[TRTLLM-10197][chore] Refactor to setup for RNN cache transceiver (#10957)

Signed-off-by: Shreyas Misra <shreyasm@nvidia.com>
This commit is contained in:
NVShreyas 2026-01-27 14:23:02 -06:00 committed by GitHub
parent f25a2c53bb
commit 6c1862fb33
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5 changed files with 476 additions and 314 deletions

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@ -21,6 +21,7 @@ set(TARGET_DIR ${CMAKE_CURRENT_SOURCE_DIR})
set(SRCS
allocateKvCache.cpp
assignReqSeqSlots.cpp
baseTransBuffer.cpp
cacheFormatter.cpp
mlaCacheFormatter.cpp
cacheTransceiver.cpp

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@ -0,0 +1,285 @@
/*
* 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.
*/
#include "baseTransBuffer.h"
#include "cacheTransBuffer.h"
#include "tensorrt_llm/common/envUtils.h"
#include "tensorrt_llm/common/logger.h"
#include "tensorrt_llm/common/opUtils.h"
#include <mutex>
namespace tensorrt_llm::batch_manager
{
BaseTransBufferManager::BaseTransBufferManager(
size_t transferBufferSize, nvinfer1::DataType dataType, std::optional<size_t> maxNumTokens)
: mDataType{dataType}
, mBufferManager{std::make_shared<runtime::CudaStream>()}
, mMaxNumTokens{maxNumTokens}
{
mTransferBufferSize = transferBufferSize;
mOnlyUseDynamicBuffer = mTransferBufferSize == 0;
mRecvBufferCount = common::getEnvRequestKVCacheConcurrent() ? common::getEnvKVCacheRecvBufferCount() : 1;
mSendBufferCount = common::getEnvKVCacheSendMaxConcurrenceNum();
mUseFabricMemory = !(common::getEnvKVCacheTransferUseSyncBuffer() || common::getEnvKVCacheTransferUseAsyncBuffer())
&& kv_cache_manager::FabricMemory::supportFbaricMemory();
if (mUseFabricMemory)
{
mTransferBufferSize = kv_cache_manager::FabricMemory::getAlignedSize(mTransferBufferSize);
}
mPreAllocBufferSize = mTransferBufferSize * (mRecvBufferCount + mSendBufferCount);
TLLM_LOG_INFO(
"BaseTransBufferManager: mMaxNumTokens:%ld, mRecvBufferCount:%ld, "
"mSendBufferCount:%ld, mTransferBufferSize:%ld, mPreAllocBufferSize:%ld, mOnlyUseDynamicBuffer:%d, "
"mUseFabricMemory:%d, mDataType:%d",
maxNumTokens.has_value() ? maxNumTokens.value() : 0, mRecvBufferCount, mSendBufferCount, mTransferBufferSize,
mPreAllocBufferSize, mOnlyUseDynamicBuffer, mUseFabricMemory, static_cast<int>(mDataType));
allocateBuffer();
}
std::optional<int> BaseTransBufferManager::assignBufferIndexForSend()
{
return assignBufferIndex(mConcurrenceSendResource, mSendBufferCount, mOnlyUseDynamicBuffer);
}
void BaseTransBufferManager::freeBufferIndexForSend(std::optional<int> bufferId)
{
freeBufferIndex(mConcurrenceSendResource, bufferId, mSendBufferCount, mOnlyUseDynamicBuffer);
}
std::optional<int> BaseTransBufferManager::assignBufferIndexForRecv()
{
return assignBufferIndex(mConcurrenceRecvResource, mRecvBufferCount, mOnlyUseDynamicBuffer);
}
void BaseTransBufferManager::freeBufferIndexForRecv(std::optional<int> bufferId)
{
freeBufferIndex(mConcurrenceRecvResource, bufferId, mRecvBufferCount, mOnlyUseDynamicBuffer);
}
std::tuple<std::vector<runtime::ITensor::SharedPtr>, size_t, bool> BaseTransBufferManager::getOrAllocateSendBuffers(
std::optional<int> bufferId, int targetNum, std::vector<size_t> const& requestedNumberOfElements,
runtime::BufferManager const& bufferManagerToUse)
{
return getOrAllocateBuffers(
bufferId, targetNum, requestedNumberOfElements, bufferManagerToUse, mConcurrenceSendResource);
}
std::tuple<std::vector<runtime::ITensor::SharedPtr>, size_t, bool> BaseTransBufferManager::getOrAllocateRecvBuffers(
std::optional<int> bufferId, int targetNum, std::vector<size_t> const& requestedNumberOfElements,
runtime::BufferManager const& bufferManagerToUse)
