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https://github.com/ROCm/composable_kernel.git
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Batched Gemm with multiD (#329)
* add batched_gemm_multiD * add ds * rename file * add batched_gemm_bias example * add batch_strides into bmm_c_permute * clean * rename example_28 to example_29 Co-authored-by: Chao Liu <chao.liu2@amd.com>
This commit is contained in:
zjing14
@@ -14,9 +14,15 @@ struct BatchedGemmCPermuteDesc
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ck::index_t stride_G0_, stride_G1_, stride_M_, stride_N_;
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};
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template <typename AElementwiseOperation,
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template <typename ALayout,
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typename BLayout,
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typename DELayout,
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typename ADataType,
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typename BDataType,
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typename EDataType,
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typename AElementwiseOperation,
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typename BElementwiseOperation,
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typename CElementwiseOperation>
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typename CDEElementwiseOperation>
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struct DeviceBatchedGemmCPermute : public BaseOperator
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{
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virtual std::unique_ptr<BaseArgument>
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@@ -28,20 +34,36 @@ struct DeviceBatchedGemmCPermute : public BaseOperator
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index_t K,
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index_t stride_A,
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index_t stride_B,
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index_t batch_stride_A,
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index_t batch_stride_B,
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BatchedGemmCPermuteDesc batched_gemm_c_permute_desc,
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index_t BatchCount,
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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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ck::index_t BatchCount) = 0;
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CDEElementwiseOperation c_element_op) = 0;
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virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
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};
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template <typename AElementwiseOperation,
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template <typename ALayout,
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typename BLayout,
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typename DELayout,
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typename ADataType,
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typename BDataType,
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typename EDataType,
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typename AElementwiseOperation,
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typename BElementwiseOperation,
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typename CElementwiseOperation>
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using DeviceBatchedGemmCPermutePtr = std::unique_ptr<
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DeviceBatchedGemmCPermute<AElementwiseOperation, BElementwiseOperation, CElementwiseOperation>>;
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typename CDEElementwiseOperation>
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using DeviceBatchedGemmCPermutePtr =
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std::unique_ptr<DeviceBatchedGemmCPermute<ALayout,
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BLayout,
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DELayout,
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ADataType,
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BDataType,
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EDataType,
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AElementwiseOperation,
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BElementwiseOperation,
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CDEElementwiseOperation>>;
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} // namespace device
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} // namespace tensor_operation
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@@ -8,6 +8,7 @@
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#include "ck/tensor_description/tensor_descriptor_helper.hpp"
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#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
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#include "ck/tensor_operation/gpu/device/device_batched_gemm_c_permute.hpp"
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#include "ck/tensor_operation/gpu/device/device_batched_gemm_multi_d_xdl.hpp"
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#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
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#include "ck/tensor_operation/gpu/grid/gridwise_gemm_multiple_d_xdl_cshuffle.hpp"
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#include "ck/device_utility/device_prop.hpp"
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@@ -45,12 +46,12 @@ namespace device {
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template <typename GridwiseGemm,
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typename FloatAB,
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typename FloatC,
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typename AGridDesc_K0_M_K1,
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typename BGridDesc_K0_N_K1,
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typename AGridDesc_AK0_M_AK1,
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typename BGridDesc_BK0_N_BK1,
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typename CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock,
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typename AElementwiseOperation,
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typename BElementwiseOperation,
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typename CElementwiseOperation,
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typename CDEElementwiseOperation,
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typename ComputePtrOffsetOfBatch,
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typename Block2CTileMap,
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bool HasMainKBlockLoop>
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@@ -60,15 +61,15 @@ __global__ void
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#endif
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kernel_batched_gemm_c_permute_xdl(const FloatAB* __restrict__ p_a_grid,
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const FloatAB* __restrict__ p_b_grid,
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FloatC* __restrict__ p_c_grid,
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FloatC* __restrict__ p_e_grid,
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const index_t batch_count,
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const AGridDesc_K0_M_K1 a_grid_desc_k0_m_k1,
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const BGridDesc_K0_N_K1 b_grid_desc_k0_n_k1,
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const AGridDesc_AK0_M_AK1 a_grid_desc_k0_m_k1,
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const BGridDesc_BK0_N_BK1 b_grid_desc_k0_n_k1,
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const CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock
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c_grid_desc_mblock_mperblock_nblock_nperblock,
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const AElementwiseOperation a_element_op,
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const BElementwiseOperation b_element_op,
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const CElementwiseOperation c_element_op,
