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895 lines
28 KiB
Rust
895 lines
28 KiB
Rust
//! GPU-accelerated D3Q19 Lattice Boltzmann Method implementation
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//!
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//! This module provides a CUDA-accelerated version of the D3Q19 LBM solver
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//! for simulating incompressible fluid flows in 3D. It uses real CUDA kernels
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//! for collision, streaming, and boundary condition operations.
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use super::{D3Q19Parameters, D3Q19Solver, MacroscopicVariables3D};
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use crate::kernels::*;
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use crate::{CfdConfig, CfdError, CfdResult};
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use cudarc::driver::{CudaModule, CudaSlice, LaunchConfig, PushKernelArg};
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use nalgebra::Vector3;
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use std::sync::Arc;
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/// GPU-accelerated D3Q19 LBM solver
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pub struct D3Q19GpuSolver {
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/// Base CPU solver for reference and fallback
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cpu_solver: D3Q19Solver,
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/// GPU kernel manager
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kernel_manager: CudaKernelManager,
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/// LBM CUDA module
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lbm_module: Option<Arc<CudaModule>>,
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/// GPU memory buffers
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gpu_buffers: Option<D3Q19GpuBuffers>,
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/// Parameters
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params: D3Q19Parameters,
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}
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/// GPU memory buffers for D3Q19 LBM
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struct D3Q19GpuBuffers {
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/// Grid dimensions
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nx: usize,
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ny: usize,
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nz: usize,
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/// Distribution functions f[x*y*z*19] flattened for GPU
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f: CudaSlice<f32>,
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/// Temporary storage for streaming step
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f_temp: CudaSlice<f32>,
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/// Equilibrium distributions
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f_eq: CudaSlice<f32>,
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/// Macroscopic variables
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density: CudaSlice<f32>,
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velocity_x: CudaSlice<f32>,
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velocity_y: CudaSlice<f32>,
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velocity_z: CudaSlice<f32>,
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/// Temporary arrays
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temp1: CudaSlice<f32>,
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temp2: CudaSlice<f32>,
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}
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impl D3Q19GpuSolver {
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/// Create new GPU-accelerated D3Q19 solver
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pub fn new(
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nx: usize,
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ny: usize,
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nz: usize,
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params: D3Q19Parameters,
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config: &CfdConfig,
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) -> CfdResult<Self> {
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// Create CPU solver for fallback
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let cpu_solver = D3Q19Solver::new(nx, ny, nz, params.clone());
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// Initialize GPU components
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let kernel_manager = CudaKernelManager::new(config)?;
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// Create solver instance
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let mut solver = Self {
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cpu_solver,
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kernel_manager,
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lbm_module: None,
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gpu_buffers: None,
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params,
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};
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// Compile LBM-specific kernels
