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ARM Linux engineer uses LLMs to find major bottlenecks for faster kernel compilation despite generating hideous code
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An ARM Linux engineer used LLMs to identify major bottlenecks that significantly speed up Linux kernel build times, despite the AI generating a large amount of unusable code.
Using AI to optimize build pipelines can yield significant time savings for kernel developers, even if the generated code itself is not directly usable. The value lies in the AI's ability to uncover non-obvious performance bottlenecks rather than writing production-ready patches.
Written by elseif from the cluster below · every claim links back to a sourceThe three things worth knowing
An ARM Linux engineer used LLMs to find significant speed improvements for Linux kernel builds.
The LLM generated a large amount of "hideous" code that was not directly usable.
The AI's primary contribution was identifying major compilation bottlenecks rather than writing the final code.
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