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bevy/benches/Cargo.toml

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move benches to separate crate to cut test/example build times
2020-09-08 20:30:44 +00:00
[package]
name = "benches"
version = "0.1.0"
Update to edition 2021 on master (#3028) Objective During work on #3009 I've found that not all jobs use actions-rs, and therefore, an previous version of Rust is used for them. So while compilation and other stuff can pass, checking markup and Android build may fail with compilation errors. Solution This PR adds `action-rs` for any job running cargo, and updates the edition to 2021.
2021-10-27 00:12:14 +00:00
edition = "2021"
Add readme to errors crate and clean up cargo files (#3125) # Objective - Document that the error codes will be rendered on the bevy website (see bevyengine/bevy-website#216) - Some Cargo.toml files did not include the license or a description field ## Solution - Readme for the errors crate - Mark internal/development crates with `publish = false` - Add missing license/descriptions to some crates - [x] merge bevyengine/bevy-website#216
2021-11-13 23:06:48 +00:00
description = "Benchmarks for Bevy engine"
publish = false
license = "MIT OR Apache-2.0"
move benches to separate crate to cut test/example build times
2020-09-08 20:30:44 +00:00
[dev-dependencies]
update syn, encase, glam and hexasphere (#8573) # Objective - Fixes #8282 - Update `syn` to 2.0, `encase` to 0.6, `glam` to 0.24 and `hexasphere` to 9.0 Blocked ~~on https://github.com/teoxoy/encase/pull/42~~ and ~~on https://github.com/OptimisticPeach/hexasphere/pull/17~~ --------- Co-authored-by: Nicola Papale <nicopap@users.noreply.github.com> Co-authored-by: JoJoJet <21144246+JoJoJet@users.noreply.github.com>
2023-05-16 01:24:17 +00:00
glam = "0.24"
Add a random access get_component benchmark (#4607) # Objective Add a benchmark to measure the performance of get_component, particularly for cases involving random access. Enables #2965
2022-04-26 21:20:13 +00:00
rand = "0.8"
rand_chacha = "0.3"
Make `System` responsible for updating its own archetypes (#4115) # Objective - Make it possible to use `System`s outside of the scheduler/executor without having to define logic to track new archetypes and call `System::add_archetype()` for each. ## Solution - Replace `System::add_archetype(&Archetype)` with `System::update_archetypes(&World)`, making systems responsible for tracking their own most recent archetype generation the way that `SystemState` already does. This has minimal (or simplifying) effect on most of the code with the exception of `FunctionSystem`, which must now track the latest `ArchetypeGeneration` it saw instead of relying on the executor to do it. Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-04-07 20:50:43 +00:00
criterion = { version = "0.3", features = ["html_reports"] }
Add benchmarks for schedule dependency resolution (#4961) # Objective - Add benchmarks to test the performance of `Schedule`'s system dependency resolution. ## Solution - Do a series of benchmarks while increasing the number of systems in the schedule to see how the run-time scales. - Split the benchmarks into a group with no dependencies, and a group with many dependencies.
2022-06-20 17:35:54 +00:00
bevy_app = { path = "../crates/bevy_app" }
Significantly reduce the amount of building required for benchmarks (#4067) # Objective - Release mode. Many time ## Solution - Less things, less time
2022-03-01 00:51:07 +00:00
bevy_ecs = { path = "../crates/bevy_ecs" }
bench: add `bevy_reflect::{List, Map, Struct}` benchmarks (#3690) # Objective Partially addresses #3594. ## Solution This adds basic benchmarks for `List`, `Map`, and `Struct` implementors, both concrete (`Vec`, `HashMap`, and defined struct types) and dynamic (`DynamicList`, `DynamicMap` and `DynamicStruct`). A few insights from the benchmarks (all measurements are local on my machine): - Applying a list with many elements to a list with no elements is slower than applying to a list of the same length: - 3-4x slower when applying to a `Vec` - 5-6x slower when applying to a `DynamicList` I suspect this could be improved by `reserve()`ing the correct length up front, but haven't tested. - Applying a `DynamicMap` to another `Map` is linear in the number of elements, but applying a `HashMap` seems to be at least quadratic. No intuition on this one. - Applying like structs (concrete -> concrete, `DynamicStruct` -> `DynamicStruct`) seems to be faster than applying unlike structs.