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const CDEElementwiseOperation cde_element_op,
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const ComputePtrOffsetOfBatch compute_ptr_offset_of_batch,
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const Block2CTileMap block_2_ctile_map)
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{
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@@ -90,11 +91,11 @@ __global__ void
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p_a_grid + a_batch_offset,
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p_b_grid + b_batch_offset,
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ck::Tuple<>{},
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p_c_grid + c_batch_offset,
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p_e_grid + c_batch_offset,
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p_shared,
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a_element_op,
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b_element_op,
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c_element_op,
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cde_element_op,
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a_grid_desc_k0_m_k1,
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b_grid_desc_k0_n_k1,
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ck::StaticallyIndexedArray<
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@@ -105,14 +106,14 @@ __global__ void
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#else
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ignore = p_a_grid;
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ignore = p_b_grid;
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ignore = p_c_grid;
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ignore = p_e_grid;
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ignore = batch_count;
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ignore = a_grid_desc_k0_m_k1;
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ignore = b_grid_desc_k0_n_k1;
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ignore = c_grid_desc_mblock_mperblock_nblock_nperblock;
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ignore = a_element_op;
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ignore = b_element_op;
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ignore = c_element_op;
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ignore = cde_element_op;
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ignore = compute_ptr_offset_of_batch;
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ignore = block_2_ctile_map;
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#endif
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@@ -120,48 +121,60 @@ __global__ void
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template <typename ALayout,
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typename BLayout,
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typename DELayout,
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typename ADataType,
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typename BDataType,
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typename CDataType,
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typename AccDataType,
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typename GemmAccDataType,
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typename CShuffleDataType,
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typename DsDataType,
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typename EDataType,
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typename AElementwiseOperation,
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typename BElementwiseOperation,
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typename CElementwiseOperation,
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typename CDEElementwiseOperation,
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GemmSpecialization GemmSpec,
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ck::index_t NumPrefetch,
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ck::index_t BlockSize,
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ck::index_t MPerBlock,
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ck::index_t NPerBlock,
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ck::index_t KPerBlock,
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ck::index_t AK1,
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ck::index_t BK1,
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ck::index_t MPerXDL,
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ck::index_t NPerXDL,
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ck::index_t MXdlPerWave,
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ck::index_t NXdlPerWave,
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typename ABlockTransferThreadClusterLengths_K0_M_K1,
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index_t NumGemmKPrefetchStage,
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index_t BlockSize,
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index_t MPerBlock,
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index_t NPerBlock,
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index_t KPerBlock,
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index_t AK1,
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index_t BK1,
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index_t MPerXDL,
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index_t NPerXDL,
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index_t MXdlPerWave,
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index_t NXdlPerWave,
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typename ABlockTransferThreadClusterLengths_AK0_M_AK1,
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typename ABlockTransferThreadClusterArrangeOrder,
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typename ABlockTransferSrcAccessOrder,
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ck::index_t ABlockTransferSrcVectorDim,
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ck::index_t ABlockTransferSrcScalarPerVector,
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ck::index_t ABlockTransferDstScalarPerVector_K1,
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bool ABlockLdsAddExtraM,
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typename BBlockTransferThreadClusterLengths_K0_N_K1,
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index_t ABlockTransferSrcVectorDim,
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index_t ABlockTransferSrcScalarPerVector,
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index_t ABlockTransferDstScalarPerVector_AK1,
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bool ABlockLdsExtraM,
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typename BBlockTransferThreadClusterLengths_BK0_N_BK1,
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typename BBlockTransferThreadClusterArrangeOrder,
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typename BBlockTransferSrcAccessOrder,
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ck::index_t BBlockTransferSrcVectorDim,
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ck::index_t BBlockTransferSrcScalarPerVector,
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ck::index_t BBlockTransferDstScalarPerVector_K1,
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bool BBlockLdsAddExtraN,
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index_t BBlockTransferSrcVectorDim,
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index_t BBlockTransferSrcScalarPerVector,
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index_t BBlockTransferDstScalarPerVector_BK1,
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bool BBlockLdsExtraN,
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index_t CShuffleMXdlPerWavePerShuffle,
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index_t CShuffleNXdlPerWavePerShuffle,
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typename CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
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index_t CDEBlockTransferScalarPerVector_NPerBlock,
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LoopScheduler LoopSched = make_default_loop_scheduler()>
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struct DeviceBatchedGemmCPermuteXdl : public DeviceBatchedGemmCPermute<AElementwiseOperation,
