Rewrite dynamic fusion
The new version introduces the following major changes:
* Change public interface to simplify and standardize the user experience
- Use the term "Workload" uniformly
- Simplify operator interface to be a set of static methods:
validate_op(), create_op()
* Separate the kernel writing into its own component (template_writer).
This is to allow the co-development of GpuKernelWriter, and to allow
easy replacement once GpuKernelWriter is mature.
* Optimize the core fusion algorithm used by the component graph. The
details can be found in GpuKernelComponentGraph::fuse()
* Use Gpu instead of Cl prefixes for most of the Workload interfaces
(except for runtime and kernel components, which have to be language specific)
This allows the potential extension to other Gpu langauges in the
future.
* Refactor runtime memory interface so that auxiliary tensor handling
is separate from the user tensor passing. This is because the former
is less stable and may require extension in the future.
* Hide source code object from the user as it is not required at the
moment
* Deprecate the old prototype entirely by disabling it in SCons build
Resolves COMPMID-5510, COMPMID-5512, COMPMID-5513
Change-Id: If69d2362856f2de4503546b7b6cf48a525cf3079
Signed-off-by: SiCong Li <sicong.li@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8406
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/dynamic_fusion/sketch/gpu/template_writer/cl/ClTemplateWriter.cpp b/src/dynamic_fusion/sketch/gpu/template_writer/cl/ClTemplateWriter.cpp
new file mode 100644
index 0000000..cb643a7
--- /dev/null
+++ b/src/dynamic_fusion/sketch/gpu/template_writer/cl/ClTemplateWriter.cpp
@@ -0,0 +1,297 @@
+/*
+ * Copyright (c) 2022 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "ClTemplateWriter.h"
+
+#include "arm_compute/core/CL/CLKernelLibrary.h"
+#include "src/dynamic_fusion/sketch/gpu/components/IGpuKernelComponent.h"
+#include "src/dynamic_fusion/sketch/gpu/template_writer/IGpuTemplateComponentWriter.h"
+
+namespace arm_compute
+{
+namespace experimental
+{
+namespace dynamic_fusion
+{
+/// @note: some tags can be unused since they could be used only for the macros, or only for the component code
+std::string ClTemplateWriter::replace_tags(const std::string &code_template, const TagLUT &tags)
+{
+ std::string replaced_code = "";
+ bool scanning_pattern = false;
+ std::string pattern_found = "";
+ for(size_t i = 0; i < code_template.size() - 1; ++i)
+ {
+ if(!scanning_pattern)
+ {
+ if(code_template[i] == '{' && code_template[i + 1] == '{')
+ {
+ i += 1;
+ scanning_pattern = true;
+ pattern_found = "";
+ }
+ else
+ {
+ replaced_code += code_template[i];
+ }
+ }
+ else
+ {
+ if(code_template[i] == '}' && code_template[i + 1] == '}')
+ {
+ i += 1;
+ scanning_pattern = false;
+ std::string err = "Pattern " + pattern_found + " not found in tags";
+ ARM_COMPUTE_ERROR_ON_MSG(tags.find(pattern_found) == tags.end(), err.c_str());
+ replaced_code += tags.find(pattern_found)->second.value;
+ }
+ else
+ {
+ pattern_found += code_template[i];
+ }
+ }
+ }
+
+ return replaced_code;
+}
+ClTemplateWriter::~ClTemplateWriter()
+{
+}
+ClTemplateWriter::ClTemplateWriter(const GpuKernelComponentGroup &components)
+ : _components{ components }
+{
+}
+std::string ClTemplateWriter::get_name()
+{
+ return write_kernel_name();
+}
+std::string ClTemplateWriter::get_code()
+{
+ return write_code();
+}
+std::string ClTemplateWriter::get_config_id()
+{
+ std::string config_id = get_name();
+ for(const auto &comp : _components)
+ {
+ config_id += "--" + comp->template_writer()->get_config_id() + "--";
+ }
+
+ return config_id;
+}
+
+CLBuildOptions ClTemplateWriter::get_build_options()
+{
+ CLBuildOptions build_opts{};
+
+ for(const auto &comp : _components)
+ {
+ build_opts.add_options(comp->template_writer()->get_build_options(_components).options());
+ }
+
+ return build_opts;
+}
+
+Window ClTemplateWriter::get_window() const
+{
+ const auto root_comp = _components.get_root_component();
+ ARM_COMPUTE_ERROR_ON_MSG(root_comp == nullptr, "No root component found");
+ return root_comp->template_writer()->get_window();
+}
+
+std::map<ITensorInfo::Id, GpuKernelArgument> ClTemplateWriter::get_tensors()
+{
+ // Assemble GpuKernelArguments
+ std::map<ITensorInfo::Id, GpuKernelArgument> tensors;
+ for(const auto t : _components.get_argument_tensors())
+ {
+ tensors.emplace(
+ t->id(),
+ GpuKernelArgument{ *t, _vtable.get_variable(t).kernel_argument_info });
+ }
+ return tensors;
+}
+
+std::string ClTemplateWriter::write_code()
+{
+ ARM_COMPUTE_ERROR_ON_MSG(_components.empty(), "No components found");
+
+ // These data structures will hold the data from all the components in the blueprint
+ std::set<std::string> headers_list{};
+ std::set<std::string> additional_macros{};
+ std::vector<std::string> component_codes{}; // vector because order matters
+
+ // Pass 1: Declare all kernel variables