2022-05-17 04:16:53 +00:00
bevy_reflect = { path = "../crates/bevy_reflect" }
Significantly reduce the amount of building required for benchmarks (#4067) # Objective - Release mode. Many time ## Solution - Less things, less time
2022-03-01 00:51:07 +00:00
bevy_tasks = { path = "../crates/bevy_tasks" }
bench: add `bevy_reflect::{List, Map, Struct}` benchmarks (#3690) # Objective Partially addresses #3594. ## Solution This adds basic benchmarks for `List`, `Map`, and `Struct` implementors, both concrete (`Vec`, `HashMap`, and defined struct types) and dynamic (`DynamicList`, `DynamicMap` and `DynamicStruct`). A few insights from the benchmarks (all measurements are local on my machine): - Applying a list with many elements to a list with no elements is slower than applying to a list of the same length: - 3-4x slower when applying to a `Vec` - 5-6x slower when applying to a `DynamicList` I suspect this could be improved by `reserve()`ing the correct length up front, but haven't tested. - Applying a `DynamicMap` to another `Map` is linear in the number of elements, but applying a `HashMap` seems to be at least quadratic. No intuition on this one. - Applying like structs (concrete -> concrete, `DynamicStruct` -> `DynamicStruct`) seems to be faster than applying unlike structs.
2022-05-17 04:16:53 +00:00
bevy_utils = { path = "../crates/bevy_utils" }
Add Beziers to `bevy_math` (#7653) # Objective - Adds foundational math for Bezier curves, useful for UI/2D/3D animation and smooth paths. https://user-images.githubusercontent.com/2632925/218883143-e138f994-1795-40da-8c59-21d779666991.mp4 ## Solution - Adds the generic `Bezier` type, and a `Point` trait. The `Point` trait allows us to use control points of any dimension, as long as they support vector math. I've implemented it for `f32`(1D), `Vec2`(2D), and `Vec3`/`Vec3A`(3D). - Adds `CubicBezierEasing` on top of `Bezier` with the addition of an implementation of cubic Bezier easing, which is a foundational tool for UI animation. - This involves solving for $t$ in the parametric Bezier function $B(t)$ using the Newton-Raphson method to find a value with error $\leq$ 1e-7, capped at 8 iterations. - Added type aliases for common Bezier curves: `CubicBezier2d`, `CubicBezier3d`, `QuadraticBezier2d`, and `QuadraticBezier3d`. These types use `Vec3A` to represent control points, as this was found to have an 80-90% speedup over using `Vec3`. - Benchmarking shows quadratic/cubic Bezier evaluations $B(t)$ take \~1.8/2.4ns respectively. Easing, which requires an iterative solve takes \~50ns for cubic Beziers. --- ## Changelog - Added `CubicBezier2d`, `CubicBezier3d`, `QuadraticBezier2d`, and `QuadraticBezier3d` types with methods for sampling position, velocity, and acceleration. The generic `Bezier` type is also available, and generic over any degree of Bezier curve. - Added `CubicBezierEasing`, with additional methods to allow for smooth easing animations.
