diff options
Diffstat (limited to 'src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwElementwiseBinary.cpp')
| -rw-r--r-- | src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwElementwiseBinary.cpp | 399 |
1 files changed, 326 insertions, 73 deletions
diff --git a/src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwElementwiseBinary.cpp b/src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwElementwiseBinary.cpp index 2935ba45ea..fb55acad53 100644 --- a/src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwElementwiseBinary.cpp +++ b/src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwElementwiseBinary.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2023 Arm Limited. + * Copyright (c) 2023-2024 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -27,14 +27,11 @@ #include "arm_compute/core/utils/helpers/AdjustVecSize.h" #include "arm_compute/core/utils/StringUtils.h" #include "arm_compute/core/Validate.h" -#include "ckw/TensorTileSampler.h" -#include "ckw/types/TensorSamplerTypes.h" #include "src/core/helpers/WindowHelpers.h" +#include "src/dynamic_fusion/sketch/gpu/ckw_driver/components/utils/CkwHelper.h" #include "src/dynamic_fusion/sketch/gpu/ckw_driver/components/utils/type_converter/Common.h" #include "src/dynamic_fusion/sketch/gpu/ckw_driver/components/utils/type_converter/ElementwiseBinary.h" -#include "src/dynamic_fusion/sketch/gpu/ckw_driver/components/utils/WriterHelper.h" -#include "src/dynamic_fusion/sketch/gpu/ckw_driver/GpuCkwKernelWriter.h" #include "src/dynamic_fusion/sketch/gpu/ckw_driver/GpuCkwScopedKernelWriter.h" #include "src/dynamic_fusion/sketch/gpu/ckw_driver/GpuCkwVariableTable.h" #include "src/dynamic_fusion/sketch/gpu/components/utils/type_printer/ElementwiseBinary.h" @@ -42,10 +39,12 @@ #include "src/dynamic_fusion/sketch/gpu/GpuKernelComponentGroup.h" #include "support/StringSupport.h" -#include <algorithm> +#include "compute_kernel_writer/include/ckw/KernelWriter.h" +#include "compute_kernel_writer/include/ckw/types/ConstantData.h" +#include "compute_kernel_writer/include/ckw/types/TensorSamplerTypes.h" +#include <cstdint> #include <string> -using namespace ckw; namespace arm_compute { namespace experimental @@ -67,67 +66,339 @@ void GpuCkwElementwiseBinary::write_component_code(const ComponentGroup &comp GpuCkwVariableTable &vtable, GpuCkwScopedKernelWriter writer) const { - const auto root_window = comp_group.get_root_component()->ckw_component_driver()->get_window(); - const auto n0 = static_cast<int32_t>(root_window.x().step()); - const auto m0 = static_cast<int32_t>(root_window.y().step()); + /******************************************************************************** + * 1 - Define tensors + ********************************************************************************/ + GpuCkwComponentArgument *lhs = vtable.declare_variable(comp_group, writer, _lhs, "lhs"); + GpuCkwComponentArgument *rhs = vtable.declare_variable(comp_group, writer, _rhs, "rhs"); + GpuCkwComponentArgument *dst = vtable.declare_variable(comp_group, writer, _dst, "dst"); - GpuCkwComponentArgument *lhs = - vtable.declare_variable(comp_group, writer, _lhs, TensorStorageType::ClBufferUint8Ptr, "lhs"); - GpuCkwComponentArgument *rhs = - vtable.declare_variable(comp_group, writer, _rhs, TensorStorageType::ClBufferUint8Ptr, "rhs"); - GpuCkwComponentArgument *dst = - vtable.declare_variable(comp_group, writer, _dst, TensorStorageType::ClBufferUint8Ptr, "dst"); + /******************************************************************************** + * 2 - Define CKW constants + ********************************************************************************/ + const auto dst_h = static_cast<int32_t>(_dst->dimension(1)); - auto &gid_0 = writer->declare_tile("gid_0", ckw::DataType::Int32); - auto &gid_1 = writer->declare_tile("gid_1", ckw::DataType::Int32); - auto &gid_2 = writer->declare_tile("gid_2", ckw::DataType::Int32); + // CKW constants + auto const_dst_h_i32 = writer->declare_constant_tile(ckw::ConstantData({{dst_h}}, ckw::DataType::Int32)); + auto const_pos_1_i32 = writer->declare_constant_tile(ckw::ConstantData({{1}}, ckw::DataType::Int32)); + auto const_0_i32 = writer->declare_constant_tile(ckw::ConstantData({{0}}, ckw::DataType::Int32)); - writer->op_get_global_id(gid_0, 0); - writer->op_get_global_id(gid_1, 1); - writer->op_get_global_id(gid_2, 2); + /******************************************************************************** + * 3 - Define the compute block parameters and destination tile (if not root component) + * Bind the tile to the tensor to share it among different components and + * initialize the compute block parameters + ********************************************************************************/ + // The compute block parameters depend on the employed tensor format - auto &const_0 = writer->declare_tile("0", 0); + // Destination compute block size + int32_t dst_n0 = -1; + int32_t dst_m0 = -1; - // Load the LHS and RHS tiles - if (!lhs->has_tile()) + // Destination compute block size left-over + int32_t dst_n0_partial = -1; + int32_t dst_m0_partial = -1; + + if (!dst->has_tile()) { - auto sampler = create_boundary_aware_2d_sampler(writer, gid_0, gid_1, _lhs->dimension(0), _lhs->dimension(1), - n0, m0, "lhs_", const_0); - sampler.format(TensorSamplerFormat::C_WH_1); // 3rd dimension collapsed with 2nd dimension - sampler.z(const_0); - sampler.b(gid_2); - writer->op_load_once(lhs, sampler); + // If ROOT component, we use ckw::TensorSamplerFormat::Dim0_Dim1xDim2_1 + // as tensor format + const auto root_window = comp_group.get_root_component()->ckw_component_driver()->get_window(); + + dst_n0 = root_window.x().step(); + dst_m0 = root_window.y().step(); + dst_n0_partial = _dst->dimension(0) % dst_n0; + dst_m0_partial = (_dst->dimension(1) * _dst->dimension(2)) % dst_m0; + + ckw::TensorSampler sampler_dst; + sampler_dst.format(ckw::TensorSamplerFormat::Dim0_Dim1xDim2_1); + if (dst_n0_partial == 0) + { + sampler_dst.address_mode_x(ckw::TensorSamplerAddressModeX::None); + } + else + { + sampler_dst.address_mode_x(ckw::TensorSamplerAddressModeX::OverlappingMin); + } + + if (dst_m0_partial == 0) + { + sampler_dst.address_mode_y(ckw::TensorSamplerAddressModeY::None); + } + else + { + sampler_dst.address_mode_y(ckw::TensorSamplerAddressModeY::ClampToBorderMaxOnly); + } + sampler_dst.address_mode_z(ckw::TensorSamplerAddressModeZ::None); + sampler_dst.storage(ckw::TensorStorageType::BufferUint8Ptr); + + // Declare destination tile + ckw::DataType dst_dt = to_ckw(_dst->data_type()); + auto tile_dst = writer->declare_tile("dst", ckw::TileInfo(dst_dt, dst_m0, dst_n0)); + + // Bind tile to the tensor + dst->init_virtual_tensor(tile_dst, sampler_dst); } - if (!rhs->has_tile()) + else { - auto sampler = create_boundary_aware_2d_sampler(writer, gid_0, gid_1, _rhs->dimension(0), _rhs->dimension(1), - n0, m0, "rhs_", const_0); - sampler.format(TensorSamplerFormat::C_WH_1); // 3rd dimension collapsed with 2nd dimension - sampler.z(const_0); - sampler.b(gid_2); - writer->op_load_once(rhs, sampler); + // Change dst_n0 and dst_m0 if NOT root component! + dst_n0 = dst->tile().tile_info().width(); + dst_m0 = dst->tile().tile_info().height(); + + // Here, it is not required the calculation of dst_n0_partial and dst_m0_partial + // because if we enter this condition it means that the element-wise op is not the + // root component and the address modes have been already set. } - auto dst_sampler = create_boundary_aware_2d_sampler(writer, gid_0, gid_1, _dst->dimension(0), _dst->dimension(1), - n0, m0, "dst_", const_0); - dst_sampler.format(TensorSamplerFormat::C_WH_1); // 3rd dimension collapsed with 2nd dimension - dst_sampler.z(const_0); - dst_sampler.b(gid_2); + const auto &tile_dst = dst->tile(); - // Prepare the output tile. - if (!dst->has_tile()) + /******************************************************************************** + * 4 - Define the compute block parameters CKW constants + ********************************************************************************/ + // ... + + /******************************************************************************** + * 5 - Define the samplers for the input tensors + ********************************************************************************/ + // Check whether the lhs tensor is a tile or tensor + // If it is a tile, create a sampler and load the content in a tile + if (!lhs->has_tile()) { - auto &tile = writer->declare_tile( - "dst_tile", ckw::TileInfo(to_ckw(_dst->data_type()), dst_sampler.height(), dst_sampler.width())); - dst->init_virtual_tensor(tile, dst_sampler); + // Sampler + ckw::TensorSampler sampler_lhs = dst->tensor_sampler(); + + bool broadcast_x = false; + bool broadcast_y = false; + + int32_t lhs_n0 = dst_n0; + int32_t lhs_m0 = dst_m0; + + // Check whether we have broadcasting + // In case of broadcast, lhs can only be a vector or scalar. + // Broadcasting in other dimensions is not supported + if (_dst->dimension(0) != _lhs->dimension(0)) + { + broadcast_x = true; + lhs_n0 = 1; + } + + if (sampler_lhs.format() == ckw::TensorSamplerFormat::Dim0_Dim1xDim2_1) + { + if (_dst->dimension(1) * _dst->dimension(2) != _lhs->dimension(1) * _lhs->dimension(2)) + { + broadcast_y = true; + lhs_m0 = 1; + } + } + else if (sampler_lhs.format() == ckw::TensorSamplerFormat::Dim0_Dim1_Dim2) + { + if (_dst->dimension(1) != _lhs->dimension(1)) + { + broadcast_y = true; + lhs_m0 = 1; + } + } + + const int32_t lhs_partial_n0 = _lhs->dimension(0) % lhs_n0; + const int32_t lhs_shift_back = (lhs_n0 - lhs_partial_n0) % lhs_n0; + + // Constants + auto const_lhs_n0_i32 = writer->declare_constant_tile(ckw::ConstantData({{lhs_n0}}, ckw::DataType::Int32)); + auto const_lhs_m0_i32 = writer->declare_constant_tile(ckw::ConstantData({{lhs_m0}}, ckw::DataType::Int32)); + auto const_lhs_shift_back_n0_i32 = + writer->declare_constant_tile(ckw::ConstantData({{lhs_shift_back}}, ckw::DataType::Int32)); + + auto tile_gid_0 = writer->declare_tile("gid_0_lhs", ckw::TileInfo(ckw::DataType::Int32)); + auto tile_gid_1 = writer->declare_tile("gid_1_lhs", ckw::TileInfo(ckw::DataType::Int32)); + auto tile_gid_2 = writer->declare_tile("gid_2_lhs", ckw::TileInfo(ckw::DataType::Int32)); + + writer->op_get_global_id(tile_gid_0, 0); + writer->op_get_global_id(tile_gid_1, 1); + writer->op_get_global_id(tile_gid_2, 2); + + auto tile_cout0 = writer->declare_tile("cout0_lhs", ckw::TileInfo(ckw::DataType::Int32)); // OFM + auto tile_mout0 = + writer->declare_tile("mout0_lhs", ckw::TileInfo(ckw::DataType::Int32)); // WIDTH or WIDTH x HEIGHT + auto tile_mout1 = writer->declare_tile("mout1_lhs", ckw::TileInfo(ckw::DataType::Int32)); // HEIGHT or 0 + auto tile_bout0 = writer->declare_tile("bout0_lhs", ckw::TileInfo(ckw::DataType::Int32)); // BATCH SIZE IDX + + // Calculate coordinates + if (!broadcast_x) + { + get_coordinate_from_gws_overlapping_min(writer, tile_cout0, tile_gid_0, const_lhs_n0_i32, + const_lhs_shift_back_n0_i32, const_0_i32); + } + else + { + writer->op_assign(tile_cout0, const_0_i32); + } + + if (!broadcast_y) + { + get_coordinate_from_gws(writer, tile_mout0, tile_gid_1, const_lhs_m0_i32); + } + else + { + writer->op_assign(tile_mout0, const_0_i32); + } + + // Get the boundary aware coordinates at each