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struct DeviceBatchedGemmCPermuteXdl : public DeviceBatchedGemmCPermute<ALayout,
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BLayout,
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DELayout,
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ADataType,
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BDataType,
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EDataType,
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AElementwiseOperation,
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BElementwiseOperation,
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CElementwiseOperation>
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CDEElementwiseOperation>
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{
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using DeviceOp = DeviceBatchedGemmCPermuteXdl;
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static constexpr auto I0 = Number<0>{};
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static constexpr auto I1 = Number<1>{};
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static constexpr auto I2 = Number<2>{};
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@@ -373,7 +386,7 @@ struct DeviceBatchedGemmCPermuteXdl : public DeviceBatchedGemmCPermute<AElementw
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}
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static auto
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MakeCGridDescriptor_M_N(index_t MRaw, index_t NRaw, index_t stride_M, index_t stride_N)
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MakeEGridDescriptor_M_N(index_t MRaw, index_t NRaw, index_t stride_M, index_t stride_N)
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{
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const auto c_grid_desc_mraw_nraw = [&]() {
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return make_naive_tensor_descriptor(make_tuple(MRaw, NRaw),
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@@ -489,9 +502,9 @@ struct DeviceBatchedGemmCPermuteXdl : public DeviceBatchedGemmCPermute<AElementw
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}
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}
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using AGridDesc_K0_M_K1 = decltype(MakeAGridDescriptor_AK0_M_AK1(1, 1, 1));
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using BGridDesc_K0_N_K1 = decltype(MakeBGridDescriptor_BK0_N_BK1(1, 1, 1));
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using CGridDesc_M_N = decltype(MakeCGridDescriptor_M_N(1, 1, 1, 1));
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using AGridDesc_AK0_M_AK1 = decltype(MakeAGridDescriptor_AK0_M_AK1(1, 1, 1));
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using BGridDesc_BK0_N_BK1 = decltype(MakeBGridDescriptor_BK0_N_BK1(1, 1, 1));
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using EGridDesc_M_N = decltype(MakeEGridDescriptor_M_N(1, 1, 1, 1));
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using EGridDesc_G0_G1_M_N = decltype(MakeEGridDescriptor_G0_G1_M_N(1, 1, 1, 1, 1, 1, 1, 1));
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struct ComputePtrOffsetOfStridedBatch
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@@ -531,18 +544,18 @@ struct DeviceBatchedGemmCPermuteXdl : public DeviceBatchedGemmCPermute<AElementw
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using GridwiseGemm = GridwiseGemmMultipleD_k0mk1_k0nk1_mn_xdl_cshuffle<
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ADataType, // TODO: distinguish A/B datatype
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AccDataType,
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CDataType, // CShuffleDataType,
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ck::Tuple<>, // DsDataType,
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CDataType, // EDataType,
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GemmAccDataType,
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CShuffleDataType,
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DsDataType,
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EDataType,
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AElementwiseOperation,
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BElementwiseOperation,
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CElementwiseOperation,
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CDEElementwiseOperation,
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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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NumPrefetch,
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AGridDesc_AK0_M_AK1,
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BGridDesc_BK0_N_BK1,
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EGridDesc_M_N,
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NumGemmKPrefetchStage,
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BlockSize,
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MPerBlock,
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NPerBlock,
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@@ -553,22 +566,22 @@ struct DeviceBatchedGemmCPermuteXdl : public DeviceBatchedGemmCPermute<AElementw
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NPerXDL,
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MXdlPerWave,
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NXdlPerWave,
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ABlockTransferThreadClusterLengths_K0_M_K1,
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ABlockTransferThreadClusterLengths_AK0_M_AK1,
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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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ABlockTransferDstScalarPerVector_AK1,
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false,
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ABlockLdsExtraM,
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BBlockTransferThreadClusterLengths_BK0_N_BK1,
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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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BBlockTransferDstScalarPerVector_BK1,
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false,
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BBlockLdsExtraN,
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CShuffleMXdlPerWavePerShuffle,
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CShuffleNXdlPerWavePerShuffle,
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CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
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@@ -576,7 +589,7 @@ struct DeviceBatchedGemmCPermuteXdl : public DeviceBatchedGemmCPermute<AElementw
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LoopSched>;
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using CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock = decltype(
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GridwiseGemm::MakeEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(CGridDesc_M_N{}));
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GridwiseGemm::MakeEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(EGridDesc_M_N{}));
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using Block2CTileMap = typename GridwiseGemm::DefaultBlock2ETileMap;
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// Argument
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@@ -584,26 +597,28 @@ struct DeviceBatchedGemmCPermuteXdl : public DeviceBatchedGemmCPermute<AElementw
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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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EDataType* p_e_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 stride_A,
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index_t stride_B,
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index_t batch_stride_A,
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index_t batch_stride_B,
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BatchedGemmCPermuteDesc batched_gemm_c_permute_desc,
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index_t BatchCount,
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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 BatchCount)
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CDEElementwiseOperation cde_element_op)
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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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p_e_grid_{p_e_grid},
