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rustytorch/crates/specialized/rtx-cfd/src/lib.rs
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2026-03-04 00:08:42 +00:00

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12 KiB
Rust

// Production-ready Computational Fluid Dynamics library for RustyTorch
// with GPU acceleration using cudarc 0.17.3
//#![deny(missing_docs)] // Temporarily disabled for development
#![allow(clippy::module_name_repetitions)]
//! # RTX CFD - Computational Fluid Dynamics for `RustyTorch`
//!
//! A production-ready CFD library with full GPU acceleration for solving incompressible
//! and compressible fluid flow problems. This crate provides:
//!
//! - **Mesh Management**: Structured and unstructured grids with adaptive refinement
//! - **Solvers**: SIMPLE, PISO algorithms for incompressible flows
//! - **Lattice Boltzmann**: D2Q9 and D3Q19 methods for complex geometries
//! - **Discretization**: Finite Volume Method (FVM) and Finite Difference Method (FDM)
//! - **Boundary Conditions**: Comprehensive BC support for all flow types
//! - **Turbulence Models**: k-ε and k-ω SST models
//! - **GPU Acceleration**: Custom CUDA kernels for maximum performance
//!
//! ## Quick Start
//!
//! ```rust
//! use rtx_cfd::{CfdConfig, init};
//!
//! // Initialize the CFD library
//! let config = CfdConfig::new()
//! .with_density(1000.0)
//! .with_viscosity(1e-6);
//!
//! // Calculate Reynolds number
//! let re = config.reynolds_number();
//! println!("Reynolds number: {}", re);
//!
//! // Initialize library
//! let _ = init();
//! ```
//!
//! ## Features
//!
//! - `cuda`: Enable NVIDIA GPU acceleration via cudarc
//! - `metal`: Enable Apple Metal GPU acceleration (macOS only)
//! - `metal4`: Enable Metal 4 features (requires macOS 26+)
//! - `rtx-integration`: Integration with RTX tensor and memory systems
/// Error types and result definitions for CFD operations
pub mod error;
/// Core traits for CFD components (solvers, fields, mesh entities)
pub mod traits;
// pub mod field;
/// Discretization schemes (FVM, FDM, TVD limiters)
pub mod discretization;
/// GPU kernels for CFD computations
pub mod kernels;
/// Mesh generation and management
pub mod mesh;
/// CFD solvers and algorithms
pub mod solvers;
// pub mod boundary;
/// GPU backend abstraction (CUDA/Metal)
pub mod compute;
/// Turbulence models (k-ε, Smagorinsky, wall functions)
pub mod turbulence;
// pub mod lbm;
// pub mod utils;
// Re-export core types for convenience
pub use error::{CfdError, CfdResult};
pub use traits::{
BoundaryCondition, BoundaryConditionType, CfdSolver, FluidField, MeshEntity, MeshEntityType,
SolverParameters, TimeIntegrator, TurbulenceModel, TurbulenceParameters,
};
/// CFD simulation configuration
#[derive(Debug, Clone)]
pub struct CfdConfig {
/// Grid dimensions
pub nx: usize,
pub ny: usize,
pub nz: usize,
/// Domain size
pub lx: f64,
pub ly: f64,
pub lz: f64,
/// Time step
pub dt: f64,
/// Physical properties
pub density: f64,
/// Dynamic viscosity
pub viscosity: f64,
/// Reference velocity
pub reference_velocity: f64,
/// Reference length
pub reference_length: f64,
/// Enable GPU acceleration
pub use_gpu: bool,
/// CUDA device ID
pub device_id: i32,
/// Memory pool size for GPU allocations (bytes)
pub gpu_memory_pool_size: usize,
}
impl Default for CfdConfig {
fn default() -> Self {
Self {
nx: 64,
ny: 64,
nz: 1,
lx: 1.0,
ly: 1.0,
lz: 1.0,
dt: 0.001,
density: 1.0, // kg/m³ (water at STP)
