-
Notifications
You must be signed in to change notification settings - Fork 2.3k
Expand file tree
/
Copy pathcacheTransceiver.cpp
More file actions
914 lines (843 loc) · 38.5 KB
/
cacheTransceiver.cpp
File metadata and controls
914 lines (843 loc) · 38.5 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
/*
* SPDX-FileCopyrightText: Copyright (c) 2025-2026 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 "tensorrt_llm/executor/cache_transmission/agent_utils/connection.h"
#include "tensorrt_llm/executor/types.h"
#include <cstdint>
#include <limits>
#include <sstream>
#define UCX_WRAPPER_LIB_NAME "tensorrt_llm_ucx_wrapper"
#if defined(_WIN32)
#include <windows.h>
#define dllOpen(name) LoadLibrary(name ".dll")
#define dllClose(handle) FreeLibrary(static_cast<HMODULE>(handle))
#define dllGetSym(handle, name) static_cast<void*>(GetProcAddress(static_cast<HMODULE>(handle), name))
#else // For non-Windows platforms
#include <dlfcn.h>
#define dllOpen(name) dlopen("lib" name ".so", RTLD_LAZY)
#define dllClose(handle) dlclose(handle)
#define dllGetSym(handle, name) dlsym(handle, name)
#endif // defined(_WIN32)
#include "tensorrt_llm/batch_manager/cacheFormatter.h"
#include "tensorrt_llm/batch_manager/cacheTransceiver.h"
#include "tensorrt_llm/batch_manager/contextProgress.h"
#include "tensorrt_llm/batch_manager/dataTransceiver.h"
#include "tensorrt_llm/batch_manager/kvCacheManager.h"
#include "tensorrt_llm/batch_manager/kvCacheType.h"
#include "tensorrt_llm/batch_manager/kvCacheUtils.h"
#include "tensorrt_llm/batch_manager/llmRequest.h"
#include "tensorrt_llm/batch_manager/mlaCacheFormatter.h"
#include "tensorrt_llm/batch_manager/rnnCacheFormatter.h"
#include "tensorrt_llm/batch_manager/rnnCacheTransBuffer.h"
#include "tensorrt_llm/batch_manager/rnnStateManager.h"
#include "tensorrt_llm/common/envUtils.h"
#include "tensorrt_llm/common/logger.h"
#include "tensorrt_llm/executor/cache_transmission/mpi_utils/connection.h"
#include "tensorrt_llm/executor/dataTransceiverState.h"
#include "tensorrt_llm/executor/serializeUtils.h"
#include "tensorrt_llm/runtime/utils/mpiUtils.h"
#include "tensorrt_llm/runtime/utils/pgUtils.h"
#include <algorithm>
#include <cstddef>
#include <numeric>
#include <unordered_set>
namespace tensorrt_llm::batch_manager
{
std::mutex CacheTransceiver::mDllMutex;
std::unique_ptr<BaseCacheTransceiver> CacheTransceiverFactory::createCacheTransceiver(
kv_cache_manager::BaseKVCacheManager* cacheManager, runtime::ModelConfig const& modelConfig,
runtime::WorldConfig const& worldConfig, executor::kv_cache::CacheState::AttentionType attentionType,
std::optional<executor::CacheTransceiverConfig> cacheTransceiverConfig)
{
if (!cacheTransceiverConfig.has_value() || !cacheTransceiverConfig.value().getBackendType().has_value())
{
TLLM_LOG_INFO("CacheTransceiver is disabled.");
return nullptr;
}
auto backendType = cacheTransceiverConfig.value().getBackendType();
if (backendType.value() == executor::CacheTransceiverConfig::BackendType::DEFAULT)
{
if (common::getEnvUseUCXKvCache())
{
backendType = executor::CacheTransceiverConfig::BackendType::UCX;
TLLM_LOG_INFO("Enable UCX KV cache transport.");
}
else if (common::getEnvUseNixlKvCache())
{
backendType = executor::CacheTransceiverConfig::BackendType::NIXL;
TLLM_LOG_INFO("Enable NIXL KV cache transport.");
}
else if (common::getEnvUseMooncakeKvCache())
