mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-05 14:11:29 +00:00
Gemm+Reduce Fusion (#128)
* add gridwise gemm v4r1 * rename * adding gemm+reduce * adding gemm+reduce * adding gemm+reduce * adding gemm+reduce * use sfc in shuffling * remove hardcode * remove hardcode * refactor * fix build * adding gemm+reduce * adding gemm+reduce * adding gemm+reduce * adding gemm+reduce * adding gemm+reduce * format * clean * adding gemm+reduce * adding profiler for gemm+reduce * adding gemm+reduce profiler * fix build * clean up * gemm+reduce * fix build * update DeviceGemm_Xdl_CShuffle; update enum to enum class * clean up * add test for gemm+reduce * clean up * refactor * fix build * fix build
This commit is contained in:
Chao Liu
@@ -5,7 +5,7 @@ namespace ck {
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namespace tensor_operation {
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namespace device {
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enum ConvolutionBackwardDataSpecialization_t
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enum struct ConvolutionBackwardDataSpecialization_t
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{
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Default,
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Filter1x1Stride1Pad0,
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@@ -7,7 +7,7 @@ namespace ck {
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namespace tensor_operation {
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namespace device {
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enum ConvolutionForwardSpecialization_t
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enum struct ConvolutionForwardSpecialization_t
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{
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Default,
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Filter1x1Pad0,
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@@ -19,10 +19,10 @@ inline std::string getConvFwdSpecializationStr(const ConvolutionForwardSpecializ
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{
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switch(s)
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{
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case Default: return "Default";
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case Filter1x1Pad0: return "Filter1x1Pad0";
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case Filter1x1Stride1Pad0: return "Filter1x1Stride1Pad0";
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case OddC: return "OddC";
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case ConvolutionForwardSpecialization_t::Default: return "Default";
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case ConvolutionForwardSpecialization_t::Filter1x1Pad0: return "Filter1x1Pad0";
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case ConvolutionForwardSpecialization_t::Filter1x1Stride1Pad0: return "Filter1x1Stride1Pad0";
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case ConvolutionForwardSpecialization_t::OddC: return "OddC";
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default: return "Unrecognized specialization!";
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}
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}
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@@ -207,41 +207,28 @@ struct DeviceConv3dFwdXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho_Wo_
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const index_t Ho = output_spatial_lengths[1];
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const index_t Wo = output_spatial_lengths[2];
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if constexpr(ConvForwardSpecialization ==
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ConvolutionForwardSpecialization_t::Filter1x1Stride1Pad0)
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{
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static_assert(ConvForwardSpecialization == -1, "Not implemented!");
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}
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else if constexpr(ConvForwardSpecialization ==
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ConvolutionForwardSpecialization_t::Filter1x1Pad0)
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{
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static_assert(ConvForwardSpecialization == -1, "Not implemented!");
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}
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else
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{
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const auto in_desc_n_di_hi_wi_c =
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make_naive_tensor_descriptor_packed(make_tuple(N, Di, Hi, Wi, C));
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const auto wei_desc_k_z_y_x_c =
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make_naive_tensor_descriptor_packed(make_tuple(K, Z, Y, X, C));
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const auto out_desc_n_do_ho_wo_k =
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make_naive_tensor_descriptor_packed(make_tuple(N, Do, Ho, Wo, K));
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static_assert(ConvForwardSpecialization == ConvolutionForwardSpecialization_t::Default,
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"Wrong! This specialization not implemented!");
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const auto descs =
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transform_forward_convolution3d_into_gemm_v4r4r4_ndhwc_kzyxc_ndhwk_pad(
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in_desc_n_di_hi_wi_c,
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wei_desc_k_z_y_x_c,
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out_desc_n_do_ho_wo_k,
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make_tuple(
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conv_filter_strides[0], conv_filter_strides[1], conv_filter_strides[2]),
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make_tuple(conv_filter_dilations[0],
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conv_filter_dilations[1],
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conv_filter_dilations[2]),
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make_tuple(input_left_pads[0], input_left_pads[1], input_left_pads[2]),
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make_tuple(input_right_pads[0], input_right_pads[1], input_right_pads[2]),
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Number<K1>{});
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const auto in_desc_n_di_hi_wi_c =
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make_naive_tensor_descriptor_packed(make_tuple(N, Di, Hi, Wi, C));
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const auto wei_desc_k_z_y_x_c =
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make_naive_tensor_descriptor_packed(make_tuple(K, Z, Y, X, C));
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const auto out_desc_n_do_ho_wo_k =
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make_naive_tensor_descriptor_packed(make_tuple(N, Do, Ho, Wo, K));
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return descs;
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}
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const auto descs = transform_forward_convolution3d_into_gemm_v4r4r4_ndhwc_kzyxc_ndhwk_pad(
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in_desc_n_di_hi_wi_c,
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wei_desc_k_z_y_x_c,
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out_desc_n_do_ho_wo_k,
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make_tuple(conv_filter_strides[0], conv_filter_strides[1], conv_filter_strides[2]),
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make_tuple(
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conv_filter_dilations[0], conv_filter_dilations[1], conv_filter_dilations[2]),
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make_tuple(input_left_pads[0], input_left_pads[1], input_left_pads[2]),
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make_tuple(input_right_pads[0], input_right_pads[1], input_right_pads[2]),
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Number<K1>{});
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return descs;
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}
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using ABCGridDescs = remove_cvref_t<decltype(MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N(
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@@ -1,6 +1,4 @@
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#ifndef DEVICE_GEMM_HPP
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#define DEVICE_GEMM_HPP
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#pragma once
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#include <iostream>
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#include "device_base.hpp"
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@@ -14,35 +12,6 @@ struct GemmShape
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ck::index_t StrideA, StrideB, StrideC;
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};
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template <typename AElementwiseOperation,
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typename BElementwiseOperation,
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typename CElementwiseOperation>
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struct DeviceGemmBias : public BaseOperator
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{
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virtual std::unique_ptr<BaseArgument>
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MakeArgumentPointer(const void* p_a,
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const void* p_b,
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const void* p_bias,
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void* p_c,
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ck::index_t M,
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ck::index_t N,
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ck::index_t K,
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ck::index_t StrideA,
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ck::index_t StrideB,
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ck::index_t StrideC,
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AElementwiseOperation a_element_op,
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BElementwiseOperation b_element_op,
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CElementwiseOperation 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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typename BElementwiseOperation,
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typename CElementwiseOperation>
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using DeviceGemmBiasPtr = std::unique_ptr<
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DeviceGemmBias<AElementwiseOperation, BElementwiseOperation, CElementwiseOperation>>;
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template <typename AElementwiseOperation,
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typename BElementwiseOperation,
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typename CElementwiseOperation>
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@@ -97,4 +66,3 @@ using DeviceGroupedGemmPtr = std::unique_ptr<
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} // namespace device
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} // namespace tensor_operation
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} // namespace ck
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#endif
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40
include/ck/tensor_operation/gpu/device/device_gemm_bias.hpp
Normal file
40
include/ck/tensor_operation/gpu/device/device_gemm_bias.hpp
Normal file
@@ -0,0 +1,40 @@
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#pragma once
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#include <iostream>
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#include "device_base.hpp"
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namespace ck {
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namespace tensor_operation {
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namespace device {
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template <typename AElementwiseOperation,
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typename BElementwiseOperation,
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typename CElementwiseOperation>
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struct DeviceGemmBias : public BaseOperator
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{
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virtual std::unique_ptr<BaseArgument>
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MakeArgumentPointer(const void* p_a,
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const void* p_b,
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const void* p_bias,
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void* p_c,
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ck::index_t M,
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ck::index_t N,
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ck::index_t K,
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ck::index_t StrideA,
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ck::index_t StrideB,
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ck::index_t StrideC,
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AElementwiseOperation a_element_op,
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BElementwiseOperation b_element_op,
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CElementwiseOperation 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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typename BElementwiseOperation,
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typename CElementwiseOperation>
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using DeviceGemmBiasPtr = std::unique_ptr<
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DeviceGemmBias<AElementwiseOperation, BElementwiseOperation, CElementwiseOperation>>;
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} // namespace device
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} // namespace tensor_operation
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} // namespace ck
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@@ -0,0 +1,49 @@
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#pragma once
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#include <iostream>
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#include "device_base.hpp"
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namespace ck {
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namespace tensor_operation {
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namespace device {
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template <typename AElementwiseOperation,