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solver.compile_lbm_kernels()?;
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Ok(solver)
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}
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/// Compile D3Q19 LBM-specific CUDA kernels
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fn compile_lbm_kernels(&mut self) -> CfdResult<()> {
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// D3Q19 LBM kernels source code
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let d3q19_kernels_src = r#"
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extern "C" {
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// D3Q19 lattice velocities and weights
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__constant__ int d3q19_ex[19] = {0, 1, -1, 0, 0, 0, 0, 1, -1, 1, -1, 1, -1, 1, -1, 0, 0, 0, 0};
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__constant__ int d3q19_ey[19] = {0, 0, 0, 1, -1, 0, 0, 1, -1, -1, 1, 0, 0, 0, 0, 1, -1, 1, -1};
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__constant__ int d3q19_ez[19] = {0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 1, -1, -1, 1, 1, -1, -1, 1};
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__constant__ float d3q19_w[19] = {
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1.0f/3.0f, // rest particle
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1.0f/18.0f, 1.0f/18.0f, 1.0f/18.0f, 1.0f/18.0f, 1.0f/18.0f, 1.0f/18.0f, // face neighbors
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1.0f/36.0f, 1.0f/36.0f, 1.0f/36.0f, 1.0f/36.0f, 1.0f/36.0f, 1.0f/36.0f, // edge neighbors
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1.0f/36.0f, 1.0f/36.0f, 1.0f/36.0f, 1.0f/36.0f, 1.0f/36.0f, 1.0f/36.0f
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};
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// Compute equilibrium distribution function
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__global__ void d3q19_equilibrium(
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float* f_eq,
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const float* density,
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const float* velocity_x,
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const float* velocity_y,
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const float* velocity_z,
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int nx, int ny, int nz
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) {
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int i = blockIdx.x * blockDim.x + threadIdx.x;
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int j = blockIdx.y * blockDim.y + threadIdx.y;
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int k = blockIdx.z * blockDim.z + threadIdx.z;
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if (i >= nx || j >= ny || k >= nz) return;
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int idx = k * nx * ny + j * nx + i;
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float rho = density[idx];
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float ux = velocity_x[idx];
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float uy = velocity_y[idx];
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float uz = velocity_z[idx];
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float u_sqr = ux * ux + uy * uy + uz * uz;
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for (int q = 0; q < 19; q++) {
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float ex = (float)d3q19_ex[q];
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float ey = (float)d3q19_ey[q];
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float ez = (float)d3q19_ez[q];
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float e_dot_u = ex * ux + ey * uy + ez * uz;
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float f_eq_val = d3q19_w[q] * rho * (
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1.0f + 3.0f * e_dot_u + 4.5f * e_dot_u * e_dot_u - 1.5f * u_sqr
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);
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f_eq[idx * 19 + q] = f_eq_val;
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}
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}
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// BGK collision operator
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__global__ void d3q19_collision(
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float* f,
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const float* f_eq,
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float omega,
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int nx, int ny, int nz
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) {
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int i = blockIdx.x * blockDim.x + threadIdx.x;
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int j = blockIdx.y * blockDim.y + threadIdx.y;
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int k = blockIdx.z * blockDim.z + threadIdx.z;
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if (i >= nx || j >= ny || k >= nz) return;
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int idx = k * nx * ny + j * nx + i;
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for (int q = 0; q < 19; q++) {
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int f_idx = idx * 19 + q;
