I am running ray in a python script on a node on a GCP cluster.
I get the following error message:
WARNING services.py:2002 – WARNING: The object store is using /tmp instead of /dev/shm because /dev/shm has only 67108864 bytes available. This will harm performance! You may be able to free up space by deleting files in /dev/shm. If you are inside a Docker container, you can increase /dev/shm size by passing ‘–shm-size=5.03gb’ to ‘docker run’ (or add it to the run_options list in a Ray cluster config). Make sure to set this to more than 30% of available RAM.
67108864 bytes of memory seem to be sufficient however. I don’t have control over the arguments passed to “docker run” in this environment but I can configure the docker files that created the images I am running. Is there a way to pass this argument ‘–shm-size=5.03gb’ INSIDE the Dockerfile?