Closed
Description
Your current environment
The output of `python collect_env.py`
Your output of `python collect_env.py` here
Collecting environment information...
PyTorch version: 2.6.0+cu124
Is debug build: False
CUDA used to build PyTorch: 12.4
ROCM used to build PyTorch: N/A
OS: AlmaLinux 9.5 (Teal Serval) (x86_64)
GCC version: (GCC) 11.5.0 20240719 (Red Hat 11.5.0-5)
Clang version: 18.1.8 (AlmaLinux OS Foundation 18.1.8-3.el9)
CMake version: version 3.26.5
Libc version: glibc-2.34
Python version: 3.11.11 (main, Apr 9 2025, 20:12:22) [GCC 11.5.0 20240719 (Red Hat 11.5.0-5)] (64-bit runtime)
Python platform: Linux-5.14.0-503.11.1.el9_5.x86_64-x86_64-with-glibc2.34
Is CUDA available: True
CUDA runtime version: 12.4.99
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration:
GPU 0: Tesla V100-PCIE-32GB
GPU 1: Tesla V100-PCIE-32GB
GPU 2: Tesla V100-PCIE-32GB
GPU 3: Tesla V100-PCIE-32GB
Nvidia driver version: 550.144.03
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): 96
On-line CPU(s) list: 0-95
Vendor ID: GenuineIntel
Model name: Intel(R) Xeon(R) Gold 5318Y CPU @ 2.10GHz
CPU family: 6
Model: 106
Thread(s) per core: 2
Core(s) per socket: 24
Socket(s): 2
Stepping: 6
CPU(s) scaling MHz: 95%
CPU max MHz: 3400.0000
CPU min MHz: 800.0000
BogoMIPS: 4200.00
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 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 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid 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 wbnoinvd dtherm ida arat pln pts vnmi avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid fsrm md_clear pconfig flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 2.3 MiB (48 instances)
L1i cache: 1.5 MiB (48 instances)
L2 cache: 60 MiB (48 instances)
L3 cache: 72 MiB (2 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0-23,48-71
NUMA node1 CPU(s): 24-47,72-95
Vulnerability Gather data sampling: Mitigation; Microcode
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Versions of relevant libraries:
[pip3] numpy==2.1.3
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-cusparselt-cu12==0.6.2
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] torch==2.6.0
[pip3] torchaudio==2.6.0
[pip3] torchvision==0.21.0
[pip3] triton==3.2.0
[conda] Could not collect
🐛 Describe the bug
Run vllm/examples/offline_inference/data_parallel.py on 2 nodes, change the model to Qwen1.5-MoE-A2.7B. Follow the Multi-node Usage. I change the dtype to "float32" because V100 is not support for "bp16".
Master-node ouput:
INFO 11-21 08:53:08 [__init__.py:239] Automatically detected platform cuda.
[<Process name='Process-1' pid=1971252 parent=1971183 started>]
DP rank 0 needs to process 200 prompts
INFO 11-21 08:53:09 [config.py:2696] Upcasting torch.bfloat16 to torch.float32.
INFO 11-21 08:53:16 [config.py:600] This model supports multiple tasks: {'score', 'embed', 'generate', 'reward', 'classify'}. Defaulting to 'generate'.
WARNING 11-21 08:53:16 [arg_utils.py:1708] Compute Capability < 8.0 is not supported by the V1 Engine. Falling back to V0.
