Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

[Bug]: Error executing method 'start_worker_execution_loop'. This might cause deadlock in distributed execution. #13276

Open
1 task done
RunningLeon opened this issue Feb 14, 2025 · 0 comments
Open
1 task done

[Bug]: Error executing method 'start_worker_execution_loop'. This might cause deadlock in distributed execution. #13276

RunningLeon opened this issue Feb 14, 2025 · 0 comments
Labels
bug Something isn't working

Comments

@RunningLeon
Copy link
Contributor

Your current environment

The error log of `python collect_env.py` 
INFO 02-14 08:29:25 __init__.py:190] Automatically detected platform cuda.
Collecting environment information...
PyTorch version: 2.5.1+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.4 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.31.4
Libc version: glibc-2.35

Python version: 3.10.12 (main, Jan 17 2025, 14:35:34) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-5.10.134-16.101.al8.x86_64-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.4.131
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: 
GPU 0: NVIDIA H800
GPU 1: NVIDIA H800
GPU 2: NVIDIA H800
GPU 3: NVIDIA H800
GPU 4: NVIDIA H800
GPU 5: NVIDIA H800
GPU 6: NVIDIA H800
GPU 7: NVIDIA H800

Nvidia driver version: 535.183.06
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                    x86_64
CPU op-mode(s):                  32-bit, 64-bit
Address sizes:                   46 bits physical, 57 bits virtual
Byte Order:                      Little Endian
CPU(s):                          192
On-line CPU(s) list:             0-191
Vendor ID:                       GenuineIntel
Model name:                      Intel(R) Xeon(R) Platinum 8468V
CPU family:                      6
Model:                           143
Thread(s) per core:              2
Core(s) per socket:              48
Socket(s):                       2
Stepping:                        8
CPU max MHz:                     3800.0000
CPU min MHz:                     800.0000
BogoMIPS:                        4800.00
Flags:                           fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 invpcid_single cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req hfi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm uintr md_clear serialize tsxldtrk pconfig arch_lbr amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
Virtualization:                  VT-x
L1d cache:                       4.5 MiB (96 instances)
L1i cache:                       3 MiB (96 instances)
L2 cache:                        192 MiB (96 instances)
L3 cache:                        195 MiB (2 instances)
NUMA node(s):                    2
NUMA node0 CPU(s):               0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62,64,66,68,70,72,74,76,78,80,82,84,86,88,90,92,94,96,98,100,102,104,106,108,110,112,114,116,118,120,122,124,126,128,130,132,134,136,138,140,142,144,146,148,150,152,154,156,158,160,162,164,166,168,170,172,174,176,178,180,182,184,186,188,190
NUMA node1 CPU(s):               1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31,33,35,37,39,41,43,45,47,49,51,53,55,57,59,61,63,65,67,69,71,73,75,77,79,81,83,85,87,89,91,93,95,97,99,101,103,105,107,109,111,113,115,117,119,121,123,125,127,129,131,133,135,137,139,141,143,145,147,149,151,153,155,157,159,161,163,165,167,169,171,173,175,177,179,181,183,185,187,189,191
Vulnerability Itlb multihit:     Not affected
Vulnerability L1tf:              Not affected
Vulnerability Mds:               Not affected
Vulnerability Meltdown:          Not affected
Vulnerability Mmio stale data:   Not affected
Vulnerability Retbleed:          Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1:        Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:        Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence
Vulnerability Srbds:             Not affected
Vulnerability Tsx async abort:   Not affected

