mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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83 lines
3.2 KiB
C++
83 lines
3.2 KiB
C++
/*
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* Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#pragma once
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#include "tensorrt_llm/kernels/userbuffers/ub_interface.h"
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#include "tensorrt_llm/runtime/worldConfig.h"
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#include <memory>
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#include <mutex>
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#include <vector>
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namespace tensorrt_llm::runtime::ub
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{
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class UserBufferDeleter
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{
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public:
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void operator()(void* ptr);
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};
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using UBBufferPtr = std::unique_ptr<void, UserBufferDeleter>;
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using UBBufferInfo = std::pair<tensorrt_llm::runtime::ub::UBBuffer, bool>;
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class UserBuffersManager
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{
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public:
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static UserBuffersManager& get_instance();
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UserBuffersManager() = default;
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//! @brief Initialize the userbuffers manager.
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//! @param tp_size Tensor parallel size.
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//! @param pp_size Pipeline parallel size.
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//! @param cp_size Compute parallel size.
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//! @param rank The rank of the current GPU.
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//! @param gpus_per_node The number of GPUs per node.
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//! @param buffer_size The size of the buffer to allocate. All buffers allocated by this manager will have this
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//! size.
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//! @param use_nccl_symmetric Whether to use NCCL symmetric communication.
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void initialize(int64_t tp_size, int64_t pp_size, int64_t cp_size, int64_t rank, int64_t gpus_per_node,
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int64_t buffer_size, bool use_nccl_symmetric);
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//! @brief Create a UB tensor from the given shape, strides and data type. The function will choose available UB
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//! buffer or create a new one if no available buffer is found.
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//! @param buffer_size The size of the buffer to allocate.
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//! @return A unique_ptr to the buffer and the UBBuffer object.
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//! @note Do not manually call release_buffer with the buffer address in tensorrt_llm::runtime::ub::UBBuffer
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std::pair<UBBufferPtr, tensorrt_llm::runtime::ub::UBBuffer> allocate_userbuffers(int64_t buffer_size);
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//! @brief Search the buffer from the list of buffers.
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//! @param addr The address of the buffer to search for.
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//! @return The buffer and whether it is assigned to a tensor. If not found, the UBBuffer is invalid.
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tensorrt_llm::runtime::ub::UBBuffer search_buffer(void* addr);
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//! @brief Get the communicator.
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//! @return The communicator.
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tensorrt_llm::runtime::ub::communicator* comm();
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//! @brief Release the buffer. It does not deallocate the buffer, but just release it to the pool.
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//! @param addr The address of the buffer to release.
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void release_buffer(void* addr);
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private:
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std::mutex mutex_;
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std::vector<UBBufferInfo> buffers_;
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int64_t buffer_size_;
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};
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void initialize_userbuffers_manager(int64_t tp_size, int64_t pp_size, int64_t cp_size, int64_t rank,
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int64_t gpus_per_node, int64_t buffer_size, bool use_nccl_symmetric);
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} // namespace tensorrt_llm::runtime::ub
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