cluster_name: ray-rllib-stress-tests

min_workers: 9
max_workers: 9

idle_timeout_minutes: 15

docker:
    image: anyscale/ray-ml:latest-gpu
    container_name: ray_container
    pull_before_run: True

provider:
    type: aws
    region: us-west-2
    availability_zone: us-west-2a
    cache_stopped_nodes: False

auth:
    ssh_user: ubuntu

head_node:
    InstanceType: p3.16xlarge

worker_nodes:
    InstanceType: m5.16xlarge

file_mounts: {
#    "/path1/on/remote/machine": "/path1/on/local/machine",
#    "/path2/on/remote/machine": "/path2/on/local/machine",
}

setup_commands:
    - apt-get install -y libglib2.0-0 libcudnn7=7.6.5.32-1+cuda10.1
    - pip install -U https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl

worker_setup_commands: []

head_start_ray_commands:
    - ray stop
    - ulimit -n 65536; OMP_NUM_THREADS=1 ray start --head --port=6379 --object-manager-port=8076 --autoscaling-config=~/ray_bootstrap_config.yaml

worker_start_ray_commands:
    - ray stop
    - ulimit -n 65536; OMP_NUM_THREADS=1 ray start --address=$RAY_HEAD_IP:6379 --object-manager-port=8076