forked from M-Labs/nalgebra
193 lines
5.1 KiB
Rust
193 lines
5.1 KiB
Rust
use rand::{IsaacRng, Rng};
|
|
use test::{self, Bencher};
|
|
use na::{Vector2, Vector3, Vector4, Matrix2, Matrix3, Matrix4,
|
|
MatrixN, U10,
|
|
DMatrix, DVector};
|
|
use std::ops::{Add, Sub, Mul, Div};
|
|
|
|
#[path="../common/macros.rs"]
|
|
mod macros;
|
|
|
|
bench_binop!(mat2_mul_m, Matrix2<f32>, Matrix2<f32>, mul);
|
|
bench_binop!(mat3_mul_m, Matrix3<f32>, Matrix3<f32>, mul);
|
|
bench_binop!(mat4_mul_m, Matrix4<f32>, Matrix4<f32>, mul);
|
|
|
|
bench_binop_ref!(mat2_tr_mul_m, Matrix2<f32>, Matrix2<f32>, tr_mul);
|
|
bench_binop_ref!(mat3_tr_mul_m, Matrix3<f32>, Matrix3<f32>, tr_mul);
|
|
bench_binop_ref!(mat4_tr_mul_m, Matrix4<f32>, Matrix4<f32>, tr_mul);
|
|
|
|
bench_binop!(mat2_add_m, Matrix2<f32>, Matrix2<f32>, add);
|
|
bench_binop!(mat3_add_m, Matrix3<f32>, Matrix3<f32>, add);
|
|
bench_binop!(mat4_add_m, Matrix4<f32>, Matrix4<f32>, add);
|
|
|
|
bench_binop!(mat2_sub_m, Matrix2<f32>, Matrix2<f32>, sub);
|
|
bench_binop!(mat3_sub_m, Matrix3<f32>, Matrix3<f32>, sub);
|
|
bench_binop!(mat4_sub_m, Matrix4<f32>, Matrix4<f32>, sub);
|
|
|
|
bench_binop!(mat2_mul_v, Matrix2<f32>, Vector2<f32>, mul);
|
|
bench_binop!(mat3_mul_v, Matrix3<f32>, Vector3<f32>, mul);
|
|
bench_binop!(mat4_mul_v, Matrix4<f32>, Vector4<f32>, mul);
|
|
|
|
bench_binop_ref!(mat2_tr_mul_v, Matrix2<f32>, Vector2<f32>, tr_mul);
|
|
bench_binop_ref!(mat3_tr_mul_v, Matrix3<f32>, Vector3<f32>, tr_mul);
|
|
bench_binop_ref!(mat4_tr_mul_v, Matrix4<f32>, Vector4<f32>, tr_mul);
|
|
|
|
bench_binop!(mat2_mul_s, Matrix2<f32>, f32, mul);
|
|
bench_binop!(mat3_mul_s, Matrix3<f32>, f32, mul);
|
|
bench_binop!(mat4_mul_s, Matrix4<f32>, f32, mul);
|
|
|
|
bench_binop!(mat2_div_s, Matrix2<f32>, f32, div);
|
|
bench_binop!(mat3_div_s, Matrix3<f32>, f32, div);
|
|
bench_binop!(mat4_div_s, Matrix4<f32>, f32, div);
|
|
|
|
bench_unop!(mat2_inv, Matrix2<f32>, try_inverse);
|
|
bench_unop!(mat3_inv, Matrix3<f32>, try_inverse);
|
|
bench_unop!(mat4_inv, Matrix4<f32>, try_inverse);
|
|
|
|
bench_unop!(mat2_transpose, Matrix2<f32>, transpose);
|
|
bench_unop!(mat3_transpose, Matrix3<f32>, transpose);
|
|
bench_unop!(mat4_transpose, Matrix4<f32>, transpose);
|
|
|
|
#[bench]
|
|
fn mat_div_scalar(b: &mut Bencher) {
|
|
let a = DMatrix::from_row_slice(1000, 1000, &vec![2.0;1000000]);
|
|
let n = 42.0;
|
|
|
|
b.iter(|| {
|
|
let mut aa = a.clone();
|
|
let mut b = aa.slice_mut((0, 0), (1000, 1000));
|
|
b /= n
|
|
})
|
|
}
|
|
|
|
#[bench]
|
|
fn mat100_add_mat100(bench: &mut Bencher) {
|
|
let a = DMatrix::<f64>::new_random(100, 100);
|
|
let b = DMatrix::<f64>::new_random(100, 100);
|
|
|
|
bench.iter(|| { &a + &b })
|
|
}
|
|
|
|
#[bench]
|
|
fn mat4_mul_mat4(bench: &mut Bencher) {
|
|
let a = DMatrix::<f64>::new_random(4, 4);
|
|
let b = DMatrix::<f64>::new_random(4, 4);
|
|
|
|