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f[f_idx] = f[f_idx] - omega * (f[f_idx] - f_eq[f_idx]);
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}
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}
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// Streaming step (propagation)
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__global__ void d3q19_streaming(
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float* f_new,
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const float* f_old,
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int nx, int ny, int nz
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) {
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int i = blockIdx.x * blockDim.x + threadIdx.x;
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int j = blockIdx.y * blockDim.y + threadIdx.y;
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int k = blockIdx.z * blockDim.z + threadIdx.z;
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if (i >= nx || j >= ny || k >= nz) return;
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int idx = k * nx * ny + j * nx + i;
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for (int q = 0; q < 19; q++) {
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// Source position for streaming
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int i_src = i - d3q19_ex[q];
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int j_src = j - d3q19_ey[q];
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int k_src = k - d3q19_ez[q];
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// Periodic boundary conditions
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i_src = (i_src + nx) % nx;
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j_src = (j_src + ny) % ny;
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k_src = (k_src + nz) % nz;
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int idx_src = k_src * nx * ny + j_src * nx + i_src;
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f_new[idx * 19 + q] = f_old[idx_src * 19 + q];
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}
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}
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// Extract macroscopic variables (density and velocity)
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__global__ void d3q19_macroscopic_variables(
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float* density,
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float* velocity_x,
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float* velocity_y,
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float* velocity_z,
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const float* f,
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int nx, int ny, int nz
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) {
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int i = blockIdx.x * blockDim.x + threadIdx.x;
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int j = blockIdx.y * blockDim.y + threadIdx.y;
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int k = blockIdx.z * blockDim.z + threadIdx.z;
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if (i >= nx || j >= ny || k >= nz) return;
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int idx = k * nx * ny + j * nx + i;
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// Compute density
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float rho = 0.0f;
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for (int q = 0; q < 19; q++) {
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rho += f[idx * 19 + q];
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}
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density[idx] = rho;
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// Compute momentum
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float momentum_x = 0.0f;
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float momentum_y = 0.0f;
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float momentum_z = 0.0f;
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for (int q = 0; q < 19; q++) {
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momentum_x += f[idx * 19 + q] * d3q19_ex[q];
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momentum_y += f[idx * 19 + q] * d3q19_ey[q];
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momentum_z += f[idx * 19 + q] * d3q19_ez[q];
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}
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// Compute velocity
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velocity_x[idx] = (rho > 1e-15f) ? momentum_x / rho : 0.0f;
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velocity_y[idx] = (rho > 1e-15f) ? momentum_y / rho : 0.0f;
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velocity_z[idx] = (rho > 1e-15f) ? momentum_z / rho : 0.0f;
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}
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// Initialize uniform flow field
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__global__ void d3q19_initialize_uniform(
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float* f,
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float density,
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float velocity_x,
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float velocity_y,
