TensorRT-LLMs/cpp/tensorrt_llm/batch_manager/cacheTransBuffer.h
Iman Tabrizian cdde15b275
[TRTLLM-8540][feat] Add support for disagg in DSv3.2 (#8735)
Signed-off-by: Iman Tabrizian <10105175+tabrizian@users.noreply.github.com>
2025-11-12 08:21:11 -08:00

126 lines
4.5 KiB
C++

/*
* SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#pragma once
#include "tensorrt_llm/batch_manager/kvCacheManager.h"
#include "tensorrt_llm/executor/executor.h"
#include "tensorrt_llm/runtime/bufferManager.h"
#include "tensorrt_llm/runtime/iTensor.h"
#include <atomic>
#include <condition_variable>
#include <cstddef>
#include <optional>
#include <unordered_map>
#include <vector>
namespace tensorrt_llm::batch_manager::kv_cache_manager
{
class FabricMemory
{
public:
explicit FabricMemory(size_t size);
~FabricMemory();
FabricMemory(FabricMemory const&) = delete;
FabricMemory& operator=(FabricMemory const&) = delete;
FabricMemory(FabricMemory&&) noexcept;
FabricMemory& operator=(FabricMemory&&) noexcept;
void* getPtr() const;
size_t getSize() const;
static size_t getAlignedSize(size_t size);
static bool supportFbaricMemory();
private:
class Impl;
std::unique_ptr<Impl> pImpl;
};
class CacheTransBufferManager
{
public:
CacheTransBufferManager(KVCacheManager::BaseKVCacheManager* cacheManager,
std::optional<size_t> maxNumTokens = std::nullopt, bool transferIndexerKCache = false);
static size_t preAllocBufferSize(std::map<SizeType32, SizeType32> const& cacheSizeBytesPerTokenPerWindow,
SizeType32 tokensPerBlock,
std::optional<executor::CacheTransceiverConfig> const& cacheTransceiverConfig = std::nullopt);
std::optional<int> assignBufferIndexForSend();
void freeBufferIndexForSend(std::optional<int> bufferId);
std::optional<int> assignBufferIndexForRecv();
void freeBufferIndexForRecv(std::optional<int> bufferId);
std::tuple<std::vector<runtime::ITensor::SharedPtr>, size_t, bool> getOrAllocateSendBuffers(
std::optional<int> bufferId, int targetNum, std::vector<size_t> const& requestedNumberOfElements,
runtime::BufferManager const& bufferManagerToUse);
std::tuple<std::vector<runtime::ITensor::SharedPtr>, size_t, bool> getOrAllocateRecvBuffers(
std::optional<int> bufferId, int targetNum, std::vector<size_t> const& requestedNumberOfElements,
runtime::BufferManager const& bufferManagerToUse);
runtime::ITensor::SharedPtr getSendBuffer(std::optional<int> bufferId);
runtime::ITensor::SharedPtr getRecvBuffer(std::optional<int> bufferId);
size_t getRecvBufferCount();
size_t getSendBufferCount();
std::optional<size_t> getMaxNumTokens()
{
return mMaxNumTokens;
}
private:
struct ConcurrenceResource
{
std::unordered_map<int, runtime::ITensor::SharedPtr> mBuffers;
std::vector<int> mBufferIndexFlag;
std::mutex mBuffersMutex;
std::condition_variable mBuffersCV;
std::atomic<int> mConcurrence = 0;
};
std::tuple<std::vector<runtime::ITensor::SharedPtr>, size_t, bool> getOrAllocateBuffers(std::optional<int> bufferId,
int targetNum, std::vector<size_t> const& requestedNumberOfElements,
runtime::BufferManager const& bufferManagerToUse, ConcurrenceResource& concurrenceResource);
void allocateBuffer();
std::optional<int> assignBufferIndex(ConcurrenceResource& resource, size_t bufferCount, bool onlyUseDynamicBuffer);
void freeBufferIndex(
ConcurrenceResource& resource, std::optional<int> bufferId, size_t bufferCount, bool onlyUseDynamicBuffer);
size_t mPreAllocBufferSize;
size_t mRecvBufferCount;
size_t mSendBufferCount;
size_t mTransferBufferSize;
bool mOnlyUseDynamicBuffer;
bool mUseFabricMemory;
size_t mNumberOfElements;
nvinfer1::DataType mDataType;
ConcurrenceResource mConcurrenceSendResource;
ConcurrenceResource mConcurrenceRecvResource;
KVCacheManager::BaseKVCacheManager* mCacheManager;
runtime::BufferManager mBufferManager;
std::vector<std::unique_ptr<FabricMemory>> mFabricMemory;
std::optional<size_t> mMaxNumTokens;
};
} // namespace tensorrt_llm::batch_manager::kv_cache_manager