Skip to content

Instantly share code, notes, and snippets.

@lukas-code

lukas-code/benchmark.rs

Last active November 24, 2023 19:44
Show Gist options
  • Save lukas-code/c97bd707d074c4cc31f241edbc7fd2a2 to your computer and use it in GitHub Desktop.
Save lukas-code/c97bd707d074c4cc31f241edbc7fd2a2 to your computer and use it in GitHub Desktop.
Download ZIP
VecDeque::drain destructor benchmark
Raw
benchmark.rs
// criterion = "0.5"
use std::collections::VecDeque;
use std::iter;
use std::rc::Rc;
use criterion::{Criterion, black_box};
fn bench_method1(c: &mut Criterion) {
let v = VecDeque::from_iter(0..512);
c.bench_function("single", |b| {
b.iter_batched(
|| v.clone(),
|mut v| {
v.drain(256..=256);
v
},
criterion::BatchSize::LargeInput,
);
});
c.bench_function("middle", |b| {
b.iter_batched(
|| v.clone(),
|mut v| {
v.drain(128..384);
v
},
criterion::BatchSize::LargeInput,
);
});
c.bench_function("front", |b| {
b.iter_batched(
|| v.clone(),
|mut v| {
v.drain(..256);
v
},
criterion::BatchSize::LargeInput,
);
});
c.bench_function("back", |b| {
b.iter_batched(
|| v.clone(),
|mut v| {
v.drain(256..);
v
},
criterion::BatchSize::LargeInput,
);
});
c.bench_function("front blackboxed", |b| {
b.iter_batched(
|| v.clone(),
|mut v| {
v.drain(black_box(0)..256);
v
},
criterion::BatchSize::LargeInput,
);
});
c.bench_function("back blackboxed", |b| {
b.iter_batched(
|| v.clone(),
|mut v| {
v.drain(256..black_box(512));
v
},
criterion::BatchSize::LargeInput,
);
});
c.bench_function("noop", |b| {
b.iter_batched(
|| v.clone(),
|v| {
v
},
criterion::BatchSize::LargeInput,
);
});
c.bench_function("loop front", |b| {
b.iter_batched(
|| v.clone(),
|mut v| {
while v.len() >= 4 {
v.drain(..4);
black_box(&mut v);
}
},
criterion::BatchSize::LargeInput,
);
});
c.bench_function("loop middle", |b| {
b.iter_batched(
|| v.clone(),
|mut v| {
while v.len() >= 8 {
v.drain(v.len() / 2 - 4..v.len() / 2 + 4);
black_box(&mut v);
}
},
criterion::BatchSize::LargeInput,
);
});
let has_destructor = Rc::new(42);
let v = VecDeque::from_iter(iter::repeat_with(|| has_destructor.clone()).take(512));
c.bench_function("with destructor", |b| {
b.iter_batched(
|| v.clone(),
|mut v| {
v.drain(..256);
v
},
criterion::BatchSize::LargeInput,
);
});
}
criterion::criterion_group!(benches, bench_method1);
criterion::criterion_main!(benches);
Raw
new->old
single time: [27.201 ns 27.364 ns 27.520 ns]
change: [+3.3129% +5.0013% +6.7602%] (p = 0.00 < 0.05)
Performance has regressed.
Found 9 outliers among 100 measurements (9.00%)
2 (2.00%) low severe
3 (3.00%) low mild
1 (1.00%) high mild
3 (3.00%) high severe
middle time: [30.346 ns 30.727 ns 31.064 ns]
change: [-3.0489% -0.4959% +1.9250%] (p = 0.69 > 0.05)
No change in performance detected.
Found 14 outliers among 100 measurements (14.00%)
7 (7.00%) low severe
2 (2.00%) low mild
5 (5.00%) high mild
front time: [11.366 ns 11.456 ns 11.549 ns]
change: [+228.92% +270.94% +312.89%] (p = 0.00 < 0.05)
Performance has regressed.
Found 6 outliers among 100 measurements (6.00%)
1 (1.00%) high mild
5 (5.00%) high severe
back time: [18.106 ns 18.185 ns 18.278 ns]
change: [+516.15% +609.16% +701.83%] (p = 0.00 < 0.05)
Performance has regressed.
Found 5 outliers among 100 measurements (5.00%)
1 (1.00%) high mild
4 (4.00%) high severe
front blackboxed time: [17.104 ns 17.157 ns 17.220 ns]
change: [+17.880% +21.546% +24.889%] (p = 0.00 < 0.05)
Performance has regressed.
Found 8 outliers among 100 measurements (8.00%)
