_op = AElementwiseOperation{};
|
||||
const BElementwiseOperation b_element_op = BElementwiseOperation{};
|
||||
const CElementwiseOperation c_element_op = CElementwiseOperation{};
|
||||
|
||||
const auto a_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
|
||||
p_a_grid, a_b_k0_m_k1_grid_desc.GetElementSpaceSize());
|
||||
const auto b_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
|
||||
@@ -289,26 +506,16 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
|
||||
|
||||
const auto K0 = a_b_k0_m_k1_grid_desc.GetLength(I1);
|
||||
|
||||
// divide block work by [M, N]
|
||||
const auto block_work_idx =
|
||||
c_block_cluster_adaptor.CalculateBottomIndex(make_multi_index(get_block_1d_id()));
|
||||
|
||||
if(!c_block_cluster_adaptor.ValidCTileIndex(
|
||||
make_tuple(block_work_idx[I1], block_work_idx[I2]),
|
||||
make_tuple(c_grid_desc_mblock_mperblock_nblock_nperblock.GetLength(I0),
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock.GetLength(I2))))
|
||||
{
|
||||
return;
|
||||
}
|
||||
|
||||
const index_t k_batch_id = block_work_idx[I0];
|
||||
const index_t block_m_id = __builtin_amdgcn_readfirstlane(blockIdx.y);
|
||||
const index_t block_n_id = __builtin_amdgcn_readfirstlane(blockIdx.x);
|
||||
const index_t k_batch_id = __builtin_amdgcn_readfirstlane(blockIdx.z);
|
||||
|
||||
// HACK: this force m/n_block_data_idx_on_grid into SGPR
|
||||
const index_t m_block_data_idx_on_grid =
|
||||
__builtin_amdgcn_readfirstlane(block_work_idx[I1] * MPerBlock);
|
||||
__builtin_amdgcn_readfirstlane(block_m_id * MPerBlock);
|
||||
|
||||
const index_t n_block_data_idx_on_grid =
|
||||
__builtin_amdgcn_readfirstlane(block_work_idx[I2] * NPerBlock);
|
||||
__builtin_amdgcn_readfirstlane(block_n_id * NPerBlock);
|
||||
|
||||
// lds max alignment
|
||||
constexpr auto max_lds_align = K1;
|
||||
@@ -444,7 +651,6 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
|
||||
// c_mtx[MPerBlock, NPerBlock] is distributed among threads, and saved in
|
||||
// register
|
||||
// sanity check
|
||||
|
||||
auto blockwise_gemm =
|
||||
BlockwiseGemmXdlops_k0mk1_k0nk1_m0n0m1n1m2m3m4n2_v1<BlockSize,
|
||||
FloatAB,
|
||||
@@ -647,7 +853,7 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
|
||||
{c_block_desc_mblock_mperblock_nblock_nperblock,
|
||||
make_multi_index(0, 0, 0, 0),
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
make_multi_index(block_work_idx[I1], 0, block_work_idx[I2], 0),
|
||||
make_multi_index(block_m_id, 0, block_n_id, 0),
|
||||
c_element_op};
|
||||
|
||||
constexpr auto mxdlperwave_forward_step =
|
||||
@@ -716,6 +922,48 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
template <typename Layout>
|
||||
struct LStr
|
||||
{
|
||||
static std::string Get() { return ""; }
|
||||
};
|
||||
|
||||
template <>
|
||||
struct LStr<ck::tensor_layout::gemm::RowMajor>
|
||||
{
|
||||
static std::string Get() { return "R"; }
|
||||
};
|
||||
|
||||
template <>
|
||||
struct LStr<ck::tensor_layout::gemm::ColumnMajor>
|
||||
{
|
||||
static std::string Get() { return "C"; }
|
||||
};
|
||||
|
||||
static std::string GetTypeString()
|
||||
{
|
||||
auto str = std::stringstream();
|
||||
|
||||
// clang-format off
|
||||
str << "GemmXdlSplitKCShuffle_"
|
||||
<< getGemmSpecializationString(GemmSpec) << "_"
|
||||
<< std::string(ALayout::name)[0]
|
||||
<< std::string(BLayout::name)[0]
|
||||
<< std::string(CLayout::name)[0]
|
||||
<< "_"
|
||||
<< "B" << BlockSize << "_"
|
||||
<< "Vec" << ABlockTransferSrcScalarPerVector << "x"
|
||||
<< BBlockTransferSrcScalarPerVector << "x"
|
||||
<< CBlockTransferScalarPerVector_NWaveNPerXDL << "_"
|
||||
<< MPerBlock << "x"
|
||||
<< NPerBlock << "x"
|
||||
<< K0PerBlock << "x"
|
||||
<< K1 ;
|
||||
// clang-format on
|
||||
|
||||
return str.str();
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace ck
|
||||
|
||||
@@ -26,7 +26,8 @@ using S = ck::Sequence<Is...>;
|
||||
|
||||
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
|
||||
|
||||
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
// static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
|
||||
static constexpr auto GemmMNPadding = ck::tensor_operation::device::GemmSpecialization::MNPadding;
|
||||
|
||||
// Compilation parameters for a[m, k] * b[k, n] = c[m, n]
|
||||
using device_gemm_xdl_splitk_f16_f16_f16_mk_kn_mn_instances = std::tuple<
|
||||
@@ -35,14 +36,22 @@ using device_gemm_xdl_splitk_f16_f16_f16_mk_kn_mn_instances = std::tuple<
|
||||
//#########################| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise|Specialization| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector|
|
||||
//#########################| | | | | | | | Operation| Operation| Operation| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NXdlPerWave_NWaveNPerXdl| _NWaveNPerXdl|
|
||||
//#########################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, 1, 1, S<1, 32, 1, 8>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, 1, 1, S<1, 16, 1, 8>, 8>,
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DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 4>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, 1, 1, S<1, 16, 1, 8>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 8, true, 1, 1, S<1, 16, 1, 4>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8>
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, 1, 1, S<1, 32, 1, 8>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, 1, 1, S<1, 16, 1, 8>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 256, 64, 192, 4, 8, 32, 32, 1, 3, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 48, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 256, 192, 64, 4, 8, 32, 32, 3, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 4>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, 1, 1, S<1, 16, 1, 8>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 8, true, 1, 1, S<1, 16, 1, 4>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 32, 192, 4, 8, 32, 32, 1, 3, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 24, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 8, 8, true, 1, 1, S<1, 16, 1, 8>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 192, 32, 4, 8, 32, 32, 3, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 8, true, 1, 1, S<1, 32, 1, 4>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 32, 64, 4, 8, 32, 32, 1, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 16, 1, 8>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 64, 32, 4, 8, 32, 32, 1, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 8, true, 1, 1, S<1, 32, 1, 4>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, 1, 1, S<1, 16, 1, 8>, 8>,
|
||||
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 8, true, 1, 1, S<1, 32, 1, 4>, 8>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
|
||||
Reference in New Issue
Block a user