{
backendType = executor::CacheTransceiverConfig::BackendType::MOONCAKE;
TLLM_LOG_INFO("Enable MOONCAKE KV cache transport.");
}
else if (common::getEnvUseMPIKvCache())
{
backendType = executor::CacheTransceiverConfig::BackendType::MPI;
TLLM_LOG_INFO("Enable MPI KV cache transport.");
TLLM_LOG_WARNING("MPI KV cache transport is deprecated, please use UCX or NIXL instead.");
}
else
{
backendType = executor::CacheTransceiverConfig::BackendType::NIXL;
}
}
cacheTransceiverConfig.value().setBackendType(backendType);
executor::kv_cache::CacheState::ModelConfig cacheStateCfg{
modelConfig.getNumKvHeadsPerLayer(), modelConfig.getSizePerHead(), modelConfig.getTokensPerBlock()};
auto ppSize = worldConfig.getPipelineParallelism();
std::vector<SizeType32> attentionLayerNumPerPP(ppSize, 0);
for (int ppRank = 0; ppRank < ppSize; ppRank++)
{
attentionLayerNumPerPP[ppRank] = modelConfig.getNbAttentionLayers(ppSize, ppRank);
}
return std::make_unique<CacheTransceiver>(cacheManager, cacheStateCfg, worldConfig, attentionLayerNumPerPP,
modelConfig.getKvDataType(), attentionType, cacheTransceiverConfig);
}
CacheTransceiver::CacheTransceiver(kv_cache_manager::BaseKVCacheManager* cacheManager,
executor::kv_cache::CacheState::ModelConfig const& cacheStateModelCfg, runtime::WorldConfig const& worldConfig,
std::vector<SizeType32> const& attentionLayerNumPerPP, nvinfer1::DataType dataType,
executor::kv_cache::CacheState::AttentionType attentionType,
std::optional<executor::CacheTransceiverConfig> cacheTransceiverConfig,
rnn_state_manager::RnnStateManager* rnnStateManager, std::vector<SizeType32> const& rnnLayerNumPerPP)
: mCacheTransceiverConfig{cacheTransceiverConfig}
, mRnnStateManager{rnnStateManager}
{
using tensorrt_llm::batch_manager::kv_cache_manager::CacheFormatter;
if (useMPI())
{
mGroupComm = std::make_shared<CacheTransceiverComm>(std::addressof(tensorrt_llm::mpi::MpiComm::session()));
}
else
{
mGroupComm = std::make_shared<CacheTransceiverComm>(tensorrt_llm::pg_utils::get_world_pg());
}
if (worldConfig.isTensorParallel() || worldConfig.isContextParallel())
{
mGroupTensorParaComm = std::make_shared<CacheTransceiverComm>(
mGroupComm->split(worldConfig.getPipelineParallelRank(), worldConfig.getRank()));
}
int kvFactor = 2;
if (cacheManager->getCacheType() == kv_cache_manager::CacheType::kSELFKONLY)
{
kvFactor = 1;
}
mCacheState = std::make_unique<executor::kv_cache::CacheState>(cacheStateModelCfg, worldConfig,
attentionLayerNumPerPP, dataType, attentionType, kvFactor, cacheManager->isEnableBlockReuse(),
cacheManager->isEnablePartialReuse(), cacheManager->isEnableIndexerKCache(),
cacheManager->getIndexerKCacheIndexHeadDim(), cacheManager->getIndexerKCacheQuantBlockSize());
if (mCacheState->getParallelConfig().mEnableAttentionDP)
{
int dpSize = mCacheState->getParallelConfig().mDPsize;
// dpRank is derived from the tensor parallel rank, which already accounts for CP.
// Layout: rank = ppRank * (TP * CP) + tpRank * CP + cpRank.
// getTensorParallelRank() correctly extracts tpRank regardless of CP.
int dpRank = mCacheState->getParallelConfig().mDPrank;
// <PP,DP,TP,CP>
mGroupDataComm = std::make_shared<CacheTransceiverComm>(mGroupComm->split(dpRank, worldConfig.getRank()));
if (worldConfig.isTensorParallel() || worldConfig.isContextParallel())
{
// Group ranks with same (ppRank, dpRank) accounting for CP.
