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src/memory_manager.h
86 строк
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Kris Hung
Optimize GPU tensor support for Python backend (#293)
26 окт 2023, 01:15
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26 окт 2023, 01:15
4c0a977
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// Copyright 2022-2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions // are met: // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above copyright // notice, this list of conditions and the following disclaimer in the // documentation and/or other materials provided with the distribution. // * Neither the name of NVIDIA CORPORATION nor the names of its // contributors may be used to endorse or promote products derived // from this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY // EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR // PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR // CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, // EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, // PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY // OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. #pragma once #include <functional> #include <mutex> #include <thread> #include <unordered_map> #include "message_queue.h" #include "triton/backend/backend_common.h" #include "triton/backend/backend_memory.h" #include "triton/core/tritonserver.h" #ifdef TRITON_ENABLE_GPU #include <cuda_runtime_api.h> #endif // TRITON_ENABLE_GPU namespace triton { namespace backend { namespace python { class MemoryRecord { public: virtual const std::function<void(void*)>& ReleaseCallback() = 0; virtual void* MemoryId() = 0; virtual ~MemoryRecord() = default; }; #ifdef TRITON_ENABLE_GPU class BackendMemoryRecord : public MemoryRecord { public: BackendMemoryRecord(std::unique_ptr<BackendMemory> backend_memory); const std::function<void(void*)>& ReleaseCallback() override; void* MemoryId() override; ~BackendMemoryRecord() { backend_memory_.reset(); } private: std::unique_ptr<BackendMemory> backend_memory_; std::function<void(void*)> release_callback_; }; #endif /// Memory manager class is used primarily for managing the lifetime of GPU /// tensors in BLS. It mainly consists of a background thread that monitors a /// message queue in shared memory. Whenever a GPU tensor is created, it will /// be pushed to the memory manager. The stub process must send a message to the /// message queue asking the memory manager to deallocate the GPU tensor. class MemoryManager { public: MemoryManager(std::unique_ptr<MessageQueue<intptr_t>>&& memory_message_queue); intptr_t AddRecord(std::unique_ptr<MemoryRecord>&& memory_record); TRITONSERVER_Error* ResetCounter(); ~MemoryManager(); private: std::thread thread_; std::unordered_map<intptr_t, std::unique_ptr<MemoryRecord>> records_; std::unique_ptr<MessageQueue<intptr_t>> message_queue_; void QueueMonitorThread(); std::mutex mu_; }; }}}; // namespace triton::backend::python