INFO 11-21 08:53:16 [config.py:1600] Defaulting to use mp for distributed inference
WARNING 11-21 08:53:16 [cuda.py:96] To see benefits of async output processing, enable CUDA graph. Since, enforce-eager is enabled, async output processor cannot be used
INFO 11-21 08:53:16 [llm_engine.py:242] Initializing a V0 LLM engine (v0.8.3) with config: model='/home/share/bz/model/Qwen1.5-MoE-A2.7B', speculative_config=None, tokenizer='/home/share/bz/model/Qwen1.5-MoE-A2.7B', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, override_neuron_config=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.float32, max_seq_len=8192, download_dir=None, load_format=LoadFormat.AUTO, tensor_parallel_size=2, pipeline_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, kv_cache_dtype=auto, device_config=cuda, decoding_config=DecodingConfig(guided_decoding_backend='xgrammar', reasoning_backend=None), observability_config=ObservabilityConfig(show_hidden_metrics=False, otlp_traces_endpoint=None, collect_model_forward_time=False, collect_model_execute_time=False), seed=None, served_model_name=/home/share/bz/model/Qwen1.5-MoE-A2.7B, num_scheduler_steps=1, multi_step_stream_outputs=True, enable_prefix_caching=None, chunked_prefill_enabled=False, use_async_output_proc=False, disable_mm_preprocessor_cache=False, mm_processor_kwargs=None, pooler_config=None, compilation_config={"splitting_ops":[],"compile_sizes":[],"cudagraph_capture_sizes":[],"max_capture_size":0}, use_cached_outputs=False,
WARNING 11-21 08:53:17 [multiproc_worker_utils.py:306] Reducing Torch parallelism from 48 threads to 1 to avoid unnecessary CPU contention. Set OMP_NUM_THREADS in the external environment to tune this value as needed.
(VllmWorkerProcess pid=1971322) INFO 11-21 08:53:17 [multiproc_worker_utils.py:225] Worker ready; awaiting tasks
(VllmWorkerProcess pid=1971322) INFO 11-21 08:53:18 [cuda.py:240] Cannot use FlashAttention-2 backend for Volta and Turing GPUs.
(VllmWorkerProcess pid=1971322) INFO 11-21 08:53:18 [cuda.py:289] Using XFormers backend.
INFO 11-21 08:53:18 [cuda.py:240] Cannot use FlashAttention-2 backend for Volta and Turing GPUs.
INFO 11-21 08:53:18 [cuda.py:289] Using XFormers backend.
INFO 11-21 08:53:19 [parallel_state.py:836] Adjusting world_size=4 rank=0 distributed_init_method=tcp://10.0.0.150:13345 for DP
(VllmWorkerProcess pid=1971322) INFO 11-21 08:53:19 [parallel_state.py:836] Adjusting world_size=4 rank=1 distributed_init_method=tcp://10.0.0.150:13345 for DP
INFO 11-21 08:53:29 [utils.py:990] Found nccl from library libnccl.so.2
INFO 11-21 08:53:29 [pynccl.py:69] vLLM is using nccl==2.21.5
(VllmWorkerProcess pid=1971322) INFO 11-21 08:53:29 [utils.py:990] Found nccl from library libnccl.so.2
(VllmWorkerProcess pid=1971322) INFO 11-21 08:53:29 [pynccl.py:69] vLLM is using nccl==2.21.5
INFO 11-21 08:53:29 [custom_all_reduce_utils.py:244] reading GPU P2P access cache from /home/bz/.cache/vllm/gpu_p2p_access_cache_for_0,1.json
(VllmWorkerProcess pid=1971322) INFO 11-21 08:53:29 [custom_all_reduce_utils.py:244] reading GPU P2P access cache from /home/bz/.cache/vllm/gpu_p2p_access_cache_for_0,1.json
INFO 11-21 08:53:29 [shm_broadcast.py:264] vLLM message queue communication handle: Handle(local_reader_ranks=[1], buffer_handle=(1, 4194304, 6, 'psm_066651ed'), local_subscribe_addr='ipc:///tmp/5fb5e506-8394-4d2f-a2e7-f5607fd0e11d', remote_subscribe_addr=None, remote_addr_ipv6=False)
(VllmWorkerProcess pid=1971322) INFO 11-21 08:53:29 [utils.py:990] Found nccl from library libnccl.so.2
(VllmWorkerProcess pid=1971322) INFO 11-21 08:53:29 [pynccl.py:69] vLLM is using nccl==2.21.5
INFO 11-21 08:53:29 [utils.py:990] Found nccl from library libnccl.so.2
INFO 11-21 08:53:29 [pynccl.py:69] vLLM is using nccl==2.21.5
INFO 11-21 08:53:29 [parallel_state.py:957] rank 0 in world size 4 is assigned as DP rank 0, PP rank 0, TP rank 0
(VllmWorkerProcess pid=1971322) INFO 11-21 08:53:29 [parallel_state.py:957] rank 1 in world size 4 is assigned as DP rank 0, PP rank 0, TP rank 1
INFO 11-21 08:53:29 [model_runner.py:1110] Starting to load model /home/share/bz/model/Qwen1.5-MoE-A2.7B...
