January 10, 2020

220 words 2 mins read

Learning the Linux Kernel Configuration Space: Results and Challenges

Learning the Linux Kernel Configuration Space: Results and Challenges

Given a configuration, can humans know in advance the size, the compilation time, or the boot time of a Linux kernel?Owing to the huge complexity of Linux (there are more than 15000 options with hard …
Talk Title Learning the Linux Kernel Configuration Space: Results and Challenges
Speakers Mathieu Acher (Professor, University of Rennes)
Conference Open Source Summit + ELC Europe
Conf Tag
Location Lyon, France
Date Oct 27-Nov 1, 2019
URL Talk Page
Slides Talk Slides
Video

Given a configuration, can humans know in advance the size, the compilation time, or the boot time of a Linux kernel?Owing to the huge complexity of Linux (there are more than 15000 options with hard constraints and subtle interactions), machines should rather assist contributors and integrators in mastering the configuration space of the kernel.In this talk, Mathieu Acher will introduce TuxML an OSS tool based on Docker/Python to massively gather data about thousands of kernel configurations. Mathieu will describe how 200K+ configurations have been automatically built and how machine learning can exploit this information to predict properties of unseen Linux configurations, with different use cases (identification of influential/buggy options, finding of small kernels, etc.)The vision is that a continuous understanding of the configuration space is undoubtedly beneficial for the Linux community, yet several technical challenges remain in terms of infrastructure and automation.

automation math exploit complexity infrastructure docker machine learning python use case
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