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typename BElementwiseOperation,
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typename CElementwiseOperation,
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typename D0ReduceOperation,
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typename D1ReduceOperation>
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struct DeviceGemmReduce : public BaseOperator
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{
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virtual std::unique_ptr<BaseArgument> MakeArgumentPointer(const void* p_a,
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const void* p_b,
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void* p_c,
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void* p_d0,
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void* p_d1,
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ck::index_t M,
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ck::index_t N,
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ck::index_t K,
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ck::index_t StrideA,
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ck::index_t StrideB,
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ck::index_t StrideC,
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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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D0ReduceOperation d0_reduce_op,
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D1ReduceOperation d1_reduce_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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typename BElementwiseOperation,
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typename CElementwiseOperation,
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typename D0ReduceOperation,
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typename D1ReduceOperation>
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using DeviceGemmReducePtr = std::unique_ptr<DeviceGemmReduce<AElementwiseOperation,
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BElementwiseOperation,
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CElementwiseOperation,
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D0ReduceOperation,
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D1ReduceOperation>>;
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} // namespace device
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} // namespace tensor_operation
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} // namespace ck
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@@ -0,0 +1,746 @@
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#pragma once
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#include <iostream>
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#include <sstream>
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#include "device.hpp"
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#include "device_gemm_reduce.hpp"
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#include "common_header.hpp"
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#include "tensor_layout.hpp"
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#include "tensor_descriptor.hpp"
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#include "tensor_descriptor_helper.hpp"
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#include "gridwise_gemm_reduce_xdl_cshuffle_v1.hpp"
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#include "gemm_specialization.hpp"
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namespace ck {
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namespace tensor_operation {
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namespace device {
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template <typename ALayout,
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typename BLayout,
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typename CLayout,
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typename ADataType,
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typename BDataType,
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typename CDataType,
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typename GemmAccDataType,
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typename CShuffleDataType,
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typename ReduceAccDataType,
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typename DDataType,
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typename AElementwiseOperation,
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typename BElementwiseOperation,
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typename CElementwiseOperation,
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typename D0ReduceOperation,
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typename D1ReduceOperation,
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GemmSpecialization_t GemmSpecialization,
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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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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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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 CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
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index_t CShuffleBlockTransferScalarPerVector_NPerBlock,
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typename CReduceThreadClusterLengths_MPerBlock_NPerBlock,
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index_t CReduceThreadLds2VGprCopySrcDstScalarPerVector_NPerBlock,
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index_t CReduceThreadVgpr2GlobalCopySrcDstScalarPerVector_MPerBlock>
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struct DeviceGemmReduce_Xdl_CShuffle : public DeviceGemmReduce<AElementwiseOperation,
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BElementwiseOperation,
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CElementwiseOperation,
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D0ReduceOperation,
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D1ReduceOperation>
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{
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using DeviceOp = DeviceGemmReduce_Xdl_CShuffle;
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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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static auto MakeAGridDescriptor_AK0_M_AK1(index_t MRaw, index_t KRaw, index_t StrideA)
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{
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const auto a_grid_desc_mraw_kraw = [&]() {
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if constexpr(is_same_v<tensor_layout::gemm::RowMajor, ALayout>)
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{
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return make_naive_tensor_descriptor(make_tuple(MRaw, KRaw),
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make_tuple(StrideA, I1));
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}
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else if constexpr(is_same_v<tensor_layout::gemm::ColumnMajor, ALayout>)
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{
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return make_naive_tensor_descriptor(make_tuple(MRaw, KRaw),
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make_tuple(I1, StrideA));
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}
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}();
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const auto M = math::integer_divide_ceil(MRaw, MPerBlock) * MPerBlock;
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const auto K = math::integer_divide_ceil(KRaw, KPerBlock) * KPerBlock;
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const auto MPad = M - MRaw;
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const auto KPad = K - KRaw;
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if constexpr(GemmSpecialization == GemmSpecialization_t::MKPadding ||
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GemmSpecialization == GemmSpecialization_t::MNKPadding)
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{
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// pad both M and K
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assert(K % AK1 == 0);
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const auto AK0 = K / AK1;
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const auto a_grid_desc_m_k =
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transform_tensor_descriptor(a_grid_desc_mraw_kraw,
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make_tuple(make_right_pad_transform(MRaw, MPad),
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make_right_pad_transform(KRaw, KPad)),
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make_tuple(Sequence<0>{}, Sequence<1>{}),
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make_tuple(Sequence<0>{}, Sequence<1>{}));
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const auto a_grid_desc_ak0_m_ak1 =
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transform_tensor_descriptor(a_grid_desc_m_k,
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make_tuple(make_unmerge_transform(make_tuple(AK0, AK1)),
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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, 2>{}, Sequence<1>{}));
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return a_grid_desc_ak0_m_ak1;
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}
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else if constexpr(GemmSpecialization == GemmSpecialization_t::MPadding ||
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GemmSpecialization == GemmSpecialization_t::MNPadding)
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{
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// pad M, but not K
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assert(KRaw % AK1 == 0);
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const auto AK0 = KRaw / AK1;
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const auto a_grid_desc_ak0_m_ak1 =
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transform_tensor_descriptor(a_grid_desc_mraw_kraw,
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make_tuple(make_unmerge_transform(make_tuple(AK0, AK1)),
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make_right_pad_transform(MRaw, MPad)),
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make_tuple(Sequence<1>{}, Sequence<0>{}),
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make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
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return a_grid_desc_ak0_m_ak1;
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}
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else if constexpr(GemmSpecialization == GemmSpecialization_t::KPadding ||
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GemmSpecialization == GemmSpecialization_t::NKPadding)
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{
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// pad K, but not M
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assert(K % AK1 == 0);
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const auto AK0 = K / AK1;
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const auto a_grid_desc_m_k = transform_tensor_descriptor(
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a_grid_desc_mraw_kraw,
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make_tuple(make_pass_through_transform(MRaw), make_right_pad_transform(KRaw, KPad)),
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make_tuple(Sequence<0>{}, Sequence<1>{}),
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make_tuple(Sequence<0>{}, Sequence<1>{}));
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const auto a_grid_desc_ak0_m_ak1 =
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transform_tensor_descriptor(a_grid_desc_m_k,
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make_tuple(make_unmerge_transform(make_tuple(AK0, AK1)),
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make_pass_through_transform(MRaw)),
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make_tuple(Sequence<1>{}, Sequence<0>{}),
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make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
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return a_grid_desc_ak0_m_ak1;
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}
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else
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{
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// not pad M or K
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assert(KRaw % AK1 == 0);
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const auto AK0 = KRaw / AK1;
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const auto a_grid_desc_ak0_m_ak1 =
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transform_tensor_descriptor(a_grid_desc_mraw_kraw,
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make_tuple(make_unmerge_transform(make_tuple(AK0, AK1)),
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make_pass_through_transform(MRaw)),
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make_tuple(Sequence<1>{}, Sequence<0>{}),
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make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
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return a_grid_desc_ak0_m_ak1;
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}
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}
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static auto MakeBGridDescriptor_BK0_N_BK1(index_t KRaw, index_t NRaw, index_t StrideB)
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{
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const auto b_grid_desc_nraw_kraw = [&]() {
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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(NRaw, KRaw),
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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(GemmSpecialization == GemmSpecialization_t::NKPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::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(GemmSpecialization == GemmSpecialization_t::NPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::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(GemmSpecialization == GemmSpecialization_t::KPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::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 MakeCGridDescriptor_M_N(index_t MRaw, index_t NRaw, index_t StrideC)
|
||||
{
|
||||
const auto c_grid_desc_mraw_nraw = [&]() {
|
||||
if constexpr(is_same<tensor_layout::gemm::RowMajor, CLayout>::value)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(MRaw, NRaw),
|
||||
make_tuple(StrideC, I1));
|
||||
}
|
||||
else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, CLayout>::value)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(MRaw, NRaw),
|
||||
make_tuple(I1, StrideC));
|
||||
}
|
||||
}();
|
||||
|
||||
