TensorRT-LLMs/cpp/tensorrt_llm/batch_manager/kvCacheTransferManager.cpp
Perkz Zheng 992781dc7b
[None][feat] update trtllm-gen nvfp4 kernels with better performance (#9510)
Signed-off-by: Perkz Zheng <67892460+PerkzZheng@users.noreply.github.com>
2025-12-03 21:35:49 +08:00

351 lines
15 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.
*/
#include <cstdint>
#include "tensorrt_llm/batch_manager/kvCacheTransferManager.h"
#include "tensorrt_llm/batch_manager/kvCacheEventManager.h"
#include "tensorrt_llm/batch_manager/kvCacheManager.h"
#include "tensorrt_llm/common/logger.h"
#include "tensorrt_llm/executor/executor.h"
#include "tensorrt_llm/kernels/kvCachePartialCopy.h"
#include "tensorrt_llm/runtime/bufferManager.h"
#include "tensorrt_llm/runtime/cudaEvent.h"
#include "tensorrt_llm/runtime/cudaStream.h"
namespace tr = tensorrt_llm::runtime;
namespace tk = tensorrt_llm::kernels;
namespace kvc = tensorrt_llm::executor::kv_cache;
namespace tensorrt_llm::batch_manager::kv_cache_manager
{
static bool gpuToFilePosix(tr::ITensor::SharedPtr const& srcPtr, std::string const& filename)
{
int fd = ::open(filename.c_str(), O_CREAT | O_WRONLY, 0664);
TLLM_CHECK_WITH_INFO(fd >= 0, "Failed to open '%s' for writing (POSIX fallback)", filename.c_str());
ssize_t numBytes = static_cast<ssize_t>(srcPtr->getSizeInBytes());
std::vector<uint8_t> hostBuffer(numBytes);
cudaError_t cpyErr = cudaMemcpy(hostBuffer.data(), srcPtr->data(), numBytes, cudaMemcpyDeviceToHost);
TLLM_CHECK_WITH_INFO(cpyErr == cudaSuccess, "cudaMemcpy to host failed, error=%d", cpyErr);
ssize_t written = ::write(fd, hostBuffer.data(), numBytes);
TLLM_CHECK_WITH_INFO(written >= 0, "POSIX write error=%zd", written);
TLLM_LOG_DEBUG("Wrote %zd bytes to %s (POSIX fallback)", written, filename.c_str());
::close(fd);
return true;
}
static bool fileToGpuPosix(tr::ITensor::SharedPtr const& dstPtr, std::string const& filename)
{
int fd = ::open(filename.c_str(), O_RDONLY);
TLLM_CHECK_WITH_INFO(fd >= 0, "Failed to open '%s' for reading (POSIX fallback)", filename.c_str());
ssize_t numBytes = static_cast<ssize_t>(dstPtr->getSizeInBytes());
std::vector<uint8_t> hostBuffer(numBytes);
ssize_t bytesRead = ::read(fd, hostBuffer.data(), numBytes);
TLLM_CHECK_WITH_INFO(bytesRead >= 0, "POSIX read error=%zd", bytesRead);
TLLM_LOG_DEBUG("Read %zd bytes from %s (POSIX fallback)", bytesRead, filename.c_str());
cudaError_t cpyErr = cudaMemcpy(dstPtr->data(), hostBuffer.data(), numBytes, cudaMemcpyHostToDevice);
TLLM_CHECK_WITH_INFO(cpyErr == cudaSuccess, "cudaMemcpy to device failed, error=%d", cpyErr);
::close(fd);
return true;
}
KVCacheTransferManager::KVCacheTransferManager(
tr::BufferManager const& bufferManager, std::shared_ptr<kvc::BaseLoopbackAgent> loopbackAgent)
: mBufferManager{bufferManager}
, mOnboardManager(std::make_shared<tr::CudaStream>())
, mOffloadManager(std::make_shared<tr::CudaStream>())
, mLoopbackAgent{loopbackAgent}
{
TLLM_CUDA_CHECK(cudaGetDevice(&mDeviceId));
TLLM_CHECK(mDeviceId != -1);
}
tr::ITensor::SharedPtr KVCacheTransferManager::computeBlockPointer(
BlockPtr const& block, std::vector<KVCacheBlockPool> const& pools, size_t poolIdx)