viscosity: 1e-3, // Pa·s (water at STP)
reference_velocity: 1.0, // m/s
reference_length: 1.0, // m
use_gpu: true,
device_id: 0,
gpu_memory_pool_size: 1024 * 1024 * 1024, // 1 GB
}
}
}
impl CfdConfig {
/// Create a new CFD configuration
#[must_use]
pub fn new() -> Self {
Self::default()
}
/// Set fluid density
#[must_use]
pub fn with_density(mut self, density: f64) -> Self {
self.density = density;
self
}
/// Set fluid viscosity
#[must_use]
pub fn with_viscosity(mut self, viscosity: f64) -> Self {
self.viscosity = viscosity;
self
}
/// Set reference velocity for non-dimensionalization
#[must_use]
pub fn with_reference_velocity(mut self, velocity: f64) -> Self {
self.reference_velocity = velocity;
self
}
/// Set reference length for non-dimensionalization
#[must_use]
pub fn with_reference_length(mut self, length: f64) -> Self {
self.reference_length = length;
self
}
/// Enable or disable GPU acceleration
#[must_use]
pub fn with_gpu(mut self, use_gpu: bool) -> Self {
self.use_gpu = use_gpu;
self
}
/// Set CUDA device ID
#[must_use]
pub fn with_device_id(mut self, device_id: i32) -> Self {
self.device_id = device_id;
self
}
/// Set GPU memory pool size
#[must_use]
pub fn with_gpu_memory_pool_size(mut self, size: usize) -> Self {
self.gpu_memory_pool_size = size;
self
}
/// Calculate Reynolds number
#[must_use]
pub fn reynolds_number(&self) -> f64 {
self.density * self.reference_velocity * self.reference_length / self.viscosity
}
/// Check if flow is laminar (Re < 2300 for pipe flow)
#[must_use]
pub fn is_laminar(&self) -> bool {
self.reynolds_number() < 2300.0
}
/// Check if flow is turbulent (Re > 4000 for pipe flow)
#[must_use]
pub fn is_turbulent(&self) -> bool {
self.reynolds_number() > 4000.0
}
/// Validate configuration parameters
pub fn validate(&self) -> CfdResult<()> {
if self.density <= 0.0 {
return Err(CfdError::invalid_parameter("Density must be positive"));
}
if self.viscosity <= 0.0 {
return Err(CfdError::invalid_parameter("Viscosity must be positive"));
}
if self.reference_velocity <= 0.0 {
return Err(CfdError::invalid_parameter(
"Reference velocity must be positive",
));
}
if self.reference_length <= 0.0 {
return Err(CfdError::invalid_parameter(
"Reference length must be positive",
));
}
if self.device_id < 0 {
return Err(CfdError::invalid_parameter(
"Device ID must be non-negative",
));
}
if self.gpu_memory_pool_size == 0 {
return Err(CfdError::invalid_parameter(
"GPU memory pool size must be positive",
));
}
Ok(())
}
}
/// Initialize the CFD library with GPU support
pub fn init() -> CfdResult<()> {
tracing::info!("Initializing RTX CFD library");
#[cfg(feature = "cuda")]
{
// Check for CUDA devices and initialize if available
match initialize_cuda() {
Ok(device_info) => {
tracing::info!("CUDA initialized successfully: {}", device_info);
}
Err(e) => {
tracing::warn!("CUDA initialization failed, falling back to CPU: {}", e);
tracing::info!("Running in CPU-only mode");
}
}
}
#[cfg(not(feature = "cuda"))]
{
tracing::info!("Running in CPU-only mode");
}
Ok(())
}
#[cfg(feature = "cuda")]
fn initialize_cuda() -> CfdResult<String> {
use crate::kernels::CudaKernelManager;
// Create a test configuration to check CUDA availability
let test_config = CfdConfig::default().with_device_id(0);
// Try to create a kernel manager to test CUDA initialization
match CudaKernelManager::new(&test_config) {
Ok(_manager) => Ok("CUDA device initialized successfully".to_string()),
Err(e) => Err(CfdError::gpu_error(&format!(