(VllmWorkerProcess pid=1971322) INFO 11-21 08:53:29 [model_runner.py:1110] Starting to load model /home/share/bz/model/Qwen1.5-MoE-A2.7B...
Loading safetensors checkpoint shards: 0% Completed | 0/8 [00:00<?, ?it/s]
Loading safetensors checkpoint shards: 12% Completed | 1/8 [00:00<00:01, 4.88it/s]
Loading safetensors checkpoint shards: 25% Completed | 2/8 [00:00<00:02, 2.26it/s]
Loading safetensors checkpoint shards: 38% Completed | 3/8 [00:01<00:02, 1.96it/s]
Loading safetensors checkpoint shards: 50% Completed | 4/8 [00:01<00:01, 2.07it/s]
Loading safetensors checkpoint shards: 62% Completed | 5/8 [00:02<00:01, 1.94it/s]
Loading safetensors checkpoint shards: 75% Completed | 6/8 [00:02<00:00, 2.06it/s]
Loading safetensors checkpoint shards: 88% Completed | 7/8 [00:03<00:00, 2.14it/s]
Loading safetensors checkpoint shards: 100% Completed | 8/8 [00:03<00:00, 1.98it/s]
Loading safetensors checkpoint shards: 100% Completed | 8/8 [00:03<00:00, 2.07it/s]
INFO 11-21 08:53:33 [loader.py:447] Loading weights took 3.88 seconds
INFO 11-21 08:53:34 [model_runner.py:1146] Model loading took 15.0978 GiB and 4.073371 seconds
(VllmWorkerProcess pid=1971322) INFO 11-21 08:53:34 [loader.py:447] Loading weights took 4.34 seconds
(VllmWorkerProcess pid=1971322) INFO 11-21 08:53:34 [model_runner.py:1146] Model loading took 15.0978 GiB and 4.530825 seconds
(VllmWorkerProcess pid=1971322) WARNING 11-21 08:56:01 [fused_moe.py:659] Using default MoE config. Performance might be sub-optimal! Config file not found at /home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/model_executor/layers/fused_moe/configs/E=15,N=1408,device_name=Tesla_V100-PCIE-32GB,dtype=float32.json
WARNING 11-21 08:56:01 [fused_moe.py:659] Using default MoE config. Performance might be sub-optimal! Config file not found at /home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/model_executor/layers/fused_moe/configs/E=15,N=1408,device_name=Tesla_V100-PCIE-32GB,dtype=float32.json
(VllmWorkerProcess pid=1971322) INFO 11-21 08:56:09 [worker.py:267] Memory profiling takes 154.44 seconds
(VllmWorkerProcess pid=1971322) INFO 11-21 08:56:09 [worker.py:267] the current vLLM instance can use total_gpu_memory (31.73GiB) x gpu_memory_utilization (0.90) = 28.56GiB
(VllmWorkerProcess pid=1971322) INFO 11-21 08:56:09 [worker.py:267] model weights take 15.10GiB; non_torch_memory takes 0.17GiB; PyTorch activation peak memory takes 1.42GiB; the rest of the memory reserved for KV Cache is 11.87GiB.
