nalgebra/benches/core/vector.rs

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use na::{DVector, SVector, Vector2, Vector3, Vector4};
use rand::Rng;
use rand_isaac::IsaacRng;
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use std::ops::{Add, Div, Mul, Sub};
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#[path = "../common/macros.rs"]
mod macros;
bench_binop!(vec2_add_v_f32, Vector2<f32>, Vector2<f32>, add);
bench_binop!(vec3_add_v_f32, Vector3<f32>, Vector3<f32>, add);
bench_binop!(vec4_add_v_f32, Vector4<f32>, Vector4<f32>, add);
bench_binop!(vec2_add_v_f64, Vector2<f64>, Vector2<f64>, add);
bench_binop!(vec3_add_v_f64, Vector3<f64>, Vector3<f64>, add);
bench_binop!(vec4_add_v_f64, Vector4<f64>, Vector4<f64>, add);
bench_binop!(vec2_sub_v, Vector2<f32>, Vector2<f32>, sub);
bench_binop!(vec3_sub_v, Vector3<f32>, Vector3<f32>, sub);
bench_binop!(vec4_sub_v, Vector4<f32>, Vector4<f32>, sub);
bench_binop!(vec2_mul_s, Vector2<f32>, f32, mul);
bench_binop!(vec3_mul_s, Vector3<f32>, f32, mul);
bench_binop!(vec4_mul_s, Vector4<f32>, f32, mul);
bench_binop!(vec2_div_s, Vector2<f32>, f32, div);
bench_binop!(vec3_div_s, Vector3<f32>, f32, div);
bench_binop!(vec4_div_s, Vector4<f32>, f32, div);
bench_binop_ref!(vec2_dot_f32, Vector2<f32>, Vector2<f32>, dot);
bench_binop_ref!(vec3_dot_f32, Vector3<f32>, Vector3<f32>, dot);
bench_binop_ref!(vec4_dot_f32, Vector4<f32>, Vector4<f32>, dot);
bench_binop_ref!(vec2_dot_f64, Vector2<f64>, Vector2<f64>, dot);
bench_binop_ref!(vec3_dot_f64, Vector3<f64>, Vector3<f64>, dot);
bench_binop_ref!(vec4_dot_f64, Vector4<f64>, Vector4<f64>, dot);
bench_binop_ref!(vec3_cross, Vector3<f32>, Vector3<f32>, cross);
bench_unop!(vec2_norm, Vector2<f32>, norm);
bench_unop!(vec3_norm, Vector3<f32>, norm);
bench_unop!(vec4_norm, Vector4<f32>, norm);
bench_unop!(vec2_normalize, Vector2<f32>, normalize);
bench_unop!(vec3_normalize, Vector3<f32>, normalize);
bench_unop!(vec4_normalize, Vector4<f32>, normalize);
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bench_binop_ref!(vec10000_dot_f64, SVector<f64, 10000>, SVector<f64, 10000>, dot);
bench_binop_ref!(vec10000_dot_f32, SVector<f32, 10000>, SVector<f32, 10000>, dot);
fn vec10000_axpy_f64(bh: &mut criterion::Criterion) {
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use rand::SeedableRng;
let mut rng = IsaacRng::seed_from_u64(0);
let mut a = DVector::new_random(10000);
let b = DVector::new_random(10000);
let n = rng.gen::<f64>();
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bh.bench_function("vec10000_axpy_f64", move |bh| {
bh.iter(|| a.axpy(n, &b, 1.0))
});
}
fn vec10000_axpy_beta_f64(bh: &mut criterion::Criterion) {
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use rand::SeedableRng;
let mut rng = IsaacRng::seed_from_u64(0);
let mut a = DVector::new_random(10000);
let b = DVector::new_random(10000);
let n = rng.gen::<f64>();
let beta = rng.gen::<f64>();
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bh.bench_function("vec10000_axpy_beta_f64", move |bh| {
bh.iter(|| a.axpy(n, &b, beta))
});
}
fn vec10000_axpy_f64_slice(bh: &mut criterion::Criterion) {
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use rand::SeedableRng;
let mut rng = IsaacRng::seed_from_u64(0);
let mut a = DVector::new_random(10000);
let b = DVector::new_random(10000);
let n = rng.gen::<f64>();
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bh.bench_function("vec10000_axpy_f64_slice", move |bh| {
bh.iter(|| {
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let mut a = a.fixed_rows_mut::<10000>(0);
let b = b.fixed_rows::<10000>(0);
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a.axpy(n, &b, 1.0)
})
});
}
fn vec10000_axpy_f64_static(bh: &mut criterion::Criterion) {
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use rand::SeedableRng;
let mut rng = IsaacRng::seed_from_u64(0);
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let mut a = SVector::<f64, 10000>::new_random();
let b = SVector::<f64, 10000>::new_random();
let n = rng.gen::<f64>();
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// NOTE: for some reasons, it is much faster if the arument are boxed (Box::new(OVector...)).
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bh.bench_function("vec10000_axpy_f64_static", move |bh| {
bh.iter(|| a.axpy(n, &b, 1.0))
});
}
fn vec10000_axpy_f32(bh: &mut criterion::Criterion) {
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use rand::SeedableRng;
let mut rng = IsaacRng::seed_from_u64(0);
let mut a = DVector::new_random(10000);
let b = DVector::new_random(10000);
let n = rng.gen::<f32>();
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bh.bench_function("vec10000_axpy_f32", move |bh| {
bh.iter(|| a.axpy(n, &b, 1.0))
});
}
fn vec10000_axpy_beta_f32(bh: &mut criterion::Criterion) {
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use rand::SeedableRng;
let mut rng = IsaacRng::seed_from_u64(0);
let mut a = DVector::new_random(10000);
let b = DVector::new_random(10000);
let n = rng.gen::<f32>();
let beta = rng.gen::<f32>();
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bh.bench_function("vec10000_axpy_beta_f32", move |bh| {
bh.iter(|| a.axpy(n, &b, beta))
});
}
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criterion_group!(
vector,
vec2_add_v_f32,
vec3_add_v_f32,
vec4_add_v_f32,
vec2_add_v_f64,
vec3_add_v_f64,
vec4_add_v_f64,
vec2_sub_v,
vec3_sub_v,
vec4_sub_v,
vec2_mul_s,
vec3_mul_s,
vec4_mul_s,
vec2_div_s,
vec3_div_s,
vec4_div_s,
vec2_dot_f32,
vec3_dot_f32,
vec4_dot_f32,
vec2_dot_f64,
vec3_dot_f64,
vec4_dot_f64,
vec3_cross,
vec2_norm,
vec3_norm,
vec4_norm,
vec2_normalize,
vec3_normalize,
vec4_normalize,
vec10000_dot_f64,
vec10000_dot_f32,
vec10000_axpy_f64,
vec10000_axpy_beta_f64,
vec10000_axpy_f64_slice,
vec10000_axpy_f64_static,
vec10000_axpy_f32,
vec10000_axpy_beta_f32
);