Module parallel

Parallel computation utilities for optimization algorithms

This module provides parallel implementations of computationally intensive operations used in optimization algorithms, including:

• Parallel function evaluations
• Parallel gradient approximations
• Multi-start optimization with parallel workers

Example

use scirs2_optimize::parallel::{parallel_finite_diff_gradient, ParallelOptions};
use ndarray::{array, ArrayView1};

fn objective(x: &ArrayView1<f64>) -> f64 {
    x.iter().map(|&xi| xi.powi(2)).sum()
}

let x = array![1.0, 2.0, 3.0];
let options = ParallelOptions::default();
let gradient = parallel_finite_diff_gradient(objective, x.view(), &options);

Structs

OptimizationResult

Result from an optimization run

ParallelMultiStart

Parallel multi-start optimization

ParallelOptions

Options for parallel computation

Functions

parallel_evaluate_batch

Parallel evaluation of multiple points

parallel_finite_diff_gradient

Parallel finite difference gradient approximation

parallel_finite_diff_hessian

Parallel computation of Hessian matrix using finite differences

parallel_line_search

Parallel line search