diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 8d7ea5d4..074ffa51 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -28,6 +28,19 @@ jobs: - uses: actions/checkout@v4 with: lfs: true + - name: Update rust toolchain + run: | + rustup update stable + rustup default stable + rustup --version + - name: Cache rust dependencies + uses: actions/cache@v4 + with: + path: | + ~/.cargo/registry + ~/.cargo/git + target + key: ${{ runner.os }}-dev-cargo-${{ hashFiles('**/Cargo.lock') }} - name: Check (default members) run: cargo check - name: Check with examples @@ -40,13 +53,30 @@ jobs: run: cargo test build_release: - name: Build & test release mode - runs-on: ubuntu-latest + name: Build & test release mode (${{ matrix.runner }}) + runs-on: ${{ matrix.runner }} needs: build_workspace + strategy: + fail-fast: false + matrix: + runner: [ubuntu-latest, ubuntu-24.04-arm, macos-14, macos-13, windows-latest] steps: - uses: actions/checkout@v4 with: lfs: true + - name: Update rust toolchain + run: | + rustup update stable + rustup default stable + rustup --version + - name: Cache rust dependencies + uses: actions/cache@v4 + with: + path: | + ~/.cargo/registry + ~/.cargo/git + target + key: ${{ matrix.runner }}-release-cargo-${{ hashFiles('**/Cargo.lock') }} - name: Build (release) run: cargo build --release - name: Test (release) @@ -59,6 +89,19 @@ jobs: - uses: actions/checkout@v4 with: lfs: true + - name: Update rust toolchain + run: | + rustup update stable + rustup default stable + rustup --version + - name: Cache rust dependencies + uses: actions/cache@v4 + with: + path: | + ~/.cargo/registry + ~/.cargo/git + target + key: ${{ runner.os }}-lib-all-cargo-${{ hashFiles('**/Cargo.lock') }} - name: Build run: | cargo build --manifest-path="splashsurf_lib/Cargo.toml" --all-targets --all-features @@ -76,6 +119,19 @@ jobs: - uses: actions/checkout@v4 with: lfs: true + - name: Update rust toolchain + run: | + rustup update stable + rustup default stable + rustup --version + - name: Cache rust dependencies + uses: actions/cache@v4 + with: + path: | + ~/.cargo/registry + ~/.cargo/git + target + key: ${{ runner.os }}-lib-no-default-cargo-${{ hashFiles('**/Cargo.lock') }} - name: Build run: | cargo build --manifest-path="splashsurf_lib/Cargo.toml" --all-targets --no-default-features @@ -87,9 +143,14 @@ jobs: name: Publish to crates.io runs-on: ubuntu-latest if: ${{ startsWith(github.ref, 'refs/tags/v') || (github.event_name == 'workflow_dispatch' && github.ref == 'refs/heads/main') }} - needs: [check_format, build_workspace, build_lib_all_features, build_lib_no_default_features] + needs: [check_format, build_workspace, build_lib_all_features, build_lib_no_default_features, build_release] steps: - uses: actions/checkout@v4 + - name: Update rust toolchain + run: | + rustup update stable + rustup default stable + rustup --version - name: Publish splashsurf_lib run: | cargo publish --package splashsurf_lib diff --git a/Cargo.lock b/Cargo.lock index 1940bf11..111fe9e2 100644 --- a/Cargo.lock +++ b/Cargo.lock @@ -906,6 +906,7 @@ dependencies = [ "num-traits", "rand", "rand_distr", + "serde", "simba", "typenum", ] @@ -971,6 +972,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "73f88a1307638156682bada9d7604135552957b7818057dcef22705b4d509495" dependencies = [ "num-traits", + "serde", ] [[package]] @@ -1656,6 +1658,8 @@ dependencies = [ "rayon", "rstar", "sdfu", + "serde", + "serde_derive", "serde_json", "simba", "thiserror", diff --git a/data/density_grid_loop_subdomain_33.json b/data/density_grid_loop_subdomain_33.json new file mode 100644 index 00000000..4f3d30a0 --- /dev/null +++ b/data/density_grid_loop_subdomain_33.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/pysplashsurf/src/pipeline.rs b/pysplashsurf/src/pipeline.rs index 3cb312ee..549f089f 100644 --- a/pysplashsurf/src/pipeline.rs +++ b/pysplashsurf/src/pipeline.rs @@ -48,6 +48,8 @@ use crate::utils::{IndexT, pyerr_unsupported_scalar}; /// Upper corner [x,y,z] of the AABB of particles to consider in the reconstruction. /// multi_threading /// Flag to enable multi-threading for the reconstruction and post-processing steps. +/// simd +/// Flag to enable SIMD vectorization for the reconstruction if supported by the CPU architecture. /// subdomain_grid /// Flag to enable spatial decomposition by dividing the domain into subdomains with dense marching cube grids for efficient multi-threading. /// subdomain_grid_auto_disable @@ -108,7 +110,7 @@ use crate::utils::{IndexT, pyerr_unsupported_scalar}; #[pyo3(name = "reconstruction_pipeline")] #[pyo3(signature = (particles, *, attributes_to_interpolate = None, particle_radius, rest_density = 1000.0, smoothing_length, cube_size, iso_surface_threshold = 0.6, - aabb_min = None, aabb_max = None, multi_threading = true, + aabb_min = None, aabb_max = None, multi_threading = true, simd = true, subdomain_grid = true, subdomain_grid_auto_disable = true, subdomain_num_cubes_per_dim = 64, check_mesh_closed = false, check_mesh_manifold = false, check_mesh_orientation = false, check_mesh_debug = false, mesh_cleanup = false, mesh_cleanup_snap_dist = None, decimate_barnacles = false, keep_vertices = false, compute_normals = false, sph_normals = false, @@ -128,6 +130,7 @@ pub fn reconstruction_pipeline<'py>( aabb_min: Option<[f64; 3]>, aabb_max: Option<[f64; 3]>, multi_threading: bool, + simd: bool, subdomain_grid: bool, subdomain_grid_auto_disable: bool, subdomain_num_cubes_per_dim: u32, @@ -192,6 +195,7 @@ pub fn reconstruction_pipeline<'py>( iso_surface_threshold, particle_aabb, enable_multi_threading: multi_threading, + enable_simd: simd, spatial_decomposition, global_neighborhood_list: false, }; diff --git a/pysplashsurf/src/reconstruction.rs b/pysplashsurf/src/reconstruction.rs index e74f3897..1a6ec9f3 100644 --- a/pysplashsurf/src/reconstruction.rs +++ b/pysplashsurf/src/reconstruction.rs @@ -122,6 +122,8 @@ impl PySurfaceReconstruction { /// Upper corner of the AABB of particles to consider in the reconstruction. /// multi_threading /// Flag to enable multi-threading for the reconstruction and post-processing steps. +/// simd +/// Flag to enable SIMD vectorization for the reconstruction if supported by the CPU architecture. /// subdomain_grid /// Flag to enable spatial decomposition by dividing the domain into subdomains with dense marching cube grids for efficient multi-threading. /// subdomain_grid_auto_disable @@ -134,7 +136,7 @@ impl PySurfaceReconstruction { #[pyo3(signature = (particles, *, particle_radius, rest_density = 1000.0, smoothing_length, cube_size, iso_surface_threshold = 0.6, aabb_min = None, aabb_max = None, - multi_threading = true, global_neighborhood_list = false, + multi_threading = true, simd = true, global_neighborhood_list = false, subdomain_grid = true, subdomain_grid_auto_disable = true, subdomain_num_cubes_per_dim = 64 ))] pub fn reconstruct_surface<'py>( @@ -147,6 +149,7 @@ pub fn reconstruct_surface<'py>( aabb_min: Option<[f64; 3]>, aabb_max: Option<[f64; 3]>, multi_threading: bool, + simd: bool, global_neighborhood_list: bool, subdomain_grid: bool, subdomain_grid_auto_disable: bool, @@ -175,6 +178,7 @@ pub fn reconstruct_surface<'py>( iso_surface_threshold, particle_aabb, enable_multi_threading: multi_threading, + enable_simd: simd, spatial_decomposition, global_neighborhood_list, }; diff --git a/splashsurf/Cargo.toml b/splashsurf/Cargo.toml index 19012bc8..0ba665f6 100644 --- a/splashsurf/Cargo.toml +++ b/splashsurf/Cargo.toml @@ -6,6 +6,7 @@ keywords = ["sph", "particle", "surface", "reconstruction", "marching-cubes"] categories = ["command-line-utilities", "graphics", "science", "simulation", "visualization"] readme = "README.md" edition = "2024" +rust-version = "1.88" authors.workspace = true license.workspace = true diff --git a/splashsurf/src/reconstruct.rs b/splashsurf/src/reconstruct.rs index 39cff1be..0cc84288 100644 --- a/splashsurf/src/reconstruct.rs +++ b/splashsurf/src/reconstruct.rs @@ -124,6 +124,17 @@ pub(crate) struct ReconstructSubcommandArgs { /// Set the number of threads for the worker thread pool #[arg(help_heading = ARGS_ADV, long, short = 'n')] pub num_threads: Option, + /// Enable vectorization of some computations using SIMD instructions (requires CPU with AVX2 or NEON support). + /// Note that vectorization is currently only available in single precision (f32) mode. + #[arg( + help_heading = ARGS_ADV, + long, + default_value = "on", + value_name = "off|on", + ignore_case = true, + require_equals = true + )] + pub simd: Switch, /// Enable automatic spatial decomposition using a regular grid-based approach (for efficient multithreading) if the domain is large enough #[arg( @@ -637,6 +648,7 @@ pub(crate) mod arguments { iso_surface_threshold: args.surface_threshold, particle_aabb, enable_multi_threading: args.parallelize_over_particles.into_bool(), + enable_simd: args.simd.into_bool(), spatial_decomposition, global_neighborhood_list: args.mesh_smoothing_weights.into_bool(), }; diff --git a/splashsurf_lib/Cargo.toml b/splashsurf_lib/Cargo.toml index d46741c2..26fa4a07 100644 --- a/splashsurf_lib/Cargo.toml +++ b/splashsurf_lib/Cargo.toml @@ -6,6 +6,7 @@ keywords = ["sph", "particle", "surface", "reconstruction", "marching-cubes"] categories = ["graphics", "science", "simulation", "visualization", "rendering"] readme = "README.md" edition = "2024" +rust-version = "1.88" documentation = "https://docs.rs/splashsurf_lib" authors.workspace = true @@ -17,9 +18,15 @@ repository.workspace = true # RUSTDOCFLAGS="--cfg docsrs" cargo +nightly doc --all-features --no-deps --open # Build with all features to properly document everything all-features = true -# Build only for a single target as this crate does not have any platform specific behavior -default-target = "x86_64-unknown-linux-gnu" -targets = [] +targets = [ + "x86_64-unknown-linux-gnu", + "i686-unknown-linux-gnu", + "aarch64-unknown-linux-gnu", + "aarch64-apple-darwin", + "x86_64-apple-darwin", + "x86_64-pc-windows-msvc", + "i686-pc-windows-msvc" +] # Ignore the tests (especially the test mesh files) for publishing exclude = ["tests/*", "benches/*"] @@ -29,6 +36,7 @@ default = [] vtk_extras = ["vtkio"] profiling = [] io = ["vtk_extras", "vtkio", "ply-rs", "nom", "serde_json", "flate2"] +serde-serialize = ["serde", "serde_derive", "serde_json", "nalgebra/serde-serialize"] [dependencies] log = "0.4" @@ -59,6 +67,10 @@ flate2 = { version = "1.0", optional = true } nom = { version = "8.0", optional = true } serde_json = { version = "1.0", optional = true } +# Serialization +serde = { version = "1.0", optional = true } +serde_derive = { version = "1.0", optional = true } + [dev-dependencies] criterion = "0.7" ultraviolet = "0.10" @@ -83,4 +95,4 @@ required-features = ["profiling", "io"] name = "splashsurf_lib_benches" path = "benches/splashsurf_lib_benches.rs" harness = false -required-features = ["io"] +required-features = ["io", "serde-serialize"] diff --git a/splashsurf_lib/benches/benches/bench_full.rs b/splashsurf_lib/benches/benches/bench_full.rs index fe29282c..be2476a5 100644 --- a/splashsurf_lib/benches/benches/bench_full.rs +++ b/splashsurf_lib/benches/benches/bench_full.rs @@ -102,6 +102,7 @@ pub fn surface_reconstruction_dam_break(c: &mut Criterion) { iso_surface_threshold: 0.6, particle_aabb: None, enable_multi_threading: true, + enable_simd: true, spatial_decomposition: SpatialDecomposition::None, global_neighborhood_list: false, }; @@ -161,6 +162,7 @@ pub fn surface_reconstruction_double_dam_break(c: &mut Criterion) { iso_surface_threshold: 0.6, particle_aabb: None, enable_multi_threading: true, + enable_simd: true, spatial_decomposition: SpatialDecomposition::None, global_neighborhood_list: false, }; @@ -220,6 +222,7 @@ pub fn surface_reconstruction_double_dam_break_inplace(c: &mut Criterion) { iso_surface_threshold: 0.6, particle_aabb: None, enable_multi_threading: true, + enable_simd: true, spatial_decomposition: SpatialDecomposition::None, global_neighborhood_list: false, }; diff --git a/splashsurf_lib/benches/benches/bench_grid_loop.rs b/splashsurf_lib/benches/benches/bench_grid_loop.rs new file mode 100644 index 00000000..4fd5ff2f --- /dev/null +++ b/splashsurf_lib/benches/benches/bench_grid_loop.rs @@ -0,0 +1,297 @@ +use criterion::{Criterion, criterion_group}; +use nalgebra::{Scalar, Vector3}; +use serde_derive::{Deserialize, Serialize}; +use splashsurf_lib::dense_subdomains; +use splashsurf_lib::kernel::CubicSplineKernel; +use splashsurf_lib::uniform_grid::UniformCartesianCubeGrid3d; +use std::time::Duration; + +// Code to generate the input data for the benchmark from dense_subdomains.rs +/* +if subdomain_particles.len() > 6800 { + println!("{}", subdomain_particles.len()); + let arguments = DensityGridLoopParameters { + levelset_grid: levelset_grid.clone(), + subdomain_particles: subdomain_particles.clone(), + subdomain_particle_densities: subdomain_particle_densities.clone(), + subdomain_mc_grid: mc_grid.clone(), + subdomain_ijk: *subdomain_idx.index(), + global_mc_grid: parameters.global_marching_cubes_grid.clone(), + cube_radius, + squared_support_with_margin, + particle_rest_mass: parameters.particle_rest_mass, + compact_support_radius: parameters.compact_support_radius, + }; + serde_json::to_writer( + std::fs::File::create(format!( + "density_grid_loop_subdomain_{}.json", + flat_subdomain_idx + )) + .unwrap(), + &arguments, + ) + .unwrap(); +} + */ + +#[derive(Clone, Serialize, Deserialize)] +pub struct DensityGridLoopParameters { + pub levelset_grid: Vec, + pub subdomain_particles: Vec>, + pub subdomain_particle_densities: Vec, + pub subdomain_mc_grid: UniformCartesianCubeGrid3d, + pub subdomain_ijk: [I; 3], + pub global_mc_grid: UniformCartesianCubeGrid3d, + pub cube_radius: I, + pub squared_support_with_margin: R, + pub particle_rest_mass: R, + pub compact_support_radius: R, +} + +pub fn grid_loop_no_simd(c: &mut Criterion) { + let params: DensityGridLoopParameters = serde_json::from_reader( + std::fs::File::open("../data/density_grid_loop_subdomain_33.json").unwrap(), + ) + .unwrap(); + + let mut group = c.benchmark_group("grid_loop"); + group.sample_size(400); + group.warm_up_time(Duration::from_secs(3)); + group.measurement_time(Duration::from_secs(20)); + + group.bench_function("grid_loop_no_simd", |b| { + b.iter(|| { + let kernel = CubicSplineKernel::new(params.compact_support_radius); + let mut params = params.clone(); + dense_subdomains::density_grid_loop_scalar( + params.levelset_grid.as_mut_slice(), + params.subdomain_particles.as_slice(), + params.subdomain_particle_densities.as_slice(), + ¶ms.subdomain_mc_grid, + ¶ms.subdomain_ijk, + ¶ms.global_mc_grid, + params.cube_radius, + params.squared_support_with_margin, + params.particle_rest_mass, + &kernel, + ); + }) + }); + + group.finish(); +} + +#[allow(unreachable_code)] +#[allow(unused_variables)] +pub fn grid_loop_neon(c: &mut Criterion) { + #[cfg(not(target_feature = "neon"))] + { + println!