Versions of relevant libraries:
[pip3] flashinfer-python==0.2.0.post2+cu124torch2.5
[pip3] numpy==1.26.4
[pip3] nvidia-cublas-cu12==12.1.3.1
[pip3] nvidia-cuda-cupti-cu12==12.1.105
[pip3] nvidia-cuda-nvrtc-cu12==12.1.105
[pip3] nvidia-cuda-runtime-cu12==12.1.105
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.0.2.54
[pip3] nvidia-curand-cu12==10.3.2.106
[pip3] nvidia-cusolver-cu12==11.4.5.107
[pip3] nvidia-cusparse-cu12==12.1.0.106
[pip3] nvidia-ml-py==12.570.86
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.8.61
[pip3] nvidia-nvtx-cu12==12.1.105
[pip3] pynvml==12.0.0
[pip3] pyzmq==26.2.1
[pip3] torch==2.5.1+cu121
[pip3] torchao==0.8.0
[pip3] torchaudio==2.5.1
[pip3] torchvision==0.20.1+cu121
[pip3] transformers==4.48.3
[pip3] transformers-stream-generator==0.0.5
[pip3] triton==3.1.0
[pip3] tritonclient==2.53.0
[conda] Could not collect
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.7.2
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0    GPU1    GPU2    GPU3    GPU4    GPU5    GPU6    GPU7    NIC0    NIC1    NIC2    NIC3    NIC4    NIC5    NIC6    NIC7    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      NV8     NV8     NV8     NV8     NV8     NV8     NV8     PIX     NODE    NODE    NODE    SYS     SYS     SYS     SYS     0,2,4,6,8,10    0               N/A
GPU1    NV8      X      NV8     NV8     NV8     NV8     NV8     NV8     NODE    PIX     NODE    NODE    SYS     SYS     SYS     SYS     0,2,4,6,8,10    0               N/A
GPU2    NV8     NV8      X      NV8     NV8     NV8     NV8     NV8     NODE    NODE    PIX     NODE    SYS     SYS     SYS     SYS     0,2,4,6,8,10    0               N/A
GPU3    NV8     NV8     NV8      X      NV8     NV8     NV8     NV8     NODE    NODE    NODE    PIX     SYS     SYS     SYS     SYS     0,2,4,6,8,10    0               N/A
GPU4    NV8     NV8     NV8     NV8      X      NV8     NV8     NV8     SYS     SYS     SYS     SYS     PIX     NODE    NODE    NODE    1,3,5,7,9,11    1               N/A
GPU5    NV8     NV8     NV8     NV8     NV8      X      NV8     NV8     SYS     SYS     SYS     SYS     NODE    PIX     NODE    NODE    1,3,5,7,9,11    1               N/A
GPU6    NV8     NV8     NV8     NV8     NV8     NV8      X      NV8     SYS     SYS     SYS     SYS     NODE    NODE    PIX     NODE    1,3,5,7,9,11    1               N/A
GPU7    NV8     NV8     NV8     NV8     NV8     NV8     NV8      X      SYS     SYS     SYS     SYS     NODE    NODE    NODE    PIX     1,3,5,7,9,11    1               N/A
NIC0    PIX     NODE    NODE    NODE    SYS     SYS     SYS     SYS      X      NODE    NODE    NODE    SYS     SYS     SYS     SYS
NIC1    NODE    PIX     NODE    NODE    SYS     SYS     SYS     SYS     NODE     X      NODE    NODE    SYS     SYS     SYS     SYS
NIC2    NODE    NODE    PIX     NODE    SYS     SYS     SYS     SYS     NODE    NODE     X      NODE    SYS     SYS     SYS     SYS
NIC3    NODE    NODE    NODE    PIX     SYS     SYS     SYS     SYS     NODE    NODE    NODE     X      SYS     SYS     SYS     SYS
NIC4    SYS     SYS     SYS     SYS     PIX     NODE    NODE    NODE    SYS     SYS     SYS     SYS      X      NODE    NODE    NODE
NIC5    SYS     SYS     SYS     SYS     NODE    PIX     NODE    NODE    SYS     SYS     SYS     SYS     NODE     X      NODE    NODE
NIC6    SYS     SYS     SYS     SYS     NODE    NODE    PIX     NODE    SYS     SYS     SYS     SYS     NODE    NODE     X      NODE
NIC7    SYS     SYS     SYS     SYS     NODE    NODE    NODE    PIX     SYS     SYS     SYS     SYS     NODE    NODE    NODE     X 

Legend:

  X    = Self
  SYS  = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
  NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
  PHB  = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
  PXB  = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
  PIX  = Connection traversing at most a single PCIe bridge
  NV#  = Connection traversing a bonded set of # NVLinks

NIC Legend:

  NIC0: mlx5_bond_0
  NIC1: mlx5_bond_1
  NIC2: mlx5_bond_2
  NIC3: mlx5_bond_3
  NIC4: mlx5_bond_4
  NIC5: mlx5_bond_5
  NIC6: mlx5_bond_6
  NIC7: mlx5_bond_7