{
return getOrAllocateBuffers(
bufferId, targetNum, requestedNumberOfElements, bufferManagerToUse, mConcurrenceRecvResource);
}
runtime::ITensor::SharedPtr BaseTransBufferManager::getSendBuffer(std::optional<int> bufferId)
{
TLLM_CHECK(bufferId.has_value() || mOnlyUseDynamicBuffer);
if (bufferId.has_value())
{
TLLM_CHECK(static_cast<size_t>(bufferId.value()) < mSendBufferCount);
return mConcurrenceSendResource.mBuffers[bufferId.value()];
}
return nullptr;
}
runtime::ITensor::SharedPtr BaseTransBufferManager::getRecvBuffer(std::optional<int> bufferId)
{
TLLM_CHECK(bufferId.has_value() || mOnlyUseDynamicBuffer);
if (bufferId.has_value())
{
TLLM_CHECK(static_cast<size_t>(bufferId.value()) < mRecvBufferCount);
// TLLM_CHECK(mConcurrenceRecvResource.mBufferIndexFlag[bufferId.value()] == 1);
return mConcurrenceRecvResource.mBuffers[bufferId.value()];
}
return nullptr;
}
std::tuple<std::vector<runtime::ITensor::SharedPtr>, size_t, bool> BaseTransBufferManager::getOrAllocateBuffers(
std::optional<int> bufferId, int targetNum, std::vector<size_t> const& requestedNumberOfElements,
runtime::BufferManager const& bufferManagerToUse, ConcurrenceResource& concurrenceResource)
{
TLLM_CHECK(bufferId.has_value() || mOnlyUseDynamicBuffer);
TLLM_CHECK(requestedNumberOfElements.size() >= static_cast<size_t>(targetNum));
std::vector<runtime::ITensor::SharedPtr> retSplitCaches;
size_t bufferCoverTargetNum = 0;
if (bufferId.has_value())
{
TLLM_CHECK(static_cast<size_t>(bufferId.value()) < concurrenceResource.mBuffers.size());
TLLM_CHECK(concurrenceResource.mBufferIndexFlag[bufferId.value()] == 1);
size_t preBufferEleSize = 0;
for (int i = 0; i < targetNum; i++)
{
// Strict checking.
if (preBufferEleSize + requestedNumberOfElements[i] <= mNumberOfElements)
{
auto slice = runtime::ITensor::slice(
concurrenceResource.mBuffers[bufferId.value()], preBufferEleSize, requestedNumberOfElements[i]);
preBufferEleSize += requestedNumberOfElements[i];
bufferCoverTargetNum++;
retSplitCaches.push_back(std::move(slice));
}
else
{
retSplitCaches.push_back(bufferManagerToUse.gpu(
runtime::ITensor::makeShape({static_cast<int64_t>(requestedNumberOfElements[i])}), mDataType));
}
}
TLLM_LOG_DEBUG("getOrAllocateBuffers bufferCoverTargetNum:%d", bufferCoverTargetNum);
if (bufferCoverTargetNum < static_cast<size_t>(targetNum))
{
TLLM_LOG_WARNING(
"CacheTransceiver getOrAllocateBuffers: bufferCoverTargetNum:%d < targetNum:%d, may use dynamic "
"buffer which will fail with NIXL backend. It is recommended to set "
"cacheTransceiverConfig.MaxTokensInBuffer (cache_transceiver_config.max_tokens_in_buffer in config "
"YAML file) to a value greater than the maximum ISL of the processed requests. Otherwise, performance "
"may be degraded or transfer may fail. requestedNumberOfElements.size():%ld, "
"mNumberOfElements:%ld, requestedNumberOfElements[0]:%ld",
bufferCoverTargetNum, targetNum, requestedNumberOfElements.size(), mNumberOfElements,
requestedNumberOfElements[0]);
}
}
else
{
for (int i = 0; i < targetNum; i++)
{
retSplitCaches.push_back(bufferManagerToUse.gpu(
runtime::ITensor::makeShape({static_cast<int64_t>(requestedNumberOfElements[i])}), mDataType));
}
bufferCoverTargetNum = targetNum;
}
return std::make_tuple(retSplitCaches, bufferCoverTargetNum, mOnlyUseDynamicBuffer);
}
void BaseTransBufferManager::allocateBuffer()
{
if (mOnlyUseDynamicBuffer)
{
return;
}
mNumberOfElements = mTransferBufferSize / common::getDTypeSize(mDataType);
mConcurrenceSendResource.mBufferIndexFlag.resize(mSendBufferCount, 0);
mConcurrenceRecvResource.mBufferIndexFlag.resize(mRecvBufferCount, 0);
if (mUseFabricMemory)
