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vllm-project / vllm

A high-throughput and memory-efficient inference and serving engine for LLMs
https://docs.vllm.ai
Apache License 2.0
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[Bug]: vllm 0.4.1 crashing after checking P2P status on single GPU #4587

Open alexandergagliano opened 2 weeks ago

alexandergagliano commented 2 weeks ago

Your current environment

Collecting environment information...
PyTorch version: 2.2.1+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 3.29.2
Libc version: glibc-2.35

Python version: 3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-105-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.3.52
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: GRID A100X-40C
Nvidia driver version: 535.129.03
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:                      40 bits physical, 48 bits virtual
Byte Order:                         Little Endian
CPU(s):                             32
On-line CPU(s) list:                0-31
Vendor ID:                          AuthenticAMD
Model name:                         AMD EPYC-Milan Processor
CPU family:                         25
Model:                              1
Thread(s) per core:                 1
Core(s) per socket:                 1
Socket(s):                          32
Stepping:                           1
BogoMIPS:                           3992.50
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm rep_good nopl cpuid extd_apicid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy svm cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext perfctr_core invpcid_single ssbd ibrs ibpb stibp vmmcall fsgsbase tsc_adjust bmi1 avx2 smep bmi2 invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves clzero xsaveerptr wbnoinvd arat npt lbrv nrip_save tsc_scale vmcb_clean pausefilter pfthreshold umip pku ospke vaes vpclmulqdq rdpid arch_capabilities
Virtualization:                     AMD-V
Hypervisor vendor:                  KVM
Virtualization type:                full
L1d cache:                          1 MiB (32 instances)
L1i cache:                          1 MiB (32 instances)
L2 cache:                           16 MiB (32 instances)
L3 cache:                           1 GiB (32 instances)
NUMA node(s):                       1
NUMA node0 CPU(s):                  0-31
Vulnerability Gather data sampling: Not affected
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 rstack overflow: Mitigation; safe RET
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; Retpolines, IBPB conditional, IBRS_FW, STIBP disabled, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected

Versions of relevant libraries:
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.26.4
[pip3] nvidia-nccl-cu12==2.19.3
[pip3] torch==2.2.1
[pip3] torchaudio==2.2.1
[pip3] torchvision==0.17.1
[pip3] triton==2.2.0
[pip3] vllm-nccl-cu12==2.18.1.0.4.0
[conda] numpy                     1.26.4                   pypi_0    pypi
[conda] nvidia-nccl-cu12          2.19.3                   pypi_0    pypi
[conda] torch                     2.2.1                    pypi_0    pypi
[conda] torchaudio                2.2.1                    pypi_0    pypi
[conda] torchvision               0.17.1                   pypi_0    pypi
[conda] triton                    2.2.0                    pypi_0    pypi
[conda] vllm-nccl-cu12            2.18.1.0.4.0             pypi_0    pypiROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.4.1
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
^[[4mGPU0       CPU Affinity    NUMA Affinity   GPU NUMA ID^[[0m
GPU0     X      0-31    0               N/A

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

🐛 Describe the bug

Thanks for the great code!

I'm getting a strange nccl issue in the latest version of vllm (0.4.1). I had no problems with earlier releases (just confirmed that v0.3.0 runs without issue. From what I can tell of the error message, the code is attempting a peer-to-peer connection, but I'm only running on a single GPU. Running the minimal example above, I get:

(speakYSE) ubuntu@speakyse:/mnt/vol_llm$ python test.py
/mnt/vol_llm/packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
  warnings.warn(
INFO 05-03 16:50:14 llm_engine.py:98] Initializing an LLM engine (v0.4.1) with config: model='facebook/opt-125m', speculative_config=None, tokenizer='facebook/opt-125m', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.float16, max_seq_len=2048, download_dir=None, load_format=auto, tensor_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=False, kv_cache_dtype=auto, quantization_param_path=None, device_config=cuda, decoding_config=DecodingConfig(guided_decoding_backend='outlines'), seed=0)

