It is not the final solution for containerized GPU applications.
It is not the final solution for containerized GPU applications.
For distributed training (which Caffe doesn't actually support, not the official version), you would have to run one container per instance, but this is more a configuration problem at the framework level, than a Docker or nvidia-docker problem.
It does strike me as tricky needing to match driver versions between the host and the container. Do you know if there is any effort to eliminate that requirement?
Also while we're chatting, is there any hope of NVIDIA open sourcing their linux drivers? How would such a move affect nvidia-docker?
All the user-level driver-files required for execution are mounted when the container is started using a volume. This way you can deploy the same container on any machine with NVIDIA drivers installed.
We have more details on our wiki: https://github.com/NVIDIA/nvidia-docker/wiki/Internals
Concerning your last question: I don't have any information on this topic, but anyway it would not really impact nvidia-docker.