mGroupTPInDPComm = std::make_shared<CacheTransceiverComm>(
mGroupComm->split(worldConfig.getPipelineParallelRank() * dpSize + dpRank, worldConfig.getRank()));
}
}
bool isMLA = attentionType == executor::kv_cache::CacheState::AttentionType::kMLA;
TLLM_CHECK_WITH_INFO(mCacheTransceiverConfig.has_value(), "CacheTransceiverConfig is not set.");
auto backendType = mCacheTransceiverConfig.value().getBackendType();
TLLM_CHECK_WITH_INFO(
backendType.has_value() && (backendType.value() != executor::CacheTransceiverConfig::BackendType::DEFAULT),
" CacheTransceiverConfig::BackendType is not set.");
std::optional<size_t> maxNumTokens = mCacheTransceiverConfig.value().getMaxTokensInBuffer();
mCacheTransBufferManagers.push_back(
std::make_unique<kv_cache_manager::CacheTransBufferManager>(cacheManager, maxNumTokens));
if (isMLA && cacheManager->isEnableIndexerKCache())
{
mCacheTransBufferManagers.push_back(
std::make_unique<kv_cache_manager::CacheTransBufferManager>(cacheManager, maxNumTokens, true));
}
// RNN specific setup
if (mRnnStateManager != nullptr)
{
TLLM_LOG_DEBUG("Setting up RNN cache transfer components.");
TLLM_CHECK(!rnnLayerNumPerPP.empty());
mRnnCacheTransBufferManager
= std::make_unique<rnn_state_manager::RnnCacheTransBufferManager>(mRnnStateManager, maxNumTokens);
auto rnnModelCfg = mRnnStateManager->getRnnCacheStateModelConfig();
auto const convStateDataType = mRnnStateManager->getConvStateDataType();
auto const ssmStateDataType = mRnnStateManager->getSsmStateDataType();
mCacheState->setRnnConfig(rnnModelCfg, rnnLayerNumPerPP, convStateDataType, ssmStateDataType);
TLLM_LOG_INFO("RNN cache transfer components initialized.");
}
mCacheTransBufferManagerPtrs.clear();
mCacheTransBufferManagerPtrs.reserve(mCacheTransBufferManagers.size() + (mRnnCacheTransBufferManager ? 1 : 0));
for (auto& manager : mCacheTransBufferManagers)
{
mCacheTransBufferManagerPtrs.push_back(manager.get());
}
if (mRnnCacheTransBufferManager)
{
mCacheTransBufferManagerPtrs.push_back(mRnnCacheTransBufferManager.get());
}
if (backendType.value() == executor::CacheTransceiverConfig::BackendType::UCX)
{
std::lock_guard<std::mutex> lock(mDllMutex);
mWrapperLibHandle = dllOpen(UCX_WRAPPER_LIB_NAME);
TLLM_CHECK_WITH_INFO(
mWrapperLibHandle != nullptr, "UCX wrapper library is not open correctly. error : %s", dlerror());
auto load_sym = [](void* handle, char const* name)
{
void* ret = dllGetSym(handle, name);
TLLM_CHECK_WITH_INFO(ret != nullptr,
"Unable to load UCX wrapper library symbol, possible cause is that TensorRT LLM library is not "
"built with UCX support, please rebuild in UCX-enabled environment.");
return ret;
};
std::unique_ptr<tensorrt_llm::executor::kv_cache::ConnectionManager> (*makeUcxConnectionManager)();
*(void**) (&makeUcxConnectionManager) = load_sym(mWrapperLibHandle, "makeUcxConnectionManager");
mManager = makeUcxConnectionManager();
TLLM_LOG_INFO("UCX Connection Manager created");
}
else if (backendType.value() == executor::CacheTransceiverConfig::BackendType::NIXL)
{
auto rnnState
= mCacheState->hasRnnConfig() ? std::make_optional(mCacheState->getRnnCacheState()) : std::nullopt;
