[josephg]

> BTW 7% is huge, odd that you would describe it as "only".

It depends on what you're doing and how optimized the baseline performance is. In my area (CRDTs) the baseline performance is terrible for a lot of these algorithms. Over about 18 months of work I've managed to improve on automerge's 2021 performance of ~5 minutes / 800MB of ram for one specific benchmark down to 4ms / 2MB. Thats 75000x faster. (Yjs in comparison takes ~1 second.)

Almost all of the performance improvement came from using more appropriate data structures and optimizing the fast-path. I couldn't find an off-the-shelf b-tree or skip list which did what I needed here. I ended up hand coding a b-tree for sequence data which run-length encodes items internally, and knows how to split and merge nodes when inserts happen. CRDTs also have a lot of fiddly computations when concurrent changes edit the same data, but users don't do that much in practice. Coding optimized fast paths for the 99% case got me another 10x performance improvement or so.

I'd take another 7% performance improvement on top of where I am, but this code is probably fast enough. I hear you that 7% is huge sometimes, and a smarter compiler is a better compiler. But 7% is a drop in the bucket for my work.

[saagarjha]

7% is huge in the context of compilers, which optimize general-purpose code.