Mostly deterministic RO with uncertainty sets (rather than distributionally RO), which can be formulated as some kind of Mixed Integer Program (does not need to be linear). Most interesting would be instances derived from real-world applications.

The only thing I could find is robust-optimization.com/instances/ , which collects instances from a few papers. Unfortunately, there seems to be no standardized data format for robust optimization problems.

At least on Linux there seem to exist specialized fast timing functions: see stackoverflow.com/a/47003703 , which recommends to use 'clock_gettime()' and claims it only takes 3-5 nanoseconds on their system. I think it is likely that alternative calls exist in other operating systems.

What kind of crazy FPS are you running at where a syscall is too expensive? In my experience, most syscalls take on the order of 100 - 1000 cycles, which would take less than a microsecond on a modern cpu.

If you are checking out Cargo, I would also check out NPM (node package manager), which is one of the most popular javascript package managers.

No of course not! I would say the opposite; the fact that it is open source helps because you can actually understand what is happening, as long as you take the time to figure it out.

I was mostly just talking about understanding the code, not just the parameters. I agree that it is annoying that a lot of parameters are repeated.

I spent a lot of time figuring out that a '>' should be a '<'...

What prompted me to write the comment, however, is the amount of details that are involved. I doubt many users could successfully tune any solver without strong knowledge of its internals.

This is great, thanks for sharing!

Are these talks recorded and posted anywhere so that I can watch them back later?