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Is there any error in the stdout/stderr of sb deploy?
As shown in the output of sb run, seems there's no CUDA GPUs found in container, can you also check whether both /dev/nvidiactl and /dev/nvidia-uvm exist in the host?
Is there any error in the stdout/stderr of sb deploy?
As shown in the output of sb run, seems there's no CUDA GPUs found in container, can you also check whether both /dev/nvidiactl and /dev/nvidia-uvm exist in the host?
There is not error while running sb deploy.
It's all fine now after kill all running cotainers.
What's the issue, what's expected?:
How to reproduce it?:
OS: ubuntu 22.04.02
GPU: GeForce RTX 3060 x1
wget https://github.com/microsoft/superbenchmark/archive/refs/tags/v0.8.0.tar.gz
tar xf v0.8.0.tar.gz
cd superbenchmark-0.8.0/
python3 -m venv --system-site-packages ./venv
source ./venv/bin/activate
python3 -m pip install .
python3 -m pip install --upgrade pip setuptools==65.7
make postinstall
cp superbench/config/default.yaml sb.yaml # and change the proc_num: 8 to proc_num: 1
nano local.ini
set +H
sb deploy -f local.ini --host-password=mysshpassword
docker images # check docker images
REPOSITORY TAG IMAGE ID CREATED SIZE
superbench/superbench latest 36fe2cd49200 2 hours ago 19.5GB
docker run -it --rm --gpus all -e NVIDIA_VISIBLE_DEVICES=0 --shm-size=1g --ulimit memlock=-1 superbench/superbench
nvidia-smi #it works.
exit
sb run -f local.ini -c sb.yaml --host-password=mysshpassword
Log message or shapshot?:
see attached
Additional information:
2023-04-14_19-16-21.tar.gz
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