2023-02-20 18:34:52 +00:00
bevy_math = { path = "../crates/bevy_math" }
move benches to separate crate to cut test/example build times
2020-09-08 20:30:44 +00:00
Remove unnecesary branches/panics from Query accesses (#6461) # Objective Supercedes #6452. Upon inspection of the [generated assembly](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-original-s) of a [simple Bevy binary](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-source-rs) compiled with `cargo rustc --release -- --emit asm`, it's apparent that there are multiple unnecessary branches in the generated assembly: ```assembly .LBB5_5: cmpq %r10, %r11 je .LBB5_15 movq (%r11), %rcx movq 328(%r15), %rdx cmpq %rdx, %rcx jae .LBB5_14 movq 312(%r15), %rdi leaq (%rcx,%rcx,2), %rcx shlq $5, %rcx movq 336(%r12), %rdx movq 64(%rdi,%rcx), %rax cmpq %rdx, %rax jbe .LBB5_4 leaq (%rdi,%rcx), %rsi movq 48(%rsi), %rbp shlq $4, %rdx cmpq $0, (%rbp,%rdx) je .LBB5_4 movq 344(%r12), %rbx cmpq %rbx, %rax jbe .LBB5_4 shlq $4, %rbx cmpq $0, (%rbp,%rbx) je .LBB5_4 addq $8, %r11 movq 88(%rdi,%rcx), %rcx testq %rcx, %rcx je .LBB5_5 movq (%rsi), %rax movq 8(%rbp,%rdx), %rdx leaq (%rdx,%rdx,4), %rdi shlq $4, %rdi movq 32(%rax,%rdi), %rdx movq 56(%rax,%rdi), %r8 movq 8(%rbp,%rbx), %rbp leaq (%rbp,%rbp,4), %rbp shlq $4, %rbp movq 32(%rax,%rbp), %r9 xorl %ebp, %ebp jmp .LBB5_13 .p2align 4, 0x90 ``` Almost every one of the instructions starting with `j` is a potential branch, which can significantly slow down accesses. Of these, two labels are both common and never used: ```asm .LBB5_14: leaq __unnamed_2(%rip), %r8 callq _ZN4core9panicking18panic_bounds_check17h70367088e72af65aE ud2 .LBB5_4: callq _ZN8bevy_ecs5query25debug_checked_unreachable17h0855ff520ceaea77E ud2 .seh_endproc ``` These correpsond to subprocedure calls to panicking due to out of bounds from indexing `Tables` and `debug_checked_unreadable`. Both of which should be inlined and optimized out, but are not. ## Solution Make `debug_checked_unreachable` a macro to forcibly inline either `unreachable!()` in debug builds, and `std::hint::unreachable_unchecked()` in release mode. Replace the `Tables` and `Archetype` index access with `get(id).unwrap_or_else(|| debug_checked_unreachable!())` to assume that the table or archetype provided exists. This has no external breaking change of any kind. The equivalent section of code with these changes removes most of the conditional jump instructions: ```asm .LBB5_5: movss (%rbx,%rbp,4), %xmm0 movl %r14d, 4(%r8,%rbp,8) addss (%rdi,%rbp,4), %xmm0 movss %xmm0, (%rdi,%rbp,4) incq %rbp .LBB5_1: cmpq %rdx, %rbp jne .LBB5_5 .p2align 4, 0x90 .LBB5_2: cmpq %rcx, %rax je .LBB5_6 movq (%rax), %rdx addq $8, %rax movq 312(%rsi), %rbp leaq (%rdx,%rdx,2), %rbx shlq $5, %rbx movq 88(%rbp,%rbx), %rdx testq %rdx, %rdx je .LBB5_2 leaq (%rbx,%rbp), %r8 movq 336(%r15), %rdi movq 344(%r15), %r9 movq 48(%rbp,%rbx), %r10 