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BatchCount_(BatchCount),
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a_grid_desc_k0_m_k1_{
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a_grid_desc_ak0_m_ak1_{
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DeviceBatchedGemmCPermuteXdl::MakeAGridDescriptor_AK0_M_AK1(M, K, stride_A)},
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b_grid_desc_k0_n_k1_{
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b_grid_desc_bk0_n_bk1_{
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DeviceBatchedGemmCPermuteXdl::MakeBGridDescriptor_BK0_N_BK1(K, N, stride_B)},
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c_grid_desc_m_n_{DeviceBatchedGemmCPermuteXdl::MakeCGridDescriptor_M_N(
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e_grid_desc_m_n_{DeviceBatchedGemmCPermuteXdl::MakeEGridDescriptor_M_N(
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batched_gemm_c_permute_desc.M_,
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batched_gemm_c_permute_desc.N_,
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batched_gemm_c_permute_desc.stride_M_,
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@@ -618,42 +633,39 @@ struct DeviceBatchedGemmCPermuteXdl : public DeviceBatchedGemmCPermute<AElementw
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batched_gemm_c_permute_desc.stride_M_,
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batched_gemm_c_permute_desc.stride_N_)},
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c_grid_desc_mblock_mperblock_nblock_nperblock{},
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compute_ptr_offset_of_batch_{
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type_convert<index_t>(a_grid_desc_k0_m_k1_.GetElementSpaceSize()),
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type_convert<index_t>(b_grid_desc_k0_n_k1_.GetElementSpaceSize()),
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e_grid_desc_g0_g1_m_n_},
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block_2_ctile_map_{GridwiseGemm::MakeDefaultBlock2ETileMap(c_grid_desc_m_n_)},
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compute_ptr_offset_of_batch_{batch_stride_A, batch_stride_B, e_grid_desc_g0_g1_m_n_},
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block_2_ctile_map_{GridwiseGemm::MakeDefaultBlock2ETileMap(e_grid_desc_m_n_)},
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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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cde_element_op_{cde_element_op}
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{
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if(GridwiseGemm::CheckValidity(a_grid_desc_k0_m_k1_,
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b_grid_desc_k0_n_k1_,
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c_grid_desc_m_n_,
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if(GridwiseGemm::CheckValidity(a_grid_desc_ak0_m_ak1_,
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b_grid_desc_bk0_n_bk1_,
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e_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::MakeEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
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c_grid_desc_m_n_);
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e_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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EDataType* p_e_grid_;
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index_t BatchCount_;
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AGridDesc_K0_M_K1 a_grid_desc_k0_m_k1_;
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BGridDesc_K0_N_K1 b_grid_desc_k0_n_k1_;
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CGridDesc_M_N c_grid_desc_m_n_;
|
||||
AGridDesc_AK0_M_AK1 a_grid_desc_ak0_m_ak1_;
|
||||
BGridDesc_BK0_N_BK1 b_grid_desc_bk0_n_bk1_;
|
||||
EGridDesc_M_N e_grid_desc_m_n_;
|
||||
EGridDesc_G0_G1_M_N e_grid_desc_g0_g1_m_n_;
|
||||
CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock c_grid_desc_mblock_mperblock_nblock_nperblock;
|
||||
ComputePtrOffsetOfStridedBatch compute_ptr_offset_of_batch_;
|
||||
Block2CTileMap block_2_ctile_map_;
|
||||
AElementwiseOperation a_element_op_;
|
||||
BElementwiseOperation b_element_op_;
|
||||
CElementwiseOperation c_element_op_;
|
||||
CDEElementwiseOperation cde_element_op_;
|
||||
};
|
||||
|
||||
// Invoker
|
||||
@@ -664,21 +676,23 @@ struct DeviceBatchedGemmCPermuteXdl : public DeviceBatchedGemmCPermute<AElementw
|
||||
float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
|
||||
{
|
||||
{
|
||||
std::cout << "arg.a_grid_desc_k0_m_k1_{" << arg.a_grid_desc_k0_m_k1_.GetLength(I0)
|
||||
<< ", " << arg.a_grid_desc_k0_m_k1_.GetLength(I1) << ", "
|
||||
<< arg.a_grid_desc_k0_m_k1_.GetLength(I2) << "}" << std::endl;
|
||||
std::cout << "arg.a_grid_desc_ak0_m_ak1_{"
|
||||
<< arg.a_grid_desc_ak0_m_ak1_.GetLength(I0) << ", "
|
||||
<< arg.a_grid_desc_ak0_m_ak1_.GetLength(I1) << ", "
|
||||
<< arg.a_grid_desc_ak0_m_ak1_.GetLength(I2) << "}" << std::endl;
|
||||
|
||||
std::cout << "arg.b_grid_desc_k0_n_k1_{" << arg.b_grid_desc_k0_n_k1_.GetLength(I0)
|
||||
<< ", " << arg.b_grid_desc_k0_n_k1_.GetLength(I1) << ", "
|
||||
<< arg.b_grid_desc_k0_n_k1_.GetLength(I2) << "}" << std::endl;
|
||||
std::cout << "arg.b_grid_desc_bk0_n_bk1_{"
|
||||
<< arg.b_grid_desc_bk0_n_bk1_.GetLength(I0) << ", "
|
||||
<< arg.b_grid_desc_bk0_n_bk1_.GetLength(I1) << ", "
|
||||
<< arg.b_grid_desc_bk0_n_bk1_.GetLength(I2) << "}" << std::endl;
|
||||
|
||||
std::cout << "arg.c_grid_desc_m_n_{" << arg.c_grid_desc_m_n_.GetLength(I0) << ", "
|
||||
<< arg.c_grid_desc_m_n_.GetLength(I1) << "}" << std::endl;
|
||||
std::cout << "arg.e_grid_desc_m_n_{" << arg.e_grid_desc_m_n_.GetLength(I0) << ", "
|
||||
<< arg.e_grid_desc_m_n_.GetLength(I1) << "}" << std::endl;
|
||||
}
|
||||
|
||||
if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
|
||||
arg.b_grid_desc_k0_n_k1_,
|
||||
arg.c_grid_desc_m_n_,
|
||||
if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_ak0_m_ak1_,
|
||||
arg.b_grid_desc_bk0_n_bk1_,
|
||||
arg.e_grid_desc_m_n_,
|
||||
arg.block_2_ctile_map_))
|
||||
{
|
||||
throw std::runtime_error(
|
||||
@@ -687,10 +701,10 @@ struct DeviceBatchedGemmCPermuteXdl : public DeviceBatchedGemmCPermute<AElementw
|
||||
}
|
||||
|
||||
const index_t grid_size =
|
||||
arg.block_2_ctile_map_.CalculateGridSize(arg.c_grid_desc_m_n_) * arg.BatchCount_;
|
||||
arg.block_2_ctile_map_.CalculateGridSize(arg.e_grid_desc_m_n_) * arg.BatchCount_;
|
||||
|
||||
const auto K =
|
||||
arg.a_grid_desc_k0_m_k1_.GetLength(I0) * arg.a_grid_desc_k0_m_k1_.GetLength(I2);
|
||||
arg.a_grid_desc_ak0_m_ak1_.GetLength(I0) * arg.a_grid_desc_ak0_m_ak1_.GetLength(I2);
|
||||
|
||||
float ave_time = 0;
|
||||
|
||||
@@ -698,13 +712,13 @@ struct DeviceBatchedGemmCPermuteXdl : public DeviceBatchedGemmCPermute<AElementw
|
||||
const auto kernel = kernel_batched_gemm_c_permute_xdl<
|
||||
GridwiseGemm,
|
||||
ADataType, // TODO: distiguish A/B datatype
|
||||
CDataType,
|
||||
remove_reference_t<DeviceBatchedGemmCPermuteXdl::AGridDesc_K0_M_K1>,
|
||||
remove_reference_t<DeviceBatchedGemmCPermuteXdl::BGridDesc_K0_N_K1>,
|
||||
EDataType,
|
||||
AGridDesc_AK0_M_AK1,
|
||||
BGridDesc_BK0_N_BK1,
|
||||
typename GridwiseGemm::EGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation,
|
||||
CDEElementwiseOperation,
|
||||
ComputePtrOffsetOfStridedBatch,
|
||||
remove_reference_t<Block2CTileMap>,
|
||||
has_main_k_block_loop_>;
|
||||
@@ -716,14 +730,14 @@ struct DeviceBatchedGemmCPermuteXdl : public DeviceBatchedGemmCPermute<AElementw
|
||||
0,
|
||||
arg.p_a_grid_,
|
||||
arg.p_b_grid_,
|
||||
arg.p_c_grid_,
|
||||
arg.p_e_grid_,
|
||||
arg.BatchCount_,
|
||||
arg.a_grid_desc_k0_m_k1_,
|
||||
arg.b_grid_desc_k0_n_k1_,
|
||||
arg.a_grid_desc_ak0_m_ak1_,
|
||||
arg.b_grid_desc_bk0_n_bk1_,
|
||||
arg.c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
arg.a_element_op_,
|
||||
arg.b_element_op_,
|
||||
arg.c_element_op_,
|
||||
arg.cde_element_op_,
|
||||
arg.compute_ptr_offset_of_batch_,
|
||||
arg.block_2_ctile_map_);
|
||||
};
|
||||
@@ -756,31 +770,27 @@ struct DeviceBatchedGemmCPermuteXdl : public DeviceBatchedGemmCPermute<AElementw
|
||||
|
||||
static bool IsSupportedArgument(const Argument& arg)
|
||||
{
|
||||
return GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
|
||||
arg.b_grid_desc_k0_n_k1_,
|
||||
arg.c_grid_desc_m_n_,
|
||||
return GridwiseGemm::CheckValidity(arg.a_grid_desc_ak0_m_ak1_,
