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Diffstat (limited to 'src/dynamic_fusion/sketch/gpu/GpuKernelComponentGraph.cpp')
-rw-r--r-- | src/dynamic_fusion/sketch/gpu/GpuKernelComponentGraph.cpp | 125 |
1 files changed, 125 insertions, 0 deletions
diff --git a/src/dynamic_fusion/sketch/gpu/GpuKernelComponentGraph.cpp b/src/dynamic_fusion/sketch/gpu/GpuKernelComponentGraph.cpp new file mode 100644 index 0000000000..6e6422c957 --- /dev/null +++ b/src/dynamic_fusion/sketch/gpu/GpuKernelComponentGraph.cpp @@ -0,0 +1,125 @@ +/* + * 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 "GpuKernelComponentGraph.h" + +#include "arm_compute/dynamic_fusion/sketch/MemoryDescriptor.h" + +namespace arm_compute +{ +namespace experimental +{ +namespace dynamic_fusion +{ +namespace +{ +/** Automatically create memory descriptors for all tensors in the graph + * + * @param[in] tensors @ref ITensorInfo map + * @param[in] graph @ref DependencyGraph of which the @p tensors are a part + * + * @return MemoryDescriptorMap An assignment map of @ref MemoryDescriptors for each ITensorInfo in the graph + */ +MemoryDescriptorMap assign_memory_descriptors(const std::map<ITensorInfo::Id, const ITensorInfo *> tensors, const DependencyGraph &graph) +{ + MemoryDescriptorMap mem_map{}; + for(auto t_id : graph.all_tensors()) + { + const auto &tensor = tensors.at(t_id); + // Only global src and dst tensors to the entire component graph are "User" tensors, which are user-specified memories + if(is_in(t_id, graph.global_src_tensors()) || is_in(t_id, graph.global_dst_tensors())) + { + mem_map[t_id] = MemoryDescriptor{ MemoryType::User }; + } + else + { + AuxMemoryInfo aux_mem_info{ tensor->total_size() }; + mem_map[t_id] = MemoryDescriptor{ MemoryType::Auxiliary, aux_mem_info }; + } + } + return mem_map; +} + +} // namespace + +std::vector<DependencyGraph::TensorId> GpuKernelComponentGraph::get_tensor_ids(const std::vector<const ITensorInfo *> tensors) +{ + std::vector<DependencyGraph::TensorId> tensor_ids{}; + std::transform( + std::begin(tensors), std::end(tensors), + std::back_inserter(tensor_ids), + [](const auto & t) + { + return t->id(); + }); + return tensor_ids; +} + +GpuKernelComponentGraph::GpuKernelComponentGraph(GpuComponentServices *services) + : _services{ services }, _components{}, _tensors{}, _dependency_graph{} +{ +} + +GpuKernelComponentStream GpuKernelComponentGraph::fuse() const +{ + // Obtain memory descriptor map + const auto mem_map = assign_memory_descriptors(_tensors, _dependency_graph); + /// @note Fusion constraints (for kernel components) are exactly the same as the invariants of @ref GpuKernelComponentGroup + /// Fusion can be framed as a mathematical optimization problem: + /// Given fusion constraints, find the "best" fusion patterns possible + /// "Best" is ill-defined at the moment. For now we define "best" fusion pattern as one + /// which results in the least number of fused kernels ( @ref GpuKernelComponentGroup ) at the end + + /// As the first iteration, we offer a sub-optimal algorithm here which ensures all + /// constraints are met, but provides no guarantee that the fusion pattern is optimal + + GpuKernelComponentStream stream{ _services, mem_map }; + // Break down into linear groups of components (constraint 1), preserving topological order + const auto linear_graphs = _dependency_graph.topological_partition(); + + // Further divide up the linear groups based on rest of the fusion constraints (rely on component group's invariants) + for(const auto &graph : linear_graphs) + { + for(unsigned int i = 0; i < graph.size(); ++i) + { + const auto comp = _components.at(graph[i].op).get(); + // Each new linear graph signals a new component group in the stream + if(i == 0) + { + stream.new_component_group(); + } + // If it violates the component group's invariant / fusion constraint, breaks up the stream by inserting a new group + bool success = stream.add_component(comp); + if(!success) + { + stream.new_component_group(); + success = stream.add_component(comp); + ARM_COMPUTE_ERROR_ON(!success); + } + } + } + return stream; +} +} // namespace dynamic_fusion +} // namespace experimental +} // namespace arm_compute |