shlq $4, %rdi movq (%r8), %rbx movq 8(%r10,%rdi), %rdi leaq (%rdi,%rdi,4), %rbp shlq $4, %rbp movq 32(%rbx,%rbp), %rdi movq 56(%rbx,%rbp), %r8 shlq $4, %r9 movq 8(%r10,%r9), %rbp leaq (%rbp,%rbp,4), %rbp shlq $4, %rbp movq 32(%rbx,%rbp), %rbx xorl %ebp, %ebp jmp .LBB5_5 .LBB5_6: addq $40, %rsp popq %rbx popq %rbp popq %rdi popq %rsi popq %r14 popq %r15 retq .seh_endproc ``` ## Performance Microbenchmarks results: <details> ``` group main no-panic-query ----- ---- -------------- busy_systems/01x_entities_03_systems 1.20 42.4±2.66µs ? ?/sec 1.00 35.3±1.68µs ? ?/sec busy_systems/01x_entities_06_systems 1.32 83.8±3.50µs ? ?/sec 1.00 63.6±1.72µs ? ?/sec busy_systems/01x_entities_09_systems 1.15 113.3±8.90µs ? ?/sec 1.00 98.2±6.15µs ? ?/sec busy_systems/01x_entities_12_systems 1.27 160.8±32.44µs ? ?/sec 1.00 126.6±4.70µs ? ?/sec busy_systems/01x_entities_15_systems 1.12 179.6±3.71µs ? ?/sec 1.00 160.3±11.03µs ? ?/sec busy_systems/02x_entities_03_systems 1.18 76.8±3.14µs ? ?/sec 1.00 65.2±3.17µs ? ?/sec busy_systems/02x_entities_06_systems 1.16 144.6±6.10µs ? ?/sec 1.00 124.5±5.14µs ? ?/sec busy_systems/02x_entities_09_systems 1.19 215.3±9.18µs ? ?/sec 1.00 181.5±5.67µs ? ?/sec busy_systems/02x_entities_12_systems 1.20 266.7±8.33µs ? ?/sec 1.00 222.0±9.53µs ? ?/sec busy_systems/02x_entities_15_systems 1.23 338.8±10.53µs ? ?/sec 1.00 276.3±6.94µs ? ?/sec busy_systems/03x_entities_03_systems 1.43 113.5±5.06µs ? ?/sec 1.00 79.6±1.49µs ? ?/sec busy_systems/03x_entities_06_systems 1.38 217.3±12.67µs ? ?/sec 1.00 157.5±3.07µs ? ?/sec busy_systems/03x_entities_09_systems 1.23 308.8±24.75µs ? ?/sec 1.00 251.6±8.93µs ? ?/sec busy_systems/03x_entities_12_systems 1.05 347.7±12.43µs ? ?/sec 1.00 330.6±11.43µs ? ?/sec busy_systems/03x_entities_15_systems 1.13 455.5±13.88µs ? ?/sec 1.00 401.7±17.29µs ? ?/sec busy_systems/04x_entities_03_systems 1.24 144.7±5.89µs ? ?/sec 1.00 116.9±6.29µs ? ?/sec busy_systems/04x_entities_06_systems 1.24 282.8±21.40µs ? ?/sec 1.00 228.6±21.31µs ? ?/sec busy_systems/04x_entities_09_systems 1.35 431.8±14.10µs ? ?/sec 1.00 319.6±9.83µs ? ?/sec busy_systems/04x_entities_12_systems 1.16 493.8±22.87µs ? ?/sec 1.00 424.9±15.24µs ? ?/sec busy_systems/04x_entities_15_systems 1.10 587.5±23.25µs ? ?/sec 1.00 531.7±16.32µs ? ?/sec busy_systems/05x_entities_03_systems 1.14 148.2±9.61µs ? ?/sec 1.00 129.5±4.32µs ? ?/sec busy_systems/05x_entities_06_systems 1.31 359.7±17.46µs ? ?/sec 1.00 273.6±10.55µs ? ?/sec busy_systems/05x_entities_09_systems 1.22 473.5±23.11µs ? ?/sec 1.00 389.3±13.62µs ? ?/sec busy_systems/05x_entities_12_systems 1.05 562.9±20.76µs ? ?/sec 1.00 536.5±24.35µs ? ?/sec busy_systems/05x_entities_15_systems 1.23 818.5±28.70µs ? ?/sec 1.00 666.6±45.87µs ? ?/sec contrived/01x_entities_03_systems 1.27 27.5±0.49µs ? ?/sec 1.00 21.6±1.71µs ? ?/sec contrived/01x_entities_06_systems 1.22 49.9±1.18µs ? ?/sec 1.00 40.7±2.62µs ? ?