Due to issues with how NVIDIA and Canonical package the CUDA toolkit, System76 is offering better
packaging for our users. This provides all of the debian packaging information needed to build
multiple versions of the CUDA toolkit in parallel, where the resulting packages may be installed
alongside each other. Users that install multiple toolkits only need to use update-alternatives
to switch between different versions of the toolkit.
This repository is designed around our debrep tool. It provides the means to generate and maintain apt repositories based on a TOML spec and file system hierarchy. Using debrep, the data contained in the assets and debian directories are merged together and built with
sbuild, then stored in a repo pool.
These packages are built with C, C++, and Python support. Similar to the CUDA packaging, it is possible to alternate between different versions of Tensorflow. We backport fixes to older versions of Tensorflow when possible. The build system we use is based on FloopCZ's work on a Cmake build system.
The cuda directory contains the metapackage required by each of the toolkits. This installs the
required shared development dependencies, as well as some system configuration files to get toolkits
working out of the box. This package should be built and installed first on the build server.
The cuda-X.Y directories contain the specific versions of the toolkit, which depend upon the
system76-cuda metapackage built from the cuda directory. These can be built and installed in
parallel, as there are no conflicting files. update-alternatives is used post-install to add a
new entry for the symlink at /usr/lib/cuda. Each cuda-X.Y directory contains its own Makefile,
which will download the installer & patches for that release, if they are not already located in
the directory.
The update-alternatives command may be used to view installed toolkits, and switch between them.
sudo update-alternatives --list cuda
sudo update-alternatives --config cuda
You may verify that you have the correct toolkit active by checking the version.txt file
associated with that release of the toolkit:
$ cat /usr/lib/cuda/version.txt
CUDA Version 9.2.88
CUDA Patch Version 9.2.88.1