accheng

Thanks for the link! I am not familiar with the company but reminds me of the whole formal methods debate in distributed systems. Sure, writing TLA+ specs is the 'correct' deterministic way to build a Raft implementation, but in reality everyone just writes messy Go/Java and patches bugs as they pop up because its faster.

Interesting, did you have any learnings that would apply to this problem now?

Check out our blog series here: ucbskyadrs.github.io!

What did you use to try to optimize scheduling?

Awesome results! Did you use the simulator from the NSDI paper directly?

Neat, thanks for the link! Seems like the agent feedback loop made a big difference for your use case. Would be interesting to see how much of a difference more advanced methods (like the genetic algs you mentioned) would make

The algorithm works for MoE load balancing in general

That's a good point! The load balancing of the original algorithm was already quite good so our goal was to try to get something that could achieve similar results but could run faster since runtime was also a concern.

Thanks for sharing your blog! Very interesting work, 100% agree with your 3 criteria on the sweet spot for AI. Most systems performance problems fit right in