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(GemmSpecialization == GemmSpecialization_t::MNPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::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(GemmSpecialization == GemmSpecialization_t::MPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::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(GemmSpecialization == GemmSpecialization_t::NPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::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;
|
||||
}
|
||||
}
|
||||
|
||||
// assume D is packed tensor
|
||||
static auto MakeDGridDescriptor_M(index_t MRaw)
|
||||
{
|
||||
const auto d_grid_desc_mraw = make_naive_tensor_descriptor_packed(make_tuple(MRaw));
|
||||
|
||||
const auto M = math::integer_divide_ceil(MRaw, MPerBlock) * MPerBlock;
|
||||
const auto MPad = M - MRaw;
|
||||
|
||||
if constexpr(GemmSpecialization == GemmSpecialization_t::MPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::MNPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::MKPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::MNKPadding)
|
||||
{
|
||||
// pad M
|
||||
return transform_tensor_descriptor(d_grid_desc_mraw,
|
||||
make_tuple(make_right_pad_transform(MRaw, MPad)),
|
||||
make_tuple(Sequence<0>{}),
|
||||
make_tuple(Sequence<0>{}));
|
||||
}
|
||||
else
|
||||
{
|
||||
// not pad M
|
||||
return d_grid_desc_mraw;
|
||||
}
|
||||
}
|
||||
|
||||
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 CGridDesc_M_N = decltype(MakeCGridDescriptor_M_N(1, 1, 1));
|
||||
using DGridDesc_M = decltype(MakeDGridDescriptor_M(1));
|
||||
|
||||
// GridwiseGemm
|
||||
using GridwiseGemm = GridwiseGemmReduce_k0mk1_k0nk1_mn_xdl_cshuffle_v1<
|
||||
ADataType, // TODO: distinguish A/B datatype
|
||||
GemmAccDataType,
|
||||
CShuffleDataType,
|
||||
CDataType,
|
||||
ReduceAccDataType,
|
||||
DDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation,
|
||||
D0ReduceOperation,
|
||||
D1ReduceOperation,
|
||||
InMemoryDataOperationEnum_t::Set,
|
||||
InMemoryDataOperationEnum_t::AtomicAdd,
|
||||
AGridDesc_AK0_M_AK1,
|
||||
BGridDesc_BK0_N_BK1,
|
||||
CGridDesc_M_N,
|
||||
DGridDesc_M,
|
||||
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,
|
||||
CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CShuffleBlockTransferScalarPerVector_NPerBlock,
|
||||
CReduceThreadClusterLengths_MPerBlock_NPerBlock,
|
||||
CReduceThreadLds2VGprCopySrcDstScalarPerVector_NPerBlock,
|
||||
CReduceThreadVgpr2GlobalCopySrcDstScalarPerVector_MPerBlock>;
|
||||
|
||||
// Argument
|
||||
struct Argument : public BaseArgument
|
||||
{
|
||||
Argument(const ADataType* p_a_grid,
|
||||
const BDataType* p_b_grid,
|
||||
CDataType* p_c_grid,
|
||||
DDataType* p_d0_grid,
|
||||
DDataType* p_d1_grid,
|
||||
index_t MRaw,
|
||||
index_t NRaw,
|
||||
index_t KRaw,
|
||||
index_t StrideA,
|
||||
index_t StrideB,
|
||||
index_t StrideC,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CElementwiseOperation c_element_op,
|
||||
D0ReduceOperation d0_reduce_op,
|
||||
D1ReduceOperation d1_reduce_op)
|
||||
: p_a_grid_{p_a_grid},
|
||||
p_b_grid_{p_b_grid},
|
||||
p_c_grid_{p_c_grid},
|
||||
p_d0_grid_{p_d0_grid},
|
||||
p_d1_grid_{p_d1_grid},
|
||||
a_grid_desc_ak0_m_ak1_{DeviceOp::MakeAGridDescriptor_AK0_M_AK1(MRaw, KRaw, StrideA)},
|
||||
b_grid_desc_bk0_n_bk1_{DeviceOp::MakeBGridDescriptor_BK0_N_BK1(KRaw, NRaw, StrideB)},
|
||||
c_grid_desc_m_n_{DeviceOp::MakeCGridDescriptor_M_N(MRaw, NRaw, StrideC)},
|
||||
d_grid_desc_m_{DeviceOp::MakeDGridDescriptor_M(MRaw)},
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock_{},
|
||||
d_grid_desc_mblock_mperblock_{},
|
||||
block_2_ctile_map_{},
|
||||
a_element_op_{a_element_op},
|
||||
b_element_op_{b_element_op},
|
||||
c_element_op_{c_element_op},
|
||||
d0_reduce_op_{d0_reduce_op},
|
||||
d1_reduce_op_{d1_reduce_op}
|
||||
{
|
||||
if(GridwiseGemm::CheckValidity(
|
||||
a_grid_desc_ak0_m_ak1_, b_grid_desc_bk0_n_bk1_, c_grid_desc_m_n_))
|
||||
{
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock_ =
|
||||
GridwiseGemm::MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
c_grid_desc_m_n_);
|
||||
|
||||
d_grid_desc_mblock_mperblock_ =
|
||||
GridwiseGemm::MakeDGridDescriptor_MBlock_MPerBlock(d_grid_desc_m_);
|
||||
|
||||
block_2_ctile_map_ = GridwiseGemm::MakeDefaultBlock2CTileMap(c_grid_desc_m_n_);
|
||||
}
|
||||
}
|
||||
|
||||
// private:
|
||||
const ADataType* p_a_grid_;
|
||||
const BDataType* p_b_grid_;
|
||||
CDataType* p_c_grid_;
|
||||
DDataType* p_d0_grid_;
|
||||
DDataType* p_d1_grid_;
|
||||
AGridDesc_AK0_M_AK1 a_grid_desc_ak0_m_ak1_;
|
||||
BGridDesc_BK0_N_BK1 b_grid_desc_bk0_n_bk1_;
|
||||
CGridDesc_M_N c_grid_desc_m_n_;
|
||||
DGridDesc_M d_grid_desc_m_;
|
||||
typename GridwiseGemm::CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock_;
|
||||
typename GridwiseGemm::DGridDescriptor_MBlock_MPerBlock d_grid_desc_mblock_mperblock_;
|
||||
typename GridwiseGemm::DefaultBlock2CTileMap block_2_ctile_map_;
|
||||
AElementwiseOperation a_element_op_;
|
||||
BElementwiseOperation b_element_op_;
|
||||
CElementwiseOperation c_element_op_;
|
||||
D0ReduceOperation d0_reduce_op_;
|
||||
D1ReduceOperation d1_reduce_op_;
|
||||
};
|
||||
|
||||
// Invoker
|
||||
struct Invoker : public BaseInvoker
|
||||
{
|
||||
using Argument = DeviceOp::Argument;
|
||||
|
||||
float Run(const Argument& arg, int /* nrepeat */ = 1)
|
||||
{
|
||||
#if 0
|
||||
{
|
||||
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.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.d_grid_desc_m_{ " << arg.d_grid_desc_m_.GetLength(I0) << "}"
|
||||
<< std::endl;
|
||||
}
|
||||
#endif
|
||||
|
||||
if(!GridwiseGemm::CheckValidity(
|
||||
arg.a_grid_desc_ak0_m_ak1_, arg.b_grid_desc_bk0_n_bk1_, arg.c_grid_desc_m_n_))
|
||||
{
|
||||
throw std::runtime_error("wrong! GridwiseGemm has invalid setting");
|
||||
}
|
||||
|
||||
const index_t grid_size = GridwiseGemm::CalculateGridSize(arg.c_grid_desc_m_n_);
|
||||
|
||||
const auto K0 = arg.a_grid_desc_ak0_m_ak1_.GetLength(I0);
|
||||
|
||||
const bool has_main_k0_block_loop = GridwiseGemm::CalculateHasMainK0BlockLoop(K0);
|
||||
|
||||
if(has_main_k0_block_loop)
|
||||
{
|
||||
const auto kernel = kernel_gemm_reduce_xdl_cshuffle_v1<
|
||||
GridwiseGemm,
|
||||
ADataType, // TODO: distiguish A/B datatype
|
||||
CDataType,
|
||||
DDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation,
|
||||
D0ReduceOperation,
|
||||
D1ReduceOperation,
|
||||
DeviceOp::AGridDesc_AK0_M_AK1,
|
||||
DeviceOp::BGridDesc_BK0_N_BK1,
|
||||
typename GridwiseGemm::CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename GridwiseGemm::DGridDescriptor_MBlock_MPerBlock,
|
||||
typename GridwiseGemm::DefaultBlock2CTileMap,
|
||||
true>;
|
||||
|
||||
launch_kernel(kernel,
|
||||
dim3(grid_size),
|
||||
dim3(BlockSize),
|
||||
0,
|
||||
arg.p_a_grid_,
|
||||
arg.p_b_grid_,
|
||||
arg.p_c_grid_,
|
||||
arg.p_d0_grid_,
|
||||
arg.p_d1_grid_,
|
||||
arg.a_element_op_,
|
||||
arg.b_element_op_,
|
||||
arg.c_element_op_,
|
||||
arg.d0_reduce_op_,
|
||||
arg.d1_reduce_op_,
|
||||
arg.a_grid_desc_ak0_m_ak1_,
|
||||
arg.b_grid_desc_bk0_n_bk1_,
|
||||
arg.c_grid_desc_mblock_mperblock_nblock_nperblock_,
|
||||
arg.d_grid_desc_mblock_mperblock_,
|
||||
arg.block_2_ctile_map_);
|
||||
}
|
||||
else
|
||||
{
|
||||
const auto kernel = kernel_gemm_reduce_xdl_cshuffle_v1<
|
||||
GridwiseGemm,
|
||||
ADataType, // TODO: distiguish A/B datatype
|
||||
CDataType,
|
||||
DDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation,
|
||||
D0ReduceOperation,
|
||||
D1ReduceOperation,
|
||||
DeviceOp::AGridDesc_AK0_M_AK1,
|
||||
DeviceOp::BGridDesc_BK0_N_BK1,
|
||||
typename GridwiseGemm::CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename GridwiseGemm::DGridDescriptor_MBlock_MPerBlock,
|
||||
typename GridwiseGemm::DefaultBlock2CTileMap,
|
||||
false>;
|
||||
|
||||
launch_kernel(kernel,
|
||||
dim3(grid_size),
|
||||
dim3(BlockSize),
|
||||
0,
|
||||
arg.p_a_grid_,
|
||||
arg.p_b_grid_,
|
||||
arg.p_c_grid_,
|
||||
arg.p_d0_grid_,
|
||||
arg.p_d1_grid_,
|
||||
arg.a_element_op_,
|
||||
arg.b_element_op_,
|
||||
arg.c_element_op_,
|
||||
arg.d0_reduce_op_,
|
||||
arg.d1_reduce_op_,
|
||||
arg.a_grid_desc_ak0_m_ak1_,
|
||||
arg.b_grid_desc_bk0_n_bk1_,
|
||||
arg.c_grid_desc_mblock_mperblock_nblock_nperblock_,
|
||||
arg.d_grid_desc_mblock_mperblock_,
|
||||
arg.block_2_ctile_map_);
|
||||
}
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
float Run(const BaseArgument* p_arg, int nrepeat = 1) override
|
||||
{
|
||||
return Run(*dynamic_cast<const Argument*>(p_arg), nrepeat);
|
||||
}
|
||||
};
|
||||
|
||||
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.c_grid_desc_m_n_);
|
||||
}
|
||||
|
||||
// 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,
|
||||
DDataType* p_d0,
|
||||
DDataType* p_d1,
|
||||
index_t MRaw,
|
||||
index_t NRaw,
|
||||
index_t KRaw,
|
||||
index_t StrideA,
|
||||
index_t StrideB,
|
||||
index_t StrideC,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CElementwiseOperation c_element_op,
|
||||
D0ReduceOperation d0_reduce_op,
|
||||
D1ReduceOperation d1_reduce_op)
|
||||
{
|
||||
return Argument{p_a,
|
||||
p_b,
|
||||
p_c,
|
||||
p_d0,
|
||||
p_d1,
|
||||
MRaw,
|
||||
NRaw,
|
||||
KRaw,
|
||||
StrideA,
|
||||
StrideB,
|
||||
StrideC,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
c_element_op,
|
||||
d0_reduce_op,
|
||||
d1_reduce_op};
|
||||
}
|
||||
|
||||
static auto MakeInvoker() { return Invoker{}; }
|
||||
|
||||
// polymorphic
|
||||
std::unique_ptr<BaseArgument> MakeArgumentPointer(const void* p_a,
|
||||
const void* p_b,
|
||||
void* p_c,
|
||||
void* p_d0,
|
||||
void* p_d1,
|
||||
index_t MRaw,
|
||||
index_t NRaw,
|
||||
index_t KRaw,
|
||||
index_t StrideA,
|
||||
index_t StrideB,
|
||||
index_t StrideC,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CElementwiseOperation c_element_op,
|
||||
D0ReduceOperation d0_reduce_op,
|
||||
D1ReduceOperation d1_reduce_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<DDataType*>(p_d0),
|
||||
static_cast<DDataType*>(p_d1),
|
||||
MRaw,
|
||||
NRaw,
|
||||
KRaw,
|
||||
StrideA,
|
||||
StrideB,
|
||||
StrideC,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
c_element_op,
|
||||
d0_reduce_op,
|
||||
d1_reduce_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 << "DeviceGemmReduce_Xdl_CShuffle"
|
||||
<< "<"
|
||||
<< BlockSize << ", "
|
||||
<< MPerBlock << ", "
|
||||
<< NPerBlock << ", "
|
||||
<< KPerBlock << ", "
|
||||
<< AK1 << ", "
|
||||
<< BK1
|
||||
<< ">";
|
||||
// clang-format on
|
||||
|
||||
return str.str();
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -4,9 +4,7 @@
|
||||
#include <iostream>
|
||||
#include <sstream>
|
||||
#include "device.hpp"
|
||||
#include "device_base.hpp"
|
||||
#include "device_gemm.hpp"
|
||||
#include "device_gemm_xdl.hpp"
|
||||
#include "device_gemm_bias.hpp"
|
||||
#include "common_header.hpp"
|
||||
#include "tensor_layout.hpp"
|
||||
#include "tensor_descriptor.hpp"
|
||||
|
||||
@@ -0,0 +1,644 @@
|
||||
#pragma once
|
||||
#include <iostream>
|
||||
#include <sstream>
|
||||
#include "device.hpp"
|
||||
#include "device_gemm.hpp"
|
||||
#include "common_header.hpp"
|
||||
#include "tensor_layout.hpp"
|
||||
#include "tensor_descriptor.hpp"
|
||||
#include "tensor_descriptor_helper.hpp"
|
||||
#include "gridwise_gemm_xdl_cshuffle_v1.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
|
||||
template <typename ALayout,
|
||||
typename BLayout,
|
||||
typename CLayout,
|
||||
typename ADataType,
|
||||
typename BDataType,
|
||||
typename CDataType,
|
||||
typename GemmAccDataType,
|
||||
typename CShuffleDataType,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CElementwiseOperation,
|
||||
GemmSpecialization_t GemmSpecialization,
|
||||
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 CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
index_t CShuffleBlockTransferScalarPerVector_NPerBlock>
|
||||
struct DeviceGemm_Xdl_CShuffle
|
||||
: public DeviceGemm<AElementwiseOperation, BElementwiseOperation, CElementwiseOperation>
|
||||
{
|
||||
using DeviceOp = DeviceGemm_Xdl_CShuffle;
|
||||
|
||||
static constexpr auto I0 = Number<0>{};
|
||||
static constexpr auto I1 = Number<1>{};
|
||||
static constexpr auto I2 = Number<2>{};
|
||||
|
||||
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(GemmSpecialization == GemmSpecialization_t::MKPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::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(GemmSpecialization == GemmSpecialization_t::MPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::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(GemmSpecialization == GemmSpecialization_t::KPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::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(GemmSpecialization == GemmSpecialization_t::NKPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::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(GemmSpecialization == GemmSpecialization_t::NPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::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(GemmSpecialization == GemmSpecialization_t::KPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::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 MakeCGridDescriptor_M_N(index_t MRaw, index_t NRaw, index_t StrideC)
|
||||
{
|
||||
const auto c_grid_desc_mraw_nraw = [&]() {
|
||||
if constexpr(is_same<tensor_layout::gemm::RowMajor, CLayout>::value)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(MRaw, NRaw),
|
||||
make_tuple(StrideC, I1));
|
||||
}
|
||||
else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, CLayout>::value)
|
||||
{
|
||||
return make_naive_tensor_descriptor(make_tuple(MRaw, NRaw),
|
||||
make_tuple(I1, StrideC));
|
||||
}
|
||||
}();
|
||||
|
||||
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(GemmSpecialization == GemmSpecialization_t::MNPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::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(GemmSpecialization == GemmSpecialization_t::MPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::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(GemmSpecialization == GemmSpecialization_t::NPadding ||
|
||||
GemmSpecialization == GemmSpecialization_t::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 CGridDesc_M_N = decltype(MakeCGridDescriptor_M_N(1, 1, 1));
|
||||
|
||||
// GridwiseGemm
|
||||
using GridwiseGemm = GridwiseGemm_k0mk1_k0nk1_mn_xdl_cshuffle_v1<
|
||||
ADataType, // TODO: distinguish A/B datatype
|
||||
GemmAccDataType,
|
||||
CShuffleDataType,
|
||||
CDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation,
|
||||
InMemoryDataOperationEnum_t::Set,
|
||||
AGridDesc_AK0_M_AK1,
|
||||
BGridDesc_BK0_N_BK1,
|
||||
CGridDesc_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,
|
||||
CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CShuffleBlockTransferScalarPerVector_NPerBlock>;
|
||||
|
||||
// Argument
|
||||
struct Argument : public BaseArgument
|
||||
{
|
||||
Argument(const ADataType* p_a_grid,
|
||||
const BDataType* p_b_grid,
|
||||
CDataType* p_c_grid,
|
||||
index_t MRaw,
|
||||
index_t NRaw,
|
||||
index_t KRaw,
|
||||
index_t StrideA,
|
||||
index_t StrideB,
|
||||
index_t StrideC,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CElementwiseOperation c_element_op)
|
||||
: p_a_grid_{p_a_grid},
|
||||
p_b_grid_{p_b_grid},
|
||||
p_c_grid_{p_c_grid},
|
||||
a_grid_desc_ak0_m_ak1_{DeviceOp::MakeAGridDescriptor_AK0_M_AK1(MRaw, KRaw, StrideA)},