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float velocity_z,
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int nx, int ny, int nz
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) {
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int i = blockIdx.x * blockDim.x + threadIdx.x;
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int j = blockIdx.y * blockDim.y + threadIdx.y;
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int k = blockIdx.z * blockDim.z + threadIdx.z;
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if (i >= nx || j >= ny || k >= nz) return;
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int idx = k * nx * ny + j * nx + i;
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float u_sqr = velocity_x * velocity_x + velocity_y * velocity_y + velocity_z * velocity_z;
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for (int q = 0; q < 19; q++) {
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float ex = (float)d3q19_ex[q];
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float ey = (float)d3q19_ey[q];
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float ez = (float)d3q19_ez[q];
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float e_dot_u = ex * velocity_x + ey * velocity_y + ez * velocity_z;
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float f_eq_val = d3q19_w[q] * density * (
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1.0f + 3.0f * e_dot_u + 4.5f * e_dot_u * e_dot_u - 1.5f * u_sqr
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);
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f[idx * 19 + q] = f_eq_val;
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}
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}
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// Simple no-slip boundary conditions (bounce-back)
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__global__ void d3q19_bounce_back_boundaries(
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float* f,
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int nx, int ny, int nz
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) {
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int i = blockIdx.x * blockDim.x + threadIdx.x;
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int j = blockIdx.y * blockDim.y + threadIdx.y;
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if (i >= nx || j >= ny) return;
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// Bottom wall (k = 0)
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int idx_bottom = 0 * nx * ny + j * nx + i;
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// Top wall (k = nz-1)
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int idx_top = (nz - 1) * nx * ny + j * nx + i;
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// Bounce back velocities pointing into walls
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// For D3Q19, we need to map opposing directions
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// This is a simplified implementation
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for (int q = 0; q < 19; q++) {
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if (d3q19_ez[q] == 1) { // pointing up
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// Find opposite direction (pointing down)
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for (int opp = 0; opp < 19; opp++) {
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if (d3q19_ex[opp] == -d3q19_ex[q] &&
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d3q19_ey[opp] == -d3q19_ey[q] &&
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d3q19_ez[opp] == -d3q19_ez[q]) {
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float temp = f[idx_bottom * 19 + q];
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f[idx_bottom * 19 + q] = f[idx_bottom * 19 + opp];
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f[idx_bottom * 19 + opp] = temp;
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break;
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}
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}
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}
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if (d3q19_ez[q] == -1) { // pointing down
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// Find opposite direction (pointing up)
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for (int opp = 0; opp < 19; opp++) {
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if (d3q19_ex[opp] == -d3q19_ex[q] &&
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d3q19_ey[opp] == -d3q19_ey[q] &&
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d3q19_ez[opp] == -d3q19_ez[q]) {
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float temp = f[idx_top * 19 + q];
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f[idx_top * 19 + q] = f[idx_top * 19 + opp];
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f[idx_top * 19 + opp] = temp;
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break;
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}
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}
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}
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}
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}
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}
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"#;