{
mFabricMemory.reserve(mSendBufferCount + mRecvBufferCount);
for (size_t i = 0; i < mSendBufferCount; i++)
{
mFabricMemory.emplace_back(std::make_unique<kv_cache_manager::FabricMemory>(mTransferBufferSize));
mConcurrenceSendResource.mBuffers[i] = runtime::ITensor::wrap(mFabricMemory.back()->getPtr(), mDataType,
runtime::ITensor::makeShape({static_cast<int64_t>(mNumberOfElements)}), mNumberOfElements);
}
for (size_t i = 0; i < mRecvBufferCount; i++)
{
mFabricMemory.emplace_back(std::make_unique<kv_cache_manager::FabricMemory>(mTransferBufferSize));
mConcurrenceRecvResource.mBuffers[i] = runtime::ITensor::wrap(mFabricMemory.back()->getPtr(), mDataType,
runtime::ITensor::makeShape({static_cast<int64_t>(mNumberOfElements)}), mNumberOfElements);
}
}
else if (common::getEnvKVCacheTransferUseAsyncBuffer())
{
for (size_t i = 0; i < mSendBufferCount; i++)
{
mConcurrenceSendResource.mBuffers[i]
= mBufferManager.gpu(runtime::ITensor::makeShape({static_cast<int64_t>(mNumberOfElements)}), mDataType);
}
for (size_t i = 0; i < mRecvBufferCount; i++)
{
mConcurrenceRecvResource.mBuffers[i]
= mBufferManager.gpu(runtime::ITensor::makeShape({static_cast<int64_t>(mNumberOfElements)}), mDataType);
}
mBufferManager.getStream().synchronize();
}
else
{
for (size_t i = 0; i < mSendBufferCount; i++)
{
mConcurrenceSendResource.mBuffers[i] = mBufferManager.gpuSync(
runtime::ITensor::makeShape({static_cast<int64_t>(mNumberOfElements)}), mDataType);
}
for (size_t i = 0; i < mRecvBufferCount; i++)
{
mConcurrenceRecvResource.mBuffers[i] = mBufferManager.gpuSync(
runtime::ITensor::makeShape({static_cast<int64_t>(mNumberOfElements)}), mDataType);
}
}
}
std::optional<int> BaseTransBufferManager::assignBufferIndex(
ConcurrenceResource& resource, size_t bufferCount, bool onlyUseDynamicBuffer)
{
if (onlyUseDynamicBuffer)
{
return std::nullopt;
}
std::unique_lock lk(resource.mBuffersMutex);
resource.mBuffersCV.wait(
lk, [&resource, bufferCount]() { return static_cast<size_t>(resource.mConcurrence) < bufferCount; });
int bufferId = -1;
for (size_t i = 0; i < bufferCount; i++)
{
if (resource.mBufferIndexFlag[i] == 0)
{
bufferId = i;
resource.mBufferIndexFlag[bufferId] = 1;
resource.mConcurrence++;
break;
}
}
TLLM_CHECK_WITH_INFO(bufferId >= 0 && static_cast<size_t>(bufferId) < bufferCount,
" assignBufferIndex: Buffer index already assigned");
return bufferId;
}
void BaseTransBufferManager::freeBufferIndex(
ConcurrenceResource& resource, std::optional<int> bufferId, size_t bufferCount, bool onlyUseDynamicBuffer)
{
if (onlyUseDynamicBuffer)
{
return;
}
if (bufferId.has_value())
{
TLLM_CHECK(static_cast<size_t>(bufferId.value()) < bufferCount);
{
std::scoped_lock lk(resource.mBuffersMutex);
resource.mBufferIndexFlag[bufferId.value()] = 0;
}
resource.mConcurrence--;
resource.mBuffersCV.notify_one();
}
}
size_t BaseTransBufferManager::getRecvBufferCount()
{
return mRecvBufferCount;
}
size_t BaseTransBufferManager::getSendBufferCount()
{
return mSendBufferCount;
}
} // namespace tensorrt_llm::batch_manager

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@ -0,0 +1,144 @@
/*
* 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/runtime/bufferManager.h"
#include "tensorrt_llm/runtime/iTensor.h"
#include <atomic>
#include <condition_variable>
#include <cstddef>
#include <memory>
#include <mutex>
#include <optional>
#include <tuple>
#include <unordered_map>
#include <vector>
namespace tensorrt_llm::batch_manager::kv_cache_manager
{
class FabricMemory;
} // namespace tensorrt_llm::batch_manager::kv_cache_manager
namespace tensorrt_llm::batch_manager
{
/// @brief Base class for cache transfer buffer management.