/sec contrived/01x_entities_09_systems 1.30 72.3±2.39µs ? ?/sec 1.00 55.4±2.60µs ? ?/sec contrived/01x_entities_12_systems 1.28 94.3±9.44µs ? ?/sec 1.00 73.7±3.62µs ? ?/sec contrived/01x_entities_15_systems 1.25 118.0±2.43µs ? ?/sec 1.00 94.1±3.99µs ? ?/sec contrived/02x_entities_03_systems 1.23 41.6±1.71µs ? ?/sec 1.00 33.7±2.30µs ? ?/sec contrived/02x_entities_06_systems 1.19 78.6±2.63µs ? ?/sec 1.00 65.9±2.35µs ? ?/sec contrived/02x_entities_09_systems 1.28 113.6±3.60µs ? ?/sec 1.00 88.6±3.60µs ? ?/sec contrived/02x_entities_12_systems 1.20 146.4±5.75µs ? ?/sec 1.00 121.7±3.35µs ? ?/sec contrived/02x_entities_15_systems 1.23 178.5±4.86µs ? ?/sec 1.00 145.7±4.00µs ? ?/sec contrived/03x_entities_03_systems 1.42 58.3±2.77µs ? ?/sec 1.00 41.1±1.54µs ? ?/sec contrived/03x_entities_06_systems 1.32 108.5±7.30µs ? ?/sec 1.00 82.4±4.86µs ? ?/sec contrived/03x_entities_09_systems 1.23 153.7±4.61µs ? ?/sec 1.00 125.0±4.76µs ? ?/sec contrived/03x_entities_12_systems 1.18 197.5±5.12µs ? ?/sec 1.00 166.8±8.14µs ? ?/sec contrived/03x_entities_15_systems 1.23 238.8±6.38µs ? ?/sec 1.00 194.6±4.55µs ? ?/sec contrived/04x_entities_03_systems 1.34 66.4±3.42µs ? ?/sec 1.00 49.5±1.98µs ? ?/sec contrived/04x_entities_06_systems 1.27 134.3±4.86µs ? ?/sec 1.00 105.8±3.58µs ? ?/sec contrived/04x_entities_09_systems 1.26 193.2±3.83µs ? ?/sec 1.00 153.0±5.60µs ? ?/sec contrived/04x_entities_12_systems 1.16 237.1±5.78µs ? ?/sec 1.00 204.9±18.77µs ? ?/sec contrived/04x_entities_15_systems 1.17 289.2±4.76µs ? ?/sec 1.00 246.3±8.57µs ? ?/sec contrived/05x_entities_03_systems 1.26 80.4±2.90µs ? ?/sec 1.00 63.7±3.07µs ? ?/sec contrived/05x_entities_06_systems 1.27 161.6±13.47µs ? ?/sec 1.00 127.2±5.59µs ? ?/sec contrived/05x_entities_09_systems 1.22 228.0±7.76µs ? ?/sec 1.00 186.2±7.68µs ? ?/sec contrived/05x_entities_12_systems 1.20 289.5±6.21µs ? ?/sec 1.00 241.8±7.52µs ? ?/sec contrived/05x_entities_15_systems 1.18 357.3±11.24µs ? ?/sec 1.00 302.7±7.21µs ? ?/sec heavy_compute/base 1.01 302.4±3.52µs ? ?/sec 1.00 300.2±3.40µs ? ?/sec iter_fragmented/base 1.00 348.1±7.51ns ? ?/sec 1.01 351.9±8.32ns ? ?/sec iter_fragmented/foreach 1.03 239.8±23.78ns ? ?/sec 1.00 233.8±18.12ns ? ?/sec iter_fragmented/foreach_wide 1.00 3.9±0.13µs ? ?/sec 1.02 4.0±0.22µs ? ?/sec iter_fragmented/wide 1.18 4.6±0.15µs ? ?/sec 1.00 3.9±0.10µs ? ?/sec iter_fragmented_sparse/base 1.02 8.1±0.15ns ? ?/sec 1.00 7.9±0.56ns ? ?/sec iter_fragmented_sparse/foreach 1.00 7.8±0.22ns ? ?/sec 1.01 7.9±0.62ns ? ?/sec iter_fragmented_sparse/foreach_wide 1.00 37.2±1.17ns ? ?/sec 1.10 40.9±0.95ns ? ?/sec iter_fragmented_sparse/wide 1.09 48.4±2.13ns ? ?/sec 1.00 44.5±18.34ns ? ?/sec iter_simple/base 1.02 8.4±0.10µs ? ?/sec 1.00 8.2±0.14µs ? ?/sec iter_simple/foreach 1.01 8.3±0.07µs ? ?/sec 1.00 8.2±0.09µs ? ?/sec iter_simple/foreach_sparse_set 1.00 25.3±0.32µs ? ?/sec 1.02 25.7±0.42µs ? ?