|
||||
arg.b_grid_desc_bk0_n_bk1_,
|
||||
arg.e_grid_desc_m_n_,
|
||||
arg.block_2_ctile_map_);
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
bool IsSupportedArgument(const BaseArgument* p_arg) override
|
||||
{
|
||||
return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
|
||||
}
|
||||
|
||||
static auto MakeArgument(const ADataType* p_a,
|
||||
const BDataType* p_b,
|
||||
CDataType* p_c,
|
||||
EDataType* p_c,
|
||||
index_t M,
|
||||
index_t N,
|
||||
index_t K,
|
||||
index_t stride_A,
|
||||
index_t stride_B,
|
||||
index_t batch_stride_A,
|
||||
index_t batch_stride_B,
|
||||
BatchedGemmCPermuteDesc batched_gemm_c_permute_desc,
|
||||
index_t BatchCount,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CElementwiseOperation c_element_op,
|
||||
index_t BatchCount)
|
||||
CDEElementwiseOperation cde_element_op)
|
||||
{
|
||||
return Argument{p_a,
|
||||
p_b,
|
||||
@@ -790,11 +800,13 @@ struct DeviceBatchedGemmCPermuteXdl : public DeviceBatchedGemmCPermute<AElementw
|
||||
K,
|
||||
stride_A,
|
||||
stride_B,
|
||||
batch_stride_A,
|
||||
batch_stride_B,
|
||||
batched_gemm_c_permute_desc,
|
||||
BatchCount,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
c_element_op,
|
||||
BatchCount};
|
||||
cde_element_op};
|
||||
}
|
||||
|
||||
static auto MakeInvoker() { return Invoker{}; }
|
||||
@@ -809,25 +821,29 @@ struct DeviceBatchedGemmCPermuteXdl : public DeviceBatchedGemmCPermute<AElementw
|
||||
index_t K,
|
||||
index_t stride_A,
|
||||
index_t stride_B,
|
||||
index_t batch_stride_A,
|
||||
index_t batch_stride_B,
|
||||
BatchedGemmCPermuteDesc batched_gemm_c_permute_desc,
|
||||
index_t BatchCount,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CElementwiseOperation c_element_op,
|
||||
index_t BatchCount) override
|
||||
CDEElementwiseOperation cde_element_op) override
|
||||
{
|
||||
return std::make_unique<Argument>(static_cast<const ADataType*>(p_a),
|
||||
static_cast<const BDataType*>(p_b),
|
||||
static_cast<CDataType*>(p_c),
|
||||
static_cast<EDataType*>(p_c),
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
stride_A,
|
||||
stride_B,
|
||||
batch_stride_A,
|
||||
batch_stride_B,
|
||||
batched_gemm_c_permute_desc,
|
||||
BatchCount,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
c_element_op,
|
||||
BatchCount);
|
||||
cde_element_op);
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
|
||||
@@ -0,0 +1,55 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
#include <iostream>
|
||||
#include <vector>
|
||||
|
||||
#include "device_base.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename CLayout,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename DsDataType,
|
||||
typename EDataType,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CDEElementwiseOperation>
|
||||
struct DeviceBatchedGemmMultiD : public BaseOperator
|
||||
{
|
||||
static constexpr index_t NumDTensor = DsDataType::Size();
|
||||
|
||||
virtual std::unique_ptr<BaseArgument>
|
||||
MakeArgumentPointer(const void* p_a,
|
||||
const void* p_b,
|
||||
std::array<const void*, NumDTensor> p_ds,
|
||||
void* p_c,
|
||||
ck::index_t M,
|
||||
ck::index_t N,
|
||||
ck::index_t K,
|
||||
ck::index_t StrideA,
|
||||
ck::index_t StrideB,
|
||||
std::array<ck::index_t, NumDTensor> StrideDs,
|
||||
ck::index_t StrideE,
|
||||
ck::index_t BatchStrideA,
|
||||
ck::index_t BatchStrideB,
|
||||
std::array<ck::index_t, NumDTensor> BatchStrideDs,
|
||||
ck::index_t BatchStrideE,
|
||||
ck::index_t Batch,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CDEElementwiseOperation cde_element_op) = 0;
|
||||
|
||||
virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
|
||||
};
|
||||
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,900 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
#include <iostream>
|
||||
#include <sstream>
|
||||
|
||||
#include "ck/utility/common_header.hpp"
|
||||
#include "ck/tensor_description/tensor_descriptor.hpp"
|
||||
#include "ck/tensor_description/tensor_descriptor_helper.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/device_batched_gemm_multi_d.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/grid/gridwise_gemm_multiple_d_xdl_cshuffle.hpp"
|
||||
#include "ck/device_utility/device_prop.hpp"
|
||||
#include "ck/device_utility/kernel_launch.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
|
||||
/*
|
||||
* \brief Wrapper function of GridwiseGemm::Run to realize BatchedGEMM.
|
||||
*
|
||||
* \tparam ComputePtrOffsetOfBatch Class that computes the base pointer offsets of A, B, C matrix
|
||||
* given the batch. For example, ComputePtrOffsetOfStridedBatch() computes the offsets of evenly
|
||||
* strided batched, but we can easily extend to other layouts. The returned offset can be either \p
|
||||
* index_t or \p long_index_t. If it returns \p long_index_t, we are not subject to the 2GB
|
||||
* limitations.
|
||||
*
|
||||
* \tparam Block2CTileMap Block2CTileMap::CalculateBottomIndex() takes in id of a workgroup and
|
||||
* returns the 2D index of the tile that it computes. \see
|
||||
* GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3::Run().
|
||||
*
|
||||
* \note Using \p ComputePtrOffsetOfBatch gives us the flexibility that 2 workgroups can compute 2
|
||||
* tiles from different matrices. Keep in mind that these 2 matrices can share the same grid
|
||||
* descriptor (like in BatchedGEMM), or use their own grid descriptors (in GroupedGemm). \link
|
||||
* device_conv3d_fwd_xdl_ndhwc_kzyxc_ndhwk.hpp kernel_gemm_xdlops_v2r3_for_conv3d \endlink for \link
|
||||
* DeviceConv3d \endlink uses the same concept, but currently does NOT encapsulate the computing of
|
||||
* pointer offset into \p ComputePtrOffsetOfStridedBatch.
|
||||
*
|
||||
* \note \p Block2CTileMap allows customized mapping between a workgroup and the C-tile it computes.
|
||||
* Together with \p ComputePtrOffsetOfBatch, we can reuse GridwiseGemm (and GridwiseGemm fusion ) to
|
||||
* realize BatchedGemm and GroupedGemm (and the corresponding GEMM fusion).
|
||||
*
|
||||
*/
|
||||
template <typename GridwiseGemm,
|
||||
typename FloatAB,
|
||||
typename FloatDsPointer,
|
||||
typename FloatC,
|
||||
typename AGridDesc_AK0_M_AK1,
|
||||
typename BGridDesc_BK0_N_BK1,
|
||||
typename DsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename EGridDesc_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CDEElementwiseOperation,
|
||||
typename ComputePtrOffsetOfBatch,
|
||||
typename Block2CTileMap,
|
||||
bool HasMainKBlockLoop>
|
||||
__global__ void
|
||||
#if CK_USE_LAUNCH_BOUNDS
|
||||
__launch_bounds__(CK_MAX_THREAD_PER_BLOCK, CK_MIN_BLOCK_PER_CU)
|
||||
#endif
|
||||
kernel_batched_gemm_xdl(const FloatAB* __restrict__ p_a_grid,
|
||||
const FloatAB* __restrict__ p_b_grid,
|
||||
FloatDsPointer p_ds_grid,
|
||||
FloatC* __restrict__ p_e_grid,
|
||||
const index_t batch_count,
|
||||
const AGridDesc_AK0_M_AK1 a_grid_desc_k0_m_k1,
|
||||
const BGridDesc_BK0_N_BK1 b_grid_desc_k0_n_k1,
|
||||
const DsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
|
||||
ds_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
const EGridDesc_MBlock_MPerBlock_NBlock_NPerBlock
|
||||
e_grid_desc_mblock_mperblock_nblock_nperblock_,
|
||||
const AElementwiseOperation a_element_op,
|
||||
const BElementwiseOperation b_element_op,
|
||||
const CDEElementwiseOperation cde_element_op,
|
||||
const ComputePtrOffsetOfBatch compute_ptr_offset_of_batch,
|
||||
const Block2CTileMap block_2_ctile_map)
|
||||
{
|
||||
|
||||
#if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__))
|
||||
const index_t num_blocks_per_batch =
|
||||
__builtin_amdgcn_readfirstlane(get_grid_size() / batch_count);
|
||||
const index_t g_idx = __builtin_amdgcn_readfirstlane(get_block_1d_id() / num_blocks_per_batch);
|
||||
|
||||
const long_index_t a_batch_offset = __builtin_amdgcn_readfirstlane(
|
||||
static_cast<long_index_t>(compute_ptr_offset_of_batch.GetAPtrOffset(g_idx)));
|
||||
const long_index_t b_batch_offset = __builtin_amdgcn_readfirstlane(
|
||||
static_cast<long_index_t>(compute_ptr_offset_of_batch.GetBPtrOffset(g_idx)));
|
||||
const long_index_t e_batch_offset = __builtin_amdgcn_readfirstlane(
|
||||
static_cast<long_index_t>(compute_ptr_offset_of_batch.GetEPtrOffset(g_idx)));
|
||||
|
||||
const auto ds_batch_offset = compute_ptr_offset_of_batch.GetDsPtrOffset(g_idx);
|
||||
|
||||
__shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()];
|
||||
|
||||
FloatDsPointer p_ds_grid_grp;
|
||||
|
||||
static constexpr index_t NumDTensor =
|
||||
DsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock::Size();
|
||||
|
||||
static_for<0, NumDTensor, 1>{}(
