061bee7e3c
# Objective - Upgrade winit to v0.30 - Fixes https://github.com/bevyengine/bevy/issues/13331 ## Solution This is a rewrite/adaptation of the new trait system described and implemented in `winit` v0.30. ## Migration Guide The custom UserEvent is now renamed as WakeUp, used to wake up the loop if anything happens outside the app (a new [custom_user_event](https://github.com/bevyengine/bevy/pull/13366/files#diff-2de8c0a8d3028d0059a3d80ae31b2bbc1cde2595ce2d317ea378fe3e0cf6ef2d) shows this behavior. The internal `UpdateState` has been removed and replaced internally by the AppLifecycle. When changed, the AppLifecycle is sent as an event. The `UpdateMode` now accepts only two values: `Continuous` and `Reactive`, but the latter exposes 3 new properties to enable reactive to device, user or window events. The previous `UpdateMode::Reactive` is now equivalent to `UpdateMode::reactive()`, while `UpdateMode::ReactiveLowPower` to `UpdateMode::reactive_low_power()`. The `ApplicationLifecycle` has been renamed as `AppLifecycle`, and now contains the possible values of the application state inside the event loop: * `Idle`: the loop has not started yet * `Running` (previously called `Started`): the loop is running * `WillSuspend`: the loop is going to be suspended * `Suspended`: the loop is suspended * `WillResume`: the loop is going to be resumed Note: the `Resumed` state has been removed since the resumed app is just running. Finally, now that `winit` enables this, it extends the `WinitPlugin` to support custom events. ## Test platforms - [x] Windows - [x] MacOs - [x] Linux (x11) - [x] Linux (Wayland) - [x] Android - [x] iOS - [x] WASM/WebGPU - [x] WASM/WebGL2 ## Outstanding issues / regressions - [ ] iOS: build failed in CI - blocking, but may just be flakiness - [x] Cross-platform: when the window is maximised, changes in the scale factor don't apply, to make them apply one has to make the window smaller again. (Re-maximising keeps the updated scale factor) - non-blocking, but good to fix - [ ] Android: it's pretty easy to quickly open and close the app and then the music keeps playing when suspended. - non-blocking but worrying - [ ] Web: the application will hang when switching tabs - Not new, duplicate of https://github.com/bevyengine/bevy/issues/13486 - [ ] Cross-platform?: Screenshot failure, `ERROR present_frames: wgpu_core::present: No work has been submitted for this frame before` taking the first screenshot, but after pressing space - non-blocking, but good to fix --------- Co-authored-by: François <francois.mockers@vleue.com> |
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Bevy Tasks
A refreshingly simple task executor for bevy. :)
This is a simple threadpool with minimal dependencies. The main usecase is a scoped fork-join, i.e. spawning tasks from
a single thread and having that thread await the completion of those tasks. This is intended specifically for
bevy as a lighter alternative to rayon for this specific usecase. There are also utilities for
generating the tasks from a slice of data. This library is intended for games and makes no attempt to ensure fairness
or ordering of spawned tasks.
It is based on async-executor, a lightweight executor that allows the end user to manage their own threads.
async-executor is based on async-task, a core piece of async-std.
Usage
In order to be able to optimize task execution in multi-threaded environments, bevy provides three different thread pools via which tasks of different kinds can be spawned. (The same API is used in single-threaded environments, even if execution is limited to a single thread. This currently applies to WASM targets.) The determining factor for what kind of work should go in each pool is latency requirements:
-
For CPU-intensive work (tasks that generally spin until completion) we have a standard [
ComputeTaskPool] and an [AsyncComputeTaskPool]. Work that does not need to be completed to present the next frame should go to the [AsyncComputeTaskPool]. -
For IO-intensive work (tasks that spend very little time in a "woken" state) we have an [
IoTaskPool] whose tasks are expected to complete very quickly. Generally speaking, they should just await receiving data from somewhere (i.e. disk) and signal other systems when the data is ready for consumption. (likely via channels)