2d623278e7
This moves the app template more toward being a more generic starting point for any Flutter application, eliminating some hard-code assumptions about there being a single window/engine pair that is directly bound to the life of the application: - Moves the runloop into its own class, making it capable of servicing any number of engine instances. - Moves the logic for setting up a window containing only a Flutter view into a window subclass for ease of re-use. - Makes quit-on-window-close an optional property. (Long term this should be even more generic, like a quit-when-last-window-closes option, but this is a short-term improvement that removes the binding between the runloop and the window). - Allows for multiple instances of Win32Window to exist without issues relating to the window class registration. Since there are getting to be a non-trivial number of files associated with the runner, this moves the source into a runner/ directory, as is already done on some other platforms. Note that creating multiple Flutter windows at the same time still doesn't work correctly even with this change, but this addresses some of the known issues, and makes it easier to test in the future (e.g., for debugging engine-level issues with multiple instances). Fixes #45397
Macrobenchmarks
Performance benchmarks use either flutter drive or the web benchmark harness.
Mobile benchmarks
Cull opacity benchmark
To run the cull opacity benchmark on a device:
flutter drive --profile test_driver/cull_opacity_perf.dart
Results should be in the file build/cull_opacity_perf.timeline_summary.json.
More detailed logs should be in build/cull_opacity_perf.timeline.json.
Cubic bezier benchmark
To run the cubic bezier benchmark on a device:
flutter drive --profile test_driver/cubic_bezier_perf.dart
Results should be in the file build/cubic_bezier_perf.timeline_summary.json.
More detailed logs should be in build/cubic_bezier_perf.timeline.json.
Backdrop filter benchmark
To run the backdrop filter benchmark on a device:
flutter drive --profile test_driver/backdrop_filter_perf.dart
Results should be in the file build/backdrop_filter_perf.timeline_summary.json.
More detailed logs should be in build/backdrop_filter_perf.timeline.json.
Post Backdrop filter benchmark
To run the post-backdrop filter benchmark on a device:
flutter drive --profile test_driver/post_backdrop_filter_perf.dart
Results should be in the file build/post_backdrop_filter_perf.timeline_summary.json.
More detailed logs should be in build/post_backdrop_filter_perf.timeline.json.
Web benchmarks
Web benchmarks are compiled from the same entrypoint in lib/web_benchmarks.dart.
How to write a web benchmark
Create a new file for your benchmark under lib/src/web. See bench_draw_rect.dart
as an example.
Choose one of the two benchmark types:
- A "raw benchmark" records performance metrics from direct interactions with
dart:uiwith no framework. This kind of benchmark is good for benchmarking low-level engine primitives, such as layer, picture, and semantics performance. - A "widget benchmark" records performance metrics using a widget. This kind of benchmark is good for measuring the performance of widgets, often together with engine work that widget-under-test incurs.
- A "widget build benchmark" records the cost of building a widget from nothing. This is different from the "widget benchmark" because typically the latter only performs incremental UI updates, such as an animation. In contrast, this benchmark pumps an empty frame to clear all previously built widgets and rebuilds them from scratch.
For a raw benchmark extend RawRecorder (tip: you can start by copying
bench_draw_rect.dart).
For a widget benchmark extend WidgetRecorder (tip: you can start by copying
bench_simple_lazy_text_scroll.dart).
For a widget build benchmark extend WidgetBuildRecorder (tip: you can start by copying
bench_build_material_checkbox.dart).
Pick a unique benchmark name and class name and add it to the benchmarks list
in lib/web_benchmarks.dart.
How to run a web benchmark
Web benchmarks can be run using flutter run in debug, profile, and release
modes, using either the HTML or the CanvasKit rendering backend. Note, however,
that running in debug mode will result in worse numbers. Profile mode is useful
for profiling in Chrome DevTools because the numbers are close to release mode
and the profile contains unobfuscated names.
Example:
cd dev/benchmarks/macrobenchmarks
# Runs in profile mode using the HTML renderer
flutter run --profile -d web-server lib/web_benchmarks.dart
# Runs in profile mode using the CanvasKit renderer
flutter run --dart-define=FLUTTER_WEB_USE_SKIA=true --profile -d web-server lib/web_benchmarks.dart
You can also run all benchmarks exactly like the devicelab runs them:
cd dev/devicelab
# Runs using the HTML renderer
../../bin/cache/dart-sdk/bin/dart bin/run.dart -t bin/tasks/web_benchmarks_html.dart
# Runs using the CanvasKit renderer
../../bin/cache/dart-sdk/bin/dart bin/run.dart -t bin/tasks/web_benchmarks_canvaskit.dart