|
||||
[&](auto i) { p_ds_grid_grp(i) = p_ds_grid[i] + ds_batch_offset[i]; });
|
||||
|
||||
GridwiseGemm::template Run<HasMainKBlockLoop>(p_a_grid + a_batch_offset,
|
||||
p_b_grid + b_batch_offset,
|
||||
p_ds_grid_grp,
|
||||
p_e_grid + e_batch_offset,
|
||||
p_shared,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
cde_element_op,
|
||||
a_grid_desc_k0_m_k1,
|
||||
b_grid_desc_k0_n_k1,
|
||||
ds_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
e_grid_desc_mblock_mperblock_nblock_nperblock_,
|
||||
block_2_ctile_map);
|
||||
#else
|
||||
ignore = p_a_grid;
|
||||
ignore = p_b_grid;
|
||||
ignore = p_ds_grid;
|
||||
ignore = p_e_grid;
|
||||
ignore = batch_count;
|
||||
ignore = a_grid_desc_k0_m_k1;
|
||||
ignore = b_grid_desc_k0_n_k1;
|
||||
ignore = ds_grid_desc_mblock_mperblock_nblock_nperblock;
|
||||
ignore = e_grid_desc_mblock_mperblock_nblock_nperblock_;
|
||||
ignore = a_element_op;
|
||||
ignore = b_element_op;
|
||||
ignore = cde_element_op;
|
||||
ignore = compute_ptr_offset_of_batch;
|
||||
ignore = block_2_ctile_map;
|
||||
#endif
|
||||
}
|
||||
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename DELayout,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename GemmAccDataType,
|
||||
typename CShuffleDataType,
|
||||
typename DsDataType,
|
||||
typename EDataType,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CDEElementwiseOperation,
|
||||
GemmSpecialization GemmSpec,
|
||||
index_t NumGemmKPrefetchStage,
|
||||
index_t BlockSize,
|
||||
index_t MPerBlock,
|
||||
index_t NPerBlock,
|
||||
index_t KPerBlock,
|
||||
index_t AK1,
|
||||
index_t BK1,
|
||||
index_t MPerXDL,
|
||||
index_t NPerXDL,
|
||||
index_t MXdlPerWave,
|
||||
index_t NXdlPerWave,
|
||||
typename ABlockTransferThreadClusterLengths_AK0_M_AK1,
|
||||
typename ABlockTransferThreadClusterArrangeOrder,
|
||||
typename ABlockTransferSrcAccessOrder,
|
||||
index_t ABlockTransferSrcVectorDim,
|
||||
index_t ABlockTransferSrcScalarPerVector,
|
||||
index_t ABlockTransferDstScalarPerVector_AK1,
|
||||
bool ABlockLdsExtraM,
|
||||
typename BBlockTransferThreadClusterLengths_BK0_N_BK1,
|
||||
typename BBlockTransferThreadClusterArrangeOrder,
|
||||
typename BBlockTransferSrcAccessOrder,
|
||||
index_t BBlockTransferSrcVectorDim,
|
||||
index_t BBlockTransferSrcScalarPerVector,
|
||||
index_t BBlockTransferDstScalarPerVector_BK1,
|
||||
bool BBlockLdsExtraN,
|
||||
index_t CShuffleMXdlPerWavePerShuffle,
|
||||
index_t CShuffleNXdlPerWavePerShuffle,
|
||||
typename CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
index_t CDEBlockTransferScalarPerVector_NPerBlock,
|
||||
LoopScheduler LoopSched = make_default_loop_scheduler()>
|
||||
struct DeviceBatchedGemmMultiDXdl : public DeviceBatchedGemmMultiD<ALayout,
|
||||
BLayout,
|
||||
DELayout,
|
||||
ADataType,
|
||||
BDataType,
|
||||
DsDataType,
|
||||
EDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CDEElementwiseOperation>
|
||||
{
|
||||
using DeviceOp = DeviceBatchedGemmMultiDXdl;
|
||||
|
||||
static constexpr index_t NumDTensor = DsDataType::Size();
|
||||
|
||||
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 auto MakeAGridDescriptor_AK0_M_AK1(index_t MRaw, index_t KRaw, index_t StrideA)
|
||||
{
|
||||
const auto a_grid_desc_mraw_kraw = [&]() {
|
||||
if constexpr(is_same_v<tensor_layout::gemm::RowMajor, ALayout>)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(MRaw, KRaw),
|
||||
make_tuple(StrideA, I1));
|
||||
}
|
||||
else if constexpr(is_same_v<tensor_layout::gemm::ColumnMajor, ALayout>)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(MRaw, KRaw),
|
||||
make_tuple(I1, StrideA));
|
||||
}
|
||||
}();
|
||||
|
||||
const auto M = math::integer_divide_ceil(MRaw, MPerBlock) * MPerBlock;
|
||||
const auto K = math::integer_divide_ceil(KRaw, KPerBlock) * KPerBlock;
|
||||
|
||||
const auto MPad = M - MRaw;
|
||||
const auto KPad = K - KRaw;
|
||||
|
||||
if constexpr(GemmSpec == GemmSpecialization::MKPadding ||
|
||||
GemmSpec == GemmSpecialization::MNKPadding)
|
||||
{
|
||||
// pad both M and K
|
||||
assert(K % AK1 == 0);
|
||||
|
||||
const auto AK0 = K / AK1;
|
||||
|
||||
const auto a_grid_desc_m_k =
|
||||
transform_tensor_descriptor(a_grid_desc_mraw_kraw,
|
||||
make_tuple(make_right_pad_transform(MRaw, MPad),
|
||||
make_right_pad_transform(KRaw, KPad)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}));
|
||||
|
||||
const auto a_grid_desc_ak0_m_ak1 =
|
||||
transform_tensor_descriptor(a_grid_desc_m_k,
|
||||
make_tuple(make_unmerge_transform(make_tuple(AK0, AK1)),
|
||||
make_pass_through_transform(M)),
|
||||
make_tuple(Sequence<1>{}, Sequence<0>{}),
|
||||
make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
|
||||
|
||||
return a_grid_desc_ak0_m_ak1;
|
||||
}
|
||||
else if constexpr(GemmSpec == GemmSpecialization::MPadding ||
|
||||
GemmSpec == GemmSpecialization::MNPadding)
|
||||
{
|
||||
// pad M, but not K
|
||||
assert(KRaw % AK1 == 0);
|
||||
|
||||
const auto AK0 = KRaw / AK1;
|
||||
|
||||
const auto a_grid_desc_ak0_m_ak1 =
|
||||
transform_tensor_descriptor(a_grid_desc_mraw_kraw,
|
||||
make_tuple(make_unmerge_transform(make_tuple(AK0, AK1)),
|
||||
make_right_pad_transform(MRaw, MPad)),
|
||||
make_tuple(Sequence<1>{}, Sequence<0>{}),
|
||||
make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
|
||||
|
||||
return a_grid_desc_ak0_m_ak1;
|
||||
}
|
||||
else if constexpr(GemmSpec == GemmSpecialization::KPadding ||
|
||||
GemmSpec == GemmSpecialization::NKPadding)
|
||||
{
|
||||
// pad K, but not M
|
||||
assert(K % AK1 == 0);
|
||||
|
||||
const auto AK0 = K / AK1;
|
||||
|
||||
const auto a_grid_desc_m_k = transform_tensor_descriptor(
|
||||
a_grid_desc_mraw_kraw,
|
||||
make_tuple(make_pass_through_transform(MRaw), make_right_pad_transform(KRaw, KPad)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}));
|
||||
|
||||
const auto a_grid_desc_ak0_m_ak1 =
|
||||
transform_tensor_descriptor(a_grid_desc_m_k,
|
||||
make_tuple(make_unmerge_transform(make_tuple(AK0, AK1)),
|
||||
make_pass_through_transform(MRaw)),
|
||||
make_tuple(Sequence<1>{}, Sequence<0>{}),
|
||||
make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
|
||||
|
||||
return a_grid_desc_ak0_m_ak1;
|
||||
}
|
||||
else
|
||||
{
|
||||
// not pad M or K
|
||||
assert(KRaw % AK1 == 0);
|
||||
|
||||
const auto AK0 = KRaw / AK1;
|
||||
|
||||
const auto a_grid_desc_ak0_m_ak1 =
|
||||
transform_tensor_descriptor(a_grid_desc_mraw_kraw,
|
||||
make_tuple(make_unmerge_transform(make_tuple(AK0, AK1)),
|
||||
make_pass_through_transform(MRaw)),
|
||||
make_tuple(Sequence<1>{}, Sequence<0>{}),
|
||||
make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
|
||||
|
||||
return a_grid_desc_ak0_m_ak1;
|
||||
}
|
||||
}
|
||||
|
||||
static auto MakeBGridDescriptor_BK0_N_BK1(index_t KRaw, index_t NRaw, index_t StrideB)
|
||||
{
|
||||
const auto b_grid_desc_nraw_kraw = [&]() {
|
||||
if constexpr(is_same<tensor_layout::gemm::RowMajor, BLayout>::value)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(NRaw, KRaw),
|
||||
make_tuple(I1, StrideB));
|
||||
}
|
||||
else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, BLayout>::value)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(NRaw, KRaw),
|
||||
make_tuple(StrideB, I1));
|
||||
}
|
||||
}();
|
||||
|
||||
const auto N = math::integer_divide_ceil(NRaw, NPerBlock) * NPerBlock;
|
||||
const auto K = math::integer_divide_ceil(KRaw, KPerBlock) * KPerBlock;
|
||||
|
||||
const auto NPad = N - NRaw;
|
||||
const auto KPad = K - KRaw;
|
||||
|
||||
if constexpr(GemmSpec == GemmSpecialization::NKPadding ||
|
||||
GemmSpec == GemmSpecialization::MNKPadding)
|
||||
{
|
||||
// pad both N and K
|
||||
assert(K % BK1 == 0);
|
||||
|
||||
const auto BK0 = K / BK1;
|
||||
|
||||
const auto b_grid_desc_n_k =
|
||||
transform_tensor_descriptor(b_grid_desc_nraw_kraw,
|
||||
make_tuple(make_right_pad_transform(NRaw, NPad),
|
||||
make_right_pad_transform(KRaw, KPad)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}));
|
||||
|
||||
const auto b_grid_desc_bk0_n_bk1 =
|
||||
transform_tensor_descriptor(b_grid_desc_n_k,
|
||||
make_tuple(make_unmerge_transform(make_tuple(BK0, BK1)),
|
||||
make_pass_through_transform(N)),
|
||||
make_tuple(Sequence<1>{}, Sequence<0>{}),
|
||||
make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
|
||||
|
||||
return b_grid_desc_bk0_n_bk1;
|
||||
}
|
||||
else if constexpr(GemmSpec == GemmSpecialization::NPadding ||
|
||||
GemmSpec == GemmSpecialization::MNPadding)
|
||||
{
|
||||
// pad N, but not K
|
||||
assert(KRaw % BK1 == 0);
|
||||
|
||||
const auto BK0 = KRaw / BK1;
|
||||
|
||||
const auto b_grid_desc_bk0_n_bk1 =
|
||||
