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docker [2019/11/29 15:00]
mimbert [Proposed solution]
docker [2019/12/03 11:03] (current)
mimbert
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 The proposed solution is to use [[https://​www.docker.com/​|Docker]] containers to run experiments. Here's the way it is supposed to work and solve the issues: The proposed solution is to use [[https://​www.docker.com/​|Docker]] containers to run experiments. Here's the way it is supposed to work and solve the issues:
-  * [[https://​docs.docker.com/​get-started/#​images-and-containers|Docker images]] are used to package a full toolchain, such as gnuradio 3.8, gnuradio 3.7, or custom tools such as OpenBTS, [[https://​www.openairinterface.org/​|OpenAirInterface]] etc. Some images will be provided and maintained by the CorteXlab team, while others may be created by experimenters,​ possibly based on ours or not. This strongly relaxes the constraints on what experimenters can do on the platform. It is even possible to use a different linux distribution if needed (we did this for OpenBTS, which was much easier to build on Ubuntu Xenial than on Debian).+  * [[https://​docs.docker.com/​get-started/#​images-and-containers|Docker images]] are used to package a full toolchain, such as gnuradio 3.8, gnuradio 3.7, or custom tools such as OpenBTS, [[https://​www.openairinterface.org/​|OpenAirInterface]] etc. [[docker images|Some images will be provided and maintained by the CorteXlab team]], while others may be created by experimenters,​ possibly based on ours or not. This strongly relaxes the constraints on what experimenters can do on the platform. It is even possible to use a different linux distribution if needed (we did this for OpenBTS, which was much easier to build on Ubuntu Xenial than on Debian).
   * Preparing an image is a much more convenient process than preparing a task, when it comes to complex software bundles such as TensorFlow, OpenBTS, etc. One just needs to install dependencies and build as if it was a real machine, there is no need to tweak or hack build steps, it just works directly.   * Preparing an image is a much more convenient process than preparing a task, when it comes to complex software bundles such as TensorFlow, OpenBTS, etc. One just needs to install dependencies and build as if it was a real machine, there is no need to tweak or hack build steps, it just works directly.
   * Image preparation can be an interactive process, or it can be automated with a [[https://​docs.docker.com/​engine/​reference/​builder/​|Dockerfile]]. The interactive way is nice for development and debug, and the automated way is an interresting step towards experimental reproducibility.   * Image preparation can be an interactive process, or it can be automated with a [[https://​docs.docker.com/​engine/​reference/​builder/​|Dockerfile]]. The interactive way is nice for development and debug, and the automated way is an interresting step towards experimental reproducibility.
docker.txt ยท Last modified: 2019/12/03 11:03 by mimbert