Cuda failure 'peer access is not supported between these two devices'

[colorzhang]

Usage stats collection is enabled. To disable this, run the following command: ray disable-usage-stats before starting Ray. See https://docs.ray.io/en/master/cluster/usage-stats.html for more details.
2023-07-08 23:11:34,236 INFO worker.py:1610 -- Started a local Ray instance. View the dashboard at 127.0.0.1:8265
INFO 07-08 23:11:35 llm_engine.py:60] Initializing an LLM engine with config: model='openlm-research/open_llama_13b', tokenizer='openlm-research/open_llama_13b', tokenizer_mode=auto, dtype=torch.float16, use_dummy_weights=False, download_dir=None, use_np_weights=False, tensor_parallel_size=4, seed=0)
INFO 07-08 23:11:35 tokenizer.py:28] For some LLaMA-based models, initializing the fast tokenizer may take a long time. To eliminate the initialization time, consider using 'hf-internal-testing/llama-tokenizer' instead of the original tokenizer.
(Worker pid=4225) Exception raised in creation task: The actor died because of an error raised in its creation task, ray::Worker.init() (pid=4225, ip=172.31.68.176, actor_id=5dc662848f950df8d330eb8a01000000, repr=<vllm.worker.worker.Worker object at 0x7f4e9ea814e0>)
(Worker pid=4225) File "/opt/conda/lib/python3.10/site-packages/vllm/worker/worker.py", line 40, in init
(Worker pid=4225) _init_distributed_environment(parallel_config, rank,
(Worker pid=4225) File "/opt/conda/lib/python3.10/site-packages/vllm/worker/worker.py", line 307, in _init_distributed_environment
(Worker pid=4225) torch.distributed.all_reduce(torch.zeros(1).cuda())
(Worker pid=4225) File "/opt/conda/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1451, in wrapper
(Worker pid=4225) return func(*args, **kwargs)
(Worker pid=4225) File "/opt/conda/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1700, in all_reduce
(Worker pid=4225) work = default_pg.allreduce([tensor], opts)
(Worker pid=4225) torch.distributed.DistBackendError: NCCL error in: ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1275, internal error, NCCL version 2.14.3
(Worker pid=4225) ncclInternalError: Internal check failed.
(Worker pid=4225) Last error:
(Worker pid=4225) Cuda failure 'peer access is not supported between these two devices'

Code:
llm = LLM(model="openlm-research/open_llama_13b", tensor_parallel_size=4)

Env:
Single EC2 instance G5.12xlarge with 4 A10G GPU

[ai8hyf]

I run into the same issue on a G5.12xlarge instance for WizardLM-30b-fp16

[mspronesti]

export NCCL_IGNORE_DISABLED_P2P=1 did the trick for me.
I wanted to open a PR to do this by default as I believe it would fix this issue without affecting the distributed inference when P2P is enabled . Any thoughts ?

[nivibilla]

I get this error even with trying the workaround mentioned by @mspronesti. Interestingly with the same G5.12xlarge instance

[mspronesti]

@nivibilla I tried the above workaround in a notebook g5.12xlarge instance in SageMaker and It worked for me. I also tried reinstalling vllm from source adding os.environ["NCCL_IGNORE_DISABLED_P2P"] = '1' in the codebase just before this line and it worked again. I guess you tried on a EC2 VM. Can you try the second way ?

steps

• clone the project
• Add the following before this line
  (Import os also)

os.environ["NCCL_IGNORE_DISABLED_P2P"] = '1'

• pip install .
• run again your distributed inference

[zhuohan123]

Thanks for reporting the issue! This should be fixed by #397. It should be merged soon. You can retry with this fix.

[zhuohan123]

Should be fixed by #397. Please re-open if you meet any new issues.

[nivibilla]

@zhuohan123 Sorry for the delayed response, I will test this out thanks!

[Tarun3679]

@mspronesti I tried adding the step in source and doing the pip install, However I am getting the following error - AttributeError: 'NoneType' object has no attribute 'fs'. Is there any other way to solve this issue?

[nivibilla]

I've tried with installing from the git with pip. And it works for me

[Tarun3679]

@nivibilla, So basically you cloned the git repo. And then did the change and used pip install command to build it! Correct? Could you share you're existing versions and the worker.py file? I tried the same. But it doesn't work.

[nivibilla]

I didn't make any changes to the repo

Just do

pip install git+https://github.com/vllm-project/vllm.git