|
||||
b_grid_desc_bk0_n_bk1_{DeviceOp::MakeBGridDescriptor_BK0_N_BK1(KRaw, NRaw, StrideB)},
|
||||
c_grid_desc_m_n_{DeviceOp::MakeCGridDescriptor_M_N(MRaw, NRaw, StrideC)},
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock_{},
|
||||
block_2_ctile_map_{},
|
||||
a_element_op_{a_element_op},
|
||||
b_element_op_{b_element_op},
|
||||
c_element_op_{c_element_op}
|
||||
{
|
||||
if(GridwiseGemm::CheckValidity(
|
||||
a_grid_desc_ak0_m_ak1_, b_grid_desc_bk0_n_bk1_, c_grid_desc_m_n_))
|
||||
{
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock_ =
|
||||
GridwiseGemm::MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
c_grid_desc_m_n_);
|
||||
|
||||
block_2_ctile_map_ = GridwiseGemm::MakeDefaultBlock2CTileMap(c_grid_desc_m_n_);
|
||||
}
|
||||
}
|
||||
|
||||
// private:
|
||||
const ADataType* p_a_grid_;
|
||||
const BDataType* p_b_grid_;
|
||||
CDataType* p_c_grid_;
|
||||
AGridDesc_AK0_M_AK1 a_grid_desc_ak0_m_ak1_;
|
||||
BGridDesc_BK0_N_BK1 b_grid_desc_bk0_n_bk1_;
|
||||
CGridDesc_M_N c_grid_desc_m_n_;
|
||||
typename GridwiseGemm::CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock_;
|
||||
typename GridwiseGemm::DefaultBlock2CTileMap block_2_ctile_map_;
|
||||
AElementwiseOperation a_element_op_;
|
||||
BElementwiseOperation b_element_op_;
|
||||
CElementwiseOperation c_element_op_;
|
||||
};
|
||||
|
||||
// Invoker
|
||||
struct Invoker : public BaseInvoker
|
||||
{
|
||||
using Argument = DeviceOp::Argument;
|
||||
|
||||
float Run(const Argument& arg, int /* nrepeat */ = 1)
|
||||
{
|
||||
#if 0
|
||||
{
|
||||
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.c_grid_desc_m_n_{ " << arg.c_grid_desc_m_n_.GetLength(I0) << ", "
|
||||
<< arg.c_grid_desc_m_n_.GetLength(I1) << "}" << std::endl;
|
||||
}
|
||||
#endif
|
||||
|
||||
if(!GridwiseGemm::CheckValidity(
|
||||
arg.a_grid_desc_ak0_m_ak1_, arg.b_grid_desc_bk0_n_bk1_, arg.c_grid_desc_m_n_))
|
||||
{
|
||||
throw std::runtime_error("wrong! GridwiseGemm has invalid setting");
|
||||
}
|
||||
|
||||
const index_t grid_size = GridwiseGemm::CalculateGridSize(arg.c_grid_desc_m_n_);
|
||||
|
||||
const auto K0 = arg.a_grid_desc_ak0_m_ak1_.GetLength(I0);
|
||||
|
||||
const bool has_main_k0_block_loop = GridwiseGemm::CalculateHasMainK0BlockLoop(K0);
|
||||
|
||||
if(has_main_k0_block_loop)
|
||||
{
|
||||
const auto kernel = kernel_gemm_xdl_cshuffle_v1<
|
||||
GridwiseGemm,
|
||||
ADataType, // TODO: distiguish A/B datatype
|
||||
CDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation,
|
||||
DeviceOp::AGridDesc_AK0_M_AK1,
|
||||
DeviceOp::BGridDesc_BK0_N_BK1,
|
||||
typename GridwiseGemm::CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename GridwiseGemm::DefaultBlock2CTileMap,
|
||||
true>;
|
||||
|
||||
launch_kernel(kernel,
|
||||
dim3(grid_size),
|
||||
dim3(BlockSize),
|
||||
0,
|
||||
arg.p_a_grid_,
|
||||
arg.p_b_grid_,
|
||||
arg.p_c_grid_,
|
||||
arg.a_element_op_,
|
||||
arg.b_element_op_,
|
||||
arg.c_element_op_,
|
||||
arg.a_grid_desc_ak0_m_ak1_,
|
||||
arg.b_grid_desc_bk0_n_bk1_,
|
||||
arg.c_grid_desc_mblock_mperblock_nblock_nperblock_,
|
||||
arg.block_2_ctile_map_);
|
||||
}
|
||||
else
|
||||
{
|
||||
const auto kernel = kernel_gemm_xdl_cshuffle_v1<
|
||||
GridwiseGemm,
|
||||
ADataType, // TODO: distiguish A/B datatype
|
||||
CDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CElementwiseOperation,
|
||||
DeviceOp::AGridDesc_AK0_M_AK1,
|
||||
DeviceOp::BGridDesc_BK0_N_BK1,
|
||||
typename GridwiseGemm::CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename GridwiseGemm::DefaultBlock2CTileMap,
|
||||
false>;
|
||||
|
||||
launch_kernel(kernel,
|
||||
dim3(grid_size),
|
||||
dim3(BlockSize),
|
||||
0,
|
||||
arg.p_a_grid_,
|
||||
arg.p_b_grid_,
|
||||
arg.p_c_grid_,
|
||||
arg.a_element_op_,
|
||||
arg.b_element_op_,
|
||||
arg.c_element_op_,
|
||||
arg.a_grid_desc_ak0_m_ak1_,
|
||||
arg.b_grid_desc_bk0_n_bk1_,
|
||||
arg.c_grid_desc_mblock_mperblock_nblock_nperblock_,
|
||||
arg.block_2_ctile_map_);
|
||||
}
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
float Run(const BaseArgument* p_arg, int nrepeat = 1) override
|
||||
{
|
||||
return Run(*dynamic_cast<const Argument*>(p_arg), nrepeat);
|
||||
}
|
||||
};
|
||||
|
||||
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.c_grid_desc_m_n_);
|
||||
}
|
||||
|
||||
// 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,
|
||||
index_t MRaw,
|
||||
index_t NRaw,
|
||||
index_t KRaw,
|
||||
index_t StrideA,
|
||||
index_t StrideB,
|
||||
index_t StrideC,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CElementwiseOperation c_element_op)
|
||||
{
|
||||
return Argument{p_a,
|
||||
p_b,
|
||||
p_c,
|
||||
MRaw,
|
||||
NRaw,
|
||||
KRaw,
|
||||
StrideA,
|
||||
StrideB,
|
||||
StrideC,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
c_element_op};
|
||||
}
|
||||
|
||||
static auto MakeInvoker() { return Invoker{}; }
|
||||
|
||||
// polymorphic
|
||||
std::unique_ptr<BaseArgument> MakeArgumentPointer(const void* p_a,
|
||||
const void* p_b,
|
||||
void* p_c,
|
||||
index_t MRaw,
|
||||
index_t NRaw,
|
||||
index_t KRaw,
|
||||
index_t StrideA,
|
||||
index_t StrideB,
|
||||
index_t StrideC,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CElementwiseOperation c_element_op,
|
||||
index_t /* KBatch */ = 1) override
|
||||
{
|
||||
return std::make_unique<Argument>(static_cast<const ADataType*>(p_a),
|
||||
static_cast<const BDataType*>(p_b),
|
||||
static_cast<CDataType*>(p_c),
|
||||
MRaw,
|
||||
NRaw,
|
||||
KRaw,
|
||||
StrideA,
|
||||
StrideB,
|
||||
StrideC,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
c_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 << "DeviceGemm_Xdl_CShuffle"
|
||||
<< "<"
|
||||
<< BlockSize << ", "
|
||||
<< MPerBlock << ", "
|
||||
<< NPerBlock << ", "
|
||||
<< KPerBlock << ", "
|
||||
<< AK1 << ", "
|
||||
<< BK1
|
||||
<< ">";
|
||||
// clang-format on
|
||||
|
||||
return str.str();
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -5,10 +5,16 @@ namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
|
||||
enum GemmSpecialization_t
|
||||
enum struct GemmSpecialization_t
|
||||
{
|
||||
Default,
|
||||
MPadding,
|
||||
NPadding,
|
||||
KPadding,
|
||||
MNPadding,
|
||||
MKPadding,
|
||||
NKPadding,
|
||||
MNKPadding,
|
||||
};
|
||||
|
||||
} // namespace device
|
||||
|
||||
@@ -1,6 +1,4 @@
|
||||
#ifndef CK_ELEMENT_WISE_OPERATION_HPP
|
||||
#define CK_ELEMENT_WISE_OPERATION_HPP
|
||||
|
||||
#pragma once
|
||||
#include "data_type.hpp"
|
||||
|
||||
namespace ck {
|
||||
@@ -365,4 +363,3 @@ struct UnarySqrt<double, double>
|
||||
} // namespace element_wise
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
#endif
|
||||
|
||||
@@ -0,0 +1,24 @@
|
||||
#pragma once
|
||||
#include "data_type.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace element_wise {
|
||||
|
||||
struct ReduceSum
|
||||
{
|
||||
__host__ __device__ static constexpr float GetReduceZeroValue() { return float(0); }
|
||||
|
||||
__host__ __device__ void Reduce(float& acc, float v) const { acc += v; }
|
||||
};
|
||||
|
||||
struct ReduceSquareSum
|
||||
{
|
||||
__host__ __device__ static constexpr float GetReduceZeroValue() { return float(0); }
|
||||
|
||||
__host__ __device__ void Reduce(float& acc, float v) const { acc += v * v; }
|
||||
};
|
||||
|
||||
} // namespace element_wise
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,892 @@
|
||||
#pragma once
|
||||
#include "common_header.hpp"
|
||||
#include "multi_index_transform_helper.hpp"
|
||||
#include "tensor_descriptor.hpp"
|
||||
#include "tensor_descriptor_helper.hpp"
|
||||
#include "blockwise_gemm_xdlops.hpp"
|
||||
#include "blockwise_tensor_slice_transfer_v4r1.hpp"
|
||||
#include "blockwise_tensor_slice_transfer_v6r1.hpp"
|
||||
#include "threadwise_tensor_slice_transfer.hpp"
|
||||
#include "gridwise_gemm_pipeline_v1.hpp"
|
||||
|
||||
namespace ck {
|
||||
|
||||
template <typename GridwiseGemm,
|
||||
typename FloatAB,
|
||||
typename FloatC,
|
||||
typename FloatD,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CElementwiseOperation,
|
||||
typename D0ReduceOperation,
|
||||
typename D1ReduceOperation,
|
||||
typename AGridDesc_AK0_M_AK1,
|
||||
typename BGridDesc_BK0_N_BK1,
|
||||
typename CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename DGridDescriptor_MBlock_MPerBlock,
|
||||
typename Block2CTileMap,
|
||||
bool HasMainK0BlockLoop>
|
||||
__global__ void
|
||||
#if CK_USE_LAUNCH_BOUNDS
|
||||
__launch_bounds__(CK_MAX_THREAD_PER_BLOCK, CK_MIN_BLOCK_PER_CU)
|
||||
#endif
|
||||
kernel_gemm_reduce_xdl_cshuffle_v1(
|
||||
const FloatAB* __restrict__ p_a_grid,
|
||||
const FloatAB* __restrict__ p_b_grid,
|
||||
FloatC* __restrict__ p_c_grid,
|
||||
FloatD* __restrict__ p_d0_grid,
|
||||
FloatD* __restrict__ p_d1_grid,
|
||||
const AElementwiseOperation a_element_op,
|
||||
const BElementwiseOperation b_element_op,
|
||||
const CElementwiseOperation c_element_op,
|
||||
const D0ReduceOperation d0_reduce_op,
|
||||
const D1ReduceOperation d1_reduce_op,
|
||||
const AGridDesc_AK0_M_AK1 a_grid_desc_ak0_m_ak1,
|
||||
const BGridDesc_BK0_N_BK1 b_grid_desc_bk0_n_bk1,
|
||||
const CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
const DGridDescriptor_MBlock_MPerBlock d_grid_desc_mblock_mperblock,
|
||||
const Block2CTileMap block_2_ctile_map)
|
||||
{
|
||||
__shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()];
|
||||
|
||||
GridwiseGemm::template Run<HasMainK0BlockLoop>(p_a_grid,
|
||||
p_b_grid,
|
||||
p_c_grid,
|
||||
p_d0_grid,
|
||||
p_d1_grid,
|
||||
p_shared,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
c_element_op,
|
||||
d0_reduce_op,
|
||||
d1_reduce_op,
|
||||
a_grid_desc_ak0_m_ak1,
|
||||
b_grid_desc_bk0_n_bk1,
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
d_grid_desc_mblock_mperblock,
|
||||
block_2_ctile_map);
|
||||
}
|
||||
|
||||
template <typename FloatAB,
|
||||
typename FloatGemmAcc,
|
||||
typename FloatCShuffle,
|
||||
typename FloatC,
|
||||
typename FloatReduceAcc,
|
||||
typename FloatD,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CElementwiseOperation,
|
||||
typename D0ReduceOperation,
|
||||
typename D1ReduceOperation,
|
||||
InMemoryDataOperationEnum_t CGlobalMemoryDataOperation,
|
||||
InMemoryDataOperationEnum_t DGlobalMemoryDataOperation,
|
||||
typename AGridDesc_AK0_M_AK1,
|
||||
typename BGridDesc_BK0_N_BK1,
|
||||
typename CGridDesc_M_N,
|
||||
typename DGridDesc_M,
|
||||
index_t NumGemmKPrefetchStage,
|
||||
index_t BlockSize,
|
||||
index_t MPerBlock,
|
||||
index_t NPerBlock,
|
||||
index_t KPerBlock,
|
||||
index_t AK1Value,
|
||||
index_t BK1Value,
|
||||
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 AThreadTransferSrcResetCoordinateAfterRun,
|
||||
index_t ABlockLdsExtraM,
|
||||
typename BBlockTransferThreadClusterLengths_BK0_N_BK1,
|
||||
typename BBlockTransferThreadClusterArrangeOrder,
|
||||
typename BBlockTransferSrcAccessOrder,
|
||||
index_t BBlockTransferSrcVectorDim,
|
||||
index_t BBlockTransferSrcScalarPerVector,
|
||||
index_t BBlockTransferDstScalarPerVector_BK1,
|
||||
bool BThreadTransferSrcResetCoordinateAfterRun,
|
||||
index_t BBlockLdsExtraN,
|
||||
index_t CShuffleMXdlPerWavePerShuffle,
|
||||
index_t CShuffleNXdlPerWavePerShuffle,
|
||||
typename CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
index_t CShuffleBlockTransferScalarPerVector_NPerBlock,
|
||||
typename CReduceThreadClusterLengths_MPerBlock_NPerBlock,
|
||||
index_t CReduceThreadLds2VGprCopySrcDstScalarPerVector_NPerBlock,
|
||||
index_t CReduceThreadVgpr2GlobalCopySrcDstScalarPerVector_MPerBlock>
|
||||
struct GridwiseGemmReduce_k0mk1_k0nk1_mn_xdl_cshuffle_v1
|
||||
{
|
||||
static constexpr auto I0 = Number<0>{};
|
||||
static constexpr auto I1 = Number<1>{};
|
||||
static constexpr auto I2 = Number<2>{};
|
||||
static constexpr auto I3 = Number<3>{};
|
||||
static constexpr auto I4 = Number<4>{};
|
||||
static constexpr auto I5 = Number<5>{};
|
||||
static constexpr auto I6 = Number<6>{};
|
||||
static constexpr auto I7 = Number<7>{};
|
||||
|
||||
// K1 should be Number<...>
|
||||
static constexpr auto AK0 = Number<KPerBlock / AK1Value>{};
|
||||
static constexpr auto BK0 = Number<KPerBlock / BK1Value>{};
|
||||
static constexpr auto AK1 = Number<AK1Value>{};
|
||||
static constexpr auto BK1 = Number<BK1Value>{};
|
||||
|
||||
__host__ __device__ static constexpr auto GetABlockDescriptor_AK0PerBlock_MPerBlock_AK1()
|
||||
{
|
||||
// A matrix in LDS memory, dst of blockwise copy
|
||||
return make_naive_tensor_descriptor(
|
||||
make_tuple(AK0, Number<MPerBlock>{}, AK1),
|
||||
make_tuple(Number<MPerBlock + ABlockLdsExtraM>{} * AK1, AK1, I1));
|
||||
}
|
||||
|
||||
__host__ __device__ static constexpr auto GetBBlockDescriptor_BK0PerBlock_NPerBlock_BK1()
|
||||
{
|
||||
// B matrix in LDS memory, dst of blockwise copy
|
||||
return make_naive_tensor_descriptor(
|
||||
make_tuple(BK0, Number<NPerBlock>{}, BK1),
|
||||
make_tuple(Number<NPerBlock + BBlockLdsExtraN>{} * BK1, BK1, I1));
|
||||
}
|
||||
|
||||
__host__ __device__ static constexpr auto
|
||||
GetCShuffleBlockDescriptor_MBlock_MPerBlock_NBlock_NPerBlock()
|
||||
{
|
||||
constexpr index_t MWave = MPerBlock / (MXdlPerWave * MPerXdl);
|
||||
constexpr index_t NWave = NPerBlock / (NXdlPerWave * NPerXdl);
|
||||
|
||||
constexpr auto c_shuffle_block_desc_mblock_mperblock_nblock_nperblock =
|
||||
make_naive_tensor_descriptor_packed(
|
||||
make_tuple(I1,
|
||||
Number<CShuffleMXdlPerWavePerShuffle * MWave * MPerXdl>{},
|
||||
I1,
|
||||
Number<CShuffleNXdlPerWavePerShuffle * NWave * NPerXdl>{}));
|
||||
|
||||
return c_shuffle_block_desc_mblock_mperblock_nblock_nperblock;
|
||||
}
|
||||
|
||||
__host__ __device__ static constexpr index_t GetSharedMemoryNumberOfByte()
|
||||
{
|
||||
// LDS allocation for A and B: be careful of alignment
|
||||
constexpr auto a_block_desc_ak0_m_ak1 = GetABlockDescriptor_AK0PerBlock_MPerBlock_AK1();
|
||||
constexpr auto b_block_desc_bk0_n_bk1 = GetBBlockDescriptor_BK0PerBlock_NPerBlock_BK1();
|
||||
|
||||
// lds max alignment
|
||||
constexpr auto max_lds_align = math::lcm(AK1, BK1);
|
||||
|
||||
constexpr auto a_block_space_size_aligned = math::integer_least_multiple(
|
||||
a_block_desc_ak0_m_ak1.GetElementSpaceSize(), max_lds_align);
|
||||
|
||||
constexpr auto b_block_space_size_aligned = math::integer_least_multiple(
|
||||
b_block_desc_bk0_n_bk1.GetElementSpaceSize(), max_lds_align);
|
||||
|
||||
// LDS allocation for C shuffle in LDS
|
||||
constexpr auto c_shuffle_block_desc_mblock_mperblock_nblock_nperblock =
|
||||
GetCShuffleBlockDescriptor_MBlock_MPerBlock_NBlock_NPerBlock();
|
||||
|
||||
constexpr auto c_block_size =
|
||||
c_shuffle_block_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize();
|
||||
|
||||
return math::max((a_block_space_size_aligned + b_block_space_size_aligned) *
|
||||
sizeof(FloatAB),
|
||||
c_block_size * sizeof(FloatCShuffle));
|
||||
}
|
||||
|
||||
// block_id to matrix tile idx (m0, n0) mapping are controlled by {M01, N01}
|
||||
__host__ __device__ static constexpr bool
|
||||
CheckValidity(const AGridDesc_AK0_M_AK1& a_grid_desc_ak0_m_ak1,
|
||||
const BGridDesc_BK0_N_BK1& b_grid_desc_bk0_n_bk1,
|
||||
const CGridDesc_M_N& c_grid_desc_m_n)
|
||||
{
|
||||
// static_assert(is_known_at_compile_time<remove_cv_t<decltype(AK1)>>::value &&
|
||||
// is_known_at_compile_time<remove_cv_t<decltype(BK1)>>::value,
|
||||
// "wrong! K1 need to be known at compile-time");
|
||||
|
||||
static_assert((MPerBlock % (MPerXdl * MXdlPerWave) == 0) &&