mManager = std::make_unique<tensorrt_llm::executor::kv_cache::AgentConnectionManager>(
mCacheTransBufferManagerPtrs, *mCacheState, "nixl", rnnState);
TLLM_LOG_INFO("NIXL Connection Manager created");
}
else if (backendType.value() == executor::CacheTransceiverConfig::BackendType::MOONCAKE)
{
auto rnnState
= mCacheState->hasRnnConfig() ? std::make_optional(mCacheState->getRnnCacheState()) : std::nullopt;
mManager = std::make_unique<tensorrt_llm::executor::kv_cache::AgentConnectionManager>(
mCacheTransBufferManagerPtrs, *mCacheState, "mooncake", rnnState);
TLLM_LOG_INFO("MOONCAKE Connection Manager created");
}
else if (backendType.value() == executor::CacheTransceiverConfig::BackendType::MPI)
{
mMpiWorldComm = std::addressof(tensorrt_llm::mpi::MpiComm::world());
mManager = std::make_unique<executor::kv_cache::MpiConnectionManager>(mMpiWorldComm);
TLLM_LOG_INFO("MPI Connection Manager created");
}
else
{
TLLM_THROW("Unsupported cache transceiver backend type ");
}
auto makeFormatter = [cacheManager, isMLA, this]()
{
std::vector<kv_cache_manager::CacheTransBufferManager*> kvBufferPtrs;
kvBufferPtrs.reserve(mCacheTransBufferManagers.size());
for (auto& mgr : mCacheTransBufferManagers)
{
kvBufferPtrs.push_back(mgr.get());
}
return createCacheFormatter(cacheManager, kvBufferPtrs, isMLA);
};
auto makeRnnFormatter = [this]() -> std::unique_ptr<RnnCacheFormatter>
{
if (mRnnStateManager != nullptr && mRnnCacheTransBufferManager != nullptr)
{
return std::make_unique<RnnCacheFormatter>(mRnnStateManager, mRnnCacheTransBufferManager.get());
}
return nullptr;
};
auto makeCacheTransferLayer
= [&]() { return CacheTransferLayer(*mCacheState, makeFormatter(), makeRnnFormatter()); };
mCacheSender = std::make_unique<CacheSender>(mManager.get(), worldConfig.getRank(), makeCacheTransferLayer());
mCacheReceiver = std::make_unique<CacheReceiver>(mManager.get(), worldConfig.getRank(), makeCacheTransferLayer());
initializeCommState();
}
CacheTransceiver::~CacheTransceiver()
{
if (mWrapperLibHandle)
{
std::lock_guard<std::mutex> lock(mDllMutex);
dllClose(mWrapperLibHandle);
}
}
void CacheTransceiver::initializeCommState()
{
mCommState = std::addressof(mCacheSender->getCommState());
}
void CacheTransceiver::setContextState(LlmRequest* llmRequest)
{
TLLM_CHECK(llmRequest && llmRequest->isContextOnlyRequest());
auto contextState = std::make_unique<executor::DataTransceiverState>();
contextState->setCommState(*mCommState);
contextState->setCacheState(*mCacheState);
if (!llmRequest->hasDraftTokens())
{
llmRequest->setContextPhaseParams(
executor::ContextPhaseParams{{}, llmRequest->mRequestId, contextState.release(), std::nullopt});
}
else
{
llmRequest->setContextPhaseParams(executor::ContextPhaseParams{
{}, llmRequest->mRequestId, contextState.release(), *llmRequest->getDraftTokens()});
}
}
void CacheTransceiver::respondAndSendAsync(LlmRequest* llmRequest)
{
TLLM_CHECK(llmRequest && llmRequest->isContextOnlyRequest());
llmRequest->setState(LlmRequestState::kDISAGG_CONTEXT_TRANS_IN_PROGRESS);
// If context phase params is already set, it means that the KV cache
// transfer is already in progress.