("Skipping NEON benchmark because the target does not support NEON."); + return; + } + + let params: DensityGridLoopParameters = serde_json::from_reader( + std::fs::File::open("../data/density_grid_loop_subdomain_33.json").unwrap(), + ) + .unwrap(); + + let reference = { + let kernel = CubicSplineKernel::new(params.compact_support_radius); + let mut params = params.clone(); + dense_subdomains::density_grid_loop_scalar( + params.levelset_grid.as_mut_slice(), + params.subdomain_particles.as_slice(), + params.subdomain_particle_densities.as_slice(), + ¶ms.subdomain_mc_grid, + ¶ms.subdomain_ijk, + ¶ms.global_mc_grid, + params.cube_radius, + params.squared_support_with_margin, + params.particle_rest_mass, + &kernel, + ); + params.levelset_grid + }; + + #[cfg(target_feature = "neon")] + { + let neon_result = unsafe { + let kernel = CubicSplineKernel::new(params.compact_support_radius); + let mut params = params.clone(); + dense_subdomains::density_grid_loop_neon( + params.levelset_grid.as_mut_slice(), + params.subdomain_particles.as_slice(), + params.subdomain_particle_densities.as_slice(), + ¶ms.subdomain_mc_grid, + ¶ms.subdomain_ijk, + ¶ms.global_mc_grid, + params.cube_radius, + params.squared_support_with_margin, + params.particle_rest_mass, + &kernel, + ); + params.levelset_grid + }; + + let eps = f32::EPSILON * 10.0; + println!("{:?}", params.subdomain_mc_grid); + for (i, (a, b)) in neon_result.iter().zip(reference.iter()).enumerate() { + let diff = (a - b).abs(); + if diff >= eps { + let ijk = params.subdomain_mc_grid.try_unflatten_point_index(i as i64); + println!( + "Mismatch at index {}: neon = {}, reference = {}, diff = {}, ijk = {:?}", + i, a, b, diff, ijk + ); + } + } + + println!("reference head: {:?}", &reference[0..10]); + println!("neon head : {:?}", &reference[0..10]); + + println!( + "reference tail: {:?}", + &neon_result[neon_result.len() - 10..] + ); + println!( + "neon tail : {:?}", + &neon_result[neon_result.len() - 10..] + ); + + assert!( + neon_result + .iter() + .zip(reference.iter()) + .all(|(a, b)| (a - b).abs() < eps) + ); + } + + let mut group = c.benchmark_group("grid_loop"); + group.sample_size(600); + group.warm_up_time(Duration::from_secs(3)); + group.measurement_time(Duration::from_secs(20)); + + #[cfg(target_feature = "neon")] + unsafe { + group.bench_function("grid_loop_neon", |b| { + b.iter(|| { + let kernel = CubicSplineKernel::new(params.compact_support_radius); + let mut params = params.clone(); + dense_subdomains::density_grid_loop_neon( + params.levelset_grid.as_mut_slice(), + params.subdomain_particles.as_slice(), + params.subdomain_particle_densities.as_slice(), + ¶ms.subdomain_mc_grid, + ¶ms.subdomain_ijk, + ¶ms.global_mc_grid, + params.cube_radius, + params.squared_support_with_margin, + params.particle_rest_mass, + &kernel, + ); + }) + }); + } + + group.finish(); +} + +#[allow(unreachable_code)] +#[allow(unused_variables)] +pub fn grid_loop_avx2(c: &mut Criterion) { + #[cfg(not(all(target_feature = "avx2", target_feature = "fma")))] + { + println!("Skipping AVX2 benchmark because the target does not support AVX2 and FMA."); + return; + } + + let params: DensityGridLoopParameters = serde_json::from_reader( + std::fs::File::open("../data/density_grid_loop_subdomain_33.json").unwrap(), + ) + .unwrap(); + + let reference = { + let kernel = CubicSplineKernel::new(params.compact_support_radius); + let mut params = params.clone(); + dense_subdomains::density_grid_loop_scalar( + params.levelset_grid.as_mut_slice(), + params.subdomain_particles.as_slice(), + params.subdomain_particle_densities.as_slice(), + ¶ms.subdomain_mc_grid, + ¶ms.subdomain_ijk, + ¶ms.global_mc_grid, + params.cube_radius, + params.squared_support_with_margin, + params.particle_rest_mass, + &kernel, + ); + params.levelset_grid + }; + + #[cfg(all(target_feature = "avx2", target_feature = "fma"))] + { + let avx_result = unsafe { + let kernel = CubicSplineKernel::new(params.compact_support_radius); + let mut params = params.clone(); + dense_subdomains::density_grid_loop_avx( + params.levelset_grid.as_mut_slice(), + params.subdomain_particles.as_slice(), + params.subdomain_particle_densities.as_slice(), + ¶ms.subdomain_mc_grid, + ¶ms.subdomain_ijk, + ¶ms.global_mc_grid, + params.cube_radius, + params.squared_support_with_margin, + params.particle_rest_mass, + &kernel, + ); + params.levelset_grid + }; + + println!