> Reasoning about l1/l2/l3 cache hit ratios and their implications basically throwing darts at the wall, in the wrong room. If you give it a benchmark feedback loop then it might get there eventually but still massive alpha for low level systems engineers who instinctively know how this stuff works and can now automate 99% of the grind.
I suspect a lot of the training set for this sort of thing is people online speculating about cache performance incorrectly.
I would think it's that the kinds of places which value this kind of knowledge often have major disincentive to share it. I'm thinking of HFT firms as one example.
Speaking as somebody who is a performance geek, my knowledge came from relentless experimenting over the years (starting in the 8 bit era). To learn, you need to do the hard yards. Beyond the basics, I haven’t seen much on high-performance engineering.
I think performance tweaking becomes almost instinctive rather than something driven by a hard set of rules. At a low enough level, every performance tweak job becomes unique and bespoke.
Of course you could find people online talking about how to write high-performance code, but beyond a few basic techniques, their advice may not work for you.
Arguably, there are fewer patterns for an LLM to infer as highly optimised code tends to become more and more opaque in the search for a nanosecond here or there.