vLLM Distributed Inference stuck when using multi -GPU

[RathoreShubh]

I am trying to run inferece server on multi GPU using this on (4 * NVIDIA GeForce RTX 3090) server.

python -u -m vllm.entrypoints.api_server --host 0.0.0.0 --model mistralai/Mistral-7B-Instruct-v0.2 --tensor-parallel-size 4

while this works fine when using --tensor-parallel-size =1 , but on using tensor-parallel-size >1 it stuck on strat up.

Thanks

[RhizoNymph]

this is happening to me too, on 2 * 3090

[s-natsubori]

try these parameters
--gpu-memory-utilization 0.7~0.9
--max-model-len 8192

[Double-bear]

try these parameters --gpu-memory-utilization 0.7~0.9 --max-model-len 8192

hello, I have tried the method you provided, but it has no effect.

[RhizoNymph]

No effect here either

[BilalKHA95]

Did you found a solution i Ve the same issue ?

[shubham-bnxt]

@BilalKHA95 try this

export NCCL_P2P_DISABLE=1

this woked for me

[BilalKHA95]

@BilalKHA95 try this

export NCCL_P2P_DISABLE=1

this woked for me

Thank's !!! it's working now, this env variable + update cuda tooltik to 12.3

[Palmik]

export NCCL_P2P_DISABLE=1

This also solved this issue for me.

[emersonium]

@BilalKHA95 try this
export NCCL_P2P_DISABLE=1
this woked for me

Thank's !!! it's working now, this env variable + update cuda tooltik to 12.3

Hi!
does this result in higher tokens/second for you ? (for a small model like: -model mistralai/Mistral-7B-Instruct-v0.2 --tensor-parallel-size 4) ? thanks!

[SuperBruceJia]

This didn't work for me:

export NCCL_P2P_DISABLE=1

Is there any solutions?

Thank you guys very much in advance!

Best regards,

Shuyue
June 9th, 2024

[DarkLight1337]

We have added documentation for this situation in #5430. Please take a look.