("{:?}", &reference[0..10]); + println!("{:?}", &avx_result[0..10]); + + assert!( + avx_result + .iter() + .zip(reference.iter()) + .all(|(a, b)| (a - b).abs() < f32::EPSILON * 100.0) + ); + } + + let mut group = c.benchmark_group("grid_loop"); + group.sample_size(600); + group.warm_up_time(Duration::from_secs(3)); + group.measurement_time(Duration::from_secs(20)); + + #[cfg(all(target_feature = "avx2", target_feature = "fma"))] + unsafe { + group.bench_function("grid_loop_avx2", |b| { + b.iter(|| { + let kernel = CubicSplineKernel::new(params.compact_support_radius); + let mut params = params.clone(); + dense_subdomains::density_grid_loop_avx( + params.levelset_grid.as_mut_slice(), + params.subdomain_particles.as_slice(), + params.subdomain_particle_densities.as_slice(), + ¶ms.subdomain_mc_grid, + ¶ms.subdomain_ijk, + ¶ms.global_mc_grid, + params.cube_radius, + params.squared_support_with_margin, + params.particle_rest_mass, + &kernel, + ); + }) + }); + } + + group.finish(); +} + +criterion_group!( + bench_grid_loop, + grid_loop_no_simd, + grid_loop_neon, + grid_loop_avx2 +); diff --git a/splashsurf_lib/benches/benches/bench_mesh.rs b/splashsurf_lib/benches/benches/bench_mesh.rs index 2d8652d5..4d49d00b 100644 --- a/splashsurf_lib/benches/benches/bench_mesh.rs +++ b/splashsurf_lib/benches/benches/bench_mesh.rs @@ -23,6 +23,7 @@ fn reconstruct_particles>(particle_file: P) -> SurfaceReconstruct iso_surface_threshold: 0.6, particle_aabb: None, enable_multi_threading: true, + enable_simd: true, spatial_decomposition: SpatialDecomposition::UniformGrid(GridDecompositionParameters { subdomain_num_cubes_per_dim: 64, auto_disable: false, diff --git a/splashsurf_lib/benches/benches/bench_subdomain_grid.rs b/splashsurf_lib/benches/benches/bench_subdomain_grid.rs index 7a46b072..592ca81e 100644 --- a/splashsurf_lib/benches/benches/bench_subdomain_grid.rs +++ b/splashsurf_lib/benches/benches/bench_subdomain_grid.rs @@ -7,7 +7,7 @@ use splashsurf_lib::{ }; use std::time::Duration; -static CANYON_PATH: &str = "C:\\canyon.xyz"; +static CANYON_PATH: &str = "/Users/floeschner/Documents/canyon.xyz"; fn parameters_canyon() -> Parameters { let particle_radius = 0.011; @@ -22,6 +22,7 @@ fn parameters_canyon() -> Parameters { iso_surface_threshold: 0.6, particle_aabb: None, enable_multi_threading: true, + enable_simd: true, spatial_decomposition: SpatialDecomposition::UniformGrid(GridDecompositionParameters { subdomain_num_cubes_per_dim: 32, auto_disable: false, @@ -31,7 +32,17 @@ fn parameters_canyon() -> Parameters { } pub fn grid_canyon(c: &mut Criterion) { - let particle_positions: &Vec> = &particles_from_file(CANYON_PATH).unwrap(); + let particle_positions: Vec> = + if let Some(particle_positions) = particles_from_file(CANYON_PATH).ok() { + particle_positions + } else { + eprintln!( + "Canyon file not found at path: {}, skipping canyon benchmarks", + CANYON_PATH + ); + return; + }; + let parameters = parameters_canyon(); let mut group = c.benchmark_group("grid_canyon"); @@ -86,7 +97,17 @@ pub fn grid_canyon(c: &mut Criterion) { } pub fn grid_optimal_num_cubes_canyon(c: &mut Criterion) { - let particle_positions: &Vec> = &particles_from_file(CANYON_PATH).unwrap(); + let particle_positions: Vec> = + if let Some(particle_positions) = particles_from_file(CANYON_PATH).ok() { + particle_positions + } else { + eprintln!( + "Canyon file not found at path: {}, skipping canyon benchmarks", + CANYON_PATH + ); + return; + }; + let mut parameters = parameters_canyon(); let mut with_cube_factor = |cube_factor: f32, num_cubes: &[u32]| { diff --git a/splashsurf_lib/benches/benches/mod.rs b/splashsurf_lib/benches/benches/mod.rs index cd2402cb..68f3810d 100644 --- a/splashsurf_lib/benches/benches/mod.rs +++ b/splashsurf_lib/benches/benches/mod.rs @@ -1,5 +1,6 @@ pub mod bench_aabb; pub mod bench_full; +pub mod bench_grid_loop; pub mod bench_mesh; pub mod bench_neighborhood; pub mod bench_subdomain_grid; diff --git a/splashsurf_lib/benches/splashsurf_lib_benches.rs b/splashsurf_lib/benches/splashsurf_lib_benches.rs index e9be90bc..20d71d0c 100644 --- a/splashsurf_lib/benches/splashsurf_lib_benches.rs +++ b/splashsurf_lib/benches/splashsurf_lib_benches.rs @@ -4,6 +4,7 @@ use criterion::criterion_main; use benches::bench_aabb::bench_aabb; use benches::bench_full::bench_full; +use benches::bench_grid_loop::bench_grid_loop; use benches::bench_mesh::bench_mesh; use benches::bench_neighborhood::bench_neighborhood; use benches::bench_subdomain_grid::bench_subdomain_grid; @@ -14,4 +15,5 @@ criterion_main!