74 releases

0.4.11 Aug 29, 2024
0.4.7 Jun 21, 2024
0.4.4 Jan 18, 2024
0.4.2 Nov 24, 2023
0.1.0 Oct 26, 2020

#1029 in Asynchronous

Download history 974/week @ 2024-08-23 950/week @ 2024-08-30 810/week @ 2024-09-06 672/week @ 2024-09-13 500/week @ 2024-09-20 401/week @ 2024-09-27 299/week @ 2024-10-04 405/week @ 2024-10-11 397/week @ 2024-10-18 472/week @ 2024-10-25 676/week @ 2024-11-01 303/week @ 2024-11-08 325/week @ 2024-11-15 464/week @ 2024-11-22 499/week @ 2024-11-29 252/week @ 2024-12-06

1,567 downloads per month
Used in 36 crates (29 directly)

ISC license

20KB
274 lines

smolscale

A global, auto-scaling scheduler for [async-task] using work-balancing.

What? Another executor?

smolscale is a work-balancing executor based on [async-task], designed to be a drop-in replacement to smol and async-global-executor. It is designed based on the idea that work-stealing, the usual approach in async executors like async-executor and tokio, is not the right algorithm for scheduling huge amounts of tiny, interdependent work units, which are what message-passing futures end up being. Instead, smolscale uses work-balancing, an approach also found in Erlang, where a global "balancer" thread periodically balances work between workers, but workers do not attempt to steal tasks from each other. This avoids the extremely frequent stealing attempts that work-stealing schedulers generate when applied to async tasks.

smolscale's approach especially excels in two circumstances:

  • When the CPU cores are not fully loaded: Traditional work stealing optimizes for the case where most workers have work to do, which is only the case in fully-loaded scenarios. When workers often wake up and go back to sleep, however, a lot of CPU time is wasted stealing work. smolscale will instead drastically reduce CPU usage in these circumstances --- a async-executor app that takes 80% of CPU time may now take only 20%. Although this does not improve fully-loaded throughput, it significantly reduces power consumption and does increase throughput in circumstances where multiple thread pools compete for CPU time.
  • When a lot of message-passing is happening: Message-passing workloads often involve tasks quickly waking up and going back to sleep. In a work-stealing scheduler, this again floods the scheduler with stealing requests. smolscale can significantly improve throughput, especially compared to executors like async-executor that do not special-case message passing.

License: ISC

Dependencies

~11–40MB
~630K SLoC