transform_tensor_descriptor(b_grid_desc_nraw_kraw,
|
||||
make_tuple(make_unmerge_transform(make_tuple(BK0, BK1)),
|
||||
make_right_pad_transform(NRaw, NPad)),
|
||||
make_tuple(Sequence<1>{}, Sequence<0>{}),
|
||||
make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
|
||||
|
||||
return b_grid_desc_bk0_n_bk1;
|
||||
}
|
||||
else if constexpr(GemmSpec == GemmSpecialization::KPadding ||
|
||||
GemmSpec == GemmSpecialization::MKPadding)
|
||||
{
|
||||
// pad K, but not N
|
||||
assert(K % BK1 == 0);
|
||||
|
||||
const auto BK0 = K / BK1;
|
||||
|
||||
const auto b_grid_desc_n_k = transform_tensor_descriptor(
|
||||
b_grid_desc_nraw_kraw,
|
||||
make_tuple(make_pass_through_transform(NRaw), make_right_pad_transform(KRaw, KPad)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}));
|
||||
|
||||
const auto b_grid_desc_bk0_n_bk1 =
|
||||
transform_tensor_descriptor(b_grid_desc_n_k,
|
||||
make_tuple(make_unmerge_transform(make_tuple(BK0, BK1)),
|
||||
make_pass_through_transform(NRaw)),
|
||||
make_tuple(Sequence<1>{}, Sequence<0>{}),
|
||||
make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
|
||||
|
||||
return b_grid_desc_bk0_n_bk1;
|
||||
}
|
||||
else
|
||||
{
|
||||
// not pad N or K
|
||||
assert(KRaw % BK1 == 0);
|
||||
|
||||
const auto BK0 = KRaw / BK1;
|
||||
|
||||
const auto b_grid_desc_bk0_n_bk1 =
|
||||
transform_tensor_descriptor(b_grid_desc_nraw_kraw,
|
||||
make_tuple(make_unmerge_transform(make_tuple(BK0, BK1)),
|
||||
make_pass_through_transform(NRaw)),
|
||||
make_tuple(Sequence<1>{}, Sequence<0>{}),
|
||||
make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
|
||||
|
||||
return b_grid_desc_bk0_n_bk1;
|
||||
}
|
||||
}
|
||||
|
||||
static auto MakeEGridDescriptor_M_N(index_t MRaw, index_t NRaw, index_t StrideE)
|
||||
{
|
||||
const auto c_grid_desc_mraw_nraw = [&]() {
|
||||
if constexpr(is_same<tensor_layout::gemm::RowMajor, DELayout>::value)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(MRaw, NRaw),
|
||||
make_tuple(StrideE, I1));
|
||||
}
|
||||
else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, DELayout>::value)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(MRaw, NRaw),
|
||||
make_tuple(I1, StrideE));
|
||||
}
|
||||
}();
|
||||
|
||||
const auto M = math::integer_divide_ceil(MRaw, MPerBlock) * MPerBlock;
|
||||
const auto N = math::integer_divide_ceil(NRaw, NPerBlock) * NPerBlock;
|
||||
|
||||
const auto MPad = M - MRaw;
|
||||
const auto NPad = N - NRaw;
|
||||
|
||||
if constexpr(GemmSpec == GemmSpecialization::MNPadding ||
|
||||
GemmSpec == GemmSpecialization::MNKPadding)
|
||||
{
|
||||
// pad M and N
|
||||
return transform_tensor_descriptor(c_grid_desc_mraw_nraw,
|
||||
make_tuple(make_right_pad_transform(MRaw, MPad),
|
||||
make_right_pad_transform(NRaw, NPad)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}));
|
||||
}
|
||||
else if constexpr(GemmSpec == GemmSpecialization::MPadding ||
|
||||
GemmSpec == GemmSpecialization::MKPadding)
|
||||
{
|
||||
// pad M, but not N
|
||||
return transform_tensor_descriptor(
|
||||
c_grid_desc_mraw_nraw,
|
||||
make_tuple(make_right_pad_transform(MRaw, MPad), make_pass_through_transform(NRaw)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}));
|
||||
}
|
||||
else if constexpr(GemmSpec == GemmSpecialization::NPadding ||
|
||||
GemmSpec == GemmSpecialization::NKPadding)
|
||||
{
|
||||
// pad N, but not M
|
||||
return transform_tensor_descriptor(
|
||||
c_grid_desc_mraw_nraw,
|
||||
make_tuple(make_pass_through_transform(MRaw), make_right_pad_transform(NRaw, NPad)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}));
|
||||
}
|
||||
else
|
||||
{
|
||||
// not pad M or N
|
||||
return c_grid_desc_mraw_nraw;
|
||||
}
|
||||
}
|
||||
|
||||
using AGridDesc_AK0_M_AK1 = decltype(MakeAGridDescriptor_AK0_M_AK1(1, 1, 1));
|
||||
using BGridDesc_BK0_N_BK1 = decltype(MakeBGridDescriptor_BK0_N_BK1(1, 1, 1));
|
||||
using EGridDesc_M_N = decltype(MakeEGridDescriptor_M_N(1, 1, 1));
|
||||
|
||||
struct ComputePtrOffsetOfStridedBatch
|
||||
{
|
||||
ComputePtrOffsetOfStridedBatch(index_t BatchStrideA,
|
||||
index_t BatchStrideB,
|
||||
std::array<ck::index_t, NumDTensor> BatchStrideDs,
|
||||
index_t BatchStrideE)
|
||||
: BatchStrideA_(BatchStrideA),
|
||||
BatchStrideB_(BatchStrideB),
|
||||
BatchStrideDs_(BatchStrideDs),
|
||||
BatchStrideE_(BatchStrideE)
|
||||
{
|
||||
}
|
||||
|
||||
__host__ __device__ constexpr long_index_t GetAPtrOffset(index_t g_idx) const
|
||||
{
|
||||
return g_idx * static_cast<long_index_t>(BatchStrideA_);
|
||||
}
|
||||
|
||||
__host__ __device__ constexpr long_index_t GetBPtrOffset(index_t g_idx) const
|
||||
{
|
||||
return g_idx * static_cast<long_index_t>(BatchStrideB_);
|
||||
}
|
||||
|
||||
__host__ __device__ constexpr auto GetDsPtrOffset(index_t g_idx) const
|
||||
{
|
||||
std::array<long_index_t, NumDTensor> ds_offset;
|
||||
static_for<0, NumDTensor, 1>{}([&](auto i) {
|
||||
ds_offset[i] = g_idx * static_cast<long_index_t>(BatchStrideDs_[i]);
|
||||
});
|
||||
return ds_offset;
|
||||
}
|
||||
|
||||
__host__ __device__ constexpr long_index_t GetEPtrOffset(index_t g_idx) const
|
||||
{
|
||||
return g_idx * static_cast<long_index_t>(BatchStrideE_);
|
||||
}
|
||||
|
||||
private:
|
||||
index_t BatchStrideA_;
|
||||
index_t BatchStrideB_;
|
||||
std::array<ck::index_t, NumDTensor> BatchStrideDs_;
|
||||
index_t BatchStrideE_;
|
||||
};
|
||||
|
||||
using GridwiseGemm = GridwiseGemmMultipleD_k0mk1_k0nk1_mn_xdl_cshuffle<
|
||||
ADataType, // TODO: distinguish A/B datatype
|
||||
GemmAccDataType,
|
||||
CShuffleDataType,
|
||||
DsDataType,
|
||||
EDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CDEElementwiseOperation,
|
||||
InMemoryDataOperationEnum::Set,
|
||||
AGridDesc_AK0_M_AK1,
|
||||
BGridDesc_BK0_N_BK1,
|
||||
EGridDesc_M_N,
|
||||
NumGemmKPrefetchStage,
|
||||
BlockSize,
|
||||
MPerBlock,
|
||||
NPerBlock,
|
||||
KPerBlock,
|
||||
AK1,
|
||||
BK1,
|
||||
MPerXDL,
|
||||
NPerXDL,
|
||||
MXdlPerWave,
|
||||
NXdlPerWave,
|
||||
ABlockTransferThreadClusterLengths_AK0_M_AK1,
|
||||
ABlockTransferThreadClusterArrangeOrder,
|
||||
ABlockTransferSrcAccessOrder,
|
||||
ABlockTransferSrcVectorDim,
|
||||
ABlockTransferSrcScalarPerVector,
|
||||
ABlockTransferDstScalarPerVector_AK1,
|
||||
false,
|
||||
ABlockLdsExtraM,
|
||||
BBlockTransferThreadClusterLengths_BK0_N_BK1,
|
||||
BBlockTransferThreadClusterArrangeOrder,
|
||||
BBlockTransferSrcAccessOrder,
|
||||
BBlockTransferSrcVectorDim,
|
||||
BBlockTransferSrcScalarPerVector,
|
||||
BBlockTransferDstScalarPerVector_BK1,
|
||||
false,
|
||||
BBlockLdsExtraN,
|
||||
CShuffleMXdlPerWavePerShuffle,
|
||||
CShuffleNXdlPerWavePerShuffle,
|
||||
CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CDEBlockTransferScalarPerVector_NPerBlock,
|
||||
LoopSched>;
|
||||
|
||||
using CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock = decltype(
|
||||
GridwiseGemm::MakeEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(EGridDesc_M_N{}));
|
||||
using Block2CTileMap = typename GridwiseGemm::DefaultBlock2ETileMap;
|
||||
|
||||
// Argument
|
||||
struct Argument : public BaseArgument
|
||||
{
|
||||
Argument(const void* p_a_grid,
|
||||
const void* p_b_grid,
|
||||
std::array<const void*, NumDTensor> p_ds_grid,
|
||||
void* p_e_grid,
|
||||
index_t M,
|
||||
index_t N,
|
||||
index_t K,
|
||||
index_t StrideA,
|
||||
index_t StrideB,
|
||||
std::array<ck::index_t, NumDTensor> StrideDs,
|
||||
index_t StrideE,
|
||||
index_t BatchStrideA,
|
||||
index_t BatchStrideB,
|
||||
std::array<ck::index_t, NumDTensor> BatchStrideDs,
|
||||
index_t BatchStrideE,
|
||||
index_t Batch,
|
||||
index_t M01,
|
||||
index_t N01,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CDEElementwiseOperation cde_element_op)
|
||||
: p_a_grid_{static_cast<const ADataType*>(p_a_grid)},
|
||||
p_b_grid_{static_cast<const BDataType*>(p_b_grid)},
|
||||
p_ds_grid_{}, // FIXME
|
||||
p_e_grid_{static_cast<EDataType*>(p_e_grid)},
|
||||
Batch_(Batch),
|
||||
a_grid_desc_ak0_m_ak1_{
|
||||
DeviceBatchedGemmMultiDXdl::MakeAGridDescriptor_AK0_M_AK1(M, K, StrideA)},
|
||||
b_grid_desc_bk0_n_bk1_{
|
||||
DeviceBatchedGemmMultiDXdl::MakeBGridDescriptor_BK0_N_BK1(K, N, StrideB)},
|
||||
ds_grid_desc_mblock_mperblock_nblock_nperblock_{},
|
||||
e_grid_desc_m_n_{DeviceBatchedGemmMultiDXdl::MakeEGridDescriptor_M_N(M, N, StrideE)},
|
||||
e_grid_desc_mblock_mperblock_nblock_nperblock_{},
|
||||
compute_ptr_offset_of_batch_{BatchStrideA, BatchStrideB, BatchStrideDs, BatchStrideE},
|
||||
block_2_ctile_map_{GridwiseGemm::MakeDefaultBlock2ETileMap(e_grid_desc_m_n_)},
|
||||
M01_{M01},
|
||||
N01_{N01},
|
||||
a_element_op_{a_element_op},