NVIDIA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
NVIDIA_REQUIRE_CUDA=cuda>=12.4 brand=tesla,driver>=470,driver<471 brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=geforce,driver>=470,driver<471 brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 brand=titanrtx,driver>=470,driver<471 brand=tesla,driver>=525,driver<526 brand=unknown,driver>=525,driver<526 brand=nvidia,driver>=525,driver<526 brand=nvidiartx,driver>=525,driver<526 brand=geforce,driver>=525,driver<526 brand=geforcertx,driver>=525,driver<526 brand=quadro,driver>=525,driver<526 brand=quadrortx,driver>=525,driver<526 brand=titan,driver>=525,driver<526 brand=titanrtx,driver>=525,driver<526 brand=tesla,driver>=535,driver<536 brand=unknown,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=geforce,driver>=535,driver<536 brand=geforcertx,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=titan,driver>=535,driver<536 brand=titanrtx,driver>=535,driver<536
NCCL_VERSION=2.21.5-1
NVIDIA_DRIVER_CAPABILITIES=compute,utility
NVIDIA_PRODUCT_NAME=CUDA
CUDA_VERSION=12.4.1
CUDA_VERSION_SHORT=cu121
NCCL_LAUNCH_MODE=GROUP
NCCL_CUMEM_ENABLE=0
TORCHINDUCTOR_COMPILE_THREADS=1
CUDA_MODULE_LOADING=LAZY

🐛 Describe the bug

Engine failed after running some time. Found similar issue #5084 but it is supposed be fixed in v0.5.1

command

export VLLM_LOGGING_LEVEL=DEBUG
export CUDA_LAUNCH_BLOCKING=1
export NCCL_DEBUG=TRACE
export VLLM_TRACE_FUNCTION=1
HF_EVALUATE_OFFLINE=1 HF_DATASETS_OFFLINE=1 TRANSFORMERS_OFFLINE=1 \
vllm serve    ./models--deepseek-ai--DeepSeek-V3/snapshots/4c1f24cc10a2a1894304c7ab52edd9710c047571    \
--enforce-eager    \
--trust-remote-code    \
 --tensor-parallel-size 8    \
 --pipeline-parallel-size 2