INFO 11-21 08:56:09 [worker.py:267] Memory profiling takes 154.47 seconds
INFO 11-21 08:56:09 [worker.py:267] the current vLLM instance can use total_gpu_memory (31.73GiB) x gpu_memory_utilization (0.90) = 28.56GiB
INFO 11-21 08:56:09 [worker.py:267] model weights take 15.10GiB; non_torch_memory takes 0.17GiB; PyTorch activation peak memory takes 1.42GiB; the rest of the memory reserved for KV Cache is 11.87GiB.
INFO 11-21 08:56:09 [executor_base.py:112] # cuda blocks: 4051, # CPU blocks: 1365
INFO 11-21 08:56:09 [executor_base.py:117] Maximum concurrency for 8192 tokens per request: 7.91x
INFO 11-21 08:56:11 [llm_engine.py:448] init engine (profile, create kv cache, warmup model) took 157.32 seconds
Processed prompts: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:07<00:00, 25.83it/s, est. speed input: 142.09 toks/s, output: 404.70 toks/s]
DP rank 0, Prompt: 'Hello, my name is', Generated text: ' Shanna and I have a problem...I LOVE DUMPLINGS! I'
DP rank 0, Prompt: 'The president of the United States is', Generated text: ' the head of state and head of government of the United States of America. The'
DP rank 0, Prompt: 'The capital of France is', Generated text: ' ___________. A. Paris B. Rome C. London D. Madrid\n\n'
DP rank 0, Prompt: 'The future of AI is', Generated text: ' in your hand. For years we have been talking about how AI is going to'
DP rank 0, Prompt: 'Hello, my name is', Generated text: ' Jessica Powell and I am a senior at Central High School. I was born and'
INFO 11-21 08:56:20 [multiproc_worker_utils.py:137] Terminating local vLLM worker processes
(VllmWorkerProcess pid=1971322) INFO 11-21 08:56:20 [multiproc_worker_utils.py:259] Worker exiting
/home/share/bz/software/Python-3.11.11/lib/python3.11/multiprocessing/resource_tracker.py:254: UserWarning: resource_tracker: There appear to be 1 leaked shared_memory objects to clean up at shutdown
warnings.warn('resource_tracker: There appear to be %d '
But when master node run successfully, another node exits unexpectedly. Here is the output of another node.
INFO 04-27 11:16:01 [__init__.py:239] Automatically detected platform cuda.
[<Process name='Process-1' pid=2033693 parent=2033624 started>]
DP rank 1 needs to process 200 prompts
INFO 04-27 11:16:03 [config.py:2696] Upcasting torch.bfloat16 to torch.float32.
INFO 04-27 11:16:11 [config.py:600] This model supports multiple tasks: {'generate', 'reward', 'embed', 'classify', 'score'}. Defaulting to 'generate'.
WARNING 04-27 11:16:11 [arg_utils.py:1708] Compute Capability < 8.0 is not supported by the V1 Engine. Falling back to V0.
INFO 04-27 11:16:11 [config.py:1600] Defaulting to use mp for distributed inference
WARNING 04-27 11:16:11 [cuda.py:96] To see benefits of async output processing, enable CUDA graph. Since, enforce-eager is enabled, async output processor cannot be used
INFO 04-27 11:16:11 [llm_engine.py:242] Initializing a V0 LLM engine (v0.8.3) with config: model='/home/share/bz/model/Qwen1.5-MoE-A2.7B', speculative_config=None, tokenizer='/home/share/bz/model/Qwen1.5-MoE-A2.7B', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, override_neuron_config=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.float32, max_seq_len=8192, download_dir=None, load_format=LoadFormat.AUTO, tensor_parallel_size=2, pipeline_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, kv_cache_dtype=auto, device_config=cuda, decoding_config=DecodingConfig(guided_decoding_backend='xgrammar', reasoning_backend=None), observability_config=ObservabilityConfig(show_hidden_metrics=False, otlp_traces_endpoint=None, collect_model_forward_time=False, collect_model_execute_time=False), seed=None, served_model_name=/home/share/bz/model/Qwen1.5-MoE-A2.7B, num_scheduler_steps=1, multi_step_stream_outputs=True, enable_prefix_caching=None, chunked_prefill_enabled=False, use_async_output_proc=False, disable_mm_preprocessor_cache=False, mm_processor_kwargs=None, pooler_config=None, compilation_config={"splitting_ops":[],"compile_sizes":[],"cudagraph_capture_sizes":[],"max_capture_size":0}, use_cached_outputs=False,
WARNING 04-27 11:16:11 [multiproc_worker_utils.py:306] Reducing Torch parallelism from 48 threads to 1 to avoid unnecessary CPU contention. Set OMP_NUM_THREADS in the external environment to tune this value as needed.