/// Handles buffer pool allocation, index assignment, and slicing.
/// Derived classes provide cache-specific size calculations.
class BaseTransBufferManager
{
public:
virtual ~BaseTransBufferManager() = default;
/// @brief Assign a buffer index for sending.
/// @return Assigned buffer index, or nullopt if using dynamic buffers.
std::optional<int> assignBufferIndexForSend();
/// @brief Free a buffer index used for sending.
/// @param bufferId The buffer index to free.
void freeBufferIndexForSend(std::optional<int> bufferId);
/// @brief Assign a buffer index for receiving.
/// @return Assigned buffer index, or nullopt if using dynamic buffers.
std::optional<int> assignBufferIndexForRecv();
/// @brief Free a buffer index used for receiving.
/// @param bufferId The buffer index to free.
void freeBufferIndexForRecv(std::optional<int> bufferId);
/// @brief Get or allocate send buffers for cache transfer.
/// @param bufferId The assigned buffer ID.
/// @param targetNum Number of target sequences.
/// @param requestedNumberOfElements Sizes requested for each target.
/// @param bufferManagerToUse Buffer manager for dynamic allocation.
/// @return Tuple of (buffers, covered target count, is dynamic only).
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);
/// @brief Get or allocate receive buffers for cache transfer.
/// @param bufferId The assigned buffer ID.
/// @param targetNum Number of target sequences.
/// @param requestedNumberOfElements Sizes requested for each target.
/// @param bufferManagerToUse Buffer manager for dynamic allocation.
/// @return Tuple of (buffers, covered target count, is dynamic only).
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);
/// @brief Get the send buffer for a given buffer ID.
runtime::ITensor::SharedPtr getSendBuffer(std::optional<int> bufferId);
/// @brief Get the receive buffer for a given buffer ID.
runtime::ITensor::SharedPtr getRecvBuffer(std::optional<int> bufferId);
/// @brief Get the number of receive buffers.
size_t getRecvBufferCount();
/// @brief Get the number of send buffers.
size_t getSendBufferCount();
/// @brief Get the maximum number of tokens configured.
std::optional<size_t> getMaxNumTokens()
{
return mMaxNumTokens;
}
protected:
/// @brief Constructor - derived classes call this after computing buffer sizes.
/// @param transferBufferSize Size of each transfer buffer in bytes.
/// @param dataType Data type for the buffers.
/// @param maxNumTokens Optional max tokens for sizing.