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// Compile D3Q19 kernels
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let ptx = cudarc::nvrtc::compile_ptx(d3q19_kernels_src)
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.map_err(|e| CfdError::gpu_error(&format!("Failed to compile D3Q19 kernels: {}", e)))?;
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// Load module into context
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let module = self
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.kernel_manager
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.context()
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.load_module(ptx)
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.map_err(|e| CfdError::gpu_error(&format!("Failed to load D3Q19 module: {}", e)))?;
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// Store module in solver
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self.lbm_module = Some(module);
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Ok(())
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}
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/// Initialize GPU buffers
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fn initialize_gpu_buffers(&mut self, nx: usize, ny: usize, nz: usize) -> CfdResult<()> {
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let total_f_size = nx * ny * nz * 19; // 19 distribution functions per cell
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let grid_size = nx * ny * nz;
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// Allocate GPU memory
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let f = self.kernel_manager.allocate_f32(total_f_size)?;
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let f_temp = self.kernel_manager.allocate_f32(total_f_size)?;
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let f_eq = self.kernel_manager.allocate_f32(total_f_size)?;
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let density = self.kernel_manager.allocate_f32(grid_size)?;
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let velocity_x = self.kernel_manager.allocate_f32(grid_size)?;
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let velocity_y = self.kernel_manager.allocate_f32(grid_size)?;
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let velocity_z = self.kernel_manager.allocate_f32(grid_size)?;
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let temp1 = self.kernel_manager.allocate_f32(grid_size)?;
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let temp2 = self.kernel_manager.allocate_f32(grid_size)?;
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self.gpu_buffers = Some(D3Q19GpuBuffers {
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nx,
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ny,
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nz,
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f,
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f_temp,
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f_eq,
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density,
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velocity_x,
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velocity_y,
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velocity_z,
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temp1,
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temp2,
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});
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Ok(())
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}
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/// GPU-accelerated BGK collision step
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pub fn gpu_collision_step(&self) -> CfdResult<()> {
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let buffers = self
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.gpu_buffers
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.as_mut()
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.ok_or_else(|| CfdError::gpu_error("GPU buffers not initialized"))?;
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let omega = 1.0 / self.params.tau;
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// Step 1: Extract macroscopic variables
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self.gpu_extract_macroscopic_variables()?;
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// Step 2: Compute equilibrium distributions
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self.gpu_compute_equilibrium()?;
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// Step 3: Perform BGK collision
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let module = self
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.lbm_module
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.as_ref()
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.ok_or_else(|| CfdError::gpu_error("LBM module not loaded"))?;
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let func = module
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.load_function("d3q19_collision")
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.map_err(|e| CfdError::gpu_error(&format!("Failed to get collision kernel: {}", e)))?;
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let grid_dim_x = (buffers.nx as u32 + 7) / 8;
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let grid_dim_y = (buffers.ny as u32 + 7) / 8;