(VllmWorkerProcess pid=2033763) INFO 04-27 11:16:12 [multiproc_worker_utils.py:225] Worker ready; awaiting tasks
(VllmWorkerProcess pid=2033763) INFO 04-27 11:16:13 [cuda.py:240] Cannot use FlashAttention-2 backend for Volta and Turing GPUs.
(VllmWorkerProcess pid=2033763) INFO 04-27 11:16:13 [cuda.py:289] Using XFormers backend.
INFO 04-27 11:16:13 [cuda.py:240] Cannot use FlashAttention-2 backend for Volta and Turing GPUs.
INFO 04-27 11:16:13 [cuda.py:289] Using XFormers backend.
INFO 04-27 11:16:14 [parallel_state.py:836] Adjusting world_size=4 rank=2 distributed_init_method=tcp://10.0.0.150:13345 for DP
(VllmWorkerProcess pid=2033763) INFO 04-27 11:16:14 [parallel_state.py:836] Adjusting world_size=4 rank=3 distributed_init_method=tcp://10.0.0.150:13345 for DP
INFO 04-27 11:16:14 [utils.py:990] Found nccl from library libnccl.so.2
(VllmWorkerProcess pid=2033763) INFO 04-27 11:16:14 [utils.py:990] Found nccl from library libnccl.so.2
INFO 04-27 11:16:14 [pynccl.py:69] vLLM is using nccl==2.21.5
(VllmWorkerProcess pid=2033763) INFO 04-27 11:16:14 [pynccl.py:69] vLLM is using nccl==2.21.5
(VllmWorkerProcess pid=2033763) INFO 04-27 11:16:14 [custom_all_reduce_utils.py:244] reading GPU P2P access cache from /home/bz/.cache/vllm/gpu_p2p_access_cache_for_0,1.json
INFO 04-27 11:16:14 [custom_all_reduce_utils.py:244] reading GPU P2P access cache from /home/bz/.cache/vllm/gpu_p2p_access_cache_for_0,1.json
INFO 04-27 11:16:14 [shm_broadcast.py:264] vLLM message queue communication handle: Handle(local_reader_ranks=[1], buffer_handle=(1, 4194304, 6, 'psm_127351eb'), local_subscribe_addr='ipc:///tmp/1cc65364-0e15-4c3b-97b0-0ef1c6bbccd2', remote_subscribe_addr=None, remote_addr_ipv6=False)
INFO 04-27 11:16:14 [utils.py:990] Found nccl from library libnccl.so.2
(VllmWorkerProcess pid=2033763) INFO 04-27 11:16:14 [utils.py:990] Found nccl from library libnccl.so.2
INFO 04-27 11:16:14 [pynccl.py:69] vLLM is using nccl==2.21.5
(VllmWorkerProcess pid=2033763) INFO 04-27 11:16:14 [pynccl.py:69] vLLM is using nccl==2.21.5
INFO 04-27 11:16:14 [parallel_state.py:957] rank 2 in world size 4 is assigned as DP rank 1, PP rank 0, TP rank 0
(VllmWorkerProcess pid=2033763) INFO 04-27 11:16:14 [parallel_state.py:957] rank 3 in world size 4 is assigned as DP rank 1, PP rank 0, TP rank 1
INFO 04-27 11:16:14 [model_runner.py:1110] Starting to load model /home/share/bz/model/Qwen1.5-MoE-A2.7B...