( bench_full, bench_neighborhood, bench_subdomain_grid, + bench_grid_loop, ); diff --git a/splashsurf_lib/src/aabb.rs b/splashsurf_lib/src/aabb.rs index 024a4506..9d623c16 100644 --- a/splashsurf_lib/src/aabb.rs +++ b/splashsurf_lib/src/aabb.rs @@ -1,12 +1,14 @@ //! Axis-aligned bounding boxes -use nalgebra::SVector; +use crate::{Real, RealConvert, ThreadSafe}; +use nalgebra::{SVector, Scalar}; use rayon::prelude::*; - -use crate::{Real, RealConvert, Scalar, ThreadSafe}; +#[cfg(feature = "serde-serialize")] +use serde_derive::{Deserialize, Serialize}; /// Type representing an axis aligned bounding box in arbitrary dimensions #[derive(Clone, Debug, Eq, PartialEq)] +#[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))] pub struct AxisAlignedBoundingBox { min: SVector, max: SVector, diff --git a/splashsurf_lib/src/dense_subdomains.rs b/splashsurf_lib/src/dense_subdomains.rs index 94426bfc..f0f787e2 100644 --- a/splashsurf_lib/src/dense_subdomains.rs +++ b/splashsurf_lib/src/dense_subdomains.rs @@ -657,12 +657,569 @@ pub(crate) struct SurfacePatch { pub exterior_vertex_edge_indices: Vec<(I, EdgeIndex)>, } -// TODO: Reduce code duplication between dense and sparse +/// Returns the lower and upper subdomain grid vertex indices possibly influenced by the given particle (upper index is exclusive) +#[inline(always)] +fn particle_influence_aabb( + particle: &Vector3, + subdomain_mc_grid: &UniformCartesianCubeGrid3d, + cube_radius: I, +) -> ([I; 3], [I; 3]) { + let extents = subdomain_mc_grid.points_per_dim(); + + // Note: This assumes that enclosing_cell can return negative indices for ghost particles + // (they are outside the subdomain grid but part of the particle list). + + // Get grid cell containing particle + let particle_cell = subdomain_mc_grid.enclosing_cell(particle); + + // Compute lower and upper bounds of the grid points possibly affected by the particle + // We want to loop over the vertices of the enclosing cells plus all points in `cube_radius` distance from the cell + + let lower = [0, 1, 2].map(|i| { + particle_cell[i] + .saturating_sub(&cube_radius) + .max(I::zero()) + .min(extents[i]) + }); + + let upper = [0, 1, 2].map(|i| { + // We add 2 because + // - we want to loop over all grid points of the cell (+1 for upper points) + the radius + // - the upper range limit is exclusive (+1) + (particle_cell[i] + cube_radius + I::two()) + .min(extents[i]) + .max(I::zero()) + }); + + (lower, upper) +} + +/// Converts a local (subdomain) grid point index to a global grid point index +fn local_to_global_point_ijk( + local_point_ijk: [I; 3], + subdomain_ijk: [I; 3], + cells_per_subdomain: [I; 3], +) -> [GlobalIndex; 3] { + let local_point_ijk = local_point_ijk.map(|i| ::from(i).unwrap()); + let subdomain_ijk = subdomain_ijk.map(|i| ::from(i).unwrap()); + let cells_per_subdomain = + cells_per_subdomain.map(|i| ::from(i).unwrap()); + let [i, j, k] = local_point_ijk; + + [ + subdomain_ijk[0] * cells_per_subdomain[0] + i, + subdomain_ijk[1] * cells_per_subdomain[1] + j, + subdomain_ijk[2] * cells_per_subdomain[2] + k, + ] +} + +/// Auto-dispatching density grid loop for f32/i64: chooses AVX2+FMA on x86, NEON on aarch64, otherwise scalar fallback +pub fn density_grid_loop_auto>( + levelset_grid: &mut [f32], + subdomain_particles: &[Vector3], + subdomain_particle_densities: &[f32], + subdomain_mc_grid: &UniformCartesianCubeGrid3d, + subdomain_ijk: &[i64; 3], + global_mc_grid: &UniformCartesianCubeGrid3d, + cube_radius: i64, + squared_support_with_margin: f32, + particle_rest_mass: f32, + kernel: &K, +) { + #[cfg(any(target_arch = "x86_64", target_arch = "x86"))] + { + if std::arch::is_x86_feature_detected!("avx2") && std::arch::is_x86_feature_detected!("fma") + { + unsafe { + return density_grid_loop_avx( + levelset_grid, + subdomain_particles, + subdomain_particle_densities, + subdomain_mc_grid, + subdomain_ijk, + global_mc_grid, + cube_radius, + squared_support_with_margin, + particle_rest_mass, + kernel, + ); + } + } + } + + // TODO: Not supported on arm (32 bit) until https://github.com/rust-lang/rust/issues/111800 is resolved + #[cfg(target_arch = "aarch64")] + { + if std::arch::is_aarch64_feature_detected!("neon") { + unsafe { + return density_grid_loop_neon( + levelset_grid, + subdomain_particles, + subdomain_particle_densities, + subdomain_mc_grid, + subdomain_ijk, + global_mc_grid, + cube_radius, + squared_support_with_margin, + particle_rest_mass, + kernel, + ); + } + } + } + + // Fallback: scalar generic implementation + density_grid_loop_scalar::( + levelset_grid, + subdomain_particles, + subdomain_particle_densities, + subdomain_mc_grid, + subdomain_ijk, + global_mc_grid, + cube_radius, + squared_support_with_margin, + particle_rest_mass, + kernel, + ); +} + +pub fn density_grid_loop_scalar>( + levelset_grid: &mut [R], + subdomain_particles: &[Vector3], + subdomain_particle_densities: &[R], + subdomain_mc_grid: &UniformCartesianCubeGrid3d, + subdomain_ijk: &[I; 3], + global_mc_grid: &UniformCartesianCubeGrid3d, + cube_radius: I, + squared_support_with_margin: R, + particle_rest_mass: R, + kernel: &K, +) { + profile!