if (llmRequest->getContextPhaseParams().has_value())
{
if (llmRequest->getContextProgress() == nullptr)
{
TLLM_LOG_WARNING("Request %ld is already responding", llmRequest->mRequestId);
}
return;
}
setContextState(llmRequest);
auto future = mCacheSender->sendAsync(*llmRequest);
TLLM_LOG_DEBUG("respondAndSendAsync: adding request %ld to mSenderFutures (ptr=%p, transferStart=%ld, size=%zu)",
llmRequest->mRequestId, static_cast<void*>(llmRequest),
static_cast<long>(llmRequest->getKvCacheTransferStart().time_since_epoch().count()),
mSenderFutures.size() + 1);
mSenderFutures.emplace_back(llmRequest, std::move(future));
}
void CacheTransceiver::respondAndSendLayerWise(
RequestVector const& requests, std::shared_ptr<ContextProgress> const& progress)
{
for (auto const& llmRequest : requests)
{
TLLM_CHECK(llmRequest && llmRequest->isContextOnlyRequest());
TLLM_CHECK(!llmRequest->getContextPhaseParams().has_value());
llmRequest->setContextProgress(progress);
TLLM_LOG_DEBUG("Request %ld is being sent layer-wise.", llmRequest->mRequestId);
llmRequest->setState(LlmRequestState::kDISAGG_CONTEXT_INIT_AND_TRANS);
setContextState(llmRequest.get());
auto future = mCacheSender->sendAsync(*llmRequest);
mSenderFutures.emplace_back(llmRequest.get(), std::move(future));
}
}
void CacheTransceiver::requestAndReceiveSync(LlmRequest* llmRequest)
{
TLLM_CHECK(llmRequest && llmRequest->isGenerationOnlyRequest());
{
auto future = mCacheReceiver->receiveAsync(*llmRequest);
future.get();
}
llmRequest->setState(LlmRequestState::kDISAGG_GENERATION_TRANS_COMPLETE);
}
void CacheTransceiver::requestAndReceiveAsync(LlmRequest* llmRequest)
{
TLLM_CHECK(llmRequest && llmRequest->isGenerationOnlyRequest());
if (std::find_if(mRequesterFutures.begin(), mRequesterFutures.end(),
[llmRequest](auto const& pair) { return pair.first->mRequestId == llmRequest->mRequestId; })
!= mRequesterFutures.end())
{
TLLM_LOG_WARNING("Request ID %zu is already in mRequestFutures.", llmRequest->mRequestId);
return;
}
auto future = mCacheReceiver->receiveAsync(*llmRequest);
mRequesterFutures.emplace_back(llmRequest, std::move(future));
llmRequest->setState(LlmRequestState::kDISAGG_GENERATION_TRANS_IN_PROGRESS);
}
std::vector<LlmRequest::RequestIdType> gatherRequestIds(
std::shared_ptr<CacheTransceiverComm> const& mComm, std::vector<LlmRequest::RequestIdType> const& requestIds)
{
int localSize = static_cast<int>(requestIds.size());
std::vector<int> sizes(mComm->getSize());
std::vector<LlmRequest::RequestIdType> retData;
if (useMPI())
{
mComm->allgather(&localSize, sizes.data(), 1, mpi::MpiType::kINT32);
std::vector<int> displs(mComm->getSize());
size_t totalSize = 0;
for (int i = 0; i < mComm->getSize(); i++)
{
displs[i] = totalSize;
totalSize += sizes[i];
}
retData.resize(totalSize);
mComm->allgatherv(requestIds.data(), static_cast<int>(requestIds.size()), mpi::MpiType::kUINT64, retData.data(),
sizes, displs, mpi::MpiType::kUINT64);
}
else
{
mComm->allgather(&localSize, std::ref(sizes), {});
size_t totalSize = std::accumulate(sizes.begin(), sizes.end(), 0);
retData.resize(totalSize);
mComm->allgatherv(std::ref(requestIds), std::ref(retData), std::cref(sizes), {});
}
return retData;
}
void updateKVCacheTransferBW(std::shared_ptr<CacheTransceiverComm> const& mComm, LlmRequest* request)
{
namespace su = executor::serialize_utils;
int worldSize = mComm->getSize();
std::ostringstream oStream;
su::serialize(request->getKvCacheTransferStart(), oStream);
su::serialize(request->getKvCacheTransferEnd(), oStream);
auto str = oStream.str();
std::vector<char> sendBuffer(str.begin(), str.end());
auto sendBufferSize = sendBuffer.size();
auto recvBufferSize = sendBufferSize * worldSize;
std::vector<char> recvBuffer(recvBufferSize);
if (useMPI())
{
mComm->allgather(sendBuffer.data(), recvBuffer.data(), sendBufferSize, mpi::MpiType::kCHAR);
}
else
{
mComm->allgather(std::ref(sendBuffer), std::ref(recvBuffer), {});
}
su::VectorWrapBuf<char> strbuf(recvBuffer);
std::istream is(&strbuf);
auto minStartTime = executor::RequestPerfMetrics::TimePoint::max();
auto maxEndTime = executor::RequestPerfMetrics::TimePoint::min();
for (int rank = 0; rank < worldSize; rank++)
{
minStartTime = std::min(su::deserialize<executor::RequestPerfMetrics::TimePoint>(is), minStartTime);
maxEndTime = std::max(su::deserialize<executor::RequestPerfMetrics::TimePoint>(is), maxEndTime);
}
// Handle KV cache size separately - gather all sizes to the leader rank
std::size_t localKVCacheSize = request->getKvCacheSize();
std::vector<std::size_t> allKVCacheSizes(worldSize, 0);
if (useMPI())
{
mComm->allgather(&localKVCacheSize, allKVCacheSizes.data(), 1, mpi::MpiType::kUINT64);
}
else
{
mComm->allgather(&localKVCacheSize, std::ref(allKVCacheSizes), {});
}
std::size_t totalKVCacheSize = 0;
for (int rank = 0; rank < worldSize; rank++)
{
totalKVCacheSize += allKVCacheSizes[rank];
}
// Update the latest KV cache transfer time for leader rank
if (mComm->getRank() == 0)
{
request->setKvCacheTransferStart(minStartTime);
request->setKvCacheTransferEnd(maxEndTime);
request->setKvCacheSize(totalKVCacheSize);
}
}
RequestStatuses CacheTransceiver::checkContextTransferStatus(
std::optional<int> const& atLeastRequestNum, bool markComplete)
{
bool blockAll = !atLeastRequestNum.has_value();
std::optional<int> senderFutureTimeoutMs = std::nullopt;
std::optional<int> kvTransferTimeoutMs = std::nullopt;
// Always use a bounded timeout to prevent unbounded blocking.
// The caller (scheduler) loops, so timed-out transfers retry on next iteration.
if (mCacheTransceiverConfig.has_value())
{
senderFutureTimeoutMs = mCacheTransceiverConfig->getKvTransferSenderFutureTimeoutMs();
kvTransferTimeoutMs = mCacheTransceiverConfig->getKvTransferTimeoutMs();
}
{
senderFutureTimeoutMs = mCacheTransceiverConfig->getKvTransferSenderFutureTimeoutMs();
kvTransferTimeoutMs = mCacheTransceiverConfig->getKvTransferTimeoutMs();
}
// Log mSenderFutures state for diagnosing dangling pointer issues.
// Each entry's pointer address and request ID are logged so we can detect
// when a pointer's underlying memory is freed (reqId changes to 0).
