[Bug]: ZMQError: Address already in use (addr='tcp://127.0.0.1:5570')
WMeng1 opened this issue · 14 comments
WMeng1 commented
Your current environment
PyTorch version: 2.4.0+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A
OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0
Clang version: 10.0.0-4ubuntu1
CMake version: version 3.30.0
Libc version: glibc-2.31
Python version: 3.11.9 (main, Apr 19 2024, 16:48:06) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.4.0-187-generic-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: 10.1.243
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration:
GPU 0: Tesla V100-SXM2-32GB
GPU 1: Tesla V100-SXM2-32GB
GPU 2: Tesla V100-SXM2-32GB
GPU 3: Tesla V100-SXM2-32GB
GPU 4: Tesla V100-SXM2-32GB
GPU 5: Tesla V100-SXM2-32GB
GPU 6: Tesla V100-SXM2-32GB
GPU 7: Tesla V100-SXM2-32GB
Nvidia driver version: 535.183.01
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
Byte Order: Little Endian
Address sizes: 46 bits physical, 48 bits virtual
CPU(s): 64
On-line CPU(s) list: 0-63
Thread(s) per core: 2
Core(s) per socket: 16
Socket(s): 2
NUMA node(s): 2
Vendor ID: GenuineIntel
CPU family: 6
Model: 85
Model name: Intel(R) Xeon(R) Gold 6226R CPU @ 2.90GHz
Stepping: 7
CPU MHz: 1200.045
CPU max MHz: 3900.0000
CPU min MHz: 1200.0000
BogoMIPS: 5800.00
Virtualization: VT-x
L1d cache: 1 MiB
L1i cache: 1 MiB
L2 cache: 32 MiB
L3 cache: 44 MiB
NUMA node0 CPU(s): 0-15,32-47
NUMA node1 CPU(s): 16-31,48-63
Vulnerability Gather data sampling: Mitigation; Microcode
Vulnerability Itlb multihit: KVM: Mitigation: Split huge pages
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Retbleed: Mitigation; Enhanced IBRS
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; BHI Vulnerable, KVM SW loop
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Mitigation; TSX disabled
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 cdp_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req pku ospke avx512_vnni md_clear flush_l1d arch_capabilities
Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] nvidia-nccl-cu12==2.20.5
[pip3] torch==2.4.0
[pip3] torchvision==0.19.0
[pip3] transformers==4.43.3
[conda] numpy 1.26.4 pypi_0 pypi
[conda] nvidia-nccl-cu12 2.20.5 pypi_0 pypi
[conda] torch 2.4.0 pypi_0 pypi
[conda] torchvision 0.19.0 pypi_0 pypi
[conda] transformers 4.43.3 pypi_0 pypi
[conda] triton 2.3.1 pypi_0 pypi
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.5.4
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0 GPU1 GPU2 GPU3 GPU4 GPU5 GPU6 GPU7 NIC0 NIC1 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X NV2 NV2 NV1 NV1 SYS SYS SYS SYS SYS 0-15,32-47 0 N/A
GPU1 NV2 X NV1 NV1 SYS NV2 SYS SYS SYS SYS 0-15,32-47 0 N/A
GPU2 NV2 NV1 X NV2 SYS SYS NV1 SYS SYS SYS 0-15,32-47 0 N/A
GPU3 NV1 NV1 NV2 X SYS SYS SYS NV2 SYS SYS 0-15,32-47 0 N/A
GPU4 NV1 SYS SYS SYS X NV2 NV2 NV1 PIX PIX 16-31,48-63 1 N/A
GPU5 SYS NV2 SYS SYS NV2 X NV1 NV1 PIX PIX 16-31,48-63 1 N/A
GPU6 SYS SYS NV1 SYS NV2 NV1 X NV2 PIX PIX 16-31,48-63 1 N/A
GPU7 SYS SYS SYS NV2 NV1 NV1 NV2 X PIX PIX 16-31,48-63 1 N/A
NIC0 SYS SYS SYS SYS PIX PIX PIX PIX X PIX
NIC1 SYS SYS SYS SYS PIX PIX PIX PIX PIX 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_0
NIC1: mlx5_1
🐛 Describe the bug
export CUDA_VISIBLE_DEVICES=1
nohup python -m vllm.entrypoints.openai.api_server \
--model /PROJECT/model/1/ \
--trust_remote_code \
--dtype half \
--host 127.0.0.1 \
--port 8000 \
