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[ARM CPU] Add ACL FC executor for FP32/FP16 precision (openvinotoolki…
…t#24123) CVS-138509 CVS-137575 CVS-147625 CVS-148130
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src/plugins/intel_cpu/src/nodes/executors/acl/acl_common_executor.cpp
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,134 @@ | ||
| // Copyright (C) 2024 Intel Corporation | ||
| // SPDX-License-Identifier: Apache-2.0 | ||
| // | ||
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| #include "acl_common_executor.hpp" | ||
| #include "acl_utils.hpp" | ||
| #include "nodes/executors/memory_arguments.hpp" | ||
| #include "utils/debug_capabilities.h" | ||
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|
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| namespace ov { | ||
| namespace intel_cpu { | ||
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| static const std::unordered_map<int, ACLArgs> argConvert = { | ||
| {ARG_SRC_0, ACL_SRC_0}, | ||
| {ARG_SRC_1, ACL_SRC_1}, | ||
| {ARG_SRC_2, ACL_SRC_2}, | ||
| {ARG_BIAS, ACL_BIAS}, | ||
| {ARG_WEI, ACL_WEI}, | ||
| {ARG_DST, ACL_DST}, | ||
| }; | ||
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| using ACLTypes = std::array<arm_compute::DataType, ACLArgs::COUNT_OF_ARGS>; | ||
| using ACLLayouts = std::array<arm_compute::DataLayout, ACLArgs::COUNT_OF_ARGS>; | ||
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| static void initACLTensorParams(const MemoryPtr& memoryPtr, | ||
| const ACLTensorAttrs& attrs, | ||
| arm_compute::TensorShape& tensorShape, | ||
| arm_compute::DataType& dataType, | ||
| arm_compute::DataLayout& dataLayout) { | ||
| dataType = precisionToAclDataType(memoryPtr->getPrecision()); | ||
| dataLayout = getAclDataLayoutByMemoryDesc(memoryPtr->getDescPtr()); | ||
| if (dataType != arm_compute::DataType::UNKNOWN) { | ||
| auto collapsed_dims = collapse_dims_to_max_rank(memoryPtr->getStaticDims(), attrs.maxDimsShape); | ||
| tensorShape = shapeCast(collapsed_dims); | ||
| if (attrs.hasLayoutTypeNHWC) { | ||
| changeLayoutToNH_C({&tensorShape}); | ||
| } | ||
| } | ||
| } | ||
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| static std::shared_ptr<arm_compute::TensorInfo> initTensorInfo(const arm_compute::TensorShape& tensorShape, | ||
| const arm_compute::DataType& dataType, | ||
| const arm_compute::DataLayout& dataLayout) { | ||
| std::shared_ptr<arm_compute::TensorInfo> aclMemoryInfo = nullptr; | ||
| if (dataType != arm_compute::DataType::UNKNOWN) { | ||
| aclMemoryInfo = std::make_shared<arm_compute::TensorInfo>( | ||
| tensorShape, 1, | ||
| dataType, | ||
| dataLayout); | ||
| } | ||
| return aclMemoryInfo; | ||
| } | ||
|
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| static std::shared_ptr<arm_compute::Tensor> initTensor(const std::shared_ptr<arm_compute::TensorInfo>& aclMemoryInfo) { | ||
| std::shared_ptr<arm_compute::Tensor> aclMemory = nullptr; | ||
| if (aclMemoryInfo) { | ||
| aclMemory = std::make_shared<arm_compute::Tensor>(); | ||
| aclMemory->allocator()->init(*aclMemoryInfo); | ||
| } | ||
| return aclMemory; | ||
| } | ||
|
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| ACLCommonExecutor::ACLCommonExecutor() { | ||
| for (int i = 0; i < ACLArgs::COUNT_OF_ARGS; ++i) { | ||
| aclTensorAttrs.memoryUsageIndicator[i] = false; | ||
| } | ||
| } | ||
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| bool ACLCommonExecutor::update(const MemoryArgs &memory) { | ||
| // Initialize ACL tensors params | ||
| ACLShapes aclMemoryShapes; | ||
| ACLTypes aclDataType{}; | ||
| ACLLayouts aclDataLayout{}; | ||
| for (auto& cpu_mem_ptr : memory) { | ||
| const ACLArgs index = argConvert.at(cpu_mem_ptr.first); | ||
| initACLTensorParams(cpu_mem_ptr.second, aclTensorAttrs, | ||
| aclMemoryShapes[index], | ||
| aclDataType[index], | ||
| aclDataLayout[index]); | ||
| } | ||
|
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| // Update ACL tensors shapes | ||
| updateTensorsShapes(aclMemoryShapes); | ||
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| // Initialize arm_compute::TensorInfo objects | ||
| ACLInfos aclMemoryInfos; | ||
| for (int i = 0; i < ACLArgs::COUNT_OF_ARGS; i++) { | ||
| aclMemoryInfos[i] = initTensorInfo(aclMemoryShapes[i], aclDataType[i], aclDataLayout[i]); | ||
| } | ||
|
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| // Validate arm_compute::TensorInfo objects for specific ACL function | ||