if (!mSenderFutures.empty())
{
TLLM_LOG_DEBUG("checkContextTransferStatus: mSenderFutures.size()=%zu, blockAll=%d, "
"kvTransferTimeoutMs=%d",
mSenderFutures.size(), blockAll ? 1 : 0,
kvTransferTimeoutMs.value_or(-1));
for (size_t i = 0; i < mSenderFutures.size(); ++i)
{
auto& [req, fut] = mSenderFutures[i];
auto startTs = req->getKvCacheTransferStart().time_since_epoch().count();
TLLM_LOG_DEBUG(" [%zu] ptr=%p reqId=%ld startTs=%ld",
i, static_cast<void const*>(req), req->mRequestId, static_cast<long>(startTs));
}
}
auto syncComm = mCacheState->getParallelConfig().mEnableAttentionDP ? mGroupTPInDPComm : mGroupTensorParaComm;
std::vector<LlmRequest::RequestIdType> contextCompleteRequestIds;
for (auto&& [request, future] : mSenderFutures)
{
if (future.wait_for(std::chrono::milliseconds(0)) == std::future_status::ready)
{
contextCompleteRequestIds.push_back(request->mRequestId);
}
}
std::unordered_map<LlmRequest::RequestIdType, int> frequencyMap;
if ((syncComm) && syncComm->getSize() > 1)
{
auto gatherRequestIdVec = gatherRequestIds(syncComm, contextCompleteRequestIds);
for (auto&& requestId : gatherRequestIdVec)
{
frequencyMap[requestId]++;
}
}
else
{
for (auto&& requestId : contextCompleteRequestIds)
{
frequencyMap[requestId]++;
}
}
std::vector<std::pair<LlmRequest::RequestIdType, int>> freqVec(frequencyMap.begin(), frequencyMap.end());
std::sort(freqVec.begin(), freqVec.end(),
[](std::pair<LlmRequest::RequestIdType, int> const& left,
std::pair<LlmRequest::RequestIdType, int> const& right) { return left.second > right.second; });
std::unordered_set<LlmRequest::RequestIdType> toCompleteIdSet;
for (auto&& [requestId, freq] : freqVec)
{
if (freq == ((syncComm) ? syncComm->getSize() : 1))
{
toCompleteIdSet.insert(requestId);
}
}
// Make sure there are at least atLeastRequestNum requests in toCompleteIdSet.
// This will preserve the order of insertion for KVCache transfer requests.
for (auto it = mSenderFutures.begin();
atLeastRequestNum.value_or(0) > static_cast<int>(toCompleteIdSet.size()) && it != mSenderFutures.end(); ++it)
{
auto& [request, future] = *it;
toCompleteIdSet.insert(request->mRequestId);
}
RequestStatuses requestsStatus{};
// Complete all the requests in toCompleteIdSet
for (auto it = mSenderFutures.begin(); it != mSenderFutures.end();)
{
auto& [request, future] = *it;
if (blockAll || (toCompleteIdSet.find(request->mRequestId) != toCompleteIdSet.end()))
{
try
{
// Wait for up to a specified timeout
auto const timeoutMs = senderFutureTimeoutMs.value_or(1000);
auto status = future.wait_for(std::chrono::milliseconds(timeoutMs));
if (status == std::future_status::ready)
{
future.get();
requestsStatus.completedRequestIds.insert(request->mRequestId);
if (markComplete)
{
request->setState(LlmRequestState::kDISAGG_CONTEXT_COMPLETE);
}
it = mSenderFutures.erase(it);
}
else if (status == std::future_status::timeout)
{
// Check if total elapsed time exceeds kv_transfer_timeout_ms.
// Without this, stuck transfers retry the per-iteration timeout forever,
// holding KV blocks indefinitely and exhausting the cache pool.
if (kvTransferTimeoutMs.has_value())
{
auto transferStart = request->getKvCacheTransferStart();
// Guard: if transfer start was never set (TimePoint epoch),
// the request pointer may be stale or the start time was not recorded.
// Treat as timed out immediately to avoid infinite retry.
bool startTimeValid = transferStart.time_since_epoch().count() > 0;
bool shouldTimeout = !startTimeValid;
long elapsedMs = 0;
if (startTimeValid)
{
auto elapsed = std::chrono::duration_cast<std::chrono::milliseconds>(
LlmRequest::getSteadyClockNow() - transferStart);
elapsedMs = static_cast<long>(elapsed.count());
shouldTimeout = elapsedMs > kvTransferTimeoutMs.value();
}
if (shouldTimeout)
{
if (startTimeValid)
{
TLLM_LOG_ERROR(
"Context KV cache transfer for request %ld exceeded total timeout: "
"elapsed %ld ms > limit %d ms. Marking as error.",
request->mRequestId, elapsedMs, kvTransferTimeoutMs.value());
try
{
mCacheSender->cancelRequest(*request);
}
catch (...)
{
}
request->setState(LlmRequestState::kDISAGG_TRANS_ERROR);
requestsStatus.errorRequestIds.insert(request->mRequestId);
}
else
{
// Start time is epoch — the LlmRequest* is likely a dangling pointer
// (request was freed while still in mSenderFutures). Do NOT dereference
// request beyond this point. Just remove the stale entry.
