diff --git a/crates/core_simd/examples/spectral_norm.rs b/crates/core_simd/examples/spectral_norm.rs new file mode 100644 index 00000000000..c515dad4dea --- /dev/null +++ b/crates/core_simd/examples/spectral_norm.rs @@ -0,0 +1,77 @@ +#![feature(portable_simd)] + +use core_simd::simd::*; + +fn a(i: usize, j: usize) -> f64 { + ((i + j) * (i + j + 1) / 2 + i + 1) as f64 +} + +fn mult_av(v: &[f64], out: &mut [f64]) { + assert!(v.len() == out.len()); + assert!(v.len() % 2 == 0); + + for (i, out) in out.iter_mut().enumerate() { + let mut sum = f64x2::splat(0.0); + + let mut j = 0; + while j < v.len() { + let b = f64x2::from_slice(&v[j..]); + let a = f64x2::from_array([a(i, j), a(i, j + 1)]); + sum += b / a; + j += 2 + } + *out = sum.horizontal_sum(); + } +} + +fn mult_atv(v: &[f64], out: &mut [f64]) { + assert!(v.len() == out.len()); + assert!(v.len() % 2 == 0); + + for (i, out) in out.iter_mut().enumerate() { + let mut sum = f64x2::splat(0.0); + + let mut j = 0; + while j < v.len() { + let b = f64x2::from_slice(&v[j..]); + let a = f64x2::from_array([a(j, i), a(j + 1, i)]); + sum += b / a; + j += 2 + } + *out = sum.horizontal_sum(); + } +} + +fn mult_atav(v: &[f64], out: &mut [f64], tmp: &mut [f64]) { + mult_av(v, tmp); + mult_atv(tmp, out); +} + +pub fn spectral_norm(n: usize) -> f64 { + assert!(n % 2 == 0, "only even lengths are accepted"); + + let mut u = vec![1.0; n]; + let mut v = u.clone(); + let mut tmp = u.clone(); + + for _ in 0..10 { + mult_atav(&u, &mut v, &mut tmp); + mult_atav(&v, &mut u, &mut tmp); + } + (dot(&u, &v) / dot(&v, &v)).sqrt() +} + +fn dot(x: &[f64], y: &[f64]) -> f64 { + // This is auto-vectorized: + x.iter().zip(y).map(|(&x, &y)| x * y).sum() +} + +#[cfg(test)] +#[test] +fn test() { + assert_eq!(&format!("{:.9}", spectral_norm(100)), "1.274219991"); +} + +fn main() { + // Empty main to make cargo happy +}