|
||||
(NPerBlock % (NXdlPerWave * NPerXdl)) == 0,
|
||||
"Invalid tuning param!");
|
||||
|
||||
const auto M = a_grid_desc_ak0_m_ak1.GetLength(I1);
|
||||
const auto N = b_grid_desc_bk0_n_bk1.GetLength(I1);
|
||||
const auto K = a_grid_desc_ak0_m_ak1.GetLength(I0) * a_grid_desc_ak0_m_ak1.GetLength(I2);
|
||||
|
||||
if(!(M == c_grid_desc_m_n.GetLength(I0) && N == c_grid_desc_m_n.GetLength(I1)))
|
||||
return false;
|
||||
|
||||
if(!(M % MPerBlock == 0 && N % NPerBlock == 0 && K % KPerBlock == 0))
|
||||
return false;
|
||||
|
||||
// check NumGemmKPrefetchStage
|
||||
if constexpr(NumGemmKPrefetchStage == 1)
|
||||
{
|
||||
// 1-stage prefetch always supported
|
||||
}
|
||||
else if constexpr(NumGemmKPrefetchStage == 2)
|
||||
{
|
||||
// 2-stage prefetch currently only support even number of K0 loop
|
||||
// TODO: add support for odd number of K0 loop
|
||||
if(!((K / KPerBlock) % 2 == 0))
|
||||
{
|
||||
return false;
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
return false;
|
||||
}
|
||||
|
||||
// TODO: also check validity of all components (blockwise-copy, threadwise-copy, etc)
|
||||
return true;
|
||||
}
|
||||
|
||||
__host__ __device__ static constexpr index_t
|
||||
CalculateGridSize(const CGridDesc_M_N& c_grid_desc_m_n)
|
||||
{
|
||||
const auto M = c_grid_desc_m_n.GetLength(I0);
|
||||
const auto N = c_grid_desc_m_n.GetLength(I1);
|
||||
|
||||
const index_t grid_size = (M / MPerBlock) * (N / NPerBlock);
|
||||
|
||||
return grid_size;
|
||||
}
|
||||
|
||||
// TODO move this function into GEMM-pipeline class
|
||||
__host__ __device__ static constexpr bool CalculateHasMainK0BlockLoop(index_t K0)
|
||||
{
|
||||
const bool has_main_k0_block_loop = ((K0 * AK1) / (NumGemmKPrefetchStage * KPerBlock)) > 1;
|
||||
|
||||
return has_main_k0_block_loop;
|
||||
}
|
||||
|
||||
__host__ __device__ static constexpr auto
|
||||
MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(const CGridDesc_M_N& c_grid_desc_m_n)
|
||||
{
|
||||
const auto M = c_grid_desc_m_n.GetLength(I0);
|
||||
const auto N = c_grid_desc_m_n.GetLength(I1);
|
||||
|
||||
const auto MBlock = M / MPerBlock;
|
||||
const auto NBlock = N / NPerBlock;
|
||||
|
||||
const auto c_grid_desc_mblock_mperblock_nblock_nperblock = transform_tensor_descriptor(
|
||||
c_grid_desc_m_n,
|
||||
make_tuple(make_unmerge_transform(make_tuple(MBlock, Number<MPerBlock>{})),
|
||||
make_unmerge_transform(make_tuple(NBlock, Number<NPerBlock>{}))),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0, 1>{}, Sequence<2, 3>{}));
|
||||
|
||||
return c_grid_desc_mblock_mperblock_nblock_nperblock;
|
||||
}
|
||||
|
||||
__host__ __device__ static constexpr auto
|
||||
MakeDGridDescriptor_MBlock_MPerBlock(const DGridDesc_M& d_grid_desc_m)
|
||||
{
|
||||
const auto M = d_grid_desc_m.GetLength(I0);
|
||||
const auto MBlock = M / MPerBlock;
|
||||
|
||||
const auto d_grid_desc_mblock_mperblock = transform_tensor_descriptor(
|
||||
d_grid_desc_m,
|
||||
make_tuple(make_unmerge_transform(make_tuple(MBlock, Number<MPerBlock>{}))),
|
||||
make_tuple(Sequence<0>{}),
|
||||
make_tuple(Sequence<0, 1>{}));
|
||||
|
||||
return d_grid_desc_mblock_mperblock;
|
||||
}
|
||||
|
||||
// return block_id to C matrix tile idx (m0, n0) mapping
|
||||
__host__ __device__ static constexpr auto
|
||||
MakeDefaultBlock2CTileMap(const CGridDesc_M_N& c_grid_desc_m_n)
|
||||
{
|
||||
const auto M = c_grid_desc_m_n.GetLength(I0);
|
||||
const auto N = c_grid_desc_m_n.GetLength(I1);
|
||||
|
||||
constexpr auto M1 = Number<MPerBlock>{};
|
||||
constexpr auto N1 = Number<NPerBlock>{};
|
||||
|
||||
const auto M0 = M / M1;
|
||||
const auto N0 = N / N1;
|
||||
|
||||
// FIXME: remove
|
||||
constexpr auto M01 = I1;
|
||||
constexpr auto N01 = I1;
|
||||
|
||||
const auto M00 = M0 / M01;
|
||||
const auto N00 = N0 / N01;
|
||||
|
||||
const auto m00_m01_n00_n01_to_m0_n0_block_cluster_adaptor =
|
||||
make_single_stage_tensor_adaptor(
|
||||
make_tuple(make_unmerge_transform(make_tuple(M00, M01)),
|
||||
make_unmerge_transform(make_tuple(N00, N01))),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0, 2>{}, Sequence<1, 3>{}));
|
||||
|
||||
const auto cblockid_to_m00_m01_n00_n01_block_cluster_adaptor =
|
||||
make_single_stage_tensor_adaptor(
|
||||
make_tuple(make_merge_transform(make_tuple(M00, N00, M01, N01))),
|
||||
make_tuple(Sequence<0, 1, 2, 3>{}),
|
||||
make_tuple(Sequence<0>{}));
|
||||
|
||||
const auto cblockid_to_m0_n0_block_cluster_adaptor =
|
||||
chain_tensor_adaptors(m00_m01_n00_n01_to_m0_n0_block_cluster_adaptor,
|
||||
cblockid_to_m00_m01_n00_n01_block_cluster_adaptor);
|
||||
|
||||
return cblockid_to_m0_n0_block_cluster_adaptor;
|
||||
}
|
||||
|
||||
using CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock = remove_cvref_t<decltype(
|
||||
MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(CGridDesc_M_N{}))>;
|
||||
|
||||
using DGridDescriptor_MBlock_MPerBlock =
|
||||
remove_cvref_t<decltype(MakeDGridDescriptor_MBlock_MPerBlock(DGridDesc_M{}))>;
|
||||
|
||||
using DefaultBlock2CTileMap =
|
||||
remove_cvref_t<decltype(MakeDefaultBlock2CTileMap(CGridDesc_M_N{}))>;
|
||||
|
||||
template <bool HasMainK0BlockLoop, typename Block2CTileMap>
|
||||
__device__ static void Run(const FloatAB* __restrict__ p_a_grid,
|
||||
const FloatAB* __restrict__ p_b_grid,
|
||||
FloatC* __restrict__ p_c_grid,
|
||||
FloatD* __restrict__ p_d0_grid,
|
||||
FloatD* __restrict__ p_d1_grid,
|
||||
void* __restrict__ p_shared,
|
||||
const AElementwiseOperation& a_element_op,
|
||||
const BElementwiseOperation& b_element_op,
|
||||
const CElementwiseOperation& c_element_op,
|
||||
const D0ReduceOperation& d0_reduce_op,
|
||||
const D1ReduceOperation& d1_reduce_op,
|
||||
const AGridDesc_AK0_M_AK1& a_grid_desc_ak0_m_ak1,
|
||||
const BGridDesc_BK0_N_BK1& b_grid_desc_bk0_n_bk1,
|
||||
const CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock&
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
const DGridDescriptor_MBlock_MPerBlock& d_grid_desc_mblock_mperblock,
|
||||
const Block2CTileMap& block_2_ctile_map)
|
||||
{
|
||||
const auto a_grid_buf = make_dynamic_buffer<AddressSpaceEnum_t::Global>(
|
||||
p_a_grid, a_grid_desc_ak0_m_ak1.GetElementSpaceSize());
|
||||
const auto b_grid_buf = make_dynamic_buffer<AddressSpaceEnum_t::Global>(
|
||||
p_b_grid, b_grid_desc_bk0_n_bk1.GetElementSpaceSize());
|
||||
auto c_grid_buf = make_dynamic_buffer<AddressSpaceEnum_t::Global>(
|
||||
p_c_grid, c_grid_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize());
|
||||
auto d0_grid_buf = make_dynamic_buffer<AddressSpaceEnum_t::Global>(
|
||||
p_d0_grid, d_grid_desc_mblock_mperblock.GetElementSpaceSize());
|
||||
auto d1_grid_buf = make_dynamic_buffer<AddressSpaceEnum_t::Global>(
|
||||
p_d1_grid, d_grid_desc_mblock_mperblock.GetElementSpaceSize());
|
||||
|
||||
// divide block work by [M, N]
|
||||
const auto block_work_idx =
|
||||
block_2_ctile_map.CalculateBottomIndex(make_multi_index(get_block_1d_id()));
|
||||
|
||||
// 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[I0] * MPerBlock);
|
||||
|
||||
const index_t n_block_data_idx_on_grid =
|
||||
__builtin_amdgcn_readfirstlane(block_work_idx[I1] * NPerBlock);
|
||||
|
||||
// lds max alignment
|
||||
constexpr auto max_lds_align = math::lcm(AK1, BK1);
|
||||
|
||||
// A matrix in LDS memory, dst of blockwise copy
|
||||
constexpr auto a_block_desc_ak0_m_ak1 = GetABlockDescriptor_AK0PerBlock_MPerBlock_AK1();
|
||||
|
||||
// B matrix in LDS memory, dst of blockwise copy
|
||||
constexpr auto b_block_desc_bk0_n_bk1 = GetBBlockDescriptor_BK0PerBlock_NPerBlock_BK1();
|
||||
|
||||
// A matrix blockwise copy
|
||||
auto a_blockwise_copy =
|
||||
BlockwiseTensorSliceTransfer_v4r1<BlockSize,
|
||||
AElementwiseOperation,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
InMemoryDataOperationEnum_t::Set,
|
||||
Sequence<AK0, MPerBlock, AK1>,
|
||||
ABlockTransferThreadClusterLengths_AK0_M_AK1,
|
||||
ABlockTransferThreadClusterArrangeOrder,
|
||||
FloatAB,
|
||||
FloatAB,
|
||||
decltype(a_grid_desc_ak0_m_ak1),
|
||||
decltype(a_block_desc_ak0_m_ak1),
|
||||
ABlockTransferSrcAccessOrder,
|
||||
Sequence<1, 0, 2>,
|
||||
ABlockTransferSrcVectorDim,
|
||||
2,
|
||||
ABlockTransferSrcScalarPerVector,
|
||||
ABlockTransferDstScalarPerVector_AK1,
|
||||
1,
|
||||
1,
|
||||
AThreadTransferSrcResetCoordinateAfterRun,
|
||||
true,
|
||||
NumGemmKPrefetchStage>(
|
||||
a_grid_desc_ak0_m_ak1,
|
||||
make_multi_index(0, m_block_data_idx_on_grid, 0),
|
||||
a_element_op,
|
||||
a_block_desc_ak0_m_ak1,
|
||||
make_multi_index(0, 0, 0),
|
||||
ck::tensor_operation::element_wise::PassThrough{});
|
||||
|
||||
// B matrix blockwise copy
|
||||
auto b_blockwise_copy =
|
||||
BlockwiseTensorSliceTransfer_v4r1<BlockSize,
|
||||
BElementwiseOperation,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
InMemoryDataOperationEnum_t::Set,
|
||||
Sequence<BK0, NPerBlock, BK1>,
|
||||
BBlockTransferThreadClusterLengths_BK0_N_BK1,
|
||||
BBlockTransferThreadClusterArrangeOrder,
|
||||
FloatAB,
|
||||
FloatAB,
|
||||
decltype(b_grid_desc_bk0_n_bk1),
|
||||
decltype(b_block_desc_bk0_n_bk1),
|
||||
BBlockTransferSrcAccessOrder,
|
||||
Sequence<1, 0, 2>,
|
||||
BBlockTransferSrcVectorDim,
|
||||
2,
|
||||
BBlockTransferSrcScalarPerVector,
|
||||
BBlockTransferDstScalarPerVector_BK1,
|
||||
1,
|
||||
1,
|
||||
BThreadTransferSrcResetCoordinateAfterRun,
|
||||
true,
|
||||
NumGemmKPrefetchStage>(
|
||||
b_grid_desc_bk0_n_bk1,
|
||||
make_multi_index(0, n_block_data_idx_on_grid, 0),
|
||||
b_element_op,
|
||||
b_block_desc_bk0_n_bk1,
|
||||
make_multi_index(0, 0, 0),
|
||||
ck::tensor_operation::element_wise::PassThrough{});
|
||||
|
||||
// GEMM definition
|
||||
// c_mtx += transpose(a_mtx) * b_mtx
|
||||
// a_mtx[K0PerBlock, MPerBlock] is in LDS
|
||||
// b_mtx[K0PerBlock, NPerBlock] is in LDS
|
||||
// c_mtx[MPerBlock, NPerBlock] is distributed among threads, and saved in
|
||||
// register
|
||||
// sanity check
|
||||
constexpr index_t KPack = math::max(
|
||||
math::lcm(AK1, BK1), MfmaSelector<FloatAB, MPerXdl, NPerXdl>::selected_mfma.k_per_blk);
|
||||
|
||||
auto blockwise_gemm =
|
||||
BlockwiseGemmXdlops_k0mk1_k0nk1_m0n0m1n1m2m3m4n2_v1<BlockSize,
|
||||
FloatAB,
|
||||
FloatGemmAcc,
|
||||
decltype(a_block_desc_ak0_m_ak1),
|
||||
decltype(b_block_desc_bk0_n_bk1),
|
||||
MPerXdl,
|
||||
NPerXdl,
|
||||
MXdlPerWave,
|
||||
NXdlPerWave,
|
||||
KPack>{};
|
||||
|
||||
auto c_thread_buf = blockwise_gemm.GetCThreadBuffer();
|
||||
|
||||
// LDS allocation for A and B: be careful of alignment
|
||||
constexpr auto a_block_space_size_aligned = math::integer_least_multiple(
|
||||
a_block_desc_ak0_m_ak1.GetElementSpaceSize(), max_lds_align);
|
||||
|
||||
auto a_block_buf = make_dynamic_buffer<AddressSpaceEnum_t::Lds>(
|
||||
static_cast<FloatAB*>(p_shared), a_block_desc_ak0_m_ak1.GetElementSpaceSize());
|
||||
|
||||
auto b_block_buf = make_dynamic_buffer<AddressSpaceEnum_t::Lds>(
|
||||
static_cast<FloatAB*>(p_shared) + a_block_space_size_aligned,
|
||||
b_block_desc_bk0_n_bk1.GetElementSpaceSize());
|
||||
|
||||
constexpr auto a_block_slice_copy_step = make_multi_index(KPerBlock / AK1, 0, 0);
|
||||
constexpr auto b_block_slice_copy_step = make_multi_index(KPerBlock / BK1, 0, 0);
|
||||
|
||||
// gridwise GEMM pipeline
|
||||
const auto gridwise_gemm_pipeline =
|
||||
GridwiseGemmPipeline_v1<remove_cvref_t<decltype(a_grid_desc_ak0_m_ak1)>,
|
||||
remove_cvref_t<decltype(a_block_desc_ak0_m_ak1)>,
|
||||
remove_cvref_t<decltype(a_blockwise_copy)>,
|
||||
remove_cvref_t<decltype(a_grid_buf)>,
|
||||
remove_cvref_t<decltype(a_block_buf)>,
|
||||
remove_cvref_t<decltype(a_block_slice_copy_step)>,
|
||||
remove_cvref_t<decltype(b_grid_desc_bk0_n_bk1)>,
|
||||
remove_cvref_t<decltype(b_block_desc_bk0_n_bk1)>,
|
||||
remove_cvref_t<decltype(b_blockwise_copy)>,
|
||||
remove_cvref_t<decltype(b_grid_buf)>,
|
||||
remove_cvref_t<decltype(b_block_buf)>,
|
||||
remove_cvref_t<decltype(b_block_slice_copy_step)>,
|
||||
remove_cvref_t<decltype(blockwise_gemm)>,
|
||||
remove_cvref_t<decltype(c_thread_buf)>,
|
||||
NumGemmKPrefetchStage,
|
||||
HasMainK0BlockLoop>{};
|
||||
|
||||
const index_t num_k_block_main_loop = __builtin_amdgcn_readfirstlane(
|
||||
(a_grid_desc_ak0_m_ak1.GetLength(I0) * a_grid_desc_ak0_m_ak1.GetLength(I2)) /
|
||||
KPerBlock);
|
||||
|
||||
gridwise_gemm_pipeline.Run(a_grid_desc_ak0_m_ak1,
|
||||
a_block_desc_ak0_m_ak1,
|
||||
a_blockwise_copy,
|
||||
a_grid_buf,
|
||||
a_block_buf,
|
||||
a_block_slice_copy_step,
|
||||
b_grid_desc_bk0_n_bk1,
|
||||
b_block_desc_bk0_n_bk1,
|
||||
b_blockwise_copy,
|
||||
b_grid_buf,
|
||||
b_block_buf,
|
||||
b_block_slice_copy_step,
|
||||
blockwise_gemm,
|
||||
c_thread_buf,
|
||||
num_k_block_main_loop);
|
||||
|
||||
// shuffle C and write out
|
||||
{
|
||||
static_assert(MXdlPerWave % CShuffleMXdlPerWavePerShuffle == 0 &&
|
||||
NXdlPerWave % CShuffleNXdlPerWavePerShuffle == 0,
|
||||
"wrong!");
|
||||
|
||||
constexpr index_t MWave = MPerBlock / (MXdlPerWave * MPerXdl);
|
||||
constexpr index_t NWave = NPerBlock / (NXdlPerWave * NPerXdl);
|
||||
|
||||
// TODO: hacky, fix it!
|
||||
constexpr auto c_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2 =
|
||||
blockwise_gemm.GetCThreadDescriptor_M0_N0_M1_N1_M2_M3_M4_N2();
|
||||
|
||||
// TODO: hacky, fix it!
|
||||
// c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp is only used to get lengths
|
||||
constexpr auto c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp =
|
||||
blockwise_gemm.GetCBlockDescriptor_M0_N0_M1_N1_M2_M3_M4_N2();
|
||||
|
||||
constexpr auto M0 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I0);
|
||||
constexpr auto N0 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I1);
|
||||
constexpr auto M1 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I2);
|
||||
constexpr auto N1 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I3);
|
||||
constexpr auto M2 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I4);
|
||||
constexpr auto M3 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I5);
|
||||
constexpr auto M4 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I6);
|
||||
constexpr auto N2 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I7);
|
||||
|
||||
constexpr auto c_shuffle_block_desc_mblock_mperblock_nblock_nperblock =
|
||||
GetCShuffleBlockDescriptor_MBlock_MPerBlock_NBlock_NPerBlock();
|
||||
|
||||
auto c_shuffle_block_buf = make_dynamic_buffer<AddressSpaceEnum_t::Lds>(
|
||||
static_cast<FloatCShuffle*>(p_shared),
|
||||
c_shuffle_block_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize());
|
||||
|
||||
constexpr auto c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2 = transform_tensor_descriptor(
|
||||
c_shuffle_block_desc_mblock_mperblock_nblock_nperblock,
|
||||
make_tuple(
|
||||
make_freeze_transform(I0),
|
||||
make_unmerge_transform(make_tuple(
|
||||
Number<CShuffleMXdlPerWavePerShuffle>{}, // M0 (MXdlPerWave) per shuffle
|
||||
M1, // M1 = MWave
|
||||
M2, // M2 * M3 * M4 = MPerXdl
|
||||
M3,
|
||||
M4)),
|
||||
make_freeze_transform(I0),
|
||||
make_unmerge_transform(make_tuple(
|
||||
Number<CShuffleNXdlPerWavePerShuffle>{}, // N0 (NXdlPerWave) per shuffle
|
||||
N1, // N1 = NWave
|
||||
N2))), // N2 = NPerXdl
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
|
||||
make_tuple(
|
||||
Sequence<>{}, Sequence<0, 2, 4, 5, 6>{}, Sequence<>{}, Sequence<1, 3, 7>{}));
|
||||
|
||||
// calculate origin of thread output tensor on global memory
|
||||
// blockwise GEMM c matrix starting index