TLLM_LOG_WARNING(
"Removing stale entry from mSenderFutures: transfer start time is "
"uninitialized (request pointer %p may be dangling).",
static_cast<void const*>(request));
}
it = mSenderFutures.erase(it);
continue;
}
}
TLLM_LOG_WARNING("Timed out waiting for context KV cache transfer after %d milliseconds.",
timeoutMs);
++it;
}
else
{
TLLM_LOG_ERROR(
"Future returned unexpected status for request %ld. Marking as error", request->mRequestId);
request->setState(LlmRequestState::kDISAGG_TRANS_ERROR);
requestsStatus.errorRequestIds.insert(request->mRequestId);
it = mSenderFutures.erase(it);
}
}
catch (std::exception const& e)
{
// Guard: the request pointer may be stale if the sender thread crashed
// and the request was freed concurrently. Check transfer start time as
// a heuristic — epoch (0) indicates likely dangling pointer.
auto transferStart = request->getKvCacheTransferStart();
bool likelyValid = transferStart.time_since_epoch().count() > 0;
if (likelyValid)
{
TLLM_LOG_ERROR(
"Error occurred during context transfer for request %ld: %s",
request->mRequestId, e.what());
request->setState(LlmRequestState::kDISAGG_TRANS_ERROR);
requestsStatus.errorRequestIds.insert(request->mRequestId);
}
else
{
TLLM_LOG_WARNING(
"Error during context transfer with likely stale request pointer %p: %s. "
"Removing entry without setting state.",
static_cast<void const*>(request), e.what());
}
it = mSenderFutures.erase(it);
}
}
else
{
++it;
}
}
if (!requestsStatus.completedRequestIds.empty() || !requestsStatus.errorRequestIds.empty())
{
TLLM_LOG_DEBUG("checkContextTransferStatus done: completed=%zu, errors=%zu, "
"mSenderFutures.size()=%zu",
requestsStatus.completedRequestIds.size(),
requestsStatus.errorRequestIds.size(),
mSenderFutures.size());
}
return requestsStatus;
}
void CacheTransceiver::checkGenTransferStatus(std::optional<int> const& atLeastRequestNum)
{
bool blockAll = !atLeastRequestNum.has_value();
std::optional<int> receiverFutureTimeoutMs = std::nullopt;
// Always use a bounded timeout to prevent unbounded blocking.
// The caller (scheduler) loops, so timed-out transfers retry on next iteration.
if (mCacheTransceiverConfig.has_value())
{
receiverFutureTimeoutMs = mCacheTransceiverConfig->getKvTransferSenderFutureTimeoutMs();
}
std::vector<LlmRequest::RequestIdType> genTransferReadyRequestIds;
for (auto&& [request, future] : mRequesterFutures)
{
if (future.wait_for(std::chrono::milliseconds(0)) == std::future_status::ready)
{
genTransferReadyRequestIds.push_back(request->mRequestId);
}
}
std::unordered_map<LlmRequest::RequestIdType, int> frequencyMap;
std::vector<LlmRequest::RequestIdType> toBlockRequestIds;
auto syncComm = mCacheState->getParallelConfig().mEnableAttentionDP ? mGroupDataComm : mGroupComm;
if ((syncComm) && syncComm->getSize() > 1)
{
auto gatherRequestIdVec = gatherRequestIds(syncComm, genTransferReadyRequestIds);
for (auto&& requestId : gatherRequestIdVec)
{
frequencyMap[requestId]++;
}
}
else
{
for (auto&& requestId : genTransferReadyRequestIds)
{
frequencyMap[requestId]++;
}
}
std::vector<std::pair<LlmRequest::RequestIdType, int>> freqVec(frequencyMap.begin(), frequencyMap.end());
std::sort(freqVec.begin(), freqVec.end(),
[](std::pair<LlmRequest::RequestIdType, int> const& left,
std::pair<LlmRequest::RequestIdType, int> const& right) { return left.second > right.second; });
std::unordered_set<LlmRequest::RequestIdType> toCompleteIdSet;
size_t idx = 0;
while (atLeastRequestNum.value_or(0) > static_cast<int>(toCompleteIdSet.size()))
{
if (idx >= freqVec.size())
{
break;
}
toCompleteIdSet.insert(freqVec.at(idx).first);
if (useMPI())
{
TLLM_LOG_DEBUG(mpi::MpiComm::world().getRank(),
" checkGenTransferStatus at least from freqVec requestId: %zu ", freqVec.at(idx).first);
}
else
{
TLLM_LOG_DEBUG(tensorrt_llm::pg_utils::get_world_pg()->getRank(),
" checkGenTransferStatus at least from freqVec requestId: %zu ", freqVec.at(idx).first);
}
idx++;
}
idx = 0;
// insert order
while (atLeastRequestNum.value_or(0) > static_cast<int>(toCompleteIdSet.size()))
{
if (idx >= mRequesterFutures.size())
{
break;
}
if (toCompleteIdSet.find(mRequesterFutures.at(idx).first->mRequestId) == toCompleteIdSet.end())