{
TLLM_CHECK_WITH_INFO(!pools.empty(), "Pool index %lu is out of bounds", poolIdx);
auto const& pool = pools.at(poolIdx);
auto ptr = block->isPrimary() ? pool.primaryPtr : pool.secondaryPtr;
auto const blockOffset = block->getMemoryPoolBlockIndex();
tr::ITensor::SharedPtr blockTensor{tr::ITensor::slice(ptr, blockOffset, 1)};
return blockTensor;
}
void KVCacheTransferManager::copyBlock(BlockPtr const& src, BlockPtr const& dst,
std::vector<KVCacheBlockPool> const& pools, bool isOffload, int numTokensToCopy, executor::KvCacheTransferMode mode,
std::string const& directory)
{
TLLM_LOG_DEBUG("copyBlock entered: srcId=%d, dstId=%d, isOffload=%s, mode=%d", src->getBlockId(), dst->getBlockId(),
(isOffload ? "true" : "false"), static_cast<int>(mode));
if (mode == executor::KvCacheTransferMode::DRAM)
{
TLLM_LOG_DEBUG("Using DRAM-based copy (GPU <-> CPU) for this block.");
// Iterate over all pools, partial-copy logic
for (size_t poolIdx = 0; poolIdx < pools.size(); ++poolIdx)
{
auto srcPtr = computeBlockPointer(src, pools, poolIdx);
auto dstPtr = computeBlockPointer(dst, pools, poolIdx);
// Does it contain block scales?
auto containsBlockScales = pools[poolIdx].containsBlockScales;
// If no partial tokens or if the dataType is not supported for partial copy, copy entire block.
// Note that nvfp4 kv cache SFs use an interleaved layout, so we need to copy the entire block.
if (numTokensToCopy <= 0 || srcPtr->getDataType() == nvinfer1::DataType::kINT4
|| srcPtr->getDataType() == nvinfer1::DataType::kFP4 || containsBlockScales)
{
// For partial copy not implemented with these data types,
// just do a full copy.
(isOffload ? mOffloadManager : mOnboardManager).copy(*srcPtr, *dstPtr);
}
else
{
int const tokensPerBlock = pools[poolIdx].tokensPerBlock;
if (numTokensToCopy >= tokensPerBlock)
{
// If requested tokens >= entire block, just do a full copy.
(isOffload ? mOffloadManager : mOnboardManager).copy(*srcPtr, *dstPtr);
}
else
{
auto stream = (isOffload ? mOffloadManager : mOnboardManager).getStream().get();
int const numLayers = pools[poolIdx].numLayers;
int const kvFactor = pools[poolIdx].kvFactor;
int const numHeads = pools[poolIdx].numKvHeads;
int const sizePerHead = pools[poolIdx].sizePerHead;
auto shape = srcPtr->getShape();
TLLM_CHECK_WITH_INFO(
shape.nbDims == 4, "Expected KVCache block to have 4 dims, got %d", shape.nbDims);
tk::kvCacheBlockPartialCopy(*dstPtr, *srcPtr, numLayers, numHeads, tokensPerBlock, sizePerHead,
numTokensToCopy, kvFactor, stream);
}
}
}
TLLM_LOG_DEBUG("copyBlock: DRAM mode complete. Returning...");
return;
}
std::vector<kvc::FileDesc> fileBlobs;
std::vector<kvc::MemoryDesc> memoryBlobs;
for (size_t poolIdx = 0; poolIdx < pools.size(); ++poolIdx)
{
auto ptr = isOffload ? computeBlockPointer(src, pools, poolIdx) : computeBlockPointer(dst, pools, poolIdx);
auto block_id = src->getBlockId();
TLLM_CHECK_WITH_INFO(
!directory.empty(), "Expected a directory path for KVCache offload, but none was provided.");
int size = std::snprintf(nullptr, 0, "%s/block_%d_pool_%zu.bin", directory.c_str(), block_id, poolIdx);
std::string filename;
filename.resize(size + 1);
