Trait SimdOps 

pub trait SimdOps {
    // Required methods
    fn add(a: &[Self], b: &[Self]) -> Vec<Self>
       where Self: Sized;
    fn sub(a: &[Self], b: &[Self]) -> Vec<Self>
       where Self: Sized;
    fn mul(a: &[Self], b: &[Self]) -> Vec<Self>
       where Self: Sized;
    fn dot(a: &[Self], b: &[Self]) -> Self
       where Self: Sized;
    fn cosine_distance(a: &[Self], b: &[Self]) -> Self
       where Self: Sized;
    fn euclidean_distance(a: &[Self], b: &[Self]) -> Self
       where Self: Sized;
    fn manhattan_distance(a: &[Self], b: &[Self]) -> Self
       where Self: Sized;
    fn norm(a: &[Self]) -> Self
       where Self: Sized;
    fn sum(a: &[Self]) -> Self
       where Self: Sized;
    fn mean(a: &[Self]) -> Self
       where Self: Sized;
}

Unified SIMD operations trait

Required Methods

fn add(a: &[Self], b: &[Self]) -> Vec<Self>

where Self: Sized,

Add two slices element-wise

fn sub(a: &[Self], b: &[Self]) -> Vec<Self>

where Self: Sized,

Subtract two slices element-wise

fn mul(a: &[Self], b: &[Self]) -> Vec<Self>

where Self: Sized,

Multiply two slices element-wise

fn dot(a: &[Self], b: &[Self]) -> Self

where Self: Sized,

Compute dot product

fn cosine_distance(a: &[Self], b: &[Self]) -> Self

where Self: Sized,

Compute cosine distance (1 - cosine_similarity)

fn euclidean_distance(a: &[Self], b: &[Self]) -> Self

where Self: Sized,

Compute Euclidean distance

fn manhattan_distance(a: &[Self], b: &[Self]) -> Self

where Self: Sized,

Compute Manhattan distance

fn norm(a: &[Self]) -> Self

where Self: Sized,

Compute L2 norm

fn sum(a: &[Self]) -> Self

where Self: Sized,

Sum all elements

fn mean(a: &[Self]) -> Self

where Self: Sized,

Compute mean

Dyn Compatibility

This trait is dyn compatible.

In older versions of Rust, dyn compatibility was called "object safety".

Implementations on Foreign Types

impl SimdOps for f32

SIMD implementation for f32

fn add(a: &[Self], b: &[Self]) -> Vec<Self>

fn sub(a: &[Self], b: &[Self]) -> Vec<Self>

fn mul(a: &[Self], b: &[Self]) -> Vec<Self>

fn dot(a: &[Self], b: &[Self]) -> Self

fn cosine_distance(a: &[Self], b: &[Self]) -> Self

fn euclidean_distance(a: &[Self], b: &[Self]) -> Self

fn manhattan_distance(a: &[Self], b: &[Self]) -> Self

fn norm(a: &[Self]) -> Self

fn sum(a: &[Self]) -> Self

fn mean(a: &[Self]) -> Self

impl SimdOps for f64

SIMD implementation for f64

fn add(a: &[Self], b: &[Self]) -> Vec<Self>

fn sub(a: &[Self], b: &[Self]) -> Vec<Self>

fn mul(a: &[Self], b: &[Self]) -> Vec<Self>

fn dot(a: &[Self], b: &[Self]) -> Self

fn cosine_distance(a: &[Self], b: &[Self]) -> Self

fn euclidean_distance(a: &[Self], b: &[Self]) -> Self

fn manhattan_distance(a: &[Self], b: &[Self]) -> Self

fn norm(a: &[Self]) -> Self

fn sum(a: &[Self]) -> Self

fn mean(a: &[Self]) -> Self

Implementors