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JuliaGPU docker recipes

Docker recipes for Julia builds with JuliaGPU packages.

Deprecation notice: With Julia 0.7/1.0, installability of the GPU stack has improved, and this image isn't worth maintaining anymore.

For a list of included packaged, refer to the REQUIRE file.

Prerequisites

Usage

Pull and start the container as follows:

$ docker pull maleadt/juliagpu
$ docker run --runtime=nvidia -v $PKG:/pkg -it maleadt/juliagpu

Replace $PKG with a named volume (see docker volume create), or the path to a local directory. When the container starts, and /pkg does not contain an initialized package installation, a pre-configured installation of the packages as listed in the REQUIRE file will be copied to the package directory and configured for your system. This will take a while, but the results will be persistent across invocations (on the condition you keep your package volume or directory intact).

The container starts in /data, which you can mount in order to access files from your host.

Note that the container has Julia as entry point, and thus can be used as if it were a regular binary (especially powerful in combination with $PWD mounted as /data):

$ alias juliagpu='docker run --runtime=nvidia -v $PKG:/pkg -v $PWD:/data -it maleadt/juliagpu'

$ juliagpu -e 'println("Hello, World!")'
Hello, World!

$ echo 'println("Hello, World!")' > test.jl
$ juliagpu test.jl
Hello, World!

Troubleshooting

  • Did you run the container with --runtime=nvidia?
  • Some packages might support a debugging mode; run again with DEBUG=true and file an issue.

Development

Members of the JuliaGPU organization can force a rebuild of the image at the JuliaGPU CI. Apart from that, the image is rebuilt weekly, including new versions of Julia and any included packages.

If you want to include a new package, create a PR modifying the REQUIRE file. Note that all included packages need to pass tests, or the image won't be pushed.

Manual build instructions:

$ docker build -t maleadt/juliagpu .
$ docker push maleadt/juliagpu

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