+ for(auto &component : _components)
+ {
+ component->template_writer()->declare_variables(_vtable, _components);
+ }
+ // Pass 2: Generate component codes
+ for(auto &component : _components)
+ {
+ const auto component_writer = component->template_writer();
+ auto curr_headers_list = component_writer->get_headers_list();
+ auto curr_additional_macros = component_writer->get_additional_macros();
+ auto curr_component_code = component_writer->get_component_code(_components);
+ const auto var_lut = component_writer->get_tag_lut(_vtable, _components); // Ideally can be merged with get_component_code once we have finer-grained code generation technique
+ component_codes.push_back(replace_tags(curr_component_code, var_lut));
+
+ headers_list.insert(curr_headers_list.begin(), curr_headers_list.end());
+ if(!additional_macros.empty()) // Some components might not have any
+ {
+ additional_macros.insert(replace_tags(curr_additional_macros, var_lut));
+ }
+ }
+
+ // Step 3: Assemble the data gathered by traversing the graph into the string "code"
+ std::string code = "";
+
+ for(auto &header : headers_list)
+ {
+#if defined(EMBEDDED_KERNELS)
+ code += CLKernelLibrary::get().get_program(header).first;
+#else // defined(EMBEDDED_KERNELS)
+ code += "#include \"" + header + "\"\n";
+#endif // defined(EMBEDDED_KERNELS)
+ }
+
+ for(auto ¯os : additional_macros)
+ {
+ code += macros;
+ }
+
+ code += write_kernel_signature(_vtable.get_variable_list(_components.get_argument_tensors()));
+
+ code += "\n{\n\n";
+
+ code += " //------------------ START KERNEL_BUILDER_COORDINATE ---------------------\n\n";
+ code += write_global_section();
+ code += " //------------------ END KERNEL_BUILDER_COORDINATE ---------------------\n";
+
+ for(const auto &component_code : component_codes)
+ {
+ code += component_code;
+ }
+
+ code += "}\n";
+
+ return code;
+}
+std::string ClTemplateWriter::write_global_section() const
+{
+ const auto dst_tensors = _components.get_dst_tensors();
+ ARM_COMPUTE_ERROR_ON_MSG(dst_tensors.size() != 1, "Only one destination tensor per kernel is allowed");
+ const auto dst_info = dst_tensors[0];
+ const auto dst_w = dst_info->dimension(0);
+ const auto tile_w = std::max(1, get_window().x().step());
+ const auto tile_h = std::max(1, get_window().y().step());
+ auto leftover_w = dst_w % tile_w;
+
+ std::string code = "";
+ code += std::string(" int g_ind_0 = GET_SPATIAL_IDX(0, ") + std::to_string(tile_w) + ", " + std::to_string(leftover_w) + ");\n";
+ code += std::string(" int g_ind_1 = GET_SPATIAL_IDX(1, ") + std::to_string(tile_h) + ", " + "0);\n";
+ code += std::string(" int g_ind_2 = GET_SPATIAL_IDX(2, 1, 0);\n\n");
+
+ code += " const bool g_cond_x = (g_ind_0 == 0);\n";
+ code += " const bool g_cond_y = (g_ind_1 == 0);\n";
+
+ return code;
+}
+std::string ClTemplateWriter::write_argument_declaration(const GpuKernelVariableTable::TensorVariable &var) const
+{
+ std::string code;
+ switch(var.kernel_argument_info.type)
+ {
+ case GpuKernelArgumentInfo::Type::Vector:
+ {
+ code += "\n VECTOR_DECLARATION(" + var.uniq_name + ")";
+ break;
+ }
+ case GpuKernelArgumentInfo::Type::Image:
+ {
+ code += "\n IMAGE_DECLARATION(" + var.uniq_name + ")";
+ break;
+ }
+ case GpuKernelArgumentInfo::Type::Image_3D:
+ {
+ code += "\n IMAGE_DECLARATION(" + var.uniq_name + "),";
+ code += "\n unsigned int " + var.uniq_name + "_stride_z";
+ break;
+ }
+ case GpuKernelArgumentInfo::Type::Image_3D_Export_To_ClImage2D:
+ {
+ code += "\n __read_only image2d_t " + var.uniq_name + "_img,";
+ code += "\n unsigned int " + var.uniq_name + "_stride_z";
+ break;
+ }
+ case GpuKernelArgumentInfo::Type::Tensor_4D_t_Buffer:
+ {
+ code += "\n TENSOR4D_T(" + var.uniq_name + ", BUFFER)";
+ break;
+ }
+ case GpuKernelArgumentInfo::Type::Tensor_4D_t_Image:
+ {
+ code += "\n TENSOR4D_T(" + var.uniq_name + ", IMAGE)";
+ break;
+ }
+ default:
+ {
+ ARM_COMPUTE_ERROR("Unsupported declaration generation for GpuKernelArgumentInfo::Type");
+ }
+ }
+ return code;
+}
+std::string ClTemplateWriter::write_kernel_signature(const GpuKernelVariableTable::VariableList &argument_list) const
+{
+ std::string code = "\n__kernel void " + write_kernel_name() + "(";
+
+ for(int i = 0; i < static_cast<int>(argument_list.size()) - 1; ++i)
+ {
+ code += write_argument_declaration(argument_list[i]) + ",";
+ }
+ if(static_cast<int>(argument_list.size()) - 1 >= 0)
+ {
+ code += write_argument_declaration(argument_list[argument_list.size() - 1]);
+ }
+
+ code += ')';
+
+ return code;
+}
+std::string ClTemplateWriter::write_kernel_name() const
+{
+ if(_components.empty())
+ {
+ return "empty_kernel";
+ }
+ std::string name = _components.empty() ? "" : _components[0]->template_writer()->get_name();
+ for(size_t i = 1; i < _components.size(); ++i)
+ {
+ name += "___";
+ name += _components[i]->template_writer()->get_name();
+ }
+
+ return name;
+}
+} // namespace dynamic_fusion
+} // namespace experimental
+} // namespace arm_compute