|
||||
const auto c_thread_mtx_on_block =
|
||||
blockwise_gemm.CalculateCThreadOriginDataIndex(I0, I0, I0, I0);
|
||||
|
||||
const index_t m_thread_data_on_block = c_thread_mtx_on_block[I0];
|
||||
const index_t n_thread_data_on_block = c_thread_mtx_on_block[I1];
|
||||
|
||||
const auto m_thread_data_on_block_to_m0_m1_m2_m3_m4_adaptor =
|
||||
make_single_stage_tensor_adaptor(
|
||||
make_tuple(make_merge_transform(make_tuple(M0, M1, M2, M3, M4))),
|
||||
make_tuple(Sequence<0, 1, 2, 3, 4>{}),
|
||||
make_tuple(Sequence<0>{}));
|
||||
|
||||
const auto m_thread_data_on_block_idx =
|
||||
m_thread_data_on_block_to_m0_m1_m2_m3_m4_adaptor.CalculateBottomIndex(
|
||||
make_multi_index(m_thread_data_on_block));
|
||||
|
||||
const auto n_thread_data_on_block_to_n0_n1_n2_adaptor =
|
||||
make_single_stage_tensor_adaptor(
|
||||
make_tuple(make_merge_transform(make_tuple(N0, N1, N2))),
|
||||
make_tuple(Sequence<0, 1, 2>{}),
|
||||
make_tuple(Sequence<0>{}));
|
||||
|
||||
const auto n_thread_data_on_block_idx =
|
||||
n_thread_data_on_block_to_n0_n1_n2_adaptor.CalculateBottomIndex(
|
||||
make_multi_index(n_thread_data_on_block));
|
||||
|
||||
// shuffle: threadwise copy C from VGPR to LDS
|
||||
auto c_thread_copy_vgpr_to_lds =
|
||||
ThreadwiseTensorSliceTransfer_v1r3<FloatGemmAcc,
|
||||
FloatCShuffle,
|
||||
decltype(c_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2),
|
||||
decltype(c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2),
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
Sequence<CShuffleMXdlPerWavePerShuffle,
|
||||
CShuffleNXdlPerWavePerShuffle,
|
||||
I1,
|
||||
I1,
|
||||
M2,
|
||||
I1,
|
||||
M4,
|
||||
I1>,
|
||||
Sequence<0, 1, 2, 3, 4, 5, 6, 7>,
|
||||
7,
|
||||
1,
|
||||
InMemoryDataOperationEnum_t::Set,
|
||||
1,
|
||||
true>{
|
||||
c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2,
|
||||
make_multi_index(0,
|
||||
0,
|
||||
m_thread_data_on_block_idx[I1],
|
||||
n_thread_data_on_block_idx[I1],
|
||||
m_thread_data_on_block_idx[I2],
|
||||
m_thread_data_on_block_idx[I3],
|
||||
m_thread_data_on_block_idx[I4],
|
||||
n_thread_data_on_block_idx[I2]),
|
||||
ck::tensor_operation::element_wise::PassThrough{}};
|
||||
|
||||
// shuffle: blockwise copy C from LDS to global
|
||||
auto c_shuffle_block_copy_lds_to_global = BlockwiseTensorSliceTransfer_v6r1<
|
||||
BlockSize, // index_t BlockSize,
|
||||
CElementwiseOperation, // ElementwiseOperation,
|
||||
CGlobalMemoryDataOperation, // DstInMemOp,
|
||||
Sequence<1,
|
||||
CShuffleMXdlPerWavePerShuffle * MWave * MPerXdl,
|
||||
1,
|
||||
CShuffleNXdlPerWavePerShuffle * NWave * NPerXdl>, // BlockSliceLengths,
|
||||
CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
Sequence<0, 1, 2, 3>, // typename ThreadClusterArrangeOrder,
|
||||
FloatCShuffle, // typename SrcData,
|
||||
FloatC, // typename DstData,
|
||||
decltype(c_shuffle_block_desc_mblock_mperblock_nblock_nperblock),
|
||||
decltype(c_grid_desc_mblock_mperblock_nblock_nperblock),
|
||||
Sequence<0, 1, 2, 3>, // typename DimAccessOrder,
|
||||
3, // index_t VectorDim,
|
||||
CShuffleBlockTransferScalarPerVector_NPerBlock, // index_t ScalarPerVector,
|
||||
true, // bool ThreadTransferSrcResetCoordinateAfterRun,
|
||||
false> // bool ThreadTransferDstResetCoordinateAfterRun>
|
||||
{c_shuffle_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[I0], 0, block_work_idx[I1], 0),
|
||||
c_element_op};
|
||||
|
||||
// LDS c_reduce_block_desc_mperblock_nperblock
|
||||
constexpr auto c_reduce_block_desc_mperblock_nperblock = transform_tensor_descriptor(
|
||||
c_shuffle_block_desc_mblock_mperblock_nblock_nperblock,
|
||||
make_tuple(
|
||||
make_freeze_transform(I0),
|
||||
make_pass_through_transform(
|
||||
c_shuffle_block_desc_mblock_mperblock_nblock_nperblock.GetLength(I1)),
|
||||
make_freeze_transform(I0),
|
||||
make_pass_through_transform(
|
||||
c_shuffle_block_desc_mblock_mperblock_nblock_nperblock.GetLength(I3))),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
|
||||
make_tuple(Sequence<>{}, Sequence<0>{}, Sequence<>{}, Sequence<1>{}));
|
||||
|
||||
static_assert(CReduceThreadClusterLengths_MPerBlock_NPerBlock::At(I0) *
|
||||
CReduceThreadClusterLengths_MPerBlock_NPerBlock::At(I1) ==
|
||||
BlockSize,
|
||||
"wrong!");
|
||||
|
||||
static_assert((CShuffleMXdlPerWavePerShuffle * MWave * MPerXdl) %
|
||||
CReduceThreadClusterLengths_MPerBlock_NPerBlock::At(I0) ==
|
||||
0 &&
|
||||
(CShuffleNXdlPerWavePerShuffle * NWave * NPerXdl) %
|
||||
CReduceThreadClusterLengths_MPerBlock_NPerBlock::At(I1) ==
|
||||
0,
|
||||
"wrong!");
|
||||
|
||||
constexpr index_t mreduce_per_thread =
|
||||
(CShuffleMXdlPerWavePerShuffle * MWave * MPerXdl) /
|
||||
CReduceThreadClusterLengths_MPerBlock_NPerBlock::At(I0);
|
||||
|
||||
constexpr index_t nreduce_per_thread =
|
||||
(CShuffleNXdlPerWavePerShuffle * NWave * NPerXdl) /
|
||||
CReduceThreadClusterLengths_MPerBlock_NPerBlock::At(I1);
|
||||
|
||||
constexpr auto c_reduce_thread_lengths_mperblock_nperblock =
|
||||
Sequence<mreduce_per_thread, nreduce_per_thread>{};
|
||||
|
||||
// VGPR c_reduce_thread_desc_mperblock_nperblock
|
||||
constexpr auto c_reduce_thread_desc_mperblock_nperblock =
|
||||
make_naive_tensor_descriptor_packed(
|
||||
make_tuple(Number<mreduce_per_thread>{}, Number<nreduce_per_thread>{}));
|
||||
|
||||
// VGPR d_reduce_thread_desc_mperblock
|
||||
constexpr auto d_reduce_thread_desc_mperblock =
|
||||
make_naive_tensor_descriptor_packed(make_tuple(Number<mreduce_per_thread>{}));
|
||||
|
||||
// VGPR d_reduce_thread_desc_mblock_mperblock
|
||||
constexpr auto d_reduce_thread_desc_mblock_mperblock =
|
||||
make_naive_tensor_descriptor_packed(make_tuple(I1, Number<mreduce_per_thread>{}));
|
||||
|
||||
// TODO: this should be implemented as a blockwise reduction
|
||||
auto c_reduce_thread_buf = make_static_buffer<AddressSpaceEnum_t::Vgpr, FloatCShuffle>(
|
||||
c_reduce_thread_desc_mperblock_nperblock.GetElementSpaceSize());
|
||||
|
||||
auto d0_thread_buf = make_static_buffer<AddressSpaceEnum_t::Vgpr, FloatCShuffle>(
|
||||
d_reduce_thread_desc_mperblock.GetElementSpaceSize());
|
||||
|
||||
auto d1_thread_buf = make_static_buffer<AddressSpaceEnum_t::Vgpr, FloatCShuffle>(
|
||||
d_reduce_thread_desc_mperblock.GetElementSpaceSize());
|
||||
|
||||
// reduce: threadwise copy from LDS to VGPR
|
||||
constexpr auto c_reduce_thread_cluster_desc = make_cluster_descriptor(
|
||||
CReduceThreadClusterLengths_MPerBlock_NPerBlock{}, Sequence<1, 0>{});
|
||||
|
||||
const auto c_reduce_thread_cluster_idx =
|
||||
c_reduce_thread_cluster_desc.CalculateBottomIndex(
|
||||
make_multi_index(get_thread_local_1d_id()));
|
||||
|
||||
const auto c_reduce_thread_data_idx_begin =
|
||||
c_reduce_thread_cluster_idx * c_reduce_thread_lengths_mperblock_nperblock;
|
||||
|
||||
auto c_reduce_thread_copy_lds_to_vgpr = ThreadwiseTensorSliceTransfer_v2<
|
||||
FloatCShuffle,
|
||||
FloatCShuffle,
|
||||
decltype(c_reduce_block_desc_mperblock_nperblock),
|
||||
decltype(c_reduce_thread_desc_mperblock_nperblock),
|
||||
decltype(c_reduce_thread_lengths_mperblock_nperblock),
|
||||
Sequence<0, 1>,
|
||||
1,
|
||||
CReduceThreadLds2VGprCopySrcDstScalarPerVector_NPerBlock,
|
||||
1,
|
||||
true>{c_reduce_block_desc_mperblock_nperblock, c_reduce_thread_data_idx_begin};
|
||||
|
||||
// reduce: copy from VGPR to global
|
||||
auto d0_reduce_thread_copy_vgpr_to_global = ThreadwiseTensorSliceTransfer_v1r3<
|
||||
FloatCShuffle,
|
||||
FloatD,
|
||||
decltype(d_reduce_thread_desc_mblock_mperblock),
|
||||
decltype(d_grid_desc_mblock_mperblock),
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
Sequence<1, mreduce_per_thread>,
|
||||
Sequence<0, 1>,
|
||||
1,
|
||||
CReduceThreadVgpr2GlobalCopySrcDstScalarPerVector_MPerBlock,
|
||||
DGlobalMemoryDataOperation,
|
||||
1,
|
||||
false>{d_grid_desc_mblock_mperblock,
|
||||
make_multi_index(block_work_idx[I0], // mblock
|
||||
c_reduce_thread_data_idx_begin[I0]), // mperblock
|
||||
ck::tensor_operation::element_wise::PassThrough{}};
|
||||
|
||||
auto d1_reduce_thread_copy_vgpr_to_global = d0_reduce_thread_copy_vgpr_to_global;
|
||||
|
||||
// space filling curve for threadwise C in VGPR
|
||||
constexpr auto sfc_c_vgpr =
|
||||
SpaceFillingCurve<Sequence<MXdlPerWave, NXdlPerWave, 1, 1, M2, 1, M4, 1>,
|
||||
Sequence<0, 1, 2, 3, 4, 5, 6, 7>,
|
||||
Sequence<CShuffleMXdlPerWavePerShuffle,
|
||||
CShuffleNXdlPerWavePerShuffle,
|
||||
1,
|
||||
1,
|
||||
M2,
|
||||
1,
|
||||
M4,
|
||||
1>>{};
|
||||
|
||||
// space filling curve for shuffled blockwise C in global mem
|
||||
constexpr auto sfc_c_global =
|
||||
SpaceFillingCurve<Sequence<1, MPerBlock, 1, NPerBlock>,
|
||||
Sequence<0, 2, 1, 3>,
|
||||
Sequence<1,
|
||||
CShuffleMXdlPerWavePerShuffle * MWave * MPerXdl,
|
||||
1,
|
||||
CShuffleNXdlPerWavePerShuffle * NWave * NPerXdl>>{};
|
||||
|
||||
constexpr index_t num_access = sfc_c_vgpr.GetNumOfAccess();
|
||||
|
||||
static_assert(num_access == sfc_c_global.GetNumOfAccess(), "wrong!");
|
||||
|
||||
static_for<0, num_access, 1>{}([&](auto access_id) {
|
||||
// make sure it's safe to write to LDS
|
||||
block_sync_lds();
|
||||
|
||||
// each thread write its data from VGPR to LDS
|
||||
c_thread_copy_vgpr_to_lds.Run(c_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2,
|
||||
sfc_c_vgpr.GetIndexTupleOfNumber(access_id),
|
||||
c_thread_buf,
|
||||
c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2,
|
||||
c_shuffle_block_buf);
|
||||
|
||||
// make sure it's safe to read from LDS
|
||||
block_sync_lds();
|
||||
|
||||
// each block copy its data from LDS to global
|
||||
c_shuffle_block_copy_lds_to_global.Run(
|
||||
c_shuffle_block_desc_mblock_mperblock_nblock_nperblock,
|
||||
c_shuffle_block_buf,
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
c_grid_buf);
|
||||
|
||||
// reduce
|
||||
{
|
||||
// copy from LDS to VGPR
|
||||
c_reduce_thread_copy_lds_to_vgpr.Run(c_reduce_block_desc_mperblock_nperblock,
|
||||
c_shuffle_block_buf,
|
||||
c_reduce_thread_desc_mperblock_nperblock,
|
||||
make_tuple(I0, I0),
|
||||
c_reduce_thread_buf);
|
||||
|
||||
// reduce in VGPR
|
||||
static_for<0, mreduce_per_thread, 1>{}([&](auto im) {
|
||||
FloatReduceAcc d0_acc = d0_reduce_op.GetReduceZeroValue();
|
||||
FloatReduceAcc d1_acc = d1_reduce_op.GetReduceZeroValue();
|
||||
|
||||
static_for<0, nreduce_per_thread, 1>{}([&](auto in) {
|
||||
constexpr auto offset =
|
||||
Number<c_reduce_thread_desc_mperblock_nperblock.CalculateOffset(
|
||||
make_tuple(im, in))>{};
|
||||
|
||||
d0_reduce_op.Reduce(d0_acc, c_reduce_thread_buf[offset]);
|
||||
d1_reduce_op.Reduce(d1_acc, c_reduce_thread_buf[offset]);
|
||||
});
|
||||
|
||||
constexpr index_t out_offset =
|
||||
d_reduce_thread_desc_mperblock.CalculateOffset(make_tuple(im));
|
||||
|
||||
d0_thread_buf(Number<out_offset>{}) = d0_acc;
|
||||
d1_thread_buf(Number<out_offset>{}) = d1_acc;
|
||||
});
|
||||
|
||||
// copy from VGPR to Global
|
||||
d0_reduce_thread_copy_vgpr_to_global.Run(d_reduce_thread_desc_mblock_mperblock,
|
||||
make_tuple(I0, I0),
|
||||
d0_thread_buf,
|
||||
d_grid_desc_mblock_mperblock,
|
||||
d0_grid_buf);
|
||||
|
||||
d1_reduce_thread_copy_vgpr_to_global.Run(d_reduce_thread_desc_mblock_mperblock,
|
||||
make_tuple(I0, I0),
|
||||
d1_thread_buf,
|
||||
d_grid_desc_mblock_mperblock,
|
||||
d1_grid_buf);
|
||||
}
|
||||
|
||||
if constexpr(access_id < num_access - 1)
|
||||
{
|
||||
constexpr auto c_global_step = sfc_c_global.GetForwardStep(access_id);
|
||||
|
||||
// move on C
|
||||
c_shuffle_block_copy_lds_to_global.MoveDstSliceWindow(
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock, c_global_step);
|
||||
|
||||
// move on D0
|
||||
d0_reduce_thread_copy_vgpr_to_global.MoveDstSliceWindow(
|
||||
d_grid_desc_mblock_mperblock,
|
||||
make_tuple(c_global_step[I0], c_global_step[I1]));
|
||||
|
||||
// move on D1
|
||||
d1_reduce_thread_copy_vgpr_to_global.MoveDstSliceWindow(
|
||||
d_grid_desc_mblock_mperblock,
|
||||
make_tuple(c_global_step[I0], c_global_step[I1]));
|
||||
}
|
||||
});
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,684 @@
|
||||
#pragma once
|
||||
#include "common_header.hpp"
|
||||
#include "multi_index_transform_helper.hpp"
|
||||
#include "tensor_descriptor.hpp"
|
||||
#include "tensor_descriptor_helper.hpp"
|
||||
#include "blockwise_gemm_xdlops.hpp"
|
||||
#include "blockwise_tensor_slice_transfer_v4r1.hpp"
|
||||
#include "blockwise_tensor_slice_transfer_v6r1.hpp"
|
||||
#include "threadwise_tensor_slice_transfer.hpp"
|
||||
#include "gridwise_gemm_pipeline_v1.hpp"
|
||||
|
||||
namespace ck {
|
||||
|
||||
template <typename GridwiseGemm,
|
||||
typename FloatAB,
|
||||
typename FloatC,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CElementwiseOperation,
|
||||
typename AGridDesc_AK0_M_AK1,
|
||||
typename BGridDesc_BK0_N_BK1,
|
||||
typename CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename Block2CTileMap,
|
||||
bool HasMainK0BlockLoop>
|
||||
__global__ void
|
||||
#if CK_USE_LAUNCH_BOUNDS
|
||||
__launch_bounds__(CK_MAX_THREAD_PER_BLOCK, CK_MIN_BLOCK_PER_CU)
|
||||
#endif
|
||||
kernel_gemm_xdl_cshuffle_v1(const FloatAB* __restrict__ p_a_grid,
|
||||
const FloatAB* __restrict__ p_b_grid,
|
||||
FloatC* __restrict__ p_c_grid,
|
||||
const AElementwiseOperation a_element_op,
|
||||
const BElementwiseOperation b_element_op,
|
||||
const CElementwiseOperation c_element_op,
|
||||
const AGridDesc_AK0_M_AK1 a_grid_desc_ak0_m_ak1,
|
||||
const BGridDesc_BK0_N_BK1 b_grid_desc_bk0_n_bk1,
|
||||
const CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
const Block2CTileMap block_2_ctile_map)
|
||||
{
|
||||
__shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()];
|
||||
|
||||
GridwiseGemm::template Run<HasMainK0BlockLoop>(p_a_grid,
|
||||
p_b_grid,
|
||||
p_c_grid,
|
||||
p_shared,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
c_element_op,
|
||||
a_grid_desc_ak0_m_ak1,
|
||||
b_grid_desc_bk0_n_bk1,
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
block_2_ctile_map);
|
||||
}
|
||||
|
||||
template <typename FloatAB,
|
||||
typename FloatGemmAcc,
|
||||
typename FloatCShuffle,
|
||||
typename FloatC,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CElementwiseOperation,
|
||||
InMemoryDataOperationEnum_t CGlobalMemoryDataOperation,
|
||||
typename AGridDesc_AK0_M_AK1,
|
||||
typename BGridDesc_BK0_N_BK1,
|
||||
typename CGridDesc_M_N,
|
||||
index_t NumGemmKPrefetchStage,
|
||||
index_t BlockSize,
|
||||
index_t MPerBlock,
|
||||
index_t NPerBlock,
|
||||
index_t KPerBlock,
|
||||
index_t AK1Value,
|
||||
index_t BK1Value,
|
||||
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 AThreadTransferSrcResetCoordinateAfterRun,
|
||||
index_t ABlockLdsExtraM,
|
||||
typename BBlockTransferThreadClusterLengths_BK0_N_BK1,
|
||||
typename BBlockTransferThreadClusterArrangeOrder,
|
||||
typename BBlockTransferSrcAccessOrder,
|
||||
index_t BBlockTransferSrcVectorDim,
|
||||
index_t BBlockTransferSrcScalarPerVector,
|
||||
index_t BBlockTransferDstScalarPerVector_BK1,
|
||||
bool BThreadTransferSrcResetCoordinateAfterRun,
|
||||
index_t BBlockLdsExtraN,
|
||||
index_t CShuffleMXdlPerWavePerShuffle,
|
||||
index_t CShuffleNXdlPerWavePerShuffle,
|
||||
typename CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
index_t CShuffleBlockTransferScalarPerVector_NPerBlock>
|
||||
struct GridwiseGemm_k0mk1_k0nk1_mn_xdl_cshuffle_v1
|
||||
{
|
||||
static constexpr auto I0 = Number<0>{};
|
||||
static constexpr auto I1 = Number<1>{};
|
||||
