You may have experienced it in various contexts: CUDA, Tensorflow, gaming applications or complex 3D graphics applications may warn you that your Nvidia card is associated with an unexpected negative NUMA value. The warning often refers to a value of “-1”. And the clever application replaces this value by a default value of “0”.

The problem is particularly annoying when dealing Machine Learning, e.g. in Jupyter notebooks. There warnings may repeatedly clatter the output of some cells – e.g. during the setup of the graphics card for some ML experiments.

Besides the question why the Nvidia drivers for Linux and/or CUDA drivers do not fix this problem by detecting just one NUMA node on the system and setting the value for the card to “0”, the question for us users is how we can get rid of the warnings.

A basic idea is that we set the right value by ourselves. I have described this simple measure in the sister blog, which unfortunately still is under construction. See:
Setting NUMA node to 0 for Nvidia cards on standard Linux PCs.

There I also briefly discuss what NUMA basically is thought for – and why it normally does not affect consumer PCs.