Not presently, but contributions welcome!

Do you know which graph I'm talking about? Is it in some publication online?

I don't think it's in a publication, but around 10mins in @tgymnich has some in his talk at EnzymeCon https://youtu.be/nPN_Z5j6JDM?feature=shared

@tgymnich do you remember what machine you used for these measurements?

This will also now depend a lot more on the program in Julia.

for example, batching something with a linear solve will almost always be faster since we now do one linear solve to be reused for all chunks

@vchuravy this must have been a bare metal AWS machine provided by @wsmoses. I believe it was with AVX512.

I'm asking because I'm including vector mode in DI, so it would be nice to have a function in Enzyme I can call to pick a decent chunk size if the user doesn't provide it. Even if the function is dumb at the moment, I feel like that's definitely something I don't want to decide myself

8/16 should be a safe bet.

I'm asking because I'm including vector mode in DI, so it would be nice to have a function in Enzyme I can call to pick a decent chunk size if the user doesn't provide it. Even if the function is dumb at the moment, I feel like that's definitely something I don't want to decide myself

Sure, open a PR to enzyme to add a function which returns 16 for now and we can add more complex analysis later.