std::snprintf(
filename.data(), filename.size(), "%s/block_%d_pool_%zu.bin", directory.c_str(), block_id, poolIdx);
if (mode == executor::KvCacheTransferMode::POSIX_DEBUG_FALLBACK)
{
TLLM_LOG_INFO("Forcing POSIX fallback for file: %s", filename.c_str());
if (isOffload)
{
gpuToFilePosix(ptr, filename);
}
else
{
fileToGpuPosix(ptr, filename);
}
continue;
}
else if (mode == executor::KvCacheTransferMode::GDS)
{
int openFlags = isOffload ? (O_CREAT | O_WRONLY) : O_RDONLY;
fileBlobs.emplace_back(filename, openFlags, 0664, ptr->getSizeInBytes());
memoryBlobs.emplace_back(ptr->data(), ptr->getSizeInBytes(), mDeviceId);
}
}
if (mode == executor::KvCacheTransferMode::GDS)
{
if (mLoopbackAgent == nullptr)
{
TLLM_LOG_DEBUG("KVCacheTransferManager: creating mLoopbackAgent lazily");
kvc::BaseAgentConfig config{std::string("GDSAgent"), true, true};
mLoopbackAgent = kvc::makeLoopbackAgent("nixl", &config);
}
kvc::FileDescs fileDescs(std::move(fileBlobs));
kvc::MemoryDescs memoryDescs(kvc::MemoryType::kVRAM, memoryBlobs);
mLoopbackAgent->executeLoopbackRequest(memoryDescs, fileDescs, isOffload);
}
}
//
// Note about recording events to wait for cudaMempyAsync calls between blocks:
// The memory copy involves raw memory blocks, which are pointed to by the
// memory pool block index. When recording events, you must use getMemoryPoolBlockIndex()
// as the raw memory block identifier. Using getBlockId() when recording events is wrong.
// getBlockId() returns the logical block id, which has nothing to do with the raw memory
// block pointers involved in a cudaMemcpy.
//
//
// Notes about need for synchronization:
//
// Relying on decoder syncing GPU with CPU to ensure that blocks are ready
// for offload/onboard/partial copy is dangerous. We have an asynchronous decoder
// that may not synchronize or synchronize at a later point in the execution stream.
// To avoid synchronization issues caused by changes to decoder design we rely on
// KVCacheTransferManager::syncWithBufferManager() that ensures that internal copy streams
// will wait for prefill and decode kernels that have already been scheduled.
//
// Earlier versions of this code did not account for all possible cases where a new block copy
// needed to wait for a previously scheduled copy to finish. For instance, it is possible
// that two primary blocks are offloaded to the same secondary block in a single step,
// scheduling the second offloading without waiting for the first one to finish leads to
// a corrupted block after offloading. It is possible that partial reuse will copy
// from a block that is currently being onboarded, scheduling the partial copy without
// waiting for the onboarding to finish will lead to a corrupted block. To handle all
// possible cases needing synchronization we record separate events for reads and writes
// to a block. When a new block copy is scheduled, we wait for all writes to the source
// block and all reads and writes to a destination block.
//
// As before, syncTransfers() must be called after last call to KVCacheManager::addSequence.
// Failing to do so will lead to corrupted blocks eventually.