INFO 05-03 16:50:15 utils.py:608] Found nccl from library /home/ubuntu/.config/vllm/nccl/cu12/libnccl.so.2.18.1
INFO 05-03 16:50:15 selector.py:28] Using FlashAttention backend.
speakyse:3688:3688 [0] NCCL INFO Bootstrap : Using enp1s0:10.1.1.23<0>
speakyse:3688:3688 [0] NCCL INFO NET/Plugin : dlerror=libnccl-net.so: cannot open shared object file: No such file or directory No plugin found (libnccl-net.so), using internal implementation
speakyse:3688:3688 [0] NCCL INFO cudaDriverVersion 12020
NCCL version 2.19.3+cuda12.3
speakyse:3688:3861 [0] NCCL INFO NET/IB : No device found.
speakyse:3688:3861 [0] NCCL INFO NET/Socket : Using [0]enp1s0:10.1.1.23<0> [1]br-febe132fd1d0:172.18.0.1<0>
speakyse:3688:3861 [0] NCCL INFO Using non-device net plugin version 0
speakyse:3688:3861 [0] NCCL INFO Using network Socket

speakyse:3688:3861 [0] misc/nvmlwrap.cc:143 NCCL WARN nvmlDeviceGetP2PStatus(0,0,NVML_P2P_CAPS_INDEX_READ) failed: Invalid Argument
speakyse:3688:3861 [0] NCCL INFO misc/nvmlwrap.cc:181 -> 2
speakyse:3688:3861 [0] NCCL INFO init.cc:351 -> 2
speakyse:3688:3861 [0] NCCL INFO init.cc:1387 -> 2
speakyse:3688:3861 [0] NCCL INFO group.cc:64 -> 2 [Async thread]
speakyse:3688:3688 [0] NCCL INFO group.cc:418 -> 2
speakyse:3688:3688 [0] NCCL INFO group.cc:95 -> 2
Traceback (most recent call last):
  File "/mnt/vol_llm/test.py", line 11, in <module>
    llm = LLM(model="facebook/opt-125m")
  File "/mnt/vol_llm/packages/vllm/entrypoints/llm.py", line 118, in __init__
    self.llm_engine = LLMEngine.from_engine_args(
  File "/mnt/vol_llm/packages/vllm/engine/llm_engine.py", line 277, in from_engine_args
    engine = cls(
  File "/mnt/vol_llm/packages/vllm/engine/llm_engine.py", line 148, in __init__
    self.model_executor = executor_class(
  File "/mnt/vol_llm/packages/vllm/executor/executor_base.py", line 41, in __init__
    self._init_executor()
  File "/mnt/vol_llm/packages/vllm/executor/gpu_executor.py", line 22, in _init_executor
    self._init_non_spec_worker()
  File "/mnt/vol_llm/packages/vllm/executor/gpu_executor.py", line 50, in _init_non_spec_worker
    self.driver_worker.init_device()
  File "/mnt/vol_llm/packages/vllm/worker/worker.py", line 110, in init_device
    init_worker_distributed_environment(self.parallel_config, self.rank,
  File "/mnt/vol_llm/packages/vllm/worker/worker.py", line 313, in init_worker_distributed_environment
    torch.distributed.all_reduce(torch.zeros(1).cuda())
  File "/mnt/vol_llm/packages/torch/distributed/c10d_logger.py", line 72, in wrapper
    return func(*args, **kwargs)
  File "/mnt/vol_llm/packages/torch/distributed/distributed_c10d.py", line 1992, in all_reduce
    work = group.allreduce([tensor], opts)
torch.distributed.DistBackendError: NCCL error in: ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1691, unhandled system error (run with NCCL_DEBUG=INFO for details), NCCL version 2.19.3
ncclSystemError: System call (e.g. socket, malloc) or external library call failed or device error. 
Last error:
nvmlDeviceGetP2PStatus(0,0,NVML_P2P_CAPS_INDEX_READ) failed: Invalid Argument

Any ideas? Thanks!

alexandergagliano commented 2 weeks ago

I'm trying to set up llama3, so I'm hoping not to have to downgrade vllm versions if possible.