--tensor-parallel-size 1 > 1_vllm.log 2>&1 &
sleep 10
export CUDA_VISIBLE_DEVICES=3
nohup python -m vllm.entrypoints.openai.api_server \
--model /PROJECT/model/2/ \
--trust_remote_code \
--dtype half \
--host 127.0.0.1 \
--port 8003 \
--tensor-parallel-size 1 > 2_vllm.log 2>&1 &
when I bash xxx.sh like this, the first server start successful. But the second will break and error message is:
Traceback (most recent call last):
File "/usr/lib/python3.10/multiprocessing/process.py", line 314, in _bootstrap
self.run()
File "/usr/lib/python3.10/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/openai/rpc/server.py", line 217, in run_rpc_server
server = AsyncEngineRPCServer(async_engine_args, usage_context, port)
File "/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/openai/rpc/server.py", line 35, in __init__
self.socket.bind(f"tcp://127.0.0.1:{port}")
File "/usr/local/lib/python3.10/dist-packages/zmq/sugar/socket.py", line 311, in bind
super().bind(addr)
File "_zmq.py", line 917, in zmq.backend.cython._zmq.Socket.bind
File "_zmq.py", line 179, in zmq.backend.cython._zmq._check_rc
zmq.error.ZMQError: Address already in use (addr='tcp://127.0.0.1:5570')
I'm not sure where the problem is, maybe at line 110 here? vllm/entrypoints/openai/rpc/server.py line:110
port = get_open_port(envs.VLLM_RPC_PORT)?
robertgshaw2-redhat commented
So you have two versions of vllm running on the same machine?
robertgshaw2-redhat commented
I will look into this
robertgshaw2-redhat commented
In the meantime, you can fall back to the old front end by running with --disable-frontend-multiprocessing
ccdv-ai commented
Got the same problem, came with ZMQ integration.
robertgshaw2-redhat commented
@ccdv-ai can you share any additional information about your setup?
Also - does --disable-frontend-multiprocessing solve your issue for now?
ccdv-ai commented
tested with v5.4.0, 4 x L40
python -u -m vllm.entrypoints.openai.api_server \
--host 0.0.0.0 \
--model models/Mistral-Large-Instruct-2407-AWQ \
--dtype "auto" \
--port 8000 \
--seed 123 \
--max-model-len 32768 \
--gpu-memory-utilization 0.90 \
--tensor-parallel-size 4 \
--max-num-seqs 32 \
--use-v2-block-manager \
--max-log-len 20 \
--enforce-eager \
--served-model-name mistral
Have to change the port each time I kill the vllm server because the port isn't released.
Can't test the --disable-frontend-multiprocessing command right now but pretty sure it came with #6883 .
I built the package from source 1 week ago and it was working.
Also got a ZMQError: Too many open files error once, will probably open another issue.
No problem with v5.3.post1
robertgshaw2-redhat commented
@ccdv-ai are you setting any environment variables? I have been unable to reproduce your issue so far
robertgshaw2-redhat commented
Specifically, did you set VLLM_PORT or VLLM_RPC_PORT?
robertgshaw2-redhat commented
This will resolve any issues associated with setting VLLM_PORT -> #7205
robertgshaw2-redhat commented
@WMeng1 I have reproduced your report. Working on a fix.
youkaichao commented
fixed by #7205
robertgshaw2-redhat commented
Needs #7222 to land.
robertgshaw2-redhat commented
Closing because #7222 landed
Deleted user commented
Hi guys, is this fix already in dockerhub?
I am still getting this error using https://hub.docker.com/layers/vllm/vllm-openai/v0.5.4/images/sha256-7ab0cf7b287876cec65752a1b7ac99790ecd2a609da80c4d1dd1fbeaf987abf6?context=explore image