/sec iter_simple/foreach_wide 1.03 41.1±0.94µs ? ?/sec 1.00 39.9±0.41µs ? ?/sec iter_simple/foreach_wide_sparse_set 1.05 123.6±2.05µs ? ?/sec 1.00 118.1±2.78µs ? ?/sec iter_simple/sparse_set 1.14 30.5±1.40µs ? ?/sec 1.00 26.9±0.64µs ? ?/sec iter_simple/system 1.01 8.4±0.25µs ? ?/sec 1.00 8.4±0.11µs ? ?/sec iter_simple/wide 1.18 48.2±0.62µs ? ?/sec 1.00 40.7±0.38µs ? ?/sec iter_simple/wide_sparse_set 1.12 140.8±21.56µs ? ?/sec 1.00 126.0±2.30µs ? ?/sec query_get/50000_entities_sparse 1.17 378.6±7.60µs ? ?/sec 1.00 324.1±23.17µs ? ?/sec query_get/50000_entities_table 1.08 330.9±10.90µs ? ?/sec 1.00 306.8±4.98µs ? ?/sec query_get_component/50000_entities_sparse 1.00 976.7±19.55µs ? ?/sec 1.00 979.8±35.87µs ? ?/sec query_get_component/50000_entities_table 1.00 1029.0±15.11µs ? ?/sec 1.05 1080.0±59.18µs ? ?/sec query_get_component_simple/system 1.13 839.7±14.18µs ? ?/sec 1.00 742.8±10.72µs ? ?/sec query_get_component_simple/unchecked 1.01 909.0±15.17µs ? ?/sec 1.00 898.0±13.56µs ? ?/sec query_get_many_10/50000_calls_sparse 1.04 5.5±0.54ms ? ?/sec 1.00 5.3±0.67ms ? ?/sec query_get_many_10/50000_calls_table 1.01 4.9±0.49ms ? ?/sec 1.00 4.8±0.45ms ? ?/sec query_get_many_2/50000_calls_sparse 1.28 848.4±210.89µs ? ?/sec 1.00 664.8±47.69µs ? ?/sec query_get_many_2/50000_calls_table 1.05 779.0±73.85µs ? ?/sec 1.00 739.2±83.02µs ? ?/sec query_get_many_5/50000_calls_sparse 1.05 2.4±0.37ms ? ?/sec 1.00 2.3±0.33ms ? ?/sec query_get_many_5/50000_calls_table 1.00 1939.9±75.22µs ? ?/sec 1.04 2.0±0.19ms ? ?/sec run_criteria/yes_using_query/001_systems 1.00 3.7±0.38µs ? ?/sec 1.30 4.9±0.14µs ? ?/sec run_criteria/yes_using_query/006_systems 1.00 8.9±0.40µs ? ?/sec 1.17 10.3±0.57µs ? ?/sec run_criteria/yes_using_query/011_systems 1.00 13.9±0.49µs ? ?/sec 1.08 15.0±0.89µs ? ?/sec run_criteria/yes_using_query/016_systems 1.00 18.8±0.74µs ? ?/sec 1.00 18.8±1.43µs ? ?/sec run_criteria/yes_using_query/021_systems 1.07 24.1±0.87µs ? ?/sec 1.00 22.6±1.58µs ? ?/sec run_criteria/yes_using_query/026_systems 1.04 27.9±0.62µs ? ?/sec 1.00 26.8±1.71µs ? ?/sec run_criteria/yes_using_query/031_systems 1.09 33.3±1.03µs ? ?/sec 1.00 30.5±2.18µs ? ?/sec run_criteria/yes_using_query/036_systems 1.14 38.7±0.80µs ? ?/sec 1.00 33.9±1.75µs ? ?/sec run_criteria/yes_using_query/041_systems 1.18 43.7±1.07µs ? ?/sec 1.00 37.0±2.39µs ? ?/sec run_criteria/yes_using_query/046_systems 1.14 47.6±1.16µs ? ?/sec 1.00 41.9±2.09µs ? ?/sec run_criteria/yes_using_query/051_systems 1.17 52.9±2.04µs ? ?/sec 1.00 45.3±1.75µs ? ?/sec run_criteria/yes_using_query/056_systems 1.25 59.2±2.38µs ? ?/sec 1.00 47.2±2.01µs ? ?/sec run_criteria/yes_using_query/061_systems 1.28 66.1±15.84µs ? ?/sec 1.00 51.5±2.47µs ? ?/sec run_criteria/yes_using_query/066_systems 1.28 70.2±2.57µs ? ?/sec 1.00 54.7±2.58µs ? ?/sec run_criteria/yes_using_query/071_systems 1.30 75.5±2.27µs ? ?/sec 1.00 58.2±3.31µs ? ?