On 8/5/2026 11:06 PM, Kyrylo Tkachov wrote:
Like most of these, I'm curious where this showed up :-)
I asked an AI agent to mine SPEC2026 and a few other workloads that are of
interest to me to find missing folds.
It turned out to be a quite productive exercise. I can recommend it as a way to
constructively use these agents for things other than writing GCC code. I don’t
think this particular fold is on a hot path or anything, but it is obviously a
beneficial one anyway (it reduces the complexity of the IR, as match.pd folds
intend)
THanks. We should probably talk further given that info. I've
proposed a talk for Cauldron, one section of which would be using LLMs
to help discover code sequences we can improve. What we've been
experimenting with is taking hot block information from QEMU (in the
form of assembly blocks with headers indicating how hot the block is),
then having the LLM mine those blocks for improved instruction
sequences. Then we (of course) validate what the LLM finds and
determine if it's worth implementing. We've found several things using
this approach for RISC-V. It has the nice property that when the LLM
flags something, you know it's hit at runtime and you can evaluate if
it's hot enough to be likely worth the time to fix.
If you wanted to co-present what you're doing, I can certainly make
room. Or if you're already proposing a session, I'll have to make sure
to attend.
Jeff