static constexpr auto I2 = Number<2>{};
|
||||
static constexpr auto I3 = Number<3>{};
|
||||
static constexpr auto I4 = Number<4>{};
|
||||
static constexpr auto I5 = Number<5>{};
|
||||
static constexpr auto I6 = Number<6>{};
|
||||
static constexpr auto I7 = Number<7>{};
|
||||
|
||||
// K1 should be Number<...>
|
||||
static constexpr auto AK0 = Number<KPerBlock / AK1Value>{};
|
||||
static constexpr auto BK0 = Number<KPerBlock / BK1Value>{};
|
||||
static constexpr auto AK1 = Number<AK1Value>{};
|
||||
static constexpr auto BK1 = Number<BK1Value>{};
|
||||
|
||||
__host__ __device__ static constexpr auto GetABlockDescriptor_AK0PerBlock_MPerBlock_AK1()
|
||||
{
|
||||
// A matrix in LDS memory, dst of blockwise copy
|
||||
return make_naive_tensor_descriptor(
|
||||
make_tuple(AK0, Number<MPerBlock>{}, AK1),
|
||||
make_tuple(Number<MPerBlock + ABlockLdsExtraM>{} * AK1, AK1, I1));
|
||||
}
|
||||
|
||||
__host__ __device__ static constexpr auto GetBBlockDescriptor_BK0PerBlock_NPerBlock_BK1()
|
||||
{
|
||||
// B matrix in LDS memory, dst of blockwise copy
|
||||
return make_naive_tensor_descriptor(
|
||||
make_tuple(BK0, Number<NPerBlock>{}, BK1),
|
||||
make_tuple(Number<NPerBlock + BBlockLdsExtraN>{} * BK1, BK1, I1));
|
||||
}
|
||||
|
||||
__host__ __device__ static constexpr auto
|
||||
GetCShuffleBlockDescriptor_MBlock_MPerBlock_NBlock_NPerBlock()
|
||||
{
|
||||
constexpr index_t MWave = MPerBlock / (MXdlPerWave * MPerXdl);
|
||||
constexpr index_t NWave = NPerBlock / (NXdlPerWave * NPerXdl);
|
||||
|
||||
constexpr auto c_shuffle_block_desc_mblock_mperblock_nblock_nperblock =
|
||||
make_naive_tensor_descriptor_packed(
|
||||
make_tuple(I1,
|
||||
Number<CShuffleMXdlPerWavePerShuffle * MWave * MPerXdl>{},
|
||||
I1,
|
||||
Number<CShuffleNXdlPerWavePerShuffle * NWave * NPerXdl>{}));
|
||||
|
||||
return c_shuffle_block_desc_mblock_mperblock_nblock_nperblock;
|
||||
}
|
||||
|
||||
__host__ __device__ static constexpr index_t GetSharedMemoryNumberOfByte()
|
||||
{
|
||||
// LDS allocation for A and B: be careful of alignment
|
||||
constexpr auto a_block_desc_ak0_m_ak1 = GetABlockDescriptor_AK0PerBlock_MPerBlock_AK1();
|
||||
constexpr auto b_block_desc_bk0_n_bk1 = GetBBlockDescriptor_BK0PerBlock_NPerBlock_BK1();
|
||||
|
||||
// lds max alignment
|
||||
constexpr auto max_lds_align = math::lcm(AK1, BK1);
|
||||
|
||||
constexpr auto a_block_space_size_aligned = math::integer_least_multiple(
|
||||
a_block_desc_ak0_m_ak1.GetElementSpaceSize(), max_lds_align);
|
||||
|
||||
constexpr auto b_block_space_size_aligned = math::integer_least_multiple(
|
||||
b_block_desc_bk0_n_bk1.GetElementSpaceSize(), max_lds_align);
|
||||
|
||||
// LDS allocation for C shuffle in LDS
|
||||
constexpr auto c_shuffle_block_desc_mblock_mperblock_nblock_nperblock =
|
||||
GetCShuffleBlockDescriptor_MBlock_MPerBlock_NBlock_NPerBlock();
|
||||
|
||||
constexpr auto c_block_size =
|
||||
c_shuffle_block_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize();
|
||||
|
||||
return math::max((a_block_space_size_aligned + b_block_space_size_aligned) *
|
||||
sizeof(FloatAB),
|
||||
c_block_size * sizeof(FloatCShuffle));
|
||||
}
|
||||
|
||||
// block_id to matrix tile idx (m0, n0) mapping are controlled by {M01, N01}
|
||||
__host__ __device__ static constexpr bool
|
||||
CheckValidity(const AGridDesc_AK0_M_AK1& a_grid_desc_ak0_m_ak1,
|
||||
const BGridDesc_BK0_N_BK1& b_grid_desc_bk0_n_bk1,
|
||||
const CGridDesc_M_N& c_grid_desc_m_n)
|
||||
{
|
||||
// static_assert(is_known_at_compile_time<remove_cv_t<decltype(AK1)>>::value &&
|
||||
// is_known_at_compile_time<remove_cv_t<decltype(BK1)>>::value,
|
||||
// "wrong! K1 need to be known at compile-time");
|
||||
|
||||
static_assert((MPerBlock % (MPerXdl * MXdlPerWave) == 0) &&
|
||||
(NPerBlock % (NXdlPerWave * NPerXdl)) == 0,
|
||||
"Invalid tuning param!");
|
||||
|
||||
const auto M = a_grid_desc_ak0_m_ak1.GetLength(I1);
|
||||
const auto N = b_grid_desc_bk0_n_bk1.GetLength(I1);
|
||||
const auto K = a_grid_desc_ak0_m_ak1.GetLength(I0) * a_grid_desc_ak0_m_ak1.GetLength(I2);
|
||||
|
||||
if(!(M == c_grid_desc_m_n.GetLength(I0) && N == c_grid_desc_m_n.GetLength(I1)))
|
||||
return false;
|
||||
|
||||
if(!(M % MPerBlock == 0 && N % NPerBlock == 0 && K % KPerBlock == 0))
|
||||
return false;
|
||||
|
||||
// check NumGemmKPrefetchStage
|
||||
if constexpr(NumGemmKPrefetchStage == 1)
|
||||
{
|
||||
// 1-stage prefetch always supported
|
||||
}
|
||||
else if constexpr(NumGemmKPrefetchStage == 2)
|
||||
{
|
||||
// 2-stage prefetch currently only support even number of K0 loop
|
||||
// TODO: add support for odd number of K0 loop
|
||||
if(!((K / KPerBlock) % 2 == 0))
|
||||
{
|
||||
return false;
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
return false;
|
||||
}
|
||||
|
||||
// TODO: also check validity of all components (blockwise-copy, threadwise-copy, etc)
|
||||
return true;
|
||||
}
|
||||
|
||||
__host__ __device__ static constexpr index_t
|
||||
CalculateGridSize(const CGridDesc_M_N& c_grid_desc_m_n)
|
||||
{
|
||||
const auto M = c_grid_desc_m_n.GetLength(I0);
|
||||
const auto N = c_grid_desc_m_n.GetLength(I1);
|
||||
|
||||
const index_t grid_size = (M / MPerBlock) * (N / NPerBlock);
|
||||
|
||||
return grid_size;
|
||||
}
|
||||
|
||||
// TODO move this function into GEMM-pipeline class
|
||||
__host__ __device__ static constexpr bool CalculateHasMainK0BlockLoop(index_t K0)
|
||||
{
|
||||
const bool has_main_k0_block_loop = ((K0 * AK1) / (NumGemmKPrefetchStage * KPerBlock)) > 1;
|
||||
|
||||
return has_main_k0_block_loop;
|
||||
}
|
||||
|
||||
__host__ __device__ static constexpr auto
|
||||
MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(const CGridDesc_M_N& c_grid_desc_m_n)
|
||||
{
|
||||
const auto M = c_grid_desc_m_n.GetLength(I0);
|
||||
const auto N = c_grid_desc_m_n.GetLength(I1);
|
||||
|
||||
const auto MBlock = M / MPerBlock;
|
||||
const auto NBlock = N / NPerBlock;
|
||||
|
||||
const auto c_grid_desc_mblock_mperblock_nblock_nperblock = transform_tensor_descriptor(
|
||||
c_grid_desc_m_n,
|
||||
make_tuple(make_unmerge_transform(make_tuple(MBlock, Number<MPerBlock>{})),
|
||||
make_unmerge_transform(make_tuple(NBlock, Number<NPerBlock>{}))),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0, 1>{}, Sequence<2, 3>{}));
|
||||
|
||||
return c_grid_desc_mblock_mperblock_nblock_nperblock;
|
||||
}
|
||||
|
||||
// return block_id to C matrix tile idx (m0, n0) mapping
|
||||
__host__ __device__ static constexpr auto
|
||||
MakeDefaultBlock2CTileMap(const CGridDesc_M_N& c_grid_desc_m_n)
|
||||
{
|
||||
const auto M = c_grid_desc_m_n.GetLength(I0);
|
||||
const auto N = c_grid_desc_m_n.GetLength(I1);
|
||||
|
||||
constexpr auto M1 = Number<MPerBlock>{};
|
||||
constexpr auto N1 = Number<NPerBlock>{};
|
||||
|
||||
const auto M0 = M / M1;
|
||||
const auto N0 = N / N1;
|
||||
|
||||
// FIXME: remove
|
||||
constexpr auto M01 = I1;
|
||||
constexpr auto N01 = I1;
|
||||
|
||||
const auto M00 = M0 / M01;
|
||||
const auto N00 = N0 / N01;
|
||||
|
||||
const auto m00_m01_n00_n01_to_m0_n0_block_cluster_adaptor =
|
||||
make_single_stage_tensor_adaptor(
|
||||
make_tuple(make_unmerge_transform(make_tuple(M00, M01)),
|
||||
make_unmerge_transform(make_tuple(N00, N01))),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0, 2>{}, Sequence<1, 3>{}));
|
||||
|
||||
const auto cblockid_to_m00_m01_n00_n01_block_cluster_adaptor =
|
||||
make_single_stage_tensor_adaptor(
|
||||
make_tuple(make_merge_transform(make_tuple(M00, N00, M01, N01))),
|
||||
make_tuple(Sequence<0, 1, 2, 3>{}),
|
||||
make_tuple(Sequence<0>{}));
|
||||
|
||||
const auto cblockid_to_m0_n0_block_cluster_adaptor =
|
||||
chain_tensor_adaptors(m00_m01_n00_n01_to_m0_n0_block_cluster_adaptor,
|
||||
cblockid_to_m00_m01_n00_n01_block_cluster_adaptor);
|
||||
|
||||
return cblockid_to_m0_n0_block_cluster_adaptor;
|
||||
}
|
||||
|
||||
using CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock = remove_cvref_t<decltype(
|
||||
MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(CGridDesc_M_N{}))>;
|
||||
|
||||
using DefaultBlock2CTileMap =
|
||||
remove_cvref_t<decltype(MakeDefaultBlock2CTileMap(CGridDesc_M_N{}))>;
|
||||
|
||||
template <bool HasMainK0BlockLoop, typename Block2CTileMap>
|
||||
__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,
|
||||
const AElementwiseOperation& a_element_op,
|
||||
const BElementwiseOperation& b_element_op,
|
||||
const CElementwiseOperation& c_element_op,
|
||||
const AGridDesc_AK0_M_AK1& a_grid_desc_ak0_m_ak1,
|
||||
const BGridDesc_BK0_N_BK1& b_grid_desc_bk0_n_bk1,
|
||||
const CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock&
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
const Block2CTileMap& block_2_ctile_map)
|
||||
{
|
||||
const auto a_grid_buf = make_dynamic_buffer<AddressSpaceEnum_t::Global>(
|
||||
p_a_grid, a_grid_desc_ak0_m_ak1.GetElementSpaceSize());
|
||||
const auto b_grid_buf = make_dynamic_buffer<AddressSpaceEnum_t::Global>(
|
||||
p_b_grid, b_grid_desc_bk0_n_bk1.GetElementSpaceSize());
|
||||
auto c_grid_buf = make_dynamic_buffer<AddressSpaceEnum_t::Global>(
|
||||
p_c_grid, c_grid_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize());
|
||||
|
||||
// divide block work by [M, N]
|
||||
const auto block_work_idx =
|
||||
block_2_ctile_map.CalculateBottomIndex(make_multi_index(get_block_1d_id()));
|
||||
|
||||
// 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[I0] * MPerBlock);
|
||||
|
||||
const index_t n_block_data_idx_on_grid =
|
||||
__builtin_amdgcn_readfirstlane(block_work_idx[I1] * NPerBlock);
|
||||
|
||||
// lds max alignment
|
||||
constexpr auto max_lds_align = math::lcm(AK1, BK1);
|
||||
|
||||
// A matrix in LDS memory, dst of blockwise copy
|
||||
constexpr auto a_block_desc_ak0_m_ak1 = GetABlockDescriptor_AK0PerBlock_MPerBlock_AK1();
|
||||
|
||||
// B matrix in LDS memory, dst of blockwise copy
|
||||
constexpr auto b_block_desc_bk0_n_bk1 = GetBBlockDescriptor_BK0PerBlock_NPerBlock_BK1();
|
||||
|
||||
// A matrix blockwise copy
|
||||
auto a_blockwise_copy =
|
||||
BlockwiseTensorSliceTransfer_v4r1<BlockSize,
|
||||
AElementwiseOperation,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
InMemoryDataOperationEnum_t::Set,
|
||||
Sequence<AK0, MPerBlock, AK1>,
|
||||
ABlockTransferThreadClusterLengths_AK0_M_AK1,
|
||||
ABlockTransferThreadClusterArrangeOrder,
|
||||
FloatAB,
|
||||
FloatAB,
|
||||
decltype(a_grid_desc_ak0_m_ak1),
|
||||
decltype(a_block_desc_ak0_m_ak1),
|
||||
ABlockTransferSrcAccessOrder,
|
||||
Sequence<1, 0, 2>,
|
||||
ABlockTransferSrcVectorDim,
|
||||
2,
|
||||
ABlockTransferSrcScalarPerVector,
|
||||
ABlockTransferDstScalarPerVector_AK1,
|
||||
1,
|
||||
1,
|
||||
AThreadTransferSrcResetCoordinateAfterRun,
|
||||
true,
|
||||
NumGemmKPrefetchStage>(
|
||||
a_grid_desc_ak0_m_ak1,
|
||||
make_multi_index(0, m_block_data_idx_on_grid, 0),
|
||||
a_element_op,
|
||||
a_block_desc_ak0_m_ak1,
|
||||
make_multi_index(0, 0, 0),
|
||||
ck::tensor_operation::element_wise::PassThrough{});
|
||||
|
||||
// B matrix blockwise copy
|
||||
auto b_blockwise_copy =
|
||||
BlockwiseTensorSliceTransfer_v4r1<BlockSize,
|
||||
BElementwiseOperation,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
InMemoryDataOperationEnum_t::Set,
|
||||
Sequence<BK0, NPerBlock, BK1>,
|
||||
BBlockTransferThreadClusterLengths_BK0_N_BK1,
|
||||
BBlockTransferThreadClusterArrangeOrder,
|
||||
FloatAB,
|
||||
FloatAB,
|
||||
decltype(b_grid_desc_bk0_n_bk1),
|
||||
decltype(b_block_desc_bk0_n_bk1),
|
||||
BBlockTransferSrcAccessOrder,
|
||||
Sequence<1, 0, 2>,
|
||||
BBlockTransferSrcVectorDim,
|
||||
2,
|
||||
BBlockTransferSrcScalarPerVector,
|
||||
BBlockTransferDstScalarPerVector_BK1,
|
||||
1,
|
||||
1,
|
||||
BThreadTransferSrcResetCoordinateAfterRun,
|
||||
true,
|
||||
NumGemmKPrefetchStage>(
|
||||
b_grid_desc_bk0_n_bk1,
|
||||
make_multi_index(0, n_block_data_idx_on_grid, 0),
|
||||
b_element_op,
|
||||
b_block_desc_bk0_n_bk1,
|
||||
make_multi_index(0, 0, 0),
|
||||
ck::tensor_operation::element_wise::PassThrough{});
|
||||
|
||||
// GEMM definition
|
||||
// c_mtx += transpose(a_mtx) * b_mtx
|
||||
// a_mtx[K0PerBlock, MPerBlock] is in LDS
|
||||
// b_mtx[K0PerBlock, NPerBlock] is in LDS
|
||||
// c_mtx[MPerBlock, NPerBlock] is distributed among threads, and saved in
|
||||
// register
|
||||
// sanity check
|
||||
constexpr index_t KPack = math::max(
|
||||
math::lcm(AK1, BK1), MfmaSelector<FloatAB, MPerXdl, NPerXdl>::selected_mfma.k_per_blk);
|
||||
|
||||
auto blockwise_gemm =
|
||||
BlockwiseGemmXdlops_k0mk1_k0nk1_m0n0m1n1m2m3m4n2_v1<BlockSize,
|
||||
FloatAB,
|
||||
FloatGemmAcc,
|
||||
decltype(a_block_desc_ak0_m_ak1),
|
||||
decltype(b_block_desc_bk0_n_bk1),
|
||||
MPerXdl,
|
||||
NPerXdl,
|
||||
MXdlPerWave,
|
||||
NXdlPerWave,
|
||||
KPack>{};
|
||||
|
||||
auto c_thread_buf = blockwise_gemm.GetCThreadBuffer();
|
||||
|
||||
// LDS allocation for A and B: be careful of alignment
|
||||
constexpr auto a_block_space_size_aligned = math::integer_least_multiple(
|
||||
a_block_desc_ak0_m_ak1.GetElementSpaceSize(), max_lds_align);
|
||||
|
||||
auto a_block_buf = make_dynamic_buffer<AddressSpaceEnum_t::Lds>(
|
||||
static_cast<FloatAB*>(p_shared), a_block_desc_ak0_m_ak1.GetElementSpaceSize());
|
||||
|
||||
auto b_block_buf = make_dynamic_buffer<AddressSpaceEnum_t::Lds>(
|
||||
static_cast<FloatAB*>(p_shared) + a_block_space_size_aligned,
|
||||
b_block_desc_bk0_n_bk1.GetElementSpaceSize());
|
||||
|
||||
constexpr auto a_block_slice_copy_step = make_multi_index(KPerBlock / AK1, 0, 0);
|
||||
constexpr auto b_block_slice_copy_step = make_multi_index(KPerBlock / BK1, 0, 0);
|
||||
|
||||
// gridwise GEMM pipeline
|
||||
const auto gridwise_gemm_pipeline =
|
||||
GridwiseGemmPipeline_v1<remove_cvref_t<decltype(a_grid_desc_ak0_m_ak1)>,
|
||||
remove_cvref_t<decltype(a_block_desc_ak0_m_ak1)>,
|
||||
remove_cvref_t<decltype(a_blockwise_copy)>,
|
||||
remove_cvref_t<decltype(a_grid_buf)>,
|
||||
remove_cvref_t<decltype(a_block_buf)>,
|
||||
remove_cvref_t<decltype(a_block_slice_copy_step)>,
|
||||
remove_cvref_t<decltype(b_grid_desc_bk0_n_bk1)>,
|
||||
remove_cvref_t<decltype(b_block_desc_bk0_n_bk1)>,
|
||||
remove_cvref_t<decltype(b_blockwise_copy)>,
|
||||
remove_cvref_t<decltype(b_grid_buf)>,
|
||||
remove_cvref_t<decltype(b_block_buf)>,
|
||||
remove_cvref_t<decltype(b_block_slice_copy_step)>,
|
||||
remove_cvref_t<decltype(blockwise_gemm)>,
|
||||
remove_cvref_t<decltype(c_thread_buf)>,
|
||||
NumGemmKPrefetchStage,
|
||||
HasMainK0BlockLoop>{};
|
||||
|
||||
const index_t num_k_block_main_loop = __builtin_amdgcn_readfirstlane(
|
||||
(a_grid_desc_ak0_m_ak1.GetLength(I0) * a_grid_desc_ak0_m_ak1.GetLength(I2)) /
|
||||
KPerBlock);
|
||||
|
||||
gridwise_gemm_pipeline.Run(a_grid_desc_ak0_m_ak1,
|
||||
a_block_desc_ak0_m_ak1,
|
||||
a_blockwise_copy,
|
||||
a_grid_buf,
|
||||
a_block_buf,
|
||||
a_block_slice_copy_step,
|
||||
b_grid_desc_bk0_n_bk1,
|
||||
b_block_desc_bk0_n_bk1,
|
||||
b_blockwise_copy,
|
||||
b_grid_buf,
|
||||
b_block_buf,
|
||||
b_block_slice_copy_step,
|
||||
blockwise_gemm,
|
||||
c_thread_buf,
|
||||
num_k_block_main_loop);
|
||||
|
||||
// shuffle C and write out
|
||||
{
|
||||
static_assert(MXdlPerWave % CShuffleMXdlPerWavePerShuffle == 0 &&
|
||||
NXdlPerWave % CShuffleNXdlPerWavePerShuffle == 0,
|
||||
"wrong!");
|
||||
|
||||
constexpr index_t MWave = MPerBlock / (MXdlPerWave * MPerXdl);
|
||||
constexpr index_t NWave = NPerBlock / (NXdlPerWave * NPerXdl);
|
||||
|
||||
// TODO: hacky, fix it!