|
||||
b_element_op_{b_element_op},
|
||||
cde_element_op_{cde_element_op}
|
||||
{
|
||||
if(GridwiseGemm::CheckValidity(a_grid_desc_ak0_m_ak1_,
|
||||
b_grid_desc_bk0_n_bk1_,
|
||||
e_grid_desc_m_n_,
|
||||
block_2_ctile_map_))
|
||||
{
|
||||
e_grid_desc_mblock_mperblock_nblock_nperblock_ =
|
||||
GridwiseGemm::MakeEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
e_grid_desc_m_n_);
|
||||
|
||||
static_for<0, NumDTensor, 1>{}([&](auto i) {
|
||||
using DDataType = remove_cvref_t<tuple_element_t<i.value, DsDataType>>;
|
||||
|
||||
p_ds_grid_(i) = static_cast<const DDataType*>(p_ds_grid[i]);
|
||||
|
||||
const auto d_grid_desc_m_n =
|
||||
DeviceOp::MakeEGridDescriptor_M_N(M, N, StrideDs[i]);
|
||||
|
||||
ds_grid_desc_mblock_mperblock_nblock_nperblock_(i) =
|
||||
GridwiseGemm::MakeEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
d_grid_desc_m_n);
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// private:
|
||||
const ADataType* p_a_grid_;
|
||||
const BDataType* p_b_grid_;
|
||||
typename GridwiseGemm::DsGridPointer p_ds_grid_;
|
||||
EDataType* p_e_grid_;
|
||||
index_t Batch_;
|
||||
|
||||
AGridDesc_AK0_M_AK1 a_grid_desc_ak0_m_ak1_;
|
||||
BGridDesc_BK0_N_BK1 b_grid_desc_bk0_n_bk1_;
|
||||
StaticallyIndexedArray<
|
||||
typename GridwiseGemm::EGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
NumDTensor>
|
||||
ds_grid_desc_mblock_mperblock_nblock_nperblock_; // FIXME: Ds desc may be of different
|
||||
// type from E
|
||||
EGridDesc_M_N e_grid_desc_m_n_;
|
||||
typename GridwiseGemm::EGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
|
||||
e_grid_desc_mblock_mperblock_nblock_nperblock_;
|
||||
|
||||
ComputePtrOffsetOfStridedBatch compute_ptr_offset_of_batch_;
|
||||
Block2CTileMap block_2_ctile_map_;
|
||||
index_t M01_;
|
||||
index_t N01_;
|
||||
AElementwiseOperation a_element_op_;
|
||||
BElementwiseOperation b_element_op_;
|
||||
CDEElementwiseOperation cde_element_op_;
|
||||
};
|
||||
|
||||
// Invoker
|
||||
struct Invoker : public BaseInvoker
|
||||
{
|
||||
using Argument = DeviceBatchedGemmMultiDXdl::Argument;
|
||||
|
||||
float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
|
||||
{
|
||||
{
|
||||
std::cout << "arg.a_grid_desc_ak0_m_ak1_{"
|
||||
<< arg.a_grid_desc_ak0_m_ak1_.GetLength(I0) << ", "
|
||||
<< arg.a_grid_desc_ak0_m_ak1_.GetLength(I1) << ", "
|
||||
<< arg.a_grid_desc_ak0_m_ak1_.GetLength(I2) << "}" << std::endl;
|
||||
|
||||
std::cout << "arg.b_grid_desc_bk0_n_bk1_{"
|
||||
<< arg.b_grid_desc_bk0_n_bk1_.GetLength(I0) << ", "
|
||||
<< arg.b_grid_desc_bk0_n_bk1_.GetLength(I1) << ", "
|
||||
<< arg.b_grid_desc_bk0_n_bk1_.GetLength(I2) << "}" << std::endl;
|
||||
|
||||
std::cout << "arg.e_grid_desc_m_n_{" << arg.e_grid_desc_m_n_.GetLength(I0) << ", "
|
||||
<< arg.e_grid_desc_m_n_.GetLength(I1) << "}" << std::endl;
|
||||
}
|
||||
|
||||
if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_ak0_m_ak1_,
|
||||
arg.b_grid_desc_bk0_n_bk1_,
|
||||
arg.e_grid_desc_m_n_,
|
||||
arg.block_2_ctile_map_))
|
||||
{
|
||||
throw std::runtime_error(
|
||||
"wrong! GridwiseBatchedGemm_km_kn_m0m1n0n1_xdlops_v2r3 has invalid setting");
|
||||
}
|
||||
|
||||
const index_t grid_size =
|
||||
arg.block_2_ctile_map_.CalculateGridSize(arg.e_grid_desc_m_n_) * arg.Batch_;
|
||||
|
||||
const auto K =
|
||||
arg.a_grid_desc_ak0_m_ak1_.GetLength(I0) * arg.a_grid_desc_ak0_m_ak1_.GetLength(I2);
|
||||
|
||||
auto launch_kernel = [&](auto has_main_k_block_loop) {
|
||||
constexpr bool has_main_loop = has_main_k_block_loop.value;
|
||||
|
||||
const auto kernel = kernel_batched_gemm_xdl<
|
||||
GridwiseGemm,
|
||||
ADataType, // TODO: distiguish A/B datatype
|
||||
typename GridwiseGemm::DsGridPointer,
|
||||
EDataType,
|
||||
DeviceOp::AGridDesc_AK0_M_AK1,
|
||||
DeviceOp::BGridDesc_BK0_N_BK1,
|
||||
ck::StaticallyIndexedArray<
|
||||
typename GridwiseGemm::EGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
NumDTensor>,
|
||||
typename GridwiseGemm::EGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CDEElementwiseOperation,
|
||||
ComputePtrOffsetOfStridedBatch,
|
||||
remove_reference_t<Block2CTileMap>,
|
||||
has_main_loop>;
|
||||
|
||||
return launch_and_time_kernel(stream_config,
|
||||
kernel,
|
||||
dim3(grid_size),
|
||||
dim3(BlockSize),
|
||||
0,
|
||||
arg.p_a_grid_,
|
||||
arg.p_b_grid_,
|
||||
arg.p_ds_grid_,
|
||||
arg.p_e_grid_,
|
||||
arg.Batch_,
|
||||
arg.a_grid_desc_ak0_m_ak1_,
|
||||
arg.b_grid_desc_bk0_n_bk1_,
|
||||
arg.ds_grid_desc_mblock_mperblock_nblock_nperblock_,
|
||||
arg.e_grid_desc_mblock_mperblock_nblock_nperblock_,
|
||||
arg.a_element_op_,
|
||||
arg.b_element_op_,
|
||||
arg.cde_element_op_,
|
||||
arg.compute_ptr_offset_of_batch_,
|
||||
arg.block_2_ctile_map_);
|
||||
};
|
||||
|
||||
float ave_time = 0;
|
||||
|
||||
if(GridwiseGemm::CalculateHasMainKBlockLoop(K))
|
||||
{
|
||||
ave_time = launch_kernel(integral_constant<bool, true>{});
|
||||
}
|
||||
else
|
||||
{
|
||||
ave_time = launch_kernel(integral_constant<bool, false>{});
|
||||
}
|
||||
|
||||
return ave_time;
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
float Run(const BaseArgument* p_arg,
|
||||
const StreamConfig& stream_config = StreamConfig{}) override
|
||||
{
|
||||
return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
|
||||
}
|
||||
};
|
||||
|
||||
static constexpr bool IsValidCompilationParameter()
|
||||
{
|
||||
// TODO: properly implement this check
|
||||
return true;
|
||||
}
|
||||
|
||||
static bool IsSupportedArgument(const Argument& arg)
|
||||
{
|
||||
return GridwiseGemm::CheckValidity(arg.a_grid_desc_ak0_m_ak1_,
|
||||
arg.b_grid_desc_bk0_n_bk1_,
|
||||
arg.e_grid_desc_m_n_,
|
||||
arg.block_2_ctile_map_);
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
bool IsSupportedArgument(const BaseArgument* p_arg) override
|
||||
{
|
||||
return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
|
||||
}
|
||||
|
||||
static auto MakeArgument(const void* p_a,
|
||||
const void* p_b,
|
||||
std::array<const void*, NumDTensor> p_ds,
|
||||
void* p_c,
|
||||
index_t M,
|
||||
index_t N,
|
||||
index_t K,
|
||||
index_t StrideA,
|
||||
index_t StrideB,
|
||||
std::array<index_t, NumDTensor> StrideDs,
|
||||
index_t StrideE,
|
||||
index_t BatchStrideA,
|
||||
index_t BatchStrideB,
|
||||
std::array<ck::index_t, NumDTensor> BatchStrideDs,
|
||||
index_t BatchStrideE,
|
||||
index_t Batch,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CDEElementwiseOperation cde_element_op)
|
||||
{
|
||||
return Argument{p_a,
|
||||
p_b,
|
||||
p_ds,
|
||||
p_c,
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
StrideA,
|
||||
StrideB,
|
||||
StrideDs,
|
||||
StrideE,
|
||||
BatchStrideA,
|
||||
BatchStrideB,
|
||||
BatchStrideDs,
|
||||
BatchStrideE,
|
||||
Batch,
|
||||
1,
|
||||
1,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
cde_element_op};
|
||||
}
|
||||
|
||||
static auto MakeInvoker() { return Invoker{}; }
|
||||
|
||||
// polymorphic
|
||||
std::unique_ptr<BaseArgument>
|
||||
MakeArgumentPointer(const void* p_a,
|
||||
const void* p_b,
|
||||
std::array<const void*, NumDTensor> p_ds,
|
||||
void* p_c,
|
||||
index_t M,
|
||||
index_t N,
|
||||
index_t K,
|
||||
index_t StrideA,
|
||||
index_t StrideB,
|
||||
std::array<ck::index_t, NumDTensor> StrideDs,
|
||||
index_t StrideE,
|
||||
index_t BatchStrideA,
|
||||
index_t BatchStrideB,
|
||||
std::array<ck::index_t, NumDTensor> BatchStrideDs,
|
||||
index_t BatchStrideE,
|
||||
index_t Batch,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CDEElementwiseOperation cde_element_op) override
|
||||
{
|
||||
return std::make_unique<Argument>(p_a,
|
||||
p_b,
|
||||
p_ds,
|
||||
p_c,
|
||||
M,
|
||||
N,
|
||||
K,
|
||||
StrideA,
|
||||
StrideB,
|
||||
StrideDs,
|
||||
StrideE,
|
||||
BatchStrideA,
|
||||
BatchStrideB,
|
||||
BatchStrideDs,
|
||||
BatchStrideE,
|
||||
Batch,
|
||||
1,
|
||||
1,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
cde_element_op);
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
|
||||
{
|
||||
return std::make_unique<Invoker>(Invoker{});
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
std::string GetTypeString() const override
|
||||
{
|
||||
auto str = std::stringstream();
|
||||
|
||||
// clang-format off
|
||||
str << "DeviceBatchedGemmMultiDXdl"
|
||||
<< "<"
|
||||
<< BlockSize << ", "
|
||||
<< MPerBlock << ", "
|
||||
<< NPerBlock << ", "
|
||||
<< KPerBlock
|
||||
<< AK1 << ", "
|
||||
<< BK1 << ", "
|
||||
<< getGemmSpecializationString(GemmSpec)
|
||||
<< ">";
|
||||
// clang-format on
|
||||
|
||||
return str.str();
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
Reference in New Issue
Block a user