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When running the container with podman instead of docker, container is not visible from other devices on the network. This seems to be discussed in upstream project: b-data/data-science-devcontainers#1 b-data/data-science-devcontainers#1 (comment) I'm using CDI.
To Reproduce Steps to reproduce the behavior: Run with: podman run --device nvidia.com/gpu=all -d -it -p 8848:8888 -v $(pwd)/data:/home/jovyan/work -e GRANT_SUDO=yes -e JUPYTER_ENABLE_LAB=yes -e JUPYTER_TOKEN=${JUPYTER_TOKEN} --user root --restart always --name gpu-jupyter cschranz/gpu-jupyter:v1.6_cuda-12.0_ubuntu-22.04
podman run --device nvidia.com/gpu=all -d -it -p 8848:8888 -v $(pwd)/data:/home/jovyan/work -e GRANT_SUDO=yes -e JUPYTER_ENABLE_LAB=yes -e JUPYTER_TOKEN=${JUPYTER_TOKEN} --user root --restart always --name gpu-jupyter cschranz/gpu-jupyter:v1.6_cuda-12.0_ubuntu-22.04
Operating System: RHEL 8
NVIDIA GPU and CUDA version Details:
# nvcc --version nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2023 NVIDIA Corporation Built on Wed_Nov_22_10:17:15_PST_2023 Cuda compilation tools, release 12.3, V12.3.107 Build cuda_12.3.r12.3/compiler.33567101_0 # nvidia-smi Mon Apr 1 12:25:55 2024 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 550.54.14 Driver Version: 550.54.14 CUDA Version: 12.4 | |-----------------------------------------+------------------------+----------------------+ | GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 Tesla P6 Off | 00000000:13:00.0 Off | 0 | | N/A 34C P0 26W / 90W | 8128MiB / 15360MiB | 0% Default | | | | N/A | +-----------------------------------------+------------------------+----------------------+ +-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| | 0 N/A N/A 77564 C /server 8126MiB | +-----------------------------------------------------------------------------------------+
The text was updated successfully, but these errors were encountered:
[...] container is not visible from other devices on the network
Can you curl -v http://127.0.0.1:8848 from the same device (i.e. the container host)?
curl -v http://127.0.0.1:8848
If so, then port 8848 is blocked (firewall?) and this issue is not related to the container.
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Issue Description
When running the container with podman instead of docker, container is not visible from other devices on the network.
This seems to be discussed in upstream project:
b-data/data-science-devcontainers#1
b-data/data-science-devcontainers#1 (comment)
I'm using CDI.
To Reproduce
Steps to reproduce the behavior:
Run with:
podman run --device nvidia.com/gpu=all -d -it -p 8848:8888 -v $(pwd)/data:/home/jovyan/work -e GRANT_SUDO=yes -e JUPYTER_ENABLE_LAB=yes -e JUPYTER_TOKEN=${JUPYTER_TOKEN} --user root --restart always --name gpu-jupyter cschranz/gpu-jupyter:v1.6_cuda-12.0_ubuntu-22.04
Environment
Operating System:
RHEL 8
NVIDIA GPU and CUDA version Details:
The text was updated successfully, but these errors were encountered: