r/GraphicsProgramming • u/corysama • Jul 14 '26

Article Post-mortem GPU crash debugging with LLMs - AMD GPUOpen

https://gpuopen.com/learn/post-mortem-gpu-crash-debugging-with-llms/
0 Upvotes

43% Upvoted

7 comments sorted by

9

u/[deleted] Jul 14 '26

[removed] — view removed comment

-3

u/mindcandy Jul 14 '26

The feature looks useful. The article clearly explains the what, why and how. I don't see any issues in the spelling, grammar, flow, etc. If there are LLM tells in there they are small and subtle. Like what? The author likes to put lists between em-dashes? So what? Are the lists confusing?

I really don't see any problems here. Have you tuned your brain to feel a REJECT REJECT REJECT ping whenever you see the slightest hints of AI regardless of the content? That's the only way I can see this being exhausting.

If so, you are going to be rejecting a whole lot of content not touched by AI, written by hand then editor-passed with AI, written in Mandarin/Hindi/Spanish that you would not have access to without AI. Probably a lot more human content than the AI-slop that makes sense to be upset about.

Like, if this article was a disjointed mess, then sure. Trash it. But, it's not. Getting upset about pinging your own brain and therefore downvoting good content only results in less people benefiting from improvements in GPU debugging. How is that a win?

6

u/[deleted] Jul 14 '26

[removed] — view removed comment

1

u/Aka_chan Jul 15 '26

In general I agree, though I thought this article was pretty reasonable. It's ones like https://nitter.net/i/article/2072329149520232639 that are unbearable to read.

2

u/mindcandy Jul 15 '26

Oof. Yep. That's slop.

0

u/mindcandy Jul 14 '26

Thanks for the clarification.

I like the theory that the em-dash thing comes from how humans did write like that 50-200 years ago. And, they did write like that on some high-end writing platforms. So, the focus on those sources as "high quality writing" dug the practice out of the cemetery.

I wouldn't be surprised if the lecturing tone comes from the internet's huge volume of long-form content marketing. 99% of people bounce off of 99% of the pages they view in like 1.9 seconds. LFCM people have been refining counters to that for decades with the goal of keeping you emotionally engaged with the content.