error log

The error log 
:540539 [0] NCCL INFO Channel 10/0 : 0[0] -> 1[1] via P2P/IPC
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Channel 11/0 : 0[0] -> 1[1] via P2P/IPC
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Channel 12/0 : 0[0] -> 1[1] via P2P/IPC
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Channel 13/0 : 0[0] -> 1[1] via P2P/IPC
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Channel 14/0 : 0[0] -> 1[1] via P2P/IPC
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Channel 15/0 : 0[0] -> 1[1] via P2P/IPC
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Connected all rings
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Connected all trees
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO NVLS comm 0x55cffbc5c320 headRank 0 nHeads 8 buffSize 1048576 memSize 2097152 nvlsPerRankSize 100663296 nvlsTotalSize 805306368
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO threadThresholds 8/8/64 | 64/8/64 | 512 | 512
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO 16 coll channels, 16 collnet channels, 16 nvls channels, 16 p2p channels, 16 p2p channels per peer
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO NCCL_LAUNCH_MODE set by environment to GROUP
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO TUNER/Plugin: Plugin load returned 2 : libnccl-net.so: cannot open shared object file: No such file or directory : when loading libnccl-tuner.so
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO TUNER/Plugin: Using internal tuner plugin.
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO ncclCommInitRank comm 0x55cffbc5c320 rank 0 nranks 8 cudaDev 0 nvmlDev 0 busId 19000 commId 0x408de440a1405b93 - Init COMPLETE
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Using non-device net plugin version 0
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Using network Socket
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO ncclCommInitRank comm 0x55d0094174e0 rank 0 nranks 2 cudaDev 0 nvmlDev 0 busId 19000 commId 0xa4338029cd1bb6db - Init START
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Setting affinity for GPU 0 to 55555555,55555555,55555555,55555555,55555555,55555555
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO comm 0x55d0094174e0 rank 0 nRanks 2 nNodes 2 localRanks 1 localRank 0 MNNVL 0
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Channel 00/02 :    0   1
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Channel 01/02 :    0   1
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Trees [0] 1/-1/-1->0->-1 [1] -1/-1/-1->0->1
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO P2P Chunksize set to 131072
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Channel 00/0 : 1[0] -> 0[0] [receive] via NET/Socket/0
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Channel 01/0 : 1[0] -> 0[0] [receive] via NET/Socket/0
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Channel 00/0 : 0[0] -> 1[0] [send] via NET/Socket/0
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Channel 01/0 : 0[0] -> 1[0] [send] via NET/Socket/0
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Connected all rings
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO Connected all trees
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO threadThresholds 8/8/64 | 16/8/64 | 512 | 512
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO 2 coll channels, 2 collnet channels, 0 nvls channels, 2 p2p channels, 2 p2p channels per peer
dsw-1056-75bdc9d5c9-hp6cz:540539:540539 [0] NCCL INFO ncclCommInitRank comm 0x55d0094174e0 rank 0 nranks 2 cudaDev 0 nvmlDev 0 busId 19000 commId 0xa4338029cd1bb6db - Init COMPLETE
dsw-1056-75bdc9d5c9-hp6cz:540539:551755 [0] NCCL INFO Using non-device net plugin version 0
dsw-1056-75bdc9d5c9-hp6cz:540539:551755 [0] NCCL INFO Using network Socket
dsw-1056-75bdc9d5c9-hp6cz:540539:551755 [0] NCCL INFO ncclCommInitRank comm 0x7f647c0203e0 rank 0 nranks 8 cudaDev 0 nvmlDev 0 busId 19000 commId 0xd346c3c43ef7f12f - Init START
dsw-1056-75bdc9d5c9-hp6cz:540539:551755 [0] NCCL INFO Setting affinity for GPU 0 to 55555555,5555555�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574] Error executing method 'start_worker_execution_loop'. This might cause deadlock in distributed execution.
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574] Traceback (most recent call last):
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574]   File "/opt/vllm/vllm/worker/worker_base.py", line 566, in execute_method
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574]     return run_method(target, method, args, kwargs)
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574]   File "/opt/vllm/vllm/utils.py", line 2220, in run_method
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574]     return func(*args, **kwargs)
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574]   File "/opt/vllm/vllm/worker/worker_base.py", line 93, in start_worker_execution_loop
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574]     output = self.execute_model(execute_model_req=None)
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574]   File "/opt/vllm/vllm/worker/worker_base.py", line 406, in execute_model
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574]     get_pp_group().recv_tensor_dict(
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574]   File "/opt/vllm/vllm/distributed/parallel_state.py", line 747, in recv_tensor_dict
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574]     recv_metadata_list = self.recv_object(src=src)
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574]   File "/opt/vllm/vllm/distributed/parallel_state.py", line 561, in recv_object
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574]     rank_size = torch.distributed.recv(size_tensor,
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574]   File "/opt/py3/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574]     return func(*args, **kwargs)
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574]   File "/opt/py3/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 2203, in recv
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574]     pg.recv([tensor], group_src_rank, tag).wait()
�[36m(RayWorkerWrapper pid=286715, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574] RuntimeError: [../third_party/gloo/gloo/transport/tcp/unbound_buffer.cc:81] Timed out waiting 1800000ms for recv operation to complete
�[36m(RayWorkerWrapper pid=286711, ip=10.130.199.172)�[0m INFO 02-13 13:59:44 worker.py:267] Memory profiling takes 8.69 seconds�[32m [repeated 14x across cluster]�[0m
�[36m(RayWorkerWrapper pid=286711, ip=10.130.199.172)�[0m INFO 02-13 13:59:44 worker.py:267] the current vLLM instance can use total_gpu_memory (79.11GiB) x gpu_memory_utilization (0.90) = 71.20GiB�[32m [repeated 14x across cluster]�[0m
�[36m(RayWorkerWrapper pid=286711, ip=10.130.199.172)�[0m INFO 02-13 13:59:44 worker.py:267] model weights take 44.71GiB; non_torch_memory takes 4.48GiB; PyTorch activation peak memory takes 1.25GiB; the rest of the memory reserved for KV Cache is 20.75GiB.�[32m [repeated 14x across cluster]�[0m
�[36m(RayWorkerWrapper pid=286711, ip=10.130.199.172)�[0m ERROR 02-13 15:44:24 worker_base.py:574] Error executing method 'execute_model'. This might cause deadlock in distributed execution.
INFO 02-14 02:10:29 async_llm_engine.py:211] Added request chatcmpl-2e196a12b6e9431b8f0fcc238cccb333.
INFO 02-14 02:10:29 async_llm_engine.py:211] Added request chatcmpl-2b52dd1202a94e8bb58c2c0fa7e0b5bf.
DEBUG 02-14 02:10:29 metrics.py:455] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 6 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.3%, CPU KV cache usage: 0.0%.
ERROR 02-14 02:10:29 async_llm_engine.py:839] Engine iteration timed out. This should never happen!
ERROR 02-14 02:10:29 async_llm_engine.py:68] Engine background task failed
ERROR 02-14 02:10:29 async_llm_engine.py:68] Traceback (most recent call last):
ERROR 02-14 02:10:29 async_llm_engine.py:68]   File "/opt/vllm/vllm/engine/async_llm_engine.py", line 819, in run_engine_loop
ERROR 02-14 02:10:29 async_llm_engine.py:68]     done, _ = await asyncio.wait(
ERROR 02-14 02:10:29 async_llm_engine.py:68]   File "/usr/lib/python3.10/asyncio/tasks.py", line 384, in wait
ERROR 02-14 02:10:29 async_llm_engine.py:68]     return await _wait(fs, timeout, return_when, loop)
ERROR 02-14 02:10:29 async_llm_engine.py:68]   File "/usr/lib/python3.10/asyncio/tasks.py", line 491, in _wait
ERROR 02-14 02:10:29 async_llm_engine.py:68]     await waiter
ERROR 02-14 02:10:29 async_llm_engine.py:68] asyncio.exceptions.CancelledError
ERROR 02-14 02:10:29 async_llm_engine.py:68] 
ERROR 02-14 02:10:29 async_llm_engine.py:68] During handling of the above exception, another exception occurred:
ERROR 02-14 02:10:29 async_llm_engine.py:68] 
ERROR 02-14 02:10:29 async_llm_engine.py:68] Traceback (most recent call last):
ERROR 02-14 02:10:29 async_llm_engine.py:68]   File "/opt/vllm/vllm/engine/async_llm_engine.py", line 58, in _log_task_completion
ERROR 02-14 02:10:29 async_llm_engine.py:68]     return_value = task.result()
ERROR 02-14 02:10:29 async_llm_engine.py:68]   File "/opt/vllm/vllm/engine/async_llm_engine.py", line 818, in run_engine_loop
ERROR 02-14 02:10:29 async_llm_engine.py:68]     async with asyncio_timeout(ENGINE_ITERATION_TIMEOUT_S):
ERROR 02-14 02:10:29 async_llm_engine.py:68]   File "/opt/vllm/vllm/engine/async_timeout.py", line 97, in __aexit__
ERROR 02-14 02:10:29 async_llm_engine.py:68]     self._do_exit(exc_type)
ERROR 02-14 02:10:29 async_llm_engine.py:68]   File "/opt/vllm/vllm/engine/async_timeout.py", line 180, in _do_exit
ERROR 02-14 02:10:29 async_llm_engine.py:68]     raise asyncio.TimeoutError
ERROR 02-14 02:10:29 async_llm_engine.py:68] asyncio.exceptions.TimeoutError
Exception in callback functools.partial(<function _log_task_completion at 0x7fada490aef0>, error_callback=<bound method AsyncLLMEngine._error_callback of <vllm.engine.async_llm_engine.AsyncLLMEngine object at 0x7fad87b387f0>>)
handle: <Handle functools.partial(<function _log_task_completion at 0x7fada490aef0>, error_callback=<bound method AsyncLLMEngine._error_callback of <vllm.engine.async_llm_engine.AsyncLLMEngine object at 0x7fad87b387f0>>)>
Traceback (most recent call last):
  File "/opt/vllm/vllm/engine/async_llm_engine.py", line 819, in run_engine_loop
    done, _ = await asyncio.wait(
  File "/usr/lib/python3.10/asyncio/tasks.py", line 384, in wait
    return await _wait(fs, timeout, return_when, loop)
  File "/usr/lib/python3.10/asyncio/tasks.py", line 491, in _wait
    await waiter
asyncio.exceptions.CancelledError