3 (3.00%) high mild
5 (5.00%) high severe
back blackboxed time: [17.904 ns 18.079 ns 18.288 ns]
change: [+38.290% +42.925% +47.105%] (p = 0.00 < 0.05)
Performance has regressed.
Found 10 outliers among 100 measurements (10.00%)
5 (5.00%) high mild
5 (5.00%) high severe
noop time: [3.2408 ns 3.3306 ns 3.4302 ns]
change: [-14.953% -5.8529% +3.7180%] (p = 0.27 > 0.05)
No change in performance detected.
Found 7 outliers among 100 measurements (7.00%)
1 (1.00%) low mild
2 (2.00%) high mild
4 (4.00%) high severe
loop front time: [614.81 ns 631.30 ns 650.10 ns]
change: [+312.32% +323.31% +336.37%] (p = 0.00 < 0.05)
Performance has regressed.
Found 4 outliers among 100 measurements (4.00%)
4 (4.00%) high mild
loop middle time: [845.83 ns 851.66 ns 858.01 ns]
change: [+17.500% +20.291% +23.042%] (p = 0.00 < 0.05)
Performance has regressed.
Found 18 outliers among 100 measurements (18.00%)
9 (9.00%) high mild
9 (9.00%) high severe
with destructor time: [356.03 ns 356.27 ns 356.52 ns]
change: [-2.0927% -1.1147% -0.2067%] (p = 0.02 < 0.05)
Change within noise threshold.
Found 12 outliers among 100 measurements (12.00%)
4 (4.00%) high mild
8 (8.00%) high severe
Raw
old->new
single time: [26.259 ns 26.539 ns 26.791 ns]
change: [-8.8511% -7.2264% -5.6593%] (p = 0.00 < 0.05)
Performance has improved.
Found 2 outliers among 100 measurements (2.00%)
1 (1.00%) high mild
1 (1.00%) high severe
middle time: [30.707 ns 31.108 ns 31.463 ns]
change: [+0.2810% +2.6158% +5.0190%] (p = 0.03 < 0.05)
Change within noise threshold.
Found 9 outliers among 100 measurements (9.00%)
4 (4.00%) low severe
5 (5.00%) low mild
front time: [2.5052 ns 2.5367 ns 2.5767 ns]
change: [-76.020% -73.459% -69.736%] (p = 0.00 < 0.05)
Performance has improved.
Found 9 outliers among 100 measurements (9.00%)
3 (3.00%) high mild
6 (6.00%) high severe
back time: [2.0339 ns 2.0819 ns 2.1351 ns]
change: [-87.187% -85.616% -83.262%] (p = 0.00 < 0.05)
Performance has improved.
Found 9 outliers among 100 measurements (9.00%)
2 (2.00%) high mild
7 (7.00%) high severe
front blackboxed time: [13.892 ns 13.983 ns 14.092 ns]
change: [-20.664% -18.300% -15.918%] (p = 0.00 < 0.05)
Performance has improved.
Found 13 outliers among 100 measurements (13.00%)
6 (6.00%) high mild
7 (7.00%) high severe
back blackboxed time: [12.278 ns 12.338 ns 12.406 ns]
change: [-30.817% -28.591% -26.533%] (p = 0.00 < 0.05)
Performance has improved.
Found 5 outliers among 100 measurements (5.00%)
2 (2.00%) high mild
3 (3.00%) high severe
noop time: [3.4973 ns 3.5853 ns 3.6758 ns]
change: [-6.2361% +3.4409% +14.771%] (p = 0.53 > 0.05)
No change in performance detected.
Found 5 outliers among 100 measurements (5.00%)
5 (5.00%) high severe
loop front time: [148.86 ns 149.48 ns 150.34 ns]
change: [-73.821% -73.588% -73.356%] (p = 0.00 < 0.05)
Performance has improved.
Found 14 outliers among 100 measurements (14.00%)
5 (5.00%) high mild
9 (9.00%) high severe
loop middle time: [740.77 ns 743.88 ns 747.16 ns]
change: [-11.650% -11.302% -10.958%] (p = 0.00 < 0.05)
Performance has improved.
Found 8 outliers among 100 measurements (8.00%)
6 (6.00%) high mild
2 (2.00%) high severe
with destructor time: [355.37 ns 355.84 ns 356.30 ns]
change: [+0.7229% +1.6541% +2.6818%] (p = 0.00 < 0.05)
Change within noise threshold.
Found 15 outliers among 100 measurements (15.00%)
1 (1.00%) high mild
14 (14.00%) high severe
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment