Build tensorflow2 with CUDA support

19. Jun 2020 | Christian Goll | CC-BY-SA-3.0

Build tensorflow2 with CUDA support

Build Tensorflow 2.1.1 with CUDA support

Tensorflow 2.1.1 is available in Tumbleweed and Leap 15.2 but has no CUDA support enabled, due to legal issues with NVIDIA. As CUDA support speeds up training and inference of neuronal networks a lot, it is desirable to have it enabled.

This post explains how to build a tensorflow package with CUDA support.


The CUDA packages for building will be added via the -p flag to the osc command, but due to a bug you need at least version 0.169.1. This version is already included in Tumbleweed but for Leap 15.2 you will have to add the openSUSE Tools repository with the command and update osc

sudo zypper ar
sudo zypper ref
sudo zypper up --allow-vendor-change osc

It is also recommended to have a decent equipped machine for building as at least 10GB memory are needed and the build takes also a lot of time. On my twelve core machine it took more than two hours.

Create CUDA archive

In this step all the relevant CUDA packages are put into a single repository so that osc can access them. For this create the repository directory ($HOME/opt/cuda-10-1 in this case) with the command

mkdir -p $HOME/opt/cuda-10-1

The in next step downloaded work with Tumbleweed and openSUSE Leap 15.2.


Download from the rpm(local) for openSUSE and install it. After that copy the rpms to the local directory with

cp /var/cuda-repo-10-1-local-10.1.*/*rpm $HOME/opt/cuda-10-1


Visit and download Local installer for RedHat/CentOS 7. After you installed the downloaded rpm you have to copy the packages with the command

cp /var/nccl-repo-2.7.3-ga-cuda10.1/*rpm $HOME/opt/cuda-10-1


You have to register at NVIDA in order to download from . There download cuDNN Runtime Library for RedHat/Centos 7.3 (RPM) and cuDNN Developer Library for RedHat/Centos 7.3 (RPM). After that copyt the rpms to $HOME/opt/cuda-10-1.

Create local repository

Now you can create a local repository which can be used with osc with the commands

cd $HOME/opt/cuda-10-1 
createrepo .

where you might have to install the createrepo package.

Compile Tensorflow

With all the packages in place you have to get the tensorflow sources. This can be done with

osc co science:machinelearning/tensorflow2

Tensorflow can now compiled in the directory science:machinelearning/tensorflow2 with the command

osc build --ccache -p $HOME/opt/cuda-10-1 -k . -M cuda-10-1 openSUSE_Leap_15.2

which will start the build of the tensorflow package. You should always use the --ccache option as this speeds up rebuild. For Tumbleweed used the command

osc build --ccache -p $HOME/opt/cuda-10-1 -k . -M cuda-10-1 openSUSE_Tumbleweed

After some hours the build should have finished and the resulting tensorflow rpms should be in the directory where you have started the build.


For a proper installation copy the rpms to $HOME/opt/cuda-10-1 and rerun createrepo. You might want to add this repository to you system with

zypper ar $HOME/opt/cuda-10-1/repodata tensorflow

in order to install the package tensorflow2.

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