//
void KVCacheTransferManager::onboard(BlockPtr const& offloadedBlock, BlockPtr const& block,
std::vector<KVCacheBlockPool> const& pools, int numTokensToCopy, executor::KvCacheTransferMode mode,
std::string const& directory)
{
// Wait for any pending writes before reading from offloadedBlock
auto offloadedBlockPendingWriteItr = mPendingWrites.find(offloadedBlock->getMemoryPoolBlockIndex());
if (offloadedBlockPendingWriteItr != mPendingWrites.end())
{
mOnboardManager.getStream().wait(offloadedBlockPendingWriteItr->second);
// Don't erase, we are not changing state of offloadedBlock
}
// Wait for any pending reads before overwriting block
auto blockPendingReadItr = mPendingReads.find(block->getMemoryPoolBlockIndex());
if (blockPendingReadItr != mPendingReads.end())
{
mOnboardManager.getStream().wait(blockPendingReadItr->second);
mPendingReads.erase(blockPendingReadItr);
}
// Wait for any pending writes before overwriting block
auto blockPendingWriteItr = mPendingWrites.find(block->getMemoryPoolBlockIndex());
if (blockPendingWriteItr != mPendingWrites.end())
{
mOnboardManager.getStream().wait(blockPendingWriteItr->second);
mPendingWrites.erase(blockPendingWriteItr);
}
copyBlock(offloadedBlock, block, pools, false, numTokensToCopy, mode, directory);
// Record new pending read from offloadedBlock
mPendingReads[offloadedBlock->getMemoryPoolBlockIndex()] = tr::CudaEvent();
mOnboardManager.getStream().record(mPendingReads[offloadedBlock->getMemoryPoolBlockIndex()]);
// Record new pending write to block
mPendingWrites[block->getMemoryPoolBlockIndex()] = tr::CudaEvent();
mOnboardManager.getStream().record(mPendingWrites[block->getMemoryPoolBlockIndex()]);
}
void KVCacheTransferManager::offload(BlockPtr const& block, BlockPtr const& offloadBlock,
std::vector<KVCacheBlockPool> const& pools, int numTokensToCopy, executor::KvCacheTransferMode mode,
std::string const& directory)
{
// Wait for any pending writes before reading from block
auto blockPendingWriteItr = mPendingWrites.find(block->getMemoryPoolBlockIndex());
if (blockPendingWriteItr != mPendingWrites.end())
{
mOffloadManager.getStream().wait(blockPendingWriteItr->second);
// Don't erase, we are not changing state of block
}
// Wait for any pending reads before overwriting offloadBlock
auto offloadBlockPendingReadItr = mPendingReads.find(offloadBlock->getMemoryPoolBlockIndex());
if (offloadBlockPendingReadItr != mPendingReads.end())
{
mOffloadManager.getStream().wait(offloadBlockPendingReadItr->second);
mPendingReads.erase(offloadBlockPendingReadItr);
}
// Wait for any pending writes before overwriting offloadBlock
auto offloadBlockPendingWriteItr = mPendingWrites.find(offloadBlock->getMemoryPoolBlockIndex());
if (offloadBlockPendingWriteItr != mPendingWrites.end())
{
mOffloadManager.getStream().wait(offloadBlockPendingWriteItr->second);
mPendingWrites.erase(offloadBlockPendingWriteItr);
}
copyBlock(block, offloadBlock, pools, true, numTokensToCopy, mode, directory);
// Record new pending read from block
mPendingReads[block->getMemoryPoolBlockIndex()] = tr::CudaEvent();
mOffloadManager.getStream().record(mPendingReads[block->getMemoryPoolBlockIndex()]);
// Record new pending write to offloadBlock
mPendingWrites[offloadBlock->getMemoryPoolBlockIndex()] = tr::CudaEvent();
mOffloadManager.getStream().record(mPendingWrites[offloadBlock->getMemoryPoolBlockIndex()]);
}
void KVCacheTransferManager::syncWithBufferManager()
{
tr::CudaEvent readyForOffloadEvent;
mBufferManager.getStream().record(readyForOffloadEvent);
mOffloadManager.getStream().wait(readyForOffloadEvent);
tr::CudaEvent readyForOnboardEvent;
mBufferManager.getStream().record(readyForOnboardEvent);
mOnboardManager.getStream().wait(readyForOnboardEvent);
// Once we synchronize, clear our list of pending thransfers.
mPendingReads.clear();
mPendingWrites.clear();
}
void KVCacheTransferManager::syncTransfers()
{
tr::CudaEvent offloadEvent;
mOffloadManager.getStream().record(offloadEvent);
mBufferManager.getStream().wait(offloadEvent);
tr::CudaEvent onboardEvent;
mOnboardManager.getStream().record(onboardEvent);
mBufferManager.getStream().wait(onboardEvent);
// Once we synchronize, clear our list of pending thransfers.
mPendingReads.clear();
mPendingWrites.clear();
}
} // namespace tensorrt_llm::batch_manager::kv_cache_manager