62 lines
1.8 KiB
Markdown
62 lines
1.8 KiB
Markdown
<h1>Running CARLA in a Docker </h1>
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This tutorial is designed for:
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* People that want to run CARLA without needing to install all dependencies.
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* Recommended solution to run multiple CARLA servers and perform GPU mapping
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This tutorial was tested in Ubuntu 16.04 and using NVIDIA 396.37 drivers.
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This method requires a version of NVIDIA drivers >=390.
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## Docker Installation
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!!! note
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Docker requires sudo to run. Follow this guide to add users to the docker sudo
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group <https://docs.docker.com/install/linux/linux-postinstall/>
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### Docker CE
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For our tests we used the Docker CE version.
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To install Docker CE we recommend using [this tutorial](https://docs.docker.com/install/linux/docker-ce/ubuntu/#extra-steps-for-aufs)
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### NVIDIA-Docker2
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To install nvidia-docker-2 we recommend using the "Quick Start"
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section from the [nvidia-dockers github](https://github.com/NVIDIA/nvidia-docker).
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## Getting it Running
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Pull the CARLA image.
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docker pull carlasim/carla:version
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For selecting a version, for instance, version 0.8.2 (stable), do:
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docker pull carlasim/carla:0.8.2
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Running CARLA under docker:
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docker run -p 2000-2002:2000-2002 --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=0 carlasim/carla:0.8.4
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The "-p 2000-2002:2000-2002" argument is to redirect host ports for the docker container.
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Use "NVIDIA_VISIBLE_DEVICES=<gpu_number>" to select the GPU.
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You can also pass parameters to the CARLA executable. With this you can chose the town and
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select the port that is going to be used:
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docker run -p 2000-2002:2000-2002 --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=0 carlasim/carla:0.8.4 /bin/bash CarlaUE4.sh < Your list of parameters >
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At the list of parameters do not forget to add "-world-port=<port_number>" so that CARLA runs on server mode
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listening to the "<port_number>"
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