Docker is unable to access GPU in LXC GPU Passthrough

M

mr-biz

New Member
Sep 4, 2021
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Hardware:
Mobo = Intel® Server Board S2600CW2R
Processors = 2x E-2650L
Ram = 256GB
PVE = 7.4-3

GPU driver = ./NVIDIA-Linux-x86_64-530.30.02.run (--no-kernel-module in LXCs)

I am successfully passing through a RTX-3060 to multiple LXCs and using them.
However, I get errors if I install Docker and the NVIDIA Container Toolkit in the LXC.
I tried installing Docker and NVIDIA Container Toolkit on the host with no errors [now uninstalled since not supported ;)]

I am most grateful for any assistance in advance!

root@pve001:~# cat /etc/pve/lxc/125.conf # Allow cgroup access # Pass through device files #lxc.mount.entry%3A /dev/nvidia1 dev/nvidia1 none bind,optional,create=file arch: amd64 cores: 4 features: nesting=1 hostname: docker-cuda memory: 8192 nameserver: 1.1.1.1 net0: name=eth0,bridge=vmbr0,firewall=1,gw=192.168.1.1,hwaddr=32:D4:08:14:FA:98,ip=192.168.1.251/24,type=veth ostype: debian rootfs: local:125/vm-125-disk-0.raw,size=50G swap: 8192 unprivileged: 1 lxc.cgroup.devices.allow: c 80:* rwm lxc.cgroup.devices.allow: c 195:* rwm lxc.cgroup.devices.allow: c 254:* rwm lxc.cgroup.devices.allow: c 255:* rwm lxc.cgroup.devices.allow: c 508:* rwm lxc.cgroup.devices.allow: c 0:* rwm lxc.cgroup.devices.allow: c 1:* rwm lxc.mount.entry: /dev/nvidia0 dev/nvidia0 none bind,optional,create=file lxc.mount.entry: /dev/nvidia-caps dev/nvidia-caps none bind,optional,create=file lxc.mount.entry: /dev/nvidiactl dev/nvidiactl none bind,optional,create=file lxc.mount.entry: /dev/nvidia-modeset dev/nvidia-modeset none bind,optional,create=file lxc.mount.entry: /dev/nvidia-uvm dev/nvidia-uvm none bind,optional,create=file lxc.mount.entry: /dev/nvidia-uvm-tools dev/nvidia-uvm-tools none bind,optional,create=file

root@docker-cuda:~# nvidia-smi Thu Mar 30 12:47:34 2023 +---------------------------------------------------------------------------------------+ | NVIDIA-SMI 530.30.02 Driver Version: 530.30.02 CUDA Version: 12.1 | |-----------------------------------------+----------------------+----------------------+ | 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 NVIDIA GeForce RTX 3060 Off| 00000000:83:00.0 Off | N/A | | 71% 63C P2 50W / 170W| 2957MiB / 12288MiB | 0% Default | | | | N/A | +-----------------------------------------+----------------------+----------------------+ +---------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=======================================================================================| +---------------------------------------------------------------------------------------+

root@docker-cuda:~# sudo docker run --rm --runtime=nvidia --gpus all nvidia/cuda:11.6.2-base-ubuntu20.04 nvidia-smi docker: Error response from daemon: failed to create shim task: OCI runtime create failed: runc create failed: unable to start container process: error during container init: error running hook #0: error running hook: exit status 1, stdout: , stderr: Auto-detected mode as 'legacy' nvidia-container-cli: mount error: failed to add device rules: unable to find any existing device filters attached to the cgroup: bpf_prog_query(BPF_CGROUP_DEVICE) failed: operation not permitted: unknown.
 
Running Docker in a container is not recommended at all due to the way LXC uses layered filesystems (which Docker does also). Sure, there certainly are ways to get it to work, but it's just not worth the hassle and might just subtly break in certain situations, as you have already discovered.

Instead, we recommend running Docker inside a VM; to quote our documentation:
If you want to run application containers, for example, Docker images, it is recommended that you run them inside a Proxmox QEMU VM. This will give you all the advantages of application containerization, while also providing the benefits that VMs offer, such as strong isolation from the host and the ability to live-migrate, which otherwise isn’t possible with containers.
Click to expand...
 