BaseTransBufferManager(
size_t transferBufferSize, nvinfer1::DataType dataType, std::optional<size_t> maxNumTokens = std::nullopt);
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;
runtime::BufferManager mBufferManager;
std::vector<std::unique_ptr<kv_cache_manager::FabricMemory>> mFabricMemory;
std::optional<size_t> mMaxNumTokens;
};
} // namespace tensorrt_llm::batch_manager

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@ -20,12 +20,17 @@
#include "tensorrt_llm/common/logger.h"
#include "tensorrt_llm/common/opUtils.h"
#include "tensorrt_llm/executor/executor.h"
#include <NvInferRuntimeBase.h>
#include <mutex>
namespace tensorrt_llm::batch_manager::kv_cache_manager
{
// ============================================================================
// FabricMemory Implementation
// ============================================================================
class FabricMemory::Impl
{
public:
@ -182,45 +187,46 @@ bool FabricMemory::supportFbaricMemory()
#endif
}
CacheTransBufferManager::CacheTransBufferManager(
// ============================================================================
// CacheTransBufferManager Implementation
// ============================================================================
size_t CacheTransBufferManager::computeTransferBufferSize(
KVCacheManager::BaseKVCacheManager* cacheManager, std::optional<size_t> maxNumTokens, bool transferIndexerKCache)
: mCacheManager{cacheManager}
, mBufferManager{std::make_shared<runtime::CudaStream>()}
, mMaxNumTokens{maxNumTokens}
{
// TODO: FP4 dataSize
TLLM_CHECK(mCacheManager);
nvinfer1::DataType dataType;
if (transferIndexerKCache)
{
mDataType = mCacheManager->getIndexerKCachePool()->getDataType();
dataType = cacheManager->getIndexerKCachePool()->getDataType();
}
else
{
mDataType = mCacheManager->getPrimaryPool(0)->getDataType();
dataType = cacheManager->getPrimaryPool(0)->getDataType();
}
auto tokensPerBlock = mCacheManager->getBlockManager().getTokensPerBlock();
auto tokensPerBlock = cacheManager->getBlockManager().getTokensPerBlock();
size_t bufferSizeFromMaxNumToken = 0;
if (maxNumTokens.has_value())
{
TLLM_CHECK(maxNumTokens.value() % tokensPerBlock == 0);
auto dataSize = common::getDTypeSize(mDataType);
auto dataSize = common::getDTypeSize(dataType);
SizeType32 kvCacheByteSizePerTokenPerLayer = 0;
if (transferIndexerKCache)
{
kvCacheByteSizePerTokenPerLayer
= mCacheManager->getIndexerKCachePool()->getDimension<-1>() * dataSize / tokensPerBlock;
= cacheManager->getIndexerKCachePool()->getDimension<-1>() * dataSize / tokensPerBlock;
}
else
{
auto primaryPool = mCacheManager->getPrimaryPool(0);
auto primaryPool = cacheManager->getPrimaryPool(0);
kvCacheByteSizePerTokenPerLayer
= primaryPool->getDimension<-1>() * primaryPool->getDimension<2>() * dataSize / tokensPerBlock;
}
for (auto layerId = 0; layerId < mCacheManager->getBlockManager().getNumLayers(); layerId++)
for (auto layerId = 0; layerId < cacheManager->getBlockManager().getNumLayers(); layerId++)
{
auto poolIdx = mCacheManager->getBlockManager().getLayerPoolIdx(layerId);
auto windowSize = static_cast<size_t>(mCacheManager->getBlockManager().getPoolWindowSize(poolIdx));
auto poolIdx = cacheManager->getBlockManager().getLayerPoolIdx(layerId);
auto windowSize = static_cast<size_t>(cacheManager->getBlockManager().getPoolWindowSize(poolIdx));
auto alignedWindowSize = (windowSize + tokensPerBlock - 1) / tokensPerBlock * tokensPerBlock;
auto validTokenNum = (alignedWindowSize < maxNumTokens.value() ? alignedWindowSize : maxNumTokens.value());
if (common::getEnvKVCacheTransferAllBlocksForWindow())
@ -233,26 +239,20 @@ CacheTransBufferManager::CacheTransBufferManager(
}
}
mTransferBufferSize
= maxNumTokens.has_value() ? bufferSizeFromMaxNumToken : common::getEnvMemSizeForKVCacheTransferBuffer();
mOnlyUseDynamicBuffer = mTransferBufferSize == 0;
mRecvBufferCount = common::getEnvRequestKVCacheConcurrent() ? common::getEnvKVCacheRecvBufferCount() : 1;
mSendBufferCount = common::getEnvKVCacheSendMaxConcurrenceNum();
mUseFabricMemory = !(common::getEnvKVCacheTransferUseSyncBuffer() || common::getEnvKVCacheTransferUseAsyncBuffer())
&& FabricMemory::supportFbaricMemory();
if (mUseFabricMemory)
{
mTransferBufferSize = FabricMemory::getAlignedSize(mTransferBufferSize);
}
mPreAllocBufferSize = mTransferBufferSize * (mRecvBufferCount + mSendBufferCount);
