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Btw, have you read this: https://async.rs/blog/stop-worrying-about-blocking-the-new-a... async-std allows to run blocking calls without hoops rather efficiently:

   async fn read_to_string(path: impl AsRef<Path>) -> io::Result<String> {
       std::fs::read_to_string(path)
   }
It doesn't have await inside! My mind was blown as I saw that.


Read the first sentence.

> This blog post describes a proposed scheduler for async-std that did not end up being merged for several reasons.

I don't think it's a particularly good idea in the first place - it's basically an automatic watchdog-driven block_in_place(). It doesn't remove the problem of blocking in futures, it just limits the damage to the local task rather than blocking the entire executor.

That's fine in the simple case of future-per-task, but it's pretty common to be polling multiple futures concurrently within one, so it's not a general solution.


> should a task execute for too long, the runtime will automatically react by spawning a new executor thread taking over the current thread’s work.

That is a super interesting strategy, though obviously only works when you can « afford » a multithreaded scheduler.

Anyway I wonder how they manage this, signals?


Nothing so fancy.

Each worker thread runs in a loop executing a queue of jobs. On every iteration it sets an atomic progress flag to true.

The runtime in which it's contained polls its workers every 1-10ms, atomically swapping in false and checking to see if the previous value was also false - if so, it steals its task queue and spins up another worker to execute it.

https://github.com/async-rs/async-std/blob/ceba324bef9641d61...


> though obviously only works when you can « afford » a multithreaded scheduler.

Yeah, for example in comparison actix-web only uses single threaded workers - one per core. Future in actix-web doesn’t have to be Send or Sync, and I think it’s incompatible with what async-std is doing here. That design is almost certainly one of the reasons actix-web tops phoronix


It also really doesn't scale. It'll do fine on your average <10 core laptop, but once you get on a multi-package system you're going to find you're constantly thrashing memory because it is making disruptive scheduling decisions and your pooled tasks have poor context locality.




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