README.md

switchyard

Real-time compute-focused async executor with job pools, thread-local data, and priorities.

Example

use switchyard::Switchyard;
use switchyard::threads::{thread_info, one_to_one};
// Create a new switchyard without thread local data
let yard = Switchyard::new(one_to_one(thread_info(), Some("thread-name")), ||()).unwrap();

// Spawn a task on priority 10 and get a JoinHandle
let handle = yard.spawn(10, async move { 5 + 5 });
// Spawn a lower priority task
let handle2 = yard.spawn(0, async move { 2 + 2 });

// Wait on the results
assert_eq!(handle.await + handle2.await, 14);

How Switchyard is Different

Switchyard is different from other existing async executors, focusing on situations where precise control of threads and execution order is needed. One such situation is using task parallelism to parallelize a compute workload.

Priorites

Each task has a priority and tasks are ran in order from high priority to low priority.

// Spawn task with lowest priority.
yard.spawn(0, async move { /* ... */ });
// Spawn task with higher priority. If both tasks are waiting, this one will run first.
yard.spawn(10, async move { /* ... */ });

Thread Local Data

Each yard has some thread local data that can be accessed using spawn_local. Both the thread local data and the future generated by the async function passed to spawn_local may be !Send and !Sync. The future will only be resumed on the thread that created it.

If the data is Send, then you can call access_per_thread_data to get a vector of mutable references to all thread's data. See it's documentation for more information.

// Create yard with thread local data. The data is !Sync.
let yard = Switchyard::new(one_to_one(thread_info(), Some("thread-name")), || Cell::new(42)).unwrap();

// Spawn task that uses thread local data. Each running thread will get their own copy.
yard.spawn_local(0, |data| async move { data.set(10) });

MSRV

1.51

Future MSRV bumps will be breaking changes.

License: MIT OR Apache-2.0 OR Zlib