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第 9 章 使用 vLLM collect 环境脚本收集系统信息

使用您从 Red Hat AI Inference Server 容器运行的 vllm collect-env 命令来收集系统信息，以对 AI Inference Server 部署进行故障排除。此脚本收集系统详情、硬件配置和依赖项信息，以帮助诊断部署问题和模型干扰服务问题。

先决条件

  • 已安装 Podman 或 Docker。
  • 您以具有 sudo 访问权限的用户身份登录。
  • 您可以访问安装了数据中心等级 AI Accelerator 的 Linux 服务器。
  • 您已拉取并成功部署了 Red Hat AI Inference Server 容器。

流程

  1. 打开终端并登录到 registry.redhat.io ： 

    $ podman login registry.redhat.io
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  2. 为已安装的 AI 加速器拉取特定的 Red Hat AI Inference Server 容器镜像。例如，要拉取 Google Cloud TPU 的 Red Hat AI Inference Server 容器，请运行以下命令： 

    $ podman pull registry.redhat.io/rhaiis/vllm-tpu-rhel9:3.2.4
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  3. 在容器中运行 collect 环境脚本： 

    $ podman run --rm -it \
  --name vllm-tpu \
  --network=host \
  --privileged \
  --device=/dev/vfio/vfio \
  --device=/dev/vfio/0 \
  -e PJRT_DEVICE=TPU \
  -e HF_HUB_OFFLINE=0 \
  -v ./.cache/rhaiis:/opt/app-root/src/.cache:Z \
  --entrypoint vllm collect-env \
  registry.redhat.io/rhaiis/vllm-tpu-rhel9:3.2.4
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验证

vllm collect-env 命令输出详情环境信息，包括：

  • 系统硬件详情
  • 操作系统详情
  • Python 环境和依赖项
  • GPU/TPU 加速器信息

查看输出结果中可能指示配置问题的任何警告或错误。在向红帽支持报告问题时，包括您系统的 collect-env 输出。

Google Cloud TPU 报告示例如下： 

==============================
        System Info
==============================
OS                           : Red Hat Enterprise Linux 9.6 (Plow) (x86_64)
GCC version                  : (GCC) 11.5.0 20240719 (Red Hat 11.5.0-5)
Clang version                : Could not collect
CMake version                : version 4.1.0
Libc version                 : glibc-2.34

==============================
       PyTorch Info
==============================
PyTorch version              : 2.9.0.dev20250716
Is debug build               : False
CUDA used to build PyTorch   : None
ROCM used to build PyTorch   : N/A

==============================
      Python Environment
==============================
Python version               : 3.12.9 (main, Jun 20 2025, 00:00:00) [GCC 11.5.0 20240719 (Red Hat 11.5.0-5)] (64-bit runtime)
Python platform              : Linux-6.8.0-1015-gcp-x86_64-with-glibc2.34

==============================
       CUDA / GPU Info
==============================
Is CUDA available            : False
CUDA runtime version         : No CUDA
CUDA_MODULE_LOADING set to   : N/A
GPU models and configuration : No CUDA
Nvidia driver version        : No CUDA
cuDNN version                : No CUDA
HIP runtime version          : N/A
MIOpen runtime version       : N/A
Is XNNPACK available         : True

==============================
          CPU Info
==============================
Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        52 bits physical, 57 bits virtual
Byte Order:                           Little Endian
CPU(s):                               44
On-line CPU(s) list:                  0-43
Vendor ID:                            AuthenticAMD
Model name:                           AMD EPYC 9B14
CPU family:                           25
Model:                                17
Thread(s) per core:                   2
Core(s) per socket:                   22
Socket(s):                            1
Stepping:                             1
BogoMIPS:                             5200.00
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext ssbd ibrs ibpb stibp vmmcall fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves avx512_bf16 clzero xsaveerptr wbnoinvd arat avx512vbmi umip avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq rdpid fsrm
Hypervisor vendor:                    KVM
Virtualization type:                  full
L1d cache:                            704 KiB (22 instances)
L1i cache:                            704 KiB (22 instances)
L2 cache:                             22 MiB (22 instances)
L3 cache:                             96 MiB (3 instances)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-43
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 Reg file data sampling: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Mitigation; Safe RET
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; Retpolines; IBPB conditional; IBRS_FW; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

==============================
Versions of relevant libraries
==============================
[pip3] numpy==1.26.4
[pip3] pyzmq==27.0.1
[pip3] torch==2.9.0.dev20250716
[pip3] torch-xla==2.9.0.dev20250716
[pip3] torchvision==0.24.0.dev20250716
[pip3] transformers==4.55.2
[pip3] triton==3.3.1
[conda] Could not collect

==============================
         vLLM Info
==============================
ROCM Version                 : Could not collect
Neuron SDK Version           : N/A
vLLM Version                 : 0.10.0+rhai1
vLLM Build Flags:
  CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
  Could not collect

==============================
     Environment Variables
==============================
VLLM_USE_V1=1
VLLM_WORKER_MULTIPROC_METHOD=spawn
VLLM_NO_USAGE_STATS=1
NCCL_CUMEM_ENABLE=0
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_default
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