| auto tensorsInfoValidateStatus = validateTensorsInfo(aclMemoryInfos); | ||
| if (!tensorsInfoValidateStatus) { | ||
| DEBUG_LOG("ACL operator validation failed: ", tensorsInfoValidateStatus.error_description()); | ||
| return false; | ||
| } | ||
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| // Initialize arm_compute::Tensor objects | ||
| for (int i = 0; i < ACLArgs::COUNT_OF_ARGS; i++) { | ||
| aclMemoryTensors[i] = initTensor(aclMemoryInfos[i]); | ||
| // Indicate that arm_compute::Tensor object can use import_memory function | ||
| if (aclMemoryTensors[i]) { | ||
| aclTensorAttrs.memoryUsageIndicator[i] = true; | ||
| } | ||
| } | ||
|
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| // Configure arm_compute::IFunction object | ||
| configureThreadSafe([&] { | ||
| iFunction = configureFunction(aclMemoryTensors); | ||
| }); | ||
| return true; | ||
| } | ||
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| void ACLCommonExecutor::execute(const MemoryArgs &memory) { | ||
| // TODO: Move import_memory() to update() function - CVS-145871 | ||
| for (auto& cpu_mem_ptr : memory) { | ||
| const ACLArgs index = argConvert.at(cpu_mem_ptr.first); | ||
| if (aclTensorAttrs.memoryUsageIndicator[index]) { | ||
| aclMemoryTensors[index]->allocator()->import_memory(memory.at(cpu_mem_ptr.first)->getData()); | ||
| } | ||
| } | ||
| iFunction->run(); | ||
| } | ||
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| ACLCommonExecutor::~ACLCommonExecutor() { | ||
| for (int i = 0; i < ACLArgs::COUNT_OF_ARGS; i++) { | ||
| if (aclTensorAttrs.memoryUsageIndicator[i]) { | ||
| aclMemoryTensors[i]->allocator()->free(); | ||
| } | ||
| } | ||
| } | ||
|
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| } // namespace intel_cpu | ||
| } // namespace ov |
58 changes: 58 additions & 0 deletions
58
src/plugins/intel_cpu/src/nodes/executors/acl/acl_common_executor.hpp
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,58 @@ | ||
| // Copyright (C) 2018-2024 Intel Corporation | ||
| // SPDX-License-Identifier: Apache-2.0 | ||
| // | ||
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| #pragma once | ||
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| #include "cpu_memory.h" | ||
| #include "nodes/executors/executor.hpp" | ||
| #include "arm_compute/runtime/NEON/NEFunctions.h" | ||
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| namespace ov { | ||
| namespace intel_cpu { | ||
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| enum ACLArgs { | ||
| ACL_SRC_0, | ||
| ACL_SRC_1, | ||
| ACL_SRC_2, | ||
| ACL_BIAS, | ||
| ACL_WEI, | ||
| ACL_DST, | ||
| COUNT_OF_ARGS | ||
| }; | ||
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| using ACLFunction = std::unique_ptr<arm_compute::IFunction>; | ||
| using ACLShapes = std::array<arm_compute::TensorShape, ACLArgs::COUNT_OF_ARGS>; | ||
| using ACLInfos = std::array<std::shared_ptr<arm_compute::TensorInfo>, ACLArgs::COUNT_OF_ARGS>; | ||
| using ACLTensors = std::array<std::shared_ptr<arm_compute::Tensor>, ACLArgs::COUNT_OF_ARGS>; | ||
|
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| struct ACLTensorAttrs { | ||
| bool hasLayoutTypeNHWC = false; | ||
| size_t maxDimsShape = arm_compute::MAX_DIMS; | ||
| std::array<bool, ACLArgs::COUNT_OF_ARGS> memoryUsageIndicator; | ||
| }; | ||
|
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| class ACLCommonExecutor : public Executor { | ||
| public: | ||
| ACLCommonExecutor(); | ||
| virtual void updateTensorsShapes(ACLShapes& aclMemoryShapes) = 0; | ||
| virtual arm_compute::Status validateTensorsInfo(const ACLInfos& aclMemoryInfos) = 0; | ||
| virtual ACLFunction configureFunction(const ACLTensors& aclMemoryTensors) = 0; | ||
| impl_desc_type implType() const override { | ||
| return impl_desc_type::acl; | ||
| } | ||
| void execute(const MemoryArgs& memory) override; | ||
| bool update(const MemoryArgs& memory) override; | ||
| ~ACLCommonExecutor(); | ||
|
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| protected: | ||
| ACLTensorAttrs aclTensorAttrs; | ||
| private: | ||
| ACLTensors aclMemoryTensors; | ||
| ACLFunction iFunction = nullptr; | ||
| }; | ||
|
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| using ACLCommonExecutorPtr = std::shared_ptr<ACLCommonExecutor>; | ||
|
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| } // namespace intel_cpu | ||
| } // namespace ov |
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