bench.iter(|| { &a * &b })
|
|
}
|
|
|
|
#[bench]
|
|
fn mat5_mul_mat5(bench: &mut Bencher) {
|
|
let a = DMatrix::<f64>::new_random(5, 5);
|
|
let b = DMatrix::<f64>::new_random(5, 5);
|
|
|
|
bench.iter(|| { &a * &b })
|
|
}
|
|
|
|
#[bench]
|
|
fn mat6_mul_mat6(bench: &mut Bencher) {
|
|
let a = DMatrix::<f64>::new_random(6, 6);
|
|
let b = DMatrix::<f64>::new_random(6, 6);
|
|
|
|
bench.iter(|| { &a * &b })
|
|
}
|
|
|
|
#[bench]
|
|
fn mat7_mul_mat7(bench: &mut Bencher) {
|
|
let a = DMatrix::<f64>::new_random(7, 7);
|
|
let b = DMatrix::<f64>::new_random(7, 7);
|
|
|
|
bench.iter(|| { &a * &b })
|
|
}
|
|
|
|
#[bench]
|
|
fn mat8_mul_mat8(bench: &mut Bencher) {
|
|
let a = DMatrix::<f64>::new_random(8, 8);
|
|
let b = DMatrix::<f64>::new_random(8, 8);
|
|
|
|
bench.iter(|| { &a * &b })
|
|
}
|
|
|
|
#[bench]
|
|
fn mat9_mul_mat9(bench: &mut Bencher) {
|
|
let a = DMatrix::<f64>::new_random(9, 9);
|
|
let b = DMatrix::<f64>::new_random(9, 9);
|
|
|
|
bench.iter(|| { &a * &b })
|
|
}
|
|
|
|
#[bench]
|
|
fn mat10_mul_mat10(bench: &mut Bencher) {
|
|
let a = DMatrix::<f64>::new_random(10, 10);
|
|
let b = DMatrix::<f64>::new_random(10, 10);
|
|
|
|
bench.iter(|| { &a * &b })
|
|
}
|
|
|
|
#[bench]
|
|
fn mat10_mul_mat10_static(bench: &mut Bencher) {
|
|
let a = MatrixN::<f64, U10>::new_random();
|
|
let b = MatrixN::<f64, U10>::new_random();
|
|
|
|
bench.iter(|| { &a * &b })
|
|
}
|
|
|
|
#[bench]
|
|
fn mat100_mul_mat100(bench: &mut Bencher) {
|
|
let a = DMatrix::<f64>::new_random(100, 100);
|
|
let b = DMatrix::<f64>::new_random(100, 100);
|
|
|
|
bench.iter(|| { &a * &b })
|
|
}
|
|
|
|
#[bench]
|
|
fn mat500_mul_mat500(bench: &mut Bencher) {
|
|
let a = DMatrix::<f64>::from_element(500, 500, 5f64);
|
|
let b = DMatrix::<f64>::from_element(500, 500, 6f64);
|
|
|
|
bench.iter(|| { &a * &b })
|
|
}
|
|
|
|
#[bench]
|
|
fn copy_from(bench: &mut Bencher) {
|
|
let a = DMatrix::<f64>::new_random(1000, 1000);
|
|
let mut b = DMatrix::<f64>::new_random(1000, 1000);
|
|
|
|
bench.iter(|| {
|
|
b.copy_from(&a);
|
|
})
|
|
}
|
|
|
|
#[bench]
|
|
fn axpy(bench: &mut Bencher) {
|
|
let x = DVector::<f64>::from_element(100000, 2.0);
|
|
let mut y = DVector::<f64>::from_element(100000, 3.0);
|
|
let a = 42.0;
|
|
|
|
bench.iter(|| {
|
|
y.axpy(a, &x, 1.0);
|
|
})
|
|
}
|
|
|
|
#[bench]
|
|
fn tr_mul_to(bench: &mut Bencher) {
|
|
let a = DMatrix::<f64>::new_random(1000, 1000);
|
|
let b = DVector::<f64>::new_random(1000);
|
|
let mut c = DVector::from_element(1000, 0.0);
|
|
|
|
bench.iter(|| {
|
|
a.tr_mul_to(&b, &mut c)
|
|
})
|
|
}
|
|
|
|
#[bench]
|
|
fn mat_mul_mat(bench: &mut Bencher) {
|
|
let a = DMatrix::<f64>::new_random(100, 100);
|
|
let b = DMatrix::<f64>::new_random(100, 100);
|
|
let mut ab = DMatrix::<f64>::from_element(100, 100, 0.0);
|
|
|
|
bench.iter(|| {
|
|
test::black_box(a.mul_to(&b, &mut ab));
|
|
})
|
|
}
|