"Failed to initialize CUDA: {}",
e
))),
}
}
/// Check if CUDA is available and working
#[must_use]
pub fn cuda_available() -> bool {
#[cfg(feature = "cuda")]
{
initialize_cuda().is_ok()
}
#[cfg(not(feature = "cuda"))]
{
false
}
}
/// Get CUDA device information if available
pub fn cuda_device_info() -> CfdResult<CudaDeviceInfo> {
#[cfg(feature = "cuda")]
{
let test_config = CfdConfig::default().with_device_id(0);
let _manager = crate::kernels::CudaKernelManager::new(&test_config)?;
Ok(CudaDeviceInfo {
device_count: 1, // Simplified for now
device_name: "CUDA Device".to_string(),
memory_total: test_config.gpu_memory_pool_size,
compute_capability: (7, 5), // Default assumption
})
}
#[cfg(not(feature = "cuda"))]
{
Err(CfdError::not_implemented(
"CUDA not available in this build",
))
}
}
/// CUDA device information
#[derive(Debug, Clone)]
pub struct CudaDeviceInfo {
/// Number of CUDA devices
pub device_count: usize,
/// Device name
pub device_name: String,
/// Total GPU memory in bytes
pub memory_total: usize,
/// Compute capability (major, minor)
pub compute_capability: (i32, i32),
}
/// Get library version information
#[must_use]
pub fn version() -> &'static str {
env!("CARGO_PKG_VERSION")
}
/// Get build information
#[must_use]
pub fn build_info() -> BuildInfo {
BuildInfo {
version: version(),
features: get_features(),
cuda_support: cfg!(feature = "cuda"),
rtx_integration: false, // cfg!(feature = "rtx-integration"),
}
}
/// Build information structure
#[derive(Debug, Clone)]
pub struct BuildInfo {
/// Library version
pub version: &'static str,
/// Enabled features
pub features: Vec<&'static str>,
/// CUDA support enabled
pub cuda_support: bool,
/// RTX integration enabled
pub rtx_integration: bool,
}
fn get_features() -> Vec<&'static str> {
let features = Vec::new();
#[cfg(feature = "cuda")]
features.push("cuda");
// #[cfg(feature = "rtx-integration")]
// features.push("rtx-integration");
features
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_cfd_config_default() {
let config = CfdConfig::default();
assert_eq!(config.density, 1.0);
assert_eq!(config.viscosity, 1e-3);
assert!(config.use_gpu);
}
#[test]
fn test_cfd_config_builder() {
let config = CfdConfig::new()
.with_density(1000.0)
.with_viscosity(1e-6)
.with_reference_velocity(10.0)
.with_gpu(false);
assert_eq!(config.density, 1000.0);
assert_eq!(config.viscosity, 1e-6);
assert_eq!(config.reference_velocity, 10.0);
assert!(!config.use_gpu);
}
#[test]
fn test_reynolds_number() {
let config = CfdConfig::new()
.with_density(1.0)
.with_viscosity(1e-3)
.with_reference_velocity(1.0)
.with_reference_length(1.0);
assert_eq!(config.reynolds_number(), 1000.0);
}
#[test]
fn test_flow_regime() {
let laminar_config = CfdConfig::new()
.with_density(1.0)
.with_viscosity(1.0)
.with_reference_velocity(1.0)
.with_reference_length(1.0);
assert!(laminar_config.is_laminar());
let turbulent_config = CfdConfig::new()
.with_density(1.0)
.with_viscosity(1e-6)
.with_reference_velocity(10.0)
.with_reference_length(1.0);
assert!(turbulent_config.is_turbulent());
}
#[test]
fn test_config_validation() {
let valid_config = CfdConfig::default();
assert!(valid_config.validate().is_ok());
let invalid_config = CfdConfig::default().with_density(-1.0);
assert!(invalid_config.validate().is_err());
}
#[test]
fn test_version() {
assert!(!version().is_empty());
}
#[test]
fn test_build_info() {
let info = build_info();
assert!(!info.version.is_empty());
}
}