{
toCompleteIdSet.insert(mRequesterFutures.at(idx).first->mRequestId);
if (useMPI())
{
TLLM_LOG_DEBUG(mpi::MpiComm::world().getRank(),
" checkGenTransferStatus at least from RequesterFuture requestId: %zu atLeastRequestNum:%d",
mRequesterFutures.at(idx).first->mRequestId, atLeastRequestNum.value_or(0));
}
else
{
TLLM_LOG_DEBUG(tensorrt_llm::pg_utils::get_world_pg()->getRank(),
" checkGenTransferStatus at least from RequesterFuture requestId: %zu atLeastRequestNum:%d",
mRequesterFutures.at(idx).first->mRequestId, atLeastRequestNum.value_or(0));
}
}
idx++;
}
for (auto&& [requestId, freq] : freqVec)
{
if (freq == ((syncComm != nullptr) ? syncComm->getSize() : 1))
{
toCompleteIdSet.insert(requestId);
}
if (useMPI())
{
TLLM_LOG_DEBUG(mpi::MpiComm::world().getRank(), " checkGenTransferStatus freqVec requestId: %zu,freq:%d ",
requestId, freq);
}
else
{
TLLM_LOG_DEBUG(tensorrt_llm::pg_utils::get_world_pg()->getRank(),
" checkGenTransferStatus freqVec requestId: %zu,freq:%d ", requestId, freq);
}
}
if (useMPI())
{
TLLM_LOG_DEBUG(mpi::MpiComm::world().getRank(),
" checkGenTransferStatus toCompleteIdSet size: %zu, atLeastRequestNum: %d ", toCompleteIdSet.size(),
atLeastRequestNum.value_or(0));
}
else
{
TLLM_LOG_DEBUG(tensorrt_llm::pg_utils::get_world_pg()->getRank(),
" checkGenTransferStatus toCompleteIdSet size: %zu, atLeastRequestNum: %d ", toCompleteIdSet.size(),
atLeastRequestNum.value_or(0));
}
auto const syncSize = (syncComm != nullptr) ? syncComm->getSize() : 1;
for (auto it = mRequesterFutures.begin(); it != mRequesterFutures.end();)
{
if (blockAll || toCompleteIdSet.find(it->first->mRequestId) != toCompleteIdSet.end())
{
try
{
// Wait for up to a specified timeout
auto const timeoutMs = receiverFutureTimeoutMs.value_or(1000);
auto status = it->second.wait_for(std::chrono::milliseconds(timeoutMs));
if (status == std::future_status::ready)
{
it->second.get();
it->first->setState(LlmRequestState::kDISAGG_GENERATION_TRANS_COMPLETE);
// Gather the kv cache transfer time from all workers and update to leader rank.
// Only call the timing collective when either all ranks block together (blockAll)
// or the request was confirmed ready on every rank in the initial poll, to avoid
// hanging in allgather when a peer timed out and skipped this request.
if (!common::getEnvKVCacheTimeOutputPath().empty())
{
auto const freqIt = frequencyMap.find(it->first->mRequestId);
if (blockAll || (freqIt != frequencyMap.end() && freqIt->second == syncSize))
{
updateKVCacheTransferBW(syncComm, it->first);
}
}
if (useMPI())
{
TLLM_LOG_DEBUG(mpi::MpiComm::world().getRank(),
"**** it->first->mRequestId: %ld, context request ID: %ld ******** get feature ***",
it->first->mRequestId, it->first->getContextPhaseParams().value().getReqId());
}
else
{
TLLM_LOG_DEBUG(tensorrt_llm::pg_utils::get_world_pg()->getRank(),
"**** it->first->mRequestId: %ld, context request ID: %ld ******** get feature ***",
it->first->mRequestId, it->first->getContextPhaseParams().value().getReqId());
}
it = mRequesterFutures.erase(it);
}
else if (status == std::future_status::timeout)
{
TLLM_LOG_WARNING(
"Timed out waiting for generation KV cache transfer after %d milliseconds.", timeoutMs);
++it;
}
else
{
TLLM_LOG_ERROR("Future returned unexpected status for request %ld. Marking as error",
it->first->mRequestId);
it->first->setState(LlmRequestState::kDISAGG_TRANS_ERROR);
it = mRequesterFutures.erase(it);
}
}
catch (std::exception const& e)
{
TLLM_LOG_ERROR(
"Error occurred during generation transfer for request %ld: %s", it->first->mRequestId, e.what());
it->first->setState(LlmRequestState::kDISAGG_TRANS_ERROR);
it = mRequesterFutures.erase(it);
}
}
else
{
++it;
}
}
}
bool CacheTransceiver::checkGenTransferComplete() const
{
return mRequesterFutures.empty();
}
bool CacheTransceiver::cancelRequest(LlmRequest* llmRequest)
{
if (llmRequest->isContextOnlyRequest())
{
return mCacheSender->cancelRequest(*llmRequest);
}
else if (llmRequest->isGenerationOnlyRequest())
{
return mCacheReceiver->cancelRequest(*llmRequest);
}
return false;
}
} // namespace tensorrt_llm::batch_manager