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/opt/vllm/vllm/engine/async_llm_engine.py", line 58, in _log_task_completion
    return_value = task.result()
  File "/opt/vllm/vllm/engine/async_llm_engine.py", line 818, in run_engine_loop
    async with asyncio_timeout(ENGINE_ITERATION_TIMEOUT_S):
  File "/opt/vllm/vllm/engine/async_timeout.py", line 97, in __aexit__
    self._do_exit(exc_type)
  File "/opt/vllm/vllm/engine/async_timeout.py", line 180, in _do_exit
    raise asyncio.TimeoutError
asyncio.exceptions.TimeoutError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "uvloop/cbhandles.pyx", line 63, in uvloop.loop.Handle._run
  File "/opt/vllm/vllm/engine/async_llm_engine.py", line 70, in _log_task_completion
    raise AsyncEngineDeadError(
vllm.engine.async_llm_engine.AsyncEngineDeadError: Task finished unexpectedly. This should never happen! Please open an issue on Github. See stack trace above for the actual cause.

Before submitting a new issue...

  • Make sure you already searched for relevant issues, and asked the chatbot living at the bottom right corner of the documentation page, which can answer lots of frequently asked questions.
@RunningLeon RunningLeon added the bug Something isn't working label Feb 14, 2025
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
bug Something isn't working
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
1 participant
@RunningLeon