/sec run_criteria/yes_using_query/076_systems 1.26 81.5±2.66µs ? ?/sec 1.00 64.5±3.13µs ? ?/sec run_criteria/yes_using_query/081_systems 1.29 89.7±2.58µs ? ?/sec 1.00 69.3±3.47µs ? ?/sec run_criteria/yes_using_query/086_systems 1.33 95.6±3.39µs ? ?/sec 1.00 71.8±3.48µs ? ?/sec run_criteria/yes_using_query/091_systems 1.25 102.0±3.67µs ? ?/sec 1.00 81.4±4.82µs ? ?/sec run_criteria/yes_using_query/096_systems 1.33 111.7±3.29µs ? ?/sec 1.00 83.8±4.15µs ? ?/sec run_criteria/yes_using_query/101_systems 1.29 113.2±12.04µs ? ?/sec 1.00 87.7±5.15µs ? ?/sec world_query_for_each/50000_entities_sparse 1.00 47.4±0.51µs ? ?/sec 1.00 47.3±0.33µs ? ?/sec world_query_for_each/50000_entities_table 1.00 27.2±0.50µs ? ?/sec 1.00 27.2±0.17µs ? ?/sec world_query_get/50000_entities_sparse_wide 1.09 210.5±1.78µs ? ?/sec 1.00 192.5±2.61µs ? ?/sec world_query_get/50000_entities_table 1.00 127.7±2.09µs ? ?/sec 1.07 136.2±5.95µs ? ?/sec world_query_get/50000_entities_table_wide 1.00 209.8±2.37µs ? ?/sec 1.15 240.6±2.04µs ? ?/sec world_query_iter/50000_entities_sparse 1.00 54.2±0.36µs ? ?/sec 1.01 54.7±0.61µs ? ?/sec world_query_iter/50000_entities_table 1.00 27.2±0.31µs ? ?/sec 1.00 27.3±0.64µs ? ?/sec ``` </details> NOTE: This PR includes a change to enable LTO on our benchmarks to get a "fully optimized" baseline for our benchmarks. Both the main and the current PR's results were with LTO enabled.
2022-11-04 06:04:55 +00:00
[profile.release]
opt-level = 3
lto = true
Change Detection Benchmarks (#4972) # Objective Fixes #4883. ## Solution - Add benchmarks for Changed and Added Disclaimer: I'm not that much familiar with benchmarking.
2022-11-04 17:53:54 +00:00
[[bench]]
name = "change_detection"
path = "benches/bevy_ecs/change_detection.rs"
harness = false
Make `System` responsible for updating its own archetypes (#4115) # Objective - Make it possible to use `System`s outside of the scheduler/executor without having to define logic to track new archetypes and call `System::add_archetype()` for each. ## Solution - Replace `System::add_archetype(&Archetype)` with `System::update_archetypes(&World)`, making systems responsible for tracking their own most recent archetype generation the way that `SystemState` already does. This has minimal (or simplifying) effect on most of the code with the exception of `FunctionSystem`, which must now track the latest `ArchetypeGeneration` it saw instead of relying on the executor to do it. Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-04-07 20:50:43 +00:00
[[bench]]
ECS benchmarks organization (#5189) ## Objective Fixes: #5110 ## Solution - Moved benches into separate modules according to the part of ECS they are testing. - Made so all ECS benches are included in one `benches.rs` so they don’t need to be added separately in `Cargo.toml`. - Renamed a bunch of files to have more coherent names. - Merged `schedule.rs` and `system_schedule.rs` into one file.