global dimension index + if (sampler_lhs.format() == ckw::TensorSamplerFormat::Dim0_Dim1xDim2_1) + { + writer->op_assign(tile_mout1, const_0_i32); + get_coordinate_from_gws(writer, tile_bout0, tile_gid_2, const_pos_1_i32); + } + else if (sampler_lhs.format() == ckw::TensorSamplerFormat::Dim0_Dim1_Dim2) + { + // For tile_mout1 and tile_bout0 the step can only be 1 + if (!broadcast_y) + { + writer->op_binary(tile_mout1, ckw::BinaryOp::Mod, tile_gid_2, const_dst_h_i32); + } + else + { + // If broadcast_y == true, it means that we have either a scalar or vector + // because broadcasting in other dimensions is not supported + writer->op_assign(tile_mout1, const_0_i32); + } + + writer->op_binary(tile_bout0, ckw::BinaryOp::Div, tile_gid_2, const_dst_h_i32); + } + + ckw::DataType lhs_dt = to_ckw(_lhs->data_type()); + auto tile_lhs = writer->declare_tile("lhs", ckw::TileInfo(lhs_dt, lhs_m0, lhs_n0)); + + writer->op_load(tile_lhs, lhs->tensor(), sampler_lhs, tile_cout0, tile_mout0, tile_mout1, tile_bout0); + + // Here, init_virtual_tensor() is used to bring the tile_lhs outside the compound statement + lhs->init_virtual_tensor(tile_lhs, sampler_lhs); } - auto &lhs_tile = lhs->tile(); - auto &rhs_tile = rhs->tile(); - auto &dst_tile = dst->tile(); + // Check whether the rhs tensor is a tile or tensor + // If it is a tile, create a sampler and load the content in a tile + if (!rhs->has_tile()) + { + // Sampler + ckw::TensorSampler sampler_rhs = dst->tensor_sampler(); - // Perform the operation. - writer->op_binary_expression(dst_tile, lhs_tile, to_ckw(_attributes), rhs_tile); + bool broadcast_x = false; + bool broadcast_y = false; + + int32_t rhs_n0 = dst_n0; + int32_t rhs_m0 = dst_m0; + + // Check whether we have broadcasting + // In case of broadcast, rhs can only be a vector or scalar. + // Broadcasting in other dimensions is not supported + if (_dst->dimension(0) != _rhs->dimension(0)) + { + broadcast_x = true; + rhs_n0 = 1; + } + + if (sampler_rhs.format() == ckw::TensorSamplerFormat::Dim0_Dim1xDim2_1) + { + if (_dst->dimension(1) * _dst->dimension(2) != _rhs->dimension(1) * _rhs->dimension(2)) + { + broadcast_y = true; + rhs_m0 = 1; + } + } + else if (sampler_rhs.format() == ckw::TensorSamplerFormat::Dim0_Dim1_Dim2) + { + if (_dst->dimension(1) != _rhs->dimension(1)) + { + broadcast_y = true; + rhs_m0 = 1; + } + } + + const int32_t rhs_partial_n0 = _rhs->dimension(0) % rhs_n0; + const int32_t rhs_shift_back = (rhs_n0 - rhs_partial_n0) % rhs_n0; + + // Constants + auto const_rhs_n0_i32 = writer->declare_constant_tile(ckw::ConstantData({{rhs_n0}}, ckw::DataType::Int32)); + auto const_rhs_m0_i32 = writer->declare_constant_tile(ckw::ConstantData({{rhs_m0}}, ckw::DataType::Int32)); + auto const_rhs_shift_back_n0_i32 = + writer->declare_constant_tile(ckw::ConstantData({{rhs_shift_back}}, ckw::DataType::Int32)); + + auto tile_gid_0 = writer->declare_tile("gid_0_rhs", ckw::TileInfo(ckw::DataType::Int32)); + auto tile_gid_1 = writer->declare_tile("gid_1_rhs", ckw::TileInfo(ckw::DataType::Int32)); + auto tile_gid_2 = writer->declare_tile("gid_2_rhs", ckw::TileInfo(ckw::DataType::Int32)); + + writer->op_get_global_id(tile_gid_0, 0); + writer->op_get_global_id(tile_gid_1, 1); + writer->op_get_global_id(tile_gid_2, 2); + + auto tile_cout0 = writer->declare_tile("cout0_rhs", ckw::TileInfo(ckw::DataType::Int32)); // OFM + auto tile_mout0 = + writer->declare_tile("mout0_rhs", ckw::TileInfo(ckw::DataType::Int32)); // WIDTH or WIDTH x HEIGHT + auto tile_mout1 = writer->declare_tile("mout1_rhs", ckw::TileInfo(ckw::DataType::Int32)); // HEIGHT or 0 + auto tile_bout0 = writer->declare_tile("bout0_rhs", ckw::TileInfo(ckw::DataType::Int32)); // BATCH SIZE IDX + + // Calculate coordinates + if (!broadcast_x) + { + get_coordinate_from_gws_overlapping_min(writer, tile_cout0, tile_gid_0, const_rhs_n0_i32, + const_rhs_shift_back_n0_i32, const_0_i32); + } + else + { + writer->op_assign(tile_cout0, const_0_i32); + } + + if (!broadcast_y) + { + get_coordinate_from_gws(writer, tile_mout0, tile_gid_1, const_rhs_m0_i32); + } + else + { + writer->op_assign(tile_mout0, const_0_i32); + } + + // Get the boundary aware coordinates at each global dimension index + if (sampler_rhs.format() == ckw::TensorSamplerFormat::Dim0_Dim1xDim2_1) + { + writer->op_assign(tile_mout1, const_0_i32); + get_coordinate_from_gws(writer, tile_bout0, tile_gid_2, const_pos_1_i32); + } + else if (sampler_rhs.format() == ckw::TensorSamplerFormat::Dim0_Dim1_Dim2) + { + // For tile_mout1 and tile_bout0 the step can only be 1 + const auto src_w = static_cast<int32_t>(_rhs->dimension(1)); + auto const_src_w = writer->declare_constant_tile(ckw::ConstantData({{src_w}}, ckw::DataType::Int32)); + if (!broadcast_y) + { + writer->op_binary(tile_mout1, ckw::BinaryOp::Mod, tile_mout1, const_src_w); + } + else + { + // If broadcast_y == true, it means that we have either a scalar or vector + // because broadcasting in other dimensions is not supported + writer->op_assign(tile_mout1, const_0_i32); + } + + writer->op_binary(tile_bout0, ckw::BinaryOp::Div, tile_mout1, const_src_w); + } + + ckw::DataType rhs_dt = to_ckw(_rhs->data_type()); + auto tile_rhs = writer->declare_tile("rhs", ckw::TileInfo(rhs_dt, rhs_m0, rhs_n0)); + + writer->op_load(tile_rhs, rhs->tensor(), sampler_rhs, tile_cout0, tile_mout0, tile_mout1, tile_bout0); + + // Here, init_virtual_tensor() is used to bring the tile_rhs outside the compound statement + rhs->init_virtual_tensor(tile_rhs, sampler_rhs); + } + + const auto &tile_lhs = lhs->tile(); + const auto &tile_rhs = rhs->tile(); + + /******************************************************************************** + * 7 - Write the rest of the code + ********************************************************************************/ + // Perform the element-wise operation + writer->op_binary(tile_dst, to_ckw(_attributes), tile_lhs, tile_rhs); + + ARM_COMPUTE_ERROR_ON_MSG(dst->has_tile() == false, "You must bind a tile before appending another component"); } Window GpuCkwElementwiseBinary::get_window() const @@ -138,8 +409,8 @@ Window GpuCkwElementwiseBinary::get_window() const // Collapse Dim 1 (W) and Dim 2 (H) together, leave Dim 0 (C) unchanged // This is in line with the collapsing convention used by operators like Conv2d output_shape.collapse(2U, 1U); - constexpr unsigned int vector_size_byte_opencl = 16; - const unsigned int num_elems_processed_per_iteration = + constexpr uint32_t vector_size_byte_opencl = 16; + const uint32_t num_elems_processed_per_iteration = adjust_vec_size(vector_size_byte_opencl / _dst->element_size(), _dst->dimension(0)); Window win = calculate_max_window(output_shape, Steps(num_elems_processed_per_iteration)); @@ -158,24 +429,6 @@ std::string GpuCkwElementwiseBinary::get_name(const ComponentGroup &comp_group) }; return join(build_params, "_"); } - -std::string GpuCkwElementwiseBinary::get_tuner_id(const ComponentGroup &comp_group) const -{ - ARM_COMPUTE_UNUSED(comp_group); - /// NOTE: Hardcoded for now, the parameters should ideally be exported by ckw (a selection of constant tiles) - std::vector<std::string> build_params = { - "elementwise_binary", - "op", - to_string(_attributes.operation()), - "dt", - lower_string(string_from_data_type(_dst->data_type())), - "dst_dim0", - support::cpp11::to_string(_dst->dimension(0)), - "dst_dim1", - support::cpp11::to_string(_dst->dimension(1)), - }; - return join(build_params, "_"); -} } // namespace dynamic_fusion } // namespace experimental } // namespace arm_compute |