Crate ringkernel_montecarlo 

GPU-accelerated Monte Carlo primitives for variance reduction.

This crate provides variance reduction techniques for Monte Carlo simulation that can be accelerated on GPU via RingKernel.

Features

• Counter-based PRNGs: Philox and other stateless generators suitable for GPU
• Variance Reduction: Antithetic variates, control variates, importance sampling
• GPU Compatibility: All types are designed for zero-copy GPU transfer

Example

use ringkernel_montecarlo::prelude::*;

// Create a Philox-based RNG
let mut rng = PhiloxRng::new(0, 42);

// Generate uniform random numbers
let u: f32 = rng.next_uniform();

// Generate normal variates
let z: f32 = rng.next_normal();

// Antithetic variates for variance reduction
let (u1, u2) = antithetic_pair(&mut rng);
// u1 and u2 are negatively correlated

Re-exports

pub use rng::GpuRng;

pub use rng::PhiloxRng;

pub use rng::PhiloxState;

pub use variance::AntitheticVariates;

pub use variance::ControlVariates;

pub use variance::ImportanceSampling;

Modules

prelude

Prelude for convenient imports.

rng

Random number generators for GPU Monte Carlo.

variance

Variance reduction techniques for Monte Carlo simulation.

Enums

MonteCarloError

Error types for Monte Carlo operations.

Type Aliases

Result

Result type for Monte Carlo operations.