(VllmWorkerProcess pid=2033763) INFO 04-27 11:16:14 [model_runner.py:1110] Starting to load model /home/share/bz/model/Qwen1.5-MoE-A2.7B...
INFO 04-27 11:18:38 [loader.py:447] Loading weights took 143.16 seconds
(VllmWorkerProcess pid=2033763) INFO 04-27 11:18:38 [loader.py:447] Loading weights took 143.17 seconds
(VllmWorkerProcess pid=2033763) INFO 04-27 11:18:38 [model_runner.py:1146] Model loading took 15.0978 GiB and 143.481158 seconds
INFO 04-27 11:18:38 [model_runner.py:1146] Model loading took 15.0978 GiB and 143.474049 seconds
(VllmWorkerProcess pid=2033763) WARNING 04-27 11:18:46 [fused_moe.py:659] Using default MoE config. Performance might be sub-optimal! Config file not found at /home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/model_executor/layers/fused_moe/configs/E=15,N=1408,device_name=Tesla_V100-PCIE-32GB,dtype=float32.json
WARNING 04-27 11:18:46 [fused_moe.py:659] Using default MoE config. Performance might be sub-optimal! Config file not found at /home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/model_executor/layers/fused_moe/configs/E=15,N=1408,device_name=Tesla_V100-PCIE-32GB,dtype=float32.json
(VllmWorkerProcess pid=2033763) INFO 04-27 11:18:54 [worker.py:267] Memory profiling takes 15.45 seconds
(VllmWorkerProcess pid=2033763) INFO 04-27 11:18:54 [worker.py:267] the current vLLM instance can use total_gpu_memory (31.73GiB) x gpu_memory_utilization (0.90) = 28.56GiB
(VllmWorkerProcess pid=2033763) INFO 04-27 11:18:54 [worker.py:267] model weights take 15.10GiB; non_torch_memory takes 0.17GiB; PyTorch activation peak memory takes 1.42GiB; the rest of the memory reserved for KV Cache is 11.87GiB.
INFO 04-27 11:18:54 [worker.py:267] Memory profiling takes 15.57 seconds
INFO 04-27 11:18:54 [worker.py:267] the current vLLM instance can use total_gpu_memory (31.73GiB) x gpu_memory_utilization (0.90) = 28.56GiB
INFO 04-27 11:18:54 [worker.py:267] model weights take 15.10GiB; non_torch_memory takes 0.17GiB; PyTorch activation peak memory takes 1.42GiB; the rest of the memory reserved for KV Cache is 11.87GiB.
INFO 04-27 11:18:54 [executor_base.py:112] # cuda blocks: 4051, # CPU blocks: 1365
INFO 04-27 11:18:54 [executor_base.py:117] Maximum concurrency for 8192 tokens per request: 7.91x
INFO 04-27 11:18:57 [llm_engine.py:448] init engine (profile, create kv cache, warmup model) took 18.51 seconds
Processed prompts: 7%|██████████▎ | 14/200 [00:07<00:39, 4.74it/s, est. speed input: 9.58 toks/s, output: 24.22 toks/s](VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] Exception in worker VllmWorkerProcess while processing method start_worker_execution_loop.
