docker: Error response from daemon: OCI runtime create failed: unable to retrieve OCI runtime error (open /run/containerd/io.containerd.runtime.v1.linux/moby/761bd05e8ceb95e1459db860b160e9dda095254a969ebd9a0b777524f73f9263/log.json: no such file or directory): exec: "nvidia-container-runtime": executable file not found in $PATH: unknown.

[wjimenez5271]

When following the latest instructions to install the nvidia driver on https://github.com/NVIDIA/nvidia-docker/, it says that nvidia-docker2 has been deprecated and one should install the nvidia container toolkit. I followed the instructions for Ubuntu 18.04 with Docker 19.03, however this does not seem to install the nvidia-container-runtime binary mentioned in the README for this project. This results in the docker not being able to start any container after updating the default runtime per the README in /etc/docker/daemon.json. Is this device plugin not compatible with the latest iteration of the nvidia driver? Here is the error message:

docker: Error response from daemon: OCI runtime create failed: unable to retrieve OCI runtime error (open /run/containerd/io.containerd.runtime.v1.linux/moby/761bd05e8ceb95e1459db860b160e9dda095254a969ebd9a0b777524f73f9263/log.json: no such file or directory): exec: "nvidia-container-runtime": executable file not found in $PATH: unknown.

and just to show:

ls /usr/bin/nvidia-container-runtime
ls: cannot access '/usr/bin/nvidia-container-runtime': No such file or directory

I also tried nvidia-container-cli as this is installed by the current package. Is it possible this repo needs to be updated to reflect nvidia-docker2's deprecation?

[ardenpm]

The docs in this repo specifically state that nvidia-container-toolkit should not be used and that nvidia-docker2 should be used instead (even though deprecated) since K8s isn't aware of the --gpus Docker flag yet (not sure if that is still the case).

So it looks like the instructions for Docker and K8s are currently different. I setup per the instructions in this repo for K8s but right now I can't run anything in Docker so I doubt it will work in K8s. When I try to run with the nvidia runtime I get segfaults immediately. Still trying to track that down.

[klueska]

I agree, the docs are confusing and should be synchronized better.

Please see my comment here for an explanation on how nvidia-docker2 and nvidia-container-toolkit are related: https://github.com/NVIDIA/k8s-device-plugin/issues/168#issuecomment-625981223

Regarding the segfault, I'm curious if it could be related to: https://github.com/NVIDIA/nvidia-docker/issues/1280#issuecomment-630754999

[ardenpm]

Indeed, that comment helped make it clear. It was also reassuring to know that basically behind the scenes its basically the same since the deprecation statements on nvidia-docker2 are a bit disconcerting.

Now on the segfault, this was/is really strange. I think mine was actually different to the one in this issue. nvidia-container-cli also would segfault immediately even just using the info commands, so I don’t think it was specific to docker.

All of my testing there was on CentOS 7 latest and I wasn’t able to resolve the problem. Since I needed to do some testing I switched to Ubuntu 18.04 and was not able to replicate the issue there at all.

I still have both images in a stopped state on AWS from my testing so I can probably get more details on the actual segfault stack trace but I am not sure if others are encountering this. The actual error was related to munmap_chunk: invalid pointer.

[kengz]

I had the same issue setting up a k8s cluster with GPUs. Went through the comments here and other related issues, and put together the steps to make it work, probably useful to people looking for solution:

Kubernetes NVIDIA GPU device plugin

• follow the official NVIDIA GPU device plugin until the step to configure runtime

• as explained in this comment, k8s still needs nvidia-container-runtime; install it:

  # install the old nvidia-container-runtime for k8s
  curl -s -L https://nvidia.github.io/nvidia-container-runtime/gpgkey | \
    sudo apt-key add -
  distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
  curl -s -L https://nvidia.github.io/nvidia-container-runtime/$distribution/nvidia-container-runtime.list | \
    sudo tee /etc/apt/sources.list.d/nvidia-container-runtime.list
  sudo apt-get update
  sudo apt-get install -y nvidia-container-runtime
  

• add the following /etc/docker/daemon.json as required by k8s

  {
      "default-runtime": "nvidia",
      "runtimes": {
          "nvidia": {
              "path": "/usr/bin/nvidia-container-runtime",
              "runtimeArgs": []
          }
      }
  }
  

• restart docker and test:

  sudo systemctl restart docker
  # test that docker can run with GPU without the --gpus flag
  docker run nvidia/cuda:10.2-runtime-ubuntu18.04 nvidia-smi
  

• finally, install the NVIDIA device plugin on your cluster:

  kubectl create -f https://raw.githubusercontent.com/NVIDIA/k8s-device-plugin/1.0.0-beta4/nvidia-device-plugin.yml
  

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