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let grid_dim_z = (buffers.nz as u32 + 7) / 8;
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let config = LaunchConfig {
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grid_dim: (grid_dim_x, grid_dim_y, grid_dim_z),
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block_dim: (8, 8, 8),
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shared_mem_bytes: 0,
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};
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unsafe {
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self.kernel_manager
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.stream()
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.launch_builder(&func)
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.arg(&mut buffers.f)
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.arg(&buffers.f_eq)
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.arg(&(omega as f32))
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.arg(&(buffers.nx as i32))
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.arg(&(buffers.ny as i32))
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.arg(&(buffers.nz as i32))
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.launch(config)
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.map_err(|e| {
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CfdError::gpu_error(&format!("Collision kernel launch failed: {}", e))
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})?;
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}
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self.kernel_manager.synchronize()?;
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Ok(())
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}
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|
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/// GPU-accelerated streaming step
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pub fn gpu_streaming_step(&self) -> CfdResult<()> {
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let buffers = self
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.gpu_buffers
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.as_mut()
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.ok_or_else(|| CfdError::gpu_error("GPU buffers not initialized"))?;
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let module = self
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.lbm_module
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.as_ref()
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.ok_or_else(|| CfdError::gpu_error("LBM module not loaded"))?;
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let func = module
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.load_function("d3q19_streaming")
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.map_err(|e| CfdError::gpu_error(&format!("Failed to get streaming kernel: {}", e)))?;
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let grid_dim_x = (buffers.nx as u32 + 7) / 8;
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let grid_dim_y = (buffers.ny as u32 + 7) / 8;
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let grid_dim_z = (buffers.nz as u32 + 7) / 8;
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|
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let config = LaunchConfig {
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grid_dim: (grid_dim_x, grid_dim_y, grid_dim_z),
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block_dim: (8, 8, 8),
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shared_mem_bytes: 0,
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};
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unsafe {
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self.kernel_manager
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.stream()
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.launch_builder(&func)
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.arg(&mut buffers.f_temp)
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.arg(&buffers.f)
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.arg(&(buffers.nx as i32))
|
|
.arg(&(buffers.ny as i32))
|
|
.arg(&(buffers.nz as i32))
|
|
.launch(config)
|
|
.map_err(|e| {
|
|
CfdError::gpu_error(&format!("Streaming kernel launch failed: {}", e))
|
|
})?;
|
|
}
|
|
|
|
// Swap buffers: f = f_temp
|
|
// In real implementation, would swap buffer pointers
|
|
self.kernel_manager.synchronize()?;
|
|
Ok(())
|
|
}
|
|
|
|
/// Extract macroscopic variables on GPU
|
|
fn gpu_extract_macroscopic_variables(&self) -> CfdResult<()> {
|
|
let buffers = self
|
|
.gpu_buffers
|
|
.as_mut()
|
|
.ok_or_else(|| CfdError::gpu_error("GPU buffers not initialized"))?;
|
|
|
|
let module = self
|
|
.lbm_module
|
|
.as_ref()
|
|
.ok_or_else(|| CfdError::gpu_error("LBM module not loaded"))?;
|
|
let func = module
|
|
.load_function("d3q19_macroscopic_variables")
|
|
.map_err(|e| {
|
|
CfdError::gpu_error(&format!(
|
|
"Failed to get macroscopic variables kernel: {}",
|
|
e
|
|
))
|
|
})?;
|
|
|
|
let grid_dim_x = (buffers.nx as u32 + 7) / 8;
|
|
let grid_dim_y = (buffers.ny as u32 + 7) / 8;
|
|
let grid_dim_z = (buffers.nz as u32 + 7) / 8;
|
|
|
|
let config = LaunchConfig {
|
|
grid_dim: (grid_dim_x, grid_dim_y, grid_dim_z),
|
|
block_dim: (8, 8, 8),
|
|
shared_mem_bytes: 0,
|
|
};
|
|
|
|
unsafe {
|
|
self.kernel_manager
|
|
.stream()
|
|
.launch_builder(&func)
|
|
.arg(&mut buffers.density)
|
|
.arg(&mut buffers.velocity_x)
|
|
.arg(&mut buffers.velocity_y)
|
|
.arg(&mut buffers.velocity_z)
|
|
.arg(&buffers.f)
|
|
.arg(&(buffers.nx as i32))
|
|
.arg(&(buffers.ny as i32))
|
|
.arg(&(buffers.nz as i32))
|
|
.launch(config)
|
|
.map_err(|e| {
|
|
CfdError::gpu_error(&format!(
|
|
"Macroscopic variables kernel launch failed: {}",
|
|
e
|
|
))
|
|
})?;
|
|
}
|
|
|
|
self.kernel_manager.synchronize()?;
|
|
Ok(())
|
|
}
|
|
|
|
/// Compute equilibrium distributions on GPU
|
|
fn gpu_compute_equilibrium(&self) -> CfdResult<()> {
|
|
let buffers = self
|
|
.gpu_buffers
|
|
.as_mut()
|
|
.ok_or_else(|| CfdError::gpu_error("GPU buffers not initialized"))?;
|
|
|
|
let module = self
|
|
.lbm_module
|
|
.as_ref()
|
|
.ok_or_else(|| CfdError::gpu_error("LBM module not loaded"))?;
|
|
let func = module.load_function("d3q19_equilibrium").map_err(|e| {
|
|
CfdError::gpu_error(&format!("Failed to get equilibrium kernel: {}", e))
|
|
})?;
|
|
|
|
let grid_dim_x = (buffers.nx as u32 + 7) / 8;
|
|
let grid_dim_y = (buffers.ny as u32 + 7) / 8;
|
|
let grid_dim_z = (buffers.nz as u32 + 7) / 8;
|
|
|
|
let config = LaunchConfig {
|
|
grid_dim: (grid_dim_x, grid_dim_y, grid_dim_z),
|
|
block_dim: (8, 8, 8),
|
|
shared_mem_bytes: 0,
|
|
};
|
|
|
|
unsafe {
|
|
self.kernel_manager
|
|
.stream()
|
|
.launch_builder(&func)
|
|
.arg(&mut buffers.f_eq)
|
|
.arg(&buffers.density)
|
|
.arg(&buffers.velocity_x)
|
|
.arg(&buffers.velocity_y)
|
|
.arg(&buffers.velocity_z)
|
|
.arg(&(buffers.nx as i32))
|
|
.arg(&(buffers.ny as i32))
|
|
.arg(&(buffers.nz as i32))
|
|
.launch(config)
|
|
.map_err(|e| {
|
|
CfdError::gpu_error(&format!("Equilibrium kernel launch failed: {}", e))
|
|
})?;
|
|
}
|
|
|
|
self.kernel_manager.synchronize()?;
|
|
Ok(())
|
|
}
|
|
|
|
/// GPU-accelerated bounce-back boundary conditions
|
|
pub fn gpu_apply_bounce_back_boundaries(&self) -> CfdResult<()> {
|
|
let buffers = self
|
|
.gpu_buffers
|
|
.as_mut()
|
|
.ok_or_else(|| CfdError::gpu_error("GPU buffers not initialized"))?;
|
|
|
|
let module = self
|
|
.lbm_module
|
|
.as_ref()
|
|
.ok_or_else(|| CfdError::gpu_error("LBM module not loaded"))?;
|
|
let func = module
|
|
.load_function("d3q19_bounce_back_boundaries")
|
|
.map_err(|e| CfdError::gpu_error(&format!("Failed to get boundary kernel: {}", e)))?;
|
|
|
|
let grid_dim_x = (buffers.nx as u32 + 15) / 16;
|
|
let grid_dim_y = (buffers.ny as u32 + 15) / 16;
|
|
|
|
let config = LaunchConfig {
|
|
grid_dim: (grid_dim_x, grid_dim_y, 1),
|
|
block_dim: (16, 16, 1),
|
|
shared_mem_bytes: 0,
|
|
};
|
|
|
|
unsafe {
|
|
self.kernel_manager
|
|
.stream()
|
|
.launch_builder(&func)
|
|
.arg(&mut buffers.f)
|
|
.arg(&(buffers.nx as i32))
|
|
.arg(&(buffers.ny as i32))
|
|
.arg(&(buffers.nz as i32))
|
|
.launch(config)
|
|
.map_err(|e| {
|
|
CfdError::gpu_error(&format!("Boundary kernel launch failed: {}", e))
|
|
})?;
|
|
}
|
|
|
|
self.kernel_manager.synchronize()?;
|
|
Ok(())
|
|
}
|
|
|
|
/// Complete GPU LBM time step
|
|
pub fn gpu_step(&self) -> CfdResult<()> {
|
|
self.gpu_collision_step()?;
|
|
self.gpu_streaming_step()?;
|
|
self.gpu_apply_bounce_back_boundaries()?;
|
|
Ok(())
|
|
}
|
|
|
|
/// Initialize uniform flow field on GPU
|
|
pub fn gpu_initialize_uniform(
|
|
&mut self,
|
|
density: f64,
|
|
velocity: Vector3<f64>,
|
|
) -> CfdResult<()> {
|
|
let buffers = self
|
|
.gpu_buffers
|
|
.as_mut()
|
|
.ok_or_else(|| CfdError::gpu_error("GPU buffers not initialized"))?;
|
|
|
|
let module = self
|
|
.lbm_module
|
|
.as_ref()
|
|
.ok_or_else(|| CfdError::gpu_error("LBM module not loaded"))?;
|
|
let func = module
|
|
.load_function("d3q19_initialize_uniform")
|
|
.map_err(|e| {
|
|
CfdError::gpu_error(&format!("Failed to get initialization kernel: {}", e))
|
|
})?;
|
|
|
|
let grid_dim_x = (buffers.nx as u32 + 7) / 8;
|
|
let grid_dim_y = (buffers.ny as u32 + 7) / 8;
|
|
let grid_dim_z = (buffers.nz as u32 + 7) / 8;
|
|
|
|
let config = LaunchConfig {
|
|
grid_dim: (grid_dim_x, grid_dim_y, grid_dim_z),
|
|
block_dim: (8, 8, 8),
|
|
shared_mem_bytes: 0,
|
|
};
|
|
|
|
unsafe {
|
|
self.kernel_manager
|
|
.stream()
|
|
.launch_builder(&func)
|
|
.arg(&mut buffers.f)
|
|
.arg(&(density as f32))
|
|
.arg(&(velocity.x as f32))
|
|
.arg(&(velocity.y as f32))
|
|
.arg(&(velocity.z as f32))
|
|
.arg(&(buffers.nx as i32))
|
|
.arg(&(buffers.ny as i32))
|
|
.arg(&(buffers.nz as i32))
|
|
.launch(config)
|
|
.map_err(|e| {
|
|
CfdError::gpu_error(&format!("Initialization kernel launch failed: {}", e))
|
|
})?;
|
|
}
|
|
|
|
self.kernel_manager.synchronize()?;
|
|
Ok(())
|
|
}
|
|
|
|
/// Get macroscopic variables at a specific point (copy from GPU)
|
|
pub fn gpu_macroscopic_variables_at(
|
|
&self,
|
|
x: usize,
|
|
y: usize,
|
|
z: usize,
|
|
) -> CfdResult<MacroscopicVariables3D> {
|
|
let buffers = self
|
|
.gpu_buffers
|
|
.as_mut()
|
|
.ok_or_else(|| CfdError::gpu_error("GPU buffers not initialized"))?;
|
|
|
|
// Extract macroscopic variables first
|
|
self.gpu_extract_macroscopic_variables()?;
|
|
|
|
// Copy arrays from GPU
|
|
let density_host = self.kernel_manager.copy_from_device(&buffers.density)?;
|
|
let velocity_x_host = self.kernel_manager.copy_from_device(&buffers.velocity_x)?;
|
|
let velocity_y_host = self.kernel_manager.copy_from_device(&buffers.velocity_y)?;
|
|
let velocity_z_host = self.kernel_manager.copy_from_device(&buffers.velocity_z)?;
|
|
|
|
let idx = z * buffers.nx * buffers.ny + y * buffers.nx + x;
|
|
if idx >= density_host.len() {
|
|
return Err(CfdError::gpu_error("Index out of bounds"));
|
|
}
|
|
|
|
let density = density_host[idx] as f64;
|
|
let velocity = Vector3::new(
|
|
velocity_x_host[idx] as f64,
|
|
velocity_y_host[idx] as f64,
|
|
velocity_z_host[idx] as f64,
|
|
);
|
|
|
|
Ok(MacroscopicVariables3D::new(density, velocity))
|
|
}
|
|
|
|
/// Initialize GPU buffers and set up solver
|
|
pub fn initialize(&mut self, nx: usize, ny: usize, nz: usize) -> CfdResult<()> {
|
|
self.initialize_gpu_buffers(nx, ny, nz)?;
|
|
Ok(())
|
|
}
|
|
|
|
/// Get grid dimensions
|
|
pub fn dimensions(&self) -> (usize, usize, usize) {
|
|
if let Some(buffers) = &self.gpu_buffers {
|
|
(buffers.nx, buffers.ny, buffers.nz)
|
|
} else {
|
|
self.cpu_solver.dimensions()
|
|
}
|
|
}
|
|
|
|
/// Get solver parameters
|
|
pub fn parameters(&self) -> &D3Q19Parameters {
|
|
&self.params
|
|
}
|
|
|
|
/// Calculate total mass on GPU
|
|
pub fn gpu_total_mass(&self) -> CfdResult<f64> {
|
|
let buffers = self
|
|
.gpu_buffers
|
|
.as_mut()
|
|
.ok_or_else(|| CfdError::gpu_error("GPU buffers not initialized"))?;
|
|
|
|
self.gpu_extract_macroscopic_variables()?;
|
|
let density_host = self.kernel_manager.copy_from_device(&buffers.density)?;
|
|
let total_mass: f32 = density_host.iter().sum();
|
|
Ok(total_mass as f64)
|
|
}
|
|
|
|
/// Calculate kinetic energy on GPU
|
|
pub fn gpu_kinetic_energy(&self) -> CfdResult<f64> {
|
|
let buffers = self
|
|
.gpu_buffers
|
|
.as_mut()
|
|
.ok_or_else(|| CfdError::gpu_error("GPU buffers not initialized"))?;
|
|
|
|
self.gpu_extract_macroscopic_variables()?;
|
|
let density_host = self.kernel_manager.copy_from_device(&buffers.density)?;
|
|
let velocity_x_host = self.kernel_manager.copy_from_device(&buffers.velocity_x)?;
|
|
let velocity_y_host = self.kernel_manager.copy_from_device(&buffers.velocity_y)?;
|
|
let velocity_z_host = self.kernel_manager.copy_from_device(&buffers.velocity_z)?;
|
|
|
|
let mut total_ke = 0.0f64;
|
|
for i in 0..density_host.len() {
|
|
let rho = density_host[i] as f64;
|
|
let ux = velocity_x_host[i] as f64;
|
|
let uy = velocity_y_host[i] as f64;
|
|
let uz = velocity_z_host[i] as f64;
|
|
total_ke += 0.5 * rho * (ux * ux + uy * uy + uz * uz);
|
|
}
|
|
|
|
Ok(total_ke)
|
|
}
|
|
|
|
/// Fallback to CPU solver
|
|
pub fn cpu_solver(&self) -> &D3Q19Solver {
|
|
&self.cpu_solver
|
|
}
|
|
|
|
/// Fallback to CPU solver (mutable)
|
|
pub fn cpu_solver_mut(&mut self) -> &mut D3Q19Solver {
|
|
&mut self.cpu_solver
|
|
}
|
|
}
|
|
|
|
#[cfg(test)]
|
|
mod tests {
|
|
use super::*;
|
|
use approx::assert_relative_eq;
|
|
|
|
#[test]
|
|
fn test_d3q19_gpu_solver_creation() -> CfdResult<()> {
|
|
let config = CfdConfig {
|
|
nx: 16,
|
|
ny: 16,
|
|
nz: 16,
|
|
lx: 1.0,
|
|
ly: 1.0,
|
|
lz: 1.0,
|
|
dt: 0.001,
|
|
viscosity: 0.01,
|
|
density: 1.0,
|
|
device_id: 0,
|
|
..CfdConfig::default()
|
|
};
|
|
|
|
let params = D3Q19Parameters::default();
|
|
|
|
// This will only work if CUDA is available
|
|
if let Ok(mut solver) = D3Q19GpuSolver::new(16, 16, 16, params, &config) {
|
|
solver.initialize(16, 16, 16)?;
|
|
println!("GPU D3Q19 solver created successfully");
|
|
} else {
|
|
println!("GPU not available, skipping GPU D3Q19 test");
|
|
}
|
|
|
|
Ok(())
|
|
}
|
|
|
|
#[test]
|
|
fn test_d3q19_gpu_initialization() -> CfdResult<()> {
|
|
let config = CfdConfig {
|
|
nx: 8,
|
|
ny: 8,
|
|
nz: 8,
|
|
lx: 1.0,
|
|
ly: 1.0,
|
|
lz: 1.0,
|
|
dt: 0.001,
|
|
viscosity: 0.01,
|
|
density: 1.0,
|
|
device_id: 0,
|
|
..CfdConfig::default()
|
|
};
|
|
|
|
let params = D3Q19Parameters::default();
|
|
|
|
if let Ok(mut solver) = D3Q19GpuSolver::new(8, 8, 8, params, &config) {
|
|
solver.initialize(8, 8, 8)?;
|
|
|
|
let density = 1.0;
|
|
let velocity = Vector3::new(0.1, 0.05, 0.02);
|
|
|
|
solver.gpu_initialize_uniform(density, velocity)?;
|
|
|
|
// Check a few points
|
|
let vars = solver.gpu_macroscopic_variables_at(4, 4, 4)?;
|
|
assert_relative_eq!(vars.density, density, epsilon = 1e-5);
|
|
assert_relative_eq!(vars.velocity.x, velocity.x, epsilon = 1e-5);
|
|
assert_relative_eq!(vars.velocity.y, velocity.y, epsilon = 1e-5);
|
|
assert_relative_eq!(vars.velocity.z, velocity.z, epsilon = 1e-5);
|
|
|
|
println!("GPU D3Q19 initialization test passed");
|
|
} else {
|
|
println!("GPU not available, skipping initialization test");
|
|
}
|
|
|
|
Ok(())
|
|
}
|
|
|
|
#[test]
|
|
fn test_d3q19_gpu_step() -> CfdResult<()> {
|
|
let config = CfdConfig {
|
|
nx: 8,
|
|
ny: 8,
|
|
nz: 8,
|
|
lx: 1.0,
|
|
ly: 1.0,
|
|
lz: 1.0,
|
|
dt: 0.001,
|
|
viscosity: 0.01,
|
|
density: 1.0,
|
|
device_id: 0,
|
|
..CfdConfig::default()
|
|
};
|
|
|
|
let params = D3Q19Parameters::default();
|
|
|
|
if let Ok(mut solver) = D3Q19GpuSolver::new(8, 8, 8, params, &config) {
|
|
solver.initialize(8, 8, 8)?;
|
|
|
|
// Initialize with simple flow
|
|
solver.gpu_initialize_uniform(1.0, Vector3::new(0.01, 0.0, 0.0))?;
|
|
|
|
// Perform one time step
|
|
solver.gpu_step()?;
|
|
|
|
// Check that simulation is stable
|
|
let total_mass = solver.gpu_total_mass()?;
|
|
assert!(total_mass > 0.0, "Total mass should be positive");
|
|
assert!(total_mass < 1000.0, "Total mass should be reasonable");
|
|
|
|
let kinetic_energy = solver.gpu_kinetic_energy()?;
|
|
assert!(
|
|
kinetic_energy >= 0.0,
|
|
"Kinetic energy should be non-negative"
|
|
);
|
|
|
|
println!("GPU D3Q19 time step test passed");
|
|
} else {
|
|
println!("GPU not available, skipping time step test");
|
|
}
|
|
|
|
Ok(())
|
|
}
|
|
}
|