@mr-biz runtime is depreciated in your docker command, as far as i remember.

Try a docker compose file, this is a minimal version that works for me

Code: 
version: "3.7"
services:
  test:
    image: nvidia/cuda:10.2-base
    command: nvidia-smi
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]
 
mr-biz said:
Hardware:
Mobo = Intel® Server Board S2600CW2R
Processors = 2x E-2650L
Ram = 256GB
PVE = 7.4-3

GPU driver = ./NVIDIA-Linux-x86_64-530.30.02.run (--no-kernel-module in LXCs)

I am successfully passing through a RTX-3060 to multiple LXCs and using them.
However, I get errors if I install Docker and the NVIDIA Container Toolkit in the LXC.
I tried installing Docker and NVIDIA Container Toolkit on the host with no errors [now uninstalled since not supported ;)]

I am most grateful for any assistance in advance!

root@pve001:~# cat /etc/pve/lxc/125.conf # Allow cgroup access # Pass through device files #lxc.mount.entry%3A /dev/nvidia1 dev/nvidia1 none bind,optional,create=file arch: amd64 cores: 4 features: nesting=1 hostname: docker-cuda memory: 8192 nameserver: 1.1.1.1 net0: name=eth0,bridge=vmbr0,firewall=1,gw=192.168.1.1,hwaddr=32:D4:08:14:FA:98,ip=192.168.1.251/24,type=veth ostype: debian rootfs: local:125/vm-125-disk-0.raw,size=50G swap: 8192 unprivileged: 1 lxc.cgroup.devices.allow: c 80:* rwm lxc.cgroup.devices.allow: c 195:* rwm lxc.cgroup.devices.allow: c 254:* rwm lxc.cgroup.devices.allow: c 255:* rwm lxc.cgroup.devices.allow: c 508:* rwm lxc.cgroup.devices.allow: c 0:* rwm lxc.cgroup.devices.allow: c 1:* rwm lxc.mount.entry: /dev/nvidia0 dev/nvidia0 none bind,optional,create=file lxc.mount.entry: /dev/nvidia-caps dev/nvidia-caps none bind,optional,create=file lxc.mount.entry: /dev/nvidiactl dev/nvidiactl none bind,optional,create=file lxc.mount.entry: /dev/nvidia-modeset dev/nvidia-modeset none bind,optional,create=file lxc.mount.entry: /dev/nvidia-uvm dev/nvidia-uvm none bind,optional,create=file lxc.mount.entry: /dev/nvidia-uvm-tools dev/nvidia-uvm-tools none bind,optional,create=file

root@docker-cuda:~# nvidia-smi Thu Mar 30 12:47:34 2023 +---------------------------------------------------------------------------------------+ | NVIDIA-SMI 530.30.02 Driver Version: 530.30.02 CUDA Version: 12.1 | |-----------------------------------------+----------------------+----------------------+ | 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 NVIDIA GeForce RTX 3060 Off| 00000000:83:00.0 Off | N/A | | 71% 63C P2 50W / 170W| 2957MiB / 12288MiB | 0% Default | | | | N/A | +-----------------------------------------+----------------------+----------------------+ +---------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=======================================================================================| +---------------------------------------------------------------------------------------+

root@docker-cuda:~# sudo docker run --rm --runtime=nvidia --gpus all nvidia/cuda:11.6.2-base-ubuntu20.04 nvidia-smi docker: Error response from daemon: failed to create shim task: OCI runtime create failed: runc create failed: unable to start container process: error during container init: error running hook #0: error running hook: exit status 1, stdout: , stderr: Auto-detected mode as 'legacy' nvidia-container-cli: mount error: failed to add device rules: unable to find any existing device filters attached to the cgroup: bpf_prog_query(BPF_CGROUP_DEVICE) failed: operation not permitted: unknown.
Click to expand...
I know it's best to run docker in a VM, and maybe someday I will switch to kubernetes or something in a vm, but for now I found the solution to this:

set “no-cgroups = true” in the Nvidia docker config file. /etc/nvidia-container-runtime/config.toml
Click to expand...

source: https://discuss.linuxcontainers.org/t/how-to-build-nvidia-docker-inside-lxd-lxc-container/17582/5
 
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