TLLM_LOG_INFO(
"CacheTransBufferManager: mMaxNumTokens:%ld, mRecvBufferCount:%ld, "
"mSendBufferCount:%ld,mTransferBufferSize:%ld, mPreAllocBufferSize:%ld,mOnlyUseDynamicBuffer:%d "
"mUseFabricMemory:%d mDataType:%d",
maxNumTokens.has_value() ? maxNumTokens.value() : 0, mRecvBufferCount, mSendBufferCount, mTransferBufferSize,
mPreAllocBufferSize, mOnlyUseDynamicBuffer, mUseFabricMemory, mDataType);
return maxNumTokens.has_value() ? bufferSizeFromMaxNumToken : common::getEnvMemSizeForKVCacheTransferBuffer();
}
allocateBuffer();
CacheTransBufferManager::CacheTransBufferManager(
KVCacheManager::BaseKVCacheManager* cacheManager, std::optional<size_t> maxNumTokens, bool transferIndexerKCache)
: BaseTransBufferManager(computeTransferBufferSize(cacheManager, maxNumTokens, transferIndexerKCache),
transferIndexerKCache ? cacheManager->getIndexerKCachePool()->getDataType()
: cacheManager->getPrimaryPool(0)->getDataType(),
maxNumTokens)
, mCacheManager{cacheManager}
{
// TODO: FP4 dataSize
TLLM_CHECK(mCacheManager);
TLLM_LOG_INFO("CacheTransBufferManager created for KV cache");
}
size_t CacheTransBufferManager::preAllocBufferSize(
@ -298,233 +298,4 @@ size_t CacheTransBufferManager::preAllocBufferSize(
return preAllocBufferSize;
}
std::optional<int> CacheTransBufferManager::assignBufferIndexForSend()
{
return assignBufferIndex(mConcurrenceSendResource, mSendBufferCount, mOnlyUseDynamicBuffer);
}
void CacheTransBufferManager::freeBufferIndexForSend(std::optional<int> bufferId)
{
freeBufferIndex(mConcurrenceSendResource, bufferId, mSendBufferCount, mOnlyUseDynamicBuffer);
}
std::optional<int> CacheTransBufferManager::assignBufferIndexForRecv()
{
return assignBufferIndex(mConcurrenceRecvResource, mRecvBufferCount, mOnlyUseDynamicBuffer);
}
void CacheTransBufferManager::freeBufferIndexForRecv(std::optional<int> bufferId)
{
freeBufferIndex(mConcurrenceRecvResource, bufferId, mRecvBufferCount, mOnlyUseDynamicBuffer);
}
std::tuple<std::vector<runtime::ITensor::SharedPtr>, size_t, bool> CacheTransBufferManager::getOrAllocateSendBuffers(
std::optional<int> bufferId, int targetNum, std::vector<size_t> const& requestedNumberOfElements,
runtime::BufferManager const& bufferManagerToUse)
{
return getOrAllocateBuffers(
bufferId, targetNum, requestedNumberOfElements, bufferManagerToUse, mConcurrenceSendResource);
}
std::tuple<std::vector<runtime::ITensor::SharedPtr>, size_t, bool> CacheTransBufferManager::getOrAllocateRecvBuffers(
std::optional<int> bufferId, int targetNum, std::vector<size_t> const& requestedNumberOfElements,
runtime::BufferManager const& bufferManagerToUse)
{
return getOrAllocateBuffers(
bufferId, targetNum, requestedNumberOfElements, bufferManagerToUse, mConcurrenceRecvResource);
}
runtime::ITensor::SharedPtr CacheTransBufferManager::getSendBuffer(std::optional<int> bufferId)
{
TLLM_CHECK(bufferId.has_value() || mOnlyUseDynamicBuffer);
if (bufferId.has_value())
{
TLLM_CHECK(static_cast<size_t>(bufferId.value()) < mSendBufferCount);
return mConcurrenceSendResource.mBuffers[bufferId.value()];
}
return nullptr;
}
runtime::ITensor::SharedPtr CacheTransBufferManager::getRecvBuffer(std::optional<int> bufferId)
{
TLLM_CHECK(bufferId.has_value() || mOnlyUseDynamicBuffer);
if (bufferId.has_value())
{
TLLM_CHECK(static_cast<size_t>(bufferId.value()) < mRecvBufferCount);
// TLLM_CHECK(mConcurrenceRecvResource.mBufferIndexFlag[bufferId.value()] == 1);
return mConcurrenceRecvResource.mBuffers[bufferId.value()];
}
return nullptr;
}
std::tuple<std::vector<runtime::ITensor::SharedPtr>, size_t, bool> CacheTransBufferManager::getOrAllocateBuffers(
std::optional<int> bufferId, int targetNum, std::vector<size_t> const& requestedNumberOfElements,
runtime::BufferManager const& bufferManagerToUse, ConcurrenceResource& concurrenceResource)
{
TLLM_CHECK(bufferId.has_value() || mOnlyUseDynamicBuffer);
TLLM_CHECK(requestedNumberOfElements.size() >= static_cast<size_t>(targetNum));
std::vector<runtime::ITensor::SharedPtr> retSplitCaches;
size_t bufferCoverTargetNum = 0;
if (bufferId.has_value())
{
TLLM_CHECK(static_cast<size_t>(bufferId.value()) < concurrenceResource.mBuffers.size());
TLLM_CHECK(concurrenceResource.mBufferIndexFlag[bufferId.value()] == 1);
size_t preBufferEleSize = 0;
for (int i = 0; i < targetNum; i++)
{
// Strict checking.
if (preBufferEleSize + requestedNumberOfElements[i] <= mNumberOfElements)
{
auto slice = runtime::ITensor::slice(
concurrenceResource.mBuffers[bufferId.value()], preBufferEleSize, requestedNumberOfElements[i]);
preBufferEleSize += requestedNumberOfElements[i];
bufferCoverTargetNum++;
retSplitCaches.push_back(std::move(slice));
}
else
{
retSplitCaches.push_back(bufferManagerToUse.gpu(
runtime::ITensor::makeShape({static_cast<int64_t>(requestedNumberOfElements[i])}), mDataType));
}
}
TLLM_LOG_DEBUG("getOrAllocateBuffers bufferCoverTargetNum:%d", bufferCoverTargetNum);
if (bufferCoverTargetNum < static_cast<size_t>(targetNum))
{
TLLM_LOG_WARNING(
"CacheTransceiver getOrAllocateBuffers: bufferCoverTargetNum:%d < targetNum:%d, may use dynamic "
"buffer which will fail with NIXL backend. It is recommended to set "
"cacheTransceiverConfig.MaxTokensInBuffer (cache_transceiver_config.max_tokens_in_buffer in config "
"YAML file) to a value greater than the maximum ISL of the processed requests. Otherwise, performance "
"may be degraded or transfer may fail. requestedNumberOfElements.size():%ld, "
"mNumberOfElements:%ld, requestedNumberOfElements[0]:%ld",
bufferCoverTargetNum, targetNum, requestedNumberOfElements.size(), mNumberOfElements,
requestedNumberOfElements[0]);
}
}
else
{
for (int i = 0; i < targetNum; i++)
{
retSplitCaches.push_back(bufferManagerToUse.gpu(
runtime::ITensor::makeShape({static_cast<int64_t>(requestedNumberOfElements[i])}), mDataType));
}
bufferCoverTargetNum = targetNum;
}
return std::make_tuple(retSplitCaches, bufferCoverTargetNum, mOnlyUseDynamicBuffer);
}
void CacheTransBufferManager::allocateBuffer()
{
if (mOnlyUseDynamicBuffer)
{
return;
}
mNumberOfElements = mTransferBufferSize / common::getDTypeSize(mDataType);
mConcurrenceSendResource.mBufferIndexFlag.resize(mSendBufferCount, 0);
mConcurrenceRecvResource.mBufferIndexFlag.resize(mRecvBufferCount, 0);
if (mUseFabricMemory)
{
mFabricMemory.reserve(mSendBufferCount + mRecvBufferCount);
for (size_t i = 0; i < mSendBufferCount; i++)
{
mFabricMemory.emplace_back(std::make_unique<FabricMemory>(mTransferBufferSize));
mConcurrenceSendResource.mBuffers[i] = runtime::ITensor::wrap(mFabricMemory.back()->getPtr(), mDataType,
runtime::ITensor::makeShape({static_cast<int64_t>(mNumberOfElements)}), mNumberOfElements);
}
for (size_t i = 0; i < mRecvBufferCount; i++)
{
mFabricMemory.emplace_back(std::make_unique<FabricMemory>(mTransferBufferSize));
mConcurrenceRecvResource.mBuffers[i] = runtime::ITensor::wrap(mFabricMemory.back()->getPtr(), mDataType,
runtime::ITensor::makeShape({static_cast<int64_t>(mNumberOfElements)}), mNumberOfElements);
}
}
else if (common::getEnvKVCacheTransferUseAsyncBuffer())
{
for (size_t i = 0; i < mSendBufferCount; i++)
{
mConcurrenceSendResource.mBuffers[i]
= mBufferManager.gpu(runtime::ITensor::makeShape({static_cast<int64_t>(mNumberOfElements)}), mDataType);
}
for (size_t i = 0; i < mRecvBufferCount; i++)
{
mConcurrenceRecvResource.mBuffers[i]
= mBufferManager.gpu(runtime::ITensor::makeShape({static_cast<int64_t>(mNumberOfElements)}), mDataType);
}
mBufferManager.getStream().synchronize();
}
else
{
for (size_t i = 0; i < mSendBufferCount; i++)
{
mConcurrenceSendResource.mBuffers[i] = mBufferManager.gpuSync(
runtime::ITensor::makeShape({static_cast<int64_t>(mNumberOfElements)}), mDataType);
}
for (size_t i = 0; i < mRecvBufferCount; i++)
{
mConcurrenceRecvResource.mBuffers[i] = mBufferManager.gpuSync(
runtime::ITensor::makeShape({static_cast<int64_t>(mNumberOfElements)}), mDataType);
}
}
}
std::optional<int> CacheTransBufferManager::assignBufferIndex(
ConcurrenceResource& resource, size_t bufferCount, bool onlyUseDynamicBuffer)
{
if (onlyUseDynamicBuffer)
{
return std::nullopt;
}
std::unique_lock lk(resource.mBuffersMutex);
resource.mBuffersCV.wait(
lk, [&resource, bufferCount]() { return static_cast<size_t>(resource.mConcurrence) < bufferCount; });
int bufferId = -1;
for (size_t i = 0; i < bufferCount; i++)
{
if (resource.mBufferIndexFlag[i] == 0)
{
bufferId = i;
resource.mBufferIndexFlag[bufferId] = 1;
resource.mConcurrence++;
break;
}
}
TLLM_CHECK_WITH_INFO(bufferId >= 0 && static_cast<size_t>(bufferId) < bufferCount,
" assignBufferIndex: Buffer index already assigned");
return bufferId;
}
void CacheTransBufferManager::freeBufferIndex(
ConcurrenceResource& resource, std::optional<int> bufferId, size_t bufferCount, bool onlyUseDynamicBuffer)
{
if (onlyUseDynamicBuffer)
{
return;
}
if (bufferId.has_value())
{
TLLM_CHECK(static_cast<size_t>(bufferId.value()) < bufferCount);
{
std::scoped_lock lk(resource.mBuffersMutex);
resource.mBufferIndexFlag[bufferId.value()] = 0;
}
resource.mConcurrence--;
resource.mBuffersCV.notify_one();
}
}
size_t CacheTransBufferManager::getRecvBufferCount()
{
return mRecvBufferCount;
}
size_t CacheTransBufferManager::getSendBufferCount()
{
return mSendBufferCount;
}
} // namespace tensorrt_llm::batch_manager::kv_cache_manager

View File

@ -17,13 +17,16 @@
#pragma once
#include "tensorrt_llm/batch_manager/baseTransBuffer.h"
#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 <map>
#include <optional>
#include <unordered_map>
#include <vector>
@ -54,7 +57,9 @@ private:
std::unique_ptr<Impl> pImpl;
};
class CacheTransBufferManager
/// @brief KV Cache specific transfer buffer manager.
/// Inherits common buffer management from BaseTransBufferManager.
class CacheTransBufferManager : public BaseTransBufferManager
{
public:
CacheTransBufferManager(KVCacheManager::BaseKVCacheManager* cacheManager,
@ -64,62 +69,18 @@ public:
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()
/// @brief Get the KV cache manager.
[[nodiscard]] KVCacheManager::BaseKVCacheManager* getCacheManager() const noexcept
{
return mMaxNumTokens;
return mCacheManager;
}
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;
};
/// @brief Compute transfer buffer size from KV cache configuration.
static size_t computeTransferBufferSize(KVCacheManager::BaseKVCacheManager* cacheManager,
std::optional<size_t> maxNumTokens, bool transferIndexerKCache);
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