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] Traceback (most recent call last):
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/executor/multiproc_worker_utils.py", line 232, in _run_worker_process
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] output = run_method(worker, method, args, kwargs)
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/utils.py", line 2347, in run_method
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] return func(*args, **kwargs)
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] ^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/worker/worker_base.py", line 91, in start_worker_execution_loop
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] output = self.execute_model(execute_model_req=None)
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/worker/worker_base.py", line 420, in execute_model
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] output = self.model_runner.execute_model(
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] return func(*args, **kwargs)
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] ^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/worker/model_runner.py", line 1768, in execute_model
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] with set_forward_context(model_input.attn_metadata,
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] File "/home/share/bz/software/Python-3.11.11/lib/python3.11/contextlib.py", line 137, in __enter__
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] return next(self.gen)
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] ^^^^^^^^^^^^^^
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/forward_context.py", line 89, in set_forward_context
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] dist.all_reduce(num_tokens_tensor, group=get_dp_group().cpu_group)
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/torch/distributed/c10d_logger.py", line 81, in wrapper
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] return func(*args, **kwargs)
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] ^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/torch/distributed/distributed_c10d.py", line 2811, in all_reduce
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] work.wait()
(VllmWorkerProcess pid=2033763) ERROR 04-27 11:19:06 [multiproc_worker_utils.py:238] RuntimeError: [/pytorch/third_party/gloo/gloo/transport/tcp/pair.cc:534] Connection closed by peer [202.197.0.150]:50561
Process Process-1:
ERROR 04-27 11:19:07 [multiproc_worker_utils.py:120] Worker VllmWorkerProcess pid 2033763 died, exit code: -15
INFO 04-27 11:19:07 [multiproc_worker_utils.py:124] Killing local vLLM worker processes
Traceback (most recent call last):
File "/home/share/bz/software/Python-3.11.11/lib/python3.11/multiprocessing/process.py", line 314, in _bootstrap
self.run()
File "/home/share/bz/software/Python-3.11.11/lib/python3.11/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "/home/share/bz/vllm/examples/offline_inference/data_parallel.py", line 119, in main
outputs = llm.generate(prompts, sampling_params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/utils.py", line 1131, in inner
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/entrypoints/llm.py", line 465, in generate
outputs = self._run_engine(use_tqdm=use_tqdm)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/entrypoints/llm.py", line 1384, in _run_engine
step_outputs = self.llm_engine.step()
^^^^^^^^^^^^^^^^^^^^^^
File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/engine/llm_engine.py", line 1430, in step
outputs = self.model_executor.execute_model(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/executor/executor_base.py", line 299, in execute_model
driver_outputs = self._driver_execute_model(execute_model_req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/executor/mp_distributed_executor.py", line 144, in _driver_execute_model
return self.driver_worker.execute_model(execute_model_req)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/worker/worker_base.py", line 420, in execute_model
output = self.model_runner.execute_model(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/worker/model_runner.py", line 1768, in execute_model
with set_forward_context(model_input.attn_metadata,
File "/home/share/bz/software/Python-3.11.11/lib/python3.11/contextlib.py", line 137, in __enter__
return next(self.gen)
^^^^^^^^^^^^^^
File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/vllm/forward_context.py", line 89, in set_forward_context
dist.all_reduce(num_tokens_tensor, group=get_dp_group().cpu_group)
File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/torch/distributed/c10d_logger.py", line 81, in wrapper
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/home/share/bz/software/Python-3.11.11/lib/python3.11/site-packages/torch/distributed/distributed_c10d.py", line 2811, in all_reduce
work.wait()
RuntimeError: [/pytorch/third_party/gloo/gloo/transport/tcp/pair.cc:534] Connection closed by peer [202.197.0.150]:60339
Processed prompts: 9%|█████████████▏ | 18/200 [00:10<01:47, 1.69it/s, est. speed input: 12.24 toks/s, output: 32.74 toks/s]
/home/share/bz/software/Python-3.11.11/lib/python3.11/multiprocessing/resource_tracker.py:254: UserWarning: resource_tracker: There appear to be 1 leaked shared_memory objects to clean up at shutdown
warnings.warn('resource_tracker: There appear to be %d '
### Before submitting a new issue...
- [x] Make sure you already searched for relevant issues, and asked the chatbot living at the bottom right corner of the [documentation page](https://docs.vllm.ai/en/latest/), which can answer lots of frequently asked questions.