2022-07-04 14:17:45 +00:00
name = "ecs"
path = "benches/bevy_ecs/benches.rs"
Add benchmarks for schedule dependency resolution (#4961) # Objective - Add benchmarks to test the performance of `Schedule`'s system dependency resolution. ## Solution - Do a series of benchmarks while increasing the number of systems in the schedule to see how the run-time scales. - Split the benchmarks into a group with no dependencies, and a group with many dependencies.
2022-06-20 17:35:54 +00:00
harness = false
bench: add `bevy_reflect::{List, Map, Struct}` benchmarks (#3690) # Objective Partially addresses #3594. ## Solution This adds basic benchmarks for `List`, `Map`, and `Struct` implementors, both concrete (`Vec`, `HashMap`, and defined struct types) and dynamic (`DynamicList`, `DynamicMap` and `DynamicStruct`). A few insights from the benchmarks (all measurements are local on my machine): - Applying a list with many elements to a list with no elements is slower than applying to a list of the same length: - 3-4x slower when applying to a `Vec` - 5-6x slower when applying to a `DynamicList` I suspect this could be improved by `reserve()`ing the correct length up front, but haven't tested. - Applying a `DynamicMap` to another `Map` is linear in the number of elements, but applying a `HashMap` seems to be at least quadratic. No intuition on this one. - Applying like structs (concrete -> concrete, `DynamicStruct` -> `DynamicStruct`) seems to be faster than applying unlike structs.
2022-05-17 04:16:53 +00:00
[[bench]]
name = "reflect_list"
path = "benches/bevy_reflect/list.rs"
harness = false
[[bench]]
name = "reflect_map"
path = "benches/bevy_reflect/map.rs"
harness = false
[[bench]]
name = "reflect_struct"
path = "benches/bevy_reflect/struct.rs"
harness = false
move benches to separate crate to cut test/example build times
2020-09-08 20:30:44 +00:00
[[bench]]
name = "iter"
path = "benches/bevy_tasks/iter.rs"
update dependencies (#470)
2020-09-10 19:54:24 +00:00
harness = false
Add Beziers to `bevy_math` (#7653) # Objective - Adds foundational math for Bezier curves, useful for UI/2D/3D animation and smooth paths. https://user-images.githubusercontent.com/2632925/218883143-e138f994-1795-40da-8c59-21d779666991.mp4 ## Solution - Adds the generic `Bezier` type, and a `Point` trait. The `Point` trait allows us to use control points of any dimension, as long as they support vector math. I've implemented it for `f32`(1D), `Vec2`(2D), and `Vec3`/`Vec3A`(3D). - Adds `CubicBezierEasing` on top of `Bezier` with the addition of an implementation of cubic Bezier easing, which is a foundational tool for UI animation. - This involves solving for $t$ in the parametric Bezier function $B(t)$ using the Newton-Raphson method to find a value with error $\leq$ 1e-7, capped at 8 iterations. - Added type aliases for common Bezier curves: `CubicBezier2d`, `CubicBezier3d`, `QuadraticBezier2d`, and `QuadraticBezier3d`. These types use `Vec3A` to represent control points, as this was found to have an 80-90% speedup over using `Vec3`. - Benchmarking shows quadratic/cubic Bezier evaluations $B(t)$ take \~1.8/2.4ns respectively. Easing, which requires an iterative solve takes \~50ns for cubic Beziers. --- ## Changelog - Added `CubicBezier2d`, `CubicBezier3d`, `QuadraticBezier2d`, and `QuadraticBezier3d` types with methods for sampling position, velocity, and acceleration. The generic `Bezier` type is also available, and generic over any degree of Bezier curve. - Added `CubicBezierEasing`, with additional methods to allow for smooth easing animations.
2023-02-20 18:34:52 +00:00
[[bench]]
name = "bezier"
path = "benches/bevy_math/bezier.rs"
harness = false
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