|
||||
constexpr auto c_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2 =
|
||||
blockwise_gemm.GetCThreadDescriptor_M0_N0_M1_N1_M2_M3_M4_N2();
|
||||
|
||||
// TODO: hacky, fix it!
|
||||
// c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp is only used to get lengths
|
||||
constexpr auto c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp =
|
||||
blockwise_gemm.GetCBlockDescriptor_M0_N0_M1_N1_M2_M3_M4_N2();
|
||||
|
||||
constexpr auto M0 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I0);
|
||||
constexpr auto N0 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I1);
|
||||
constexpr auto M1 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I2);
|
||||
constexpr auto N1 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I3);
|
||||
constexpr auto M2 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I4);
|
||||
constexpr auto M3 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I5);
|
||||
constexpr auto M4 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I6);
|
||||
constexpr auto N2 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I7);
|
||||
|
||||
constexpr auto c_shuffle_block_desc_mblock_mperblock_nblock_nperblock =
|
||||
GetCShuffleBlockDescriptor_MBlock_MPerBlock_NBlock_NPerBlock();
|
||||
|
||||
auto c_shuffle_block_buf = make_dynamic_buffer<AddressSpaceEnum_t::Lds>(
|
||||
static_cast<FloatCShuffle*>(p_shared),
|
||||
c_shuffle_block_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize());
|
||||
|
||||
constexpr auto c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2 = transform_tensor_descriptor(
|
||||
c_shuffle_block_desc_mblock_mperblock_nblock_nperblock,
|
||||
make_tuple(
|
||||
make_freeze_transform(I0),
|
||||
make_unmerge_transform(make_tuple(
|
||||
Number<CShuffleMXdlPerWavePerShuffle>{}, // M0 (MXdlPerWave) per shuffle
|
||||
M1, // M1 = MWave
|
||||
M2, // M2 * M3 * M4 = MPerXdl
|
||||
M3,
|
||||
M4)),
|
||||
make_freeze_transform(I0),
|
||||
make_unmerge_transform(make_tuple(
|
||||
Number<CShuffleNXdlPerWavePerShuffle>{}, // N0 (NXdlPerWave) per shuffle
|
||||
N1, // N1 = NWave
|
||||
N2))), // N2 = NPerXdl
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
|
||||
make_tuple(
|
||||
Sequence<>{}, Sequence<0, 2, 4, 5, 6>{}, Sequence<>{}, Sequence<1, 3, 7>{}));
|
||||
|
||||
// calculate origin of thread output tensor on global memory
|
||||
// blockwise GEMM c matrix starting index
|
||||
const auto c_thread_mtx_on_block =
|
||||
blockwise_gemm.CalculateCThreadOriginDataIndex(I0, I0, I0, I0);
|
||||
|
||||
const index_t m_thread_data_on_block = c_thread_mtx_on_block[I0];
|
||||
const index_t n_thread_data_on_block = c_thread_mtx_on_block[I1];
|
||||
|
||||
const auto m_thread_data_on_block_to_m0_m1_m2_m3_m4_adaptor =
|
||||
make_single_stage_tensor_adaptor(
|
||||
make_tuple(make_merge_transform(make_tuple(M0, M1, M2, M3, M4))),
|
||||
make_tuple(Sequence<0, 1, 2, 3, 4>{}),
|
||||
make_tuple(Sequence<0>{}));
|
||||
|
||||
const auto m_thread_data_on_block_idx =
|
||||
m_thread_data_on_block_to_m0_m1_m2_m3_m4_adaptor.CalculateBottomIndex(
|
||||
make_multi_index(m_thread_data_on_block));
|
||||
|
||||
const auto n_thread_data_on_block_to_n0_n1_n2_adaptor =
|
||||
make_single_stage_tensor_adaptor(
|
||||
make_tuple(make_merge_transform(make_tuple(N0, N1, N2))),
|
||||
make_tuple(Sequence<0, 1, 2>{}),
|
||||
make_tuple(Sequence<0>{}));
|
||||
|
||||
const auto n_thread_data_on_block_idx =
|
||||
n_thread_data_on_block_to_n0_n1_n2_adaptor.CalculateBottomIndex(
|
||||
make_multi_index(n_thread_data_on_block));
|
||||
|
||||
// shuffle: threadwise copy C from VGPR to LDS
|
||||
auto c_thread_copy_vgpr_to_lds =
|
||||
ThreadwiseTensorSliceTransfer_v1r3<FloatGemmAcc,
|
||||
FloatCShuffle,
|
||||
decltype(c_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2),
|
||||
decltype(c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2),
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
Sequence<CShuffleMXdlPerWavePerShuffle,
|
||||
CShuffleNXdlPerWavePerShuffle,
|
||||
I1,
|
||||
I1,
|
||||
M2,
|
||||
I1,
|
||||
M4,
|
||||
I1>,
|
||||
Sequence<0, 1, 2, 3, 4, 5, 6, 7>,
|
||||
7,
|
||||
1,
|
||||
InMemoryDataOperationEnum_t::Set,
|
||||
1,
|
||||
true>{
|
||||
c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2,
|
||||
make_multi_index(0,
|
||||
0,
|
||||
m_thread_data_on_block_idx[I1],
|
||||
n_thread_data_on_block_idx[I1],
|
||||
m_thread_data_on_block_idx[I2],
|
||||
m_thread_data_on_block_idx[I3],
|
||||
m_thread_data_on_block_idx[I4],
|
||||
n_thread_data_on_block_idx[I2]),
|
||||
ck::tensor_operation::element_wise::PassThrough{}};
|
||||
|
||||
// shuffle: blockwise copy C from LDS to global
|
||||
auto c_shuffle_block_copy_lds_to_global = BlockwiseTensorSliceTransfer_v6r1<
|
||||
BlockSize, // index_t BlockSize,
|
||||
CElementwiseOperation, // ElementwiseOperation,
|
||||
CGlobalMemoryDataOperation, // DstInMemOp,
|
||||
Sequence<1,
|
||||
CShuffleMXdlPerWavePerShuffle * MWave * MPerXdl,
|
||||
1,
|
||||
CShuffleNXdlPerWavePerShuffle * NWave * NPerXdl>, // BlockSliceLengths,
|
||||
CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
Sequence<0, 1, 2, 3>, // typename ThreadClusterArrangeOrder,
|
||||
FloatCShuffle, // typename SrcData,
|
||||
FloatC, // typename DstData,
|
||||
decltype(c_shuffle_block_desc_mblock_mperblock_nblock_nperblock),
|
||||
decltype(c_grid_desc_mblock_mperblock_nblock_nperblock),
|
||||
Sequence<0, 1, 2, 3>, // typename DimAccessOrder,
|
||||
3, // index_t VectorDim,
|
||||
CShuffleBlockTransferScalarPerVector_NPerBlock, // index_t ScalarPerVector,
|
||||
true, // bool ThreadTransferSrcResetCoordinateAfterRun,
|
||||
false> // bool ThreadTransferDstResetCoordinateAfterRun>
|
||||
{c_shuffle_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[I0], 0, block_work_idx[I1], 0),
|
||||
c_element_op};
|
||||
|
||||
// space filling curve for threadwise C in VGPR
|
||||
constexpr auto sfc_c_vgpr =
|
||||
SpaceFillingCurve<Sequence<MXdlPerWave, NXdlPerWave, 1, 1, M2, 1, M4, 1>,
|
||||
Sequence<0, 1, 2, 3, 4, 5, 6, 7>,
|
||||
Sequence<CShuffleMXdlPerWavePerShuffle,
|
||||
CShuffleNXdlPerWavePerShuffle,
|
||||
1,
|
||||
1,
|
||||
M2,
|
||||
1,
|
||||
M4,
|
||||
1>>{};
|
||||
|
||||
// space filling curve for shuffled blockwise C in global mem
|
||||
constexpr auto sfc_c_global =
|
||||
SpaceFillingCurve<Sequence<1, MPerBlock, 1, NPerBlock>,
|
||||
Sequence<0, 2, 1, 3>,
|
||||
Sequence<1,
|
||||
CShuffleMXdlPerWavePerShuffle * MWave * MPerXdl,
|
||||
1,
|
||||
CShuffleNXdlPerWavePerShuffle * NWave * NPerXdl>>{};
|
||||
|
||||
constexpr index_t num_access = sfc_c_vgpr.GetNumOfAccess();
|
||||
|
||||
static_assert(num_access == sfc_c_global.GetNumOfAccess(), "wrong!");
|
||||
|
||||
static_for<0, num_access, 1>{}([&](auto access_id) {
|
||||
// make sure it's safe to write to LDS
|
||||
block_sync_lds();
|
||||
|
||||
// each thread write its data from VGPR to LDS
|
||||
c_thread_copy_vgpr_to_lds.Run(c_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2,
|
||||
sfc_c_vgpr.GetIndexTupleOfNumber(access_id),
|
||||
c_thread_buf,
|
||||
c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2,
|
||||
c_shuffle_block_buf);
|
||||
|
||||
// make sure it's safe to read from LDS
|
||||
block_sync_lds();
|
||||
|
||||
// each block copy its data from LDS to global
|
||||
c_shuffle_block_copy_lds_to_global.Run(
|
||||
c_shuffle_block_desc_mblock_mperblock_nblock_nperblock,
|
||||
c_shuffle_block_buf,
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
c_grid_buf);
|
||||
|
||||
if constexpr(access_id < num_access - 1)
|
||||
{
|
||||
constexpr auto c_global_step = sfc_c_global.GetForwardStep(access_id);
|
||||
|
||||
// move on C
|
||||
c_shuffle_block_copy_lds_to_global.MoveDstSliceWindow(
|
||||
c_grid_desc_mblock_mperblock_nblock_nperblock, c_global_step);
|
||||
}
|
||||
});
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace ck
|
||||
@@ -277,14 +277,14 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
|
||||
__host__ __device__ static constexpr auto
|
||||
GetCBlockDescriptor_MBlock_MPerBlock_NBlock_NPerBlock()
|
||||
{
|
||||
constexpr index_t MWaves = MPerBlock / (MRepeat * MPerXDL);
|
||||
constexpr index_t NWaves = NPerBlock / (NRepeat * NPerXDL);
|
||||
constexpr index_t MWave = MPerBlock / (MRepeat * MPerXDL);
|
||||
constexpr index_t NWave = NPerBlock / (NRepeat * NPerXDL);
|
||||
|
||||
return make_naive_tensor_descriptor_packed(
|
||||
make_tuple(I1,
|
||||
Number<CShuffleMRepeatPerShuffle * MWaves * MPerXDL>{},
|
||||
Number<CShuffleMRepeatPerShuffle * MWave * MPerXDL>{},
|
||||
I1,
|
||||
Number<CShuffleNRepeatPerShuffle * NWaves * NPerXDL>{}));
|
||||
Number<CShuffleNRepeatPerShuffle * NWave * NPerXDL>{}));
|
||||
}
|
||||
|
||||
using CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock =
|
||||
@@ -539,8 +539,8 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
|
||||
|
||||
// output: register to global memory
|
||||
{
|
||||
constexpr index_t MWaves = MPerBlock / (MRepeat * MPerXDL);
|
||||
constexpr index_t NWaves = NPerBlock / (NRepeat * NPerXDL);
|
||||
constexpr index_t MWave = MPerBlock / (MRepeat * MPerXDL);
|
||||
constexpr index_t NWave = NPerBlock / (NRepeat * NPerXDL);
|
||||
|
||||
constexpr auto c_m0_n0_m1_n1_m2_m3_m4_n2_block_desc =
|
||||
blockwise_gemm.GetCBlockDescriptor_M0_N0_M1_N1_M2_M3_M4_N2();
|
||||
@@ -564,8 +564,8 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
|
||||
static_cast<FloatC*>(p_shared_block),
|
||||
c_block_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize());
|
||||
|
||||
static_assert(M1 == MWaves, "");
|
||||
static_assert(N1 == NWaves, "");
|
||||
static_assert(M1 == MWave, "");
|
||||
static_assert(N1 == NWave, "");
|
||||
static_assert(M2 * M3 * M4 == MPerXDL, "");
|
||||
static_assert(N2 == NPerXDL, "");
|
||||
|
||||
@@ -646,14 +646,15 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
|
||||
n_thread_data_on_block_idx[I2]),
|
||||
ck::tensor_operation::element_wise::PassThrough{}};
|
||||
|
||||
// LDS to global
|
||||
auto c_block_copy_lds_to_global = BlockwiseTensorSliceTransfer_v6r1<
|
||||
BlockSize, // index_t BlockSize,
|
||||
CElementwiseOperation, // ElementwiseOperation,
|
||||
CGlobalMemoryDataOperation, // DstInMemOp,
|
||||
Sequence<1,
|
||||
CShuffleMRepeatPerShuffle * MWaves * MPerXDL,
|
||||
CShuffleMRepeatPerShuffle * MWave * MPerXDL,
|
||||
1,
|
||||
CShuffleNRepeatPerShuffle * NWaves * NPerXDL>, // BlockSliceLengths,
|
||||
CShuffleNRepeatPerShuffle * NWave * NPerXDL>, // BlockSliceLengths,
|
||||
CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
Sequence<0, 1, 2, 3>, // typename ThreadClusterArrangeOrder,
|
||||
FloatC, // typename SrcData,
|
||||
@@ -672,11 +673,11 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4r2
|
||||
c_element_op};
|
||||
|
||||
constexpr auto mxdlperwave_forward_step =
|
||||
make_multi_index(0, CShuffleMRepeatPerShuffle * MWaves * MPerXDL, 0, 0);
|
||||
make_multi_index(0, CShuffleMRepeatPerShuffle * MWave * MPerXDL, 0, 0);
|
||||
constexpr auto nxdlperwave_forward_step =
|
||||
make_multi_index(0, 0, 0, CShuffleNRepeatPerShuffle * NWaves * NPerXDL);
|
||||
make_multi_index(0, 0, 0, CShuffleNRepeatPerShuffle * NWave * NPerXDL);
|
||||
constexpr auto nxdlperwave_backward_step =
|
||||
make_multi_index(0, 0, 0, -CShuffleNRepeatPerShuffle * NWaves * NPerXDL);
|
||||
make_multi_index(0, 0, 0, -CShuffleNRepeatPerShuffle * NWave * NPerXDL);
|
||||
|
||||
static_for<0, MRepeat, CShuffleMRepeatPerShuffle>{}([&](auto mxdlperwave_iter) {
|
||||
constexpr auto mxdlperwave = mxdlperwave_iter;
|
||||
|
||||
@@ -10,6 +10,7 @@
|
||||
#include "blockwise_tensor_slice_transfer_v6r1.hpp"
|
||||
#include "threadwise_tensor_slice_transfer.hpp"
|
||||
#include "gridwise_gemm_pipeline_v1.hpp"
|
||||
#include "tensor_space_filling_curve.hpp"
|
||||
|
||||
namespace ck {
|
||||
|
||||
@@ -657,6 +658,7 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v3r1
|
||||
n_thread_data_on_block_idx[I2]),
|
||||
ck::tensor_operation::element_wise::PassThrough{}};
|
||||
|
||||
// LDS to global
|
||||
auto c_block_copy_lds_to_global = BlockwiseTensorSliceTransfer_v6r1<
|
||||
BlockSize, // index_t BlockSize,
|
||||
CElementwiseOperation, // ElementwiseOperation,
|
||||
|
||||
Reference in New Issue
Block a user