("density grid loop (scalar)"); + let mc_grid = subdomain_mc_grid; + + for (p_i, rho_i) in subdomain_particles + .iter() + .copied() + .zip(subdomain_particle_densities.iter().copied()) + { + let (lower, upper) = particle_influence_aabb(&p_i, &mc_grid, cube_radius); + + // Loop over all grid points around the enclosing cell + for i in I::range(lower[0], upper[0]).iter() { + for j in I::range(lower[1], upper[1]).iter() { + for k in I::range(lower[2], upper[2]).iter() { + let point_ijk = [i, j, k]; + let local_point = mc_grid + .get_point(point_ijk) + .expect("point has to be part of the subdomain grid"); + + let mc_cells_per_subdomain = mc_grid.cells_per_dim(); + + // Use global coordinate calculation for consistency with neighboring domains + let global_point_ijk = local_to_global_point_ijk( + point_ijk, + *subdomain_ijk, + *mc_cells_per_subdomain, + ); + let global_point = global_mc_grid + .get_point(global_point_ijk) + .expect("point has to be part of the global mc grid"); + let point_coordinates = global_mc_grid.point_coordinates(&global_point); + + let dx = p_i - point_coordinates; + let dx_norm_sq = dx.norm_squared(); + + if dx_norm_sq < squared_support_with_margin { + let v_i = particle_rest_mass / rho_i; + let r = dx_norm_sq.sqrt(); + let w_ij = kernel.evaluate(r); + //let w_ij = kernel.evaluate(dx_norm_sq); + + let interpolated_value = v_i * w_ij; + + let flat_point_idx = mc_grid.flatten_point_index(&local_point); + let flat_point_idx = flat_point_idx.to_usize().unwrap(); + levelset_grid[flat_point_idx] += interpolated_value; + } + } + } + } + } +} + +#[cfg(all(target_arch = "aarch64"))] +#[target_feature(enable = "neon")] +pub fn density_grid_loop_neon>( + levelset_grid: &mut [f32], + subdomain_particles: &[Vector3], + subdomain_particle_densities: &[f32], + subdomain_mc_grid: &UniformCartesianCubeGrid3d, + subdomain_ijk: &[i64; 3], + global_mc_grid: &UniformCartesianCubeGrid3d, + cube_radius: i64, + _squared_support_with_margin: f32, + particle_rest_mass: f32, + kernel: &K, +) { + use core::arch::aarch64::*; + const LANES: usize = 4; + + // Ensure that we can safely compute global MC vertex positions via u32 indices per dimension + assert!( + global_mc_grid + .points_per_dim() + .iter() + .copied() + .all(|p| p < u32::MAX as i64), + "global marching cubes grid has too many vertices per dimension ({:?}) to fit into u32 (max: {}) for density_grid_loop_neon", + global_mc_grid.points_per_dim(), + u32::MAX + ); + + let kernel_neon = kernel::CubicSplineKernelNeonF32::new(kernel.compact_support_radius()); + + profile!("density grid loop (neon)"); + let mc_grid = subdomain_mc_grid; + let mc_points = mc_grid.points_per_dim(); + let dim_y = mc_points[1] as usize; + let dim_z = mc_points[2] as usize; + + // Preload constants used inside the hot loops + const K_OFFSETS_ARR: [u32; 4] = [0, 1, 2, 3]; + let k_offsets = unsafe { vld1q_u32(K_OFFSETS_ARR.as_ptr()) }; + let global_min = global_mc_grid.aabb().min(); + let min_z_v = vdupq_n_f32(global_min[2]); + let cube_size = global_mc_grid.cell_size(); + let support = kernel.compact_support_radius(); + let support_sq_v = vdupq_n_f32(support * support); + + for (p_i, rho_i) in subdomain_particles + .iter() + .copied() + .zip(subdomain_particle_densities.iter().copied()) + { + let v_i = particle_rest_mass / rho_i; + + let (lower, upper) = particle_influence_aabb(&p_i, &mc_grid, cube_radius); + let lower = lower.map(|i| i as usize); + let upper = upper.map(|i| i as usize); + + let remainder = (upper[2] - lower[2]) % LANES; + let upper_k_aligned = upper[2] - remainder; + + let subdomain_ijk = subdomain_ijk.map(|i| i as u32); + let mc_cells = mc_grid.cells_per_dim().map(|i| i as u32); + + // Broadcast particle coordinates once per particle + let particle_xs = vdupq_n_f32(p_i[0]); + let particle_ys = vdupq_n_f32(p_i[1]); + let particle_zs = vdupq_n_f32(p_i[2]); + + // Function to evaluate kernel contribution of current particle to 8 grid points at once + let evaluate_contribution = + |k: usize, grid_xs: float32x4_t, grid_ys: float32x4_t| -> float32x4_t { + // Compute global k for 4 consecutive points + let global_k_base = vdupq_n_u32(subdomain_ijk[2] * mc_cells[2] + k as u32); + let global_k = vaddq_u32(global_k_base, k_offsets); + let global_k_f32 = vcvtq_f32_u32(global_k); + let grid_zs = vmlaq_n_f32(min_z_v, global_k_f32, cube_size); + // Deltas + let dxs = vsubq_f32(particle_xs, grid_xs); + let dys = vsubq_f32(particle_ys, grid_ys); + let dzs = vsubq_f32(particle_zs, grid_zs); + // Distance squared + let dist_sq = vmlaq_f32(vmulq_f32(dxs, dxs), dys, dys); + let dist_sq = vmlaq_f32(dist_sq, dzs, dzs); + // Cheap mask to skip work if all lanes are outside support + let inside_mask = vcltq_f32(dist_sq, support_sq_v); + let any_inside = vmaxvq_u32(inside_mask); + if any_inside == 0 { + return vdupq_n_f32(0.0); + } + // Compute weights, then mask out lanes outside support + let dist = vsqrtq_f32(dist_sq); + let w = kernel_neon.evaluate(dist); + vbslq_f32(inside_mask, w, vdupq_n_f32(0.0)) + }; + + // Loop over grid points in support region of the particle + for i in lower[0]..upper[0] { + for j in lower[1]..upper[1] { + let flat_index_base = (i * dim_y + j) * dim_z; + + let global_i = subdomain_ijk[0] * mc_cells[0] + i as u32; + let global_j = subdomain_ijk[1] * mc_cells[1] + j as u32; + + let grid_x = global_i as f32 * cube_size + global_min[0]; + let grid_y = global_j as f32 * cube_size + global_min[1]; + let grid_xs = vdupq_n_f32(grid_x); + let grid_ys = vdupq_n_f32(grid_y); + + for k in (lower[2]..upper_k_aligned).step_by(LANES) { + let flat_point_idx = flat_index_base + k; + let w_ij = evaluate_contribution(k, grid_xs, grid_ys); + + let prev_val = unsafe { + vld1q_f32(levelset_grid.as_ptr().offset(flat_point_idx as isize)) + }; + let val = vmlaq_n_f32(prev_val, w_ij, v_i); + unsafe { + vst1q_f32( + levelset_grid.as_mut_ptr().offset(flat_point_idx as isize), + val, + ) + }; + } + + // Handle remainder + if remainder > 0 { + let flat_point_idx = flat_index_base + upper_k_aligned; + let w_ij = evaluate_contribution(upper_k_aligned, grid_xs, grid_ys); + let w_ij_v = vmulq_n_f32(w_ij, v_i); + let w_ij_v = + unsafe { std::mem::transmute::(w_ij_v) }; + for rr in 0..remainder { + levelset_grid[flat_point_idx + rr] += w_ij_v[rr]; + } + } + } + } + } +} + +#[cfg(any(target_arch = "x86_64", target_arch = "x86"))] +#[target_feature(enable = "avx2,fma")] +pub fn density_grid_loop_avx>( + levelset_grid: &mut [f32], + subdomain_particles: &[Vector3], + subdomain_particle_densities: &[f32], + subdomain_mc_grid: &UniformCartesianCubeGrid3d, + subdomain_ijk: &[i64; 3], + global_mc_grid: &UniformCartesianCubeGrid3d, + cube_radius: i64, + _squared_support_with_margin: f32, + particle_rest_mass: f32, + kernel: &K, +) { + #[cfg(target_arch = "x86")] + use core::arch::x86::*; + #[cfg(target_arch = "x86_64")] + use core::arch::x86_64::*; + + const LANES: usize = 8; + + // Ensure that we can safely compute global MC vertex positions via i32 indices per dimension + assert!( + global_mc_grid + .points_per_dim() + .iter() + .copied() + .all(|p| p < i32::MAX as i64), + "global marching cubes grid has too many vertices per dimension ({:?}) to fit into i32 (max: {}) for density_grid_loop_avx", + global_mc_grid.points_per_dim(), + i32::MAX + ); + + let kernel_avx = kernel::CubicSplineKernelAvxF32::new(kernel.compact_support_radius()); + + profile!("density grid loop (avx)"); + let mc_grid = subdomain_mc_grid; + let mc_points = mc_grid.points_per_dim(); + let dim_y = mc_points[1] as usize; + let dim_z = mc_points[2] as usize; + + // Preload constants used inside the hot loops + let k_offsets_i32 = _mm256_setr_epi32(0, 1, 2, 3, 4, 5, 6, 7); + let global_min = global_mc_grid.aabb().min(); + let min_z_v = _mm256_set1_ps(global_min[2]); + let cube_size = global_mc_grid.cell_size(); + let cube_size_ps = _mm256_set1_ps(cube_size); + let support = kernel.compact_support_radius(); + let support_sq_v = _mm256_set1_ps(support * support); + + for (p_i, rho_i) in subdomain_particles + .iter() + .copied() + .zip(subdomain_particle_densities.iter().copied()) + { + let v_i = particle_rest_mass / rho_i; + + let (lower, upper) = particle_influence_aabb(&p_i, &mc_grid, cube_radius); + let lower = lower.map(|i| i as usize); + let upper = upper.map(|i| i as usize); + + let remainder = (upper[2] - lower[2]) % LANES; + let upper_k_aligned = upper[2] - remainder; + + let subdomain_ijk_i32 = subdomain_ijk.map(|i| i as i32); + let mc_cells = mc_grid.cells_per_dim().map(|i| i as i32); + + // Broadcast particle coordinates once per particle + let particle_xs = _mm256_set1_ps(p_i[0]); + let particle_ys = _mm256_set1_ps(p_i[1]); + let particle_zs = _mm256_set1_ps(p_i[2]); + let v_i_ps = _mm256_set1_ps(v_i); + + // Function to evaluate kernel contribution of current particle to 8 grid points at once + let evaluate_contribution = |k: usize, grid_xs: __m256, grid_ys: __m256| -> __m256 { + // Compute global k for 8 consecutive points using i32 lanes and convert to f32 + let base_k = subdomain_ijk_i32[2] * mc_cells[2] + k as i32; + let global_k_i32 = _mm256_add_epi32(_mm256_set1_epi32(base_k), k_offsets_i32); + let global_k_f32 = _mm256_cvtepi32_ps(global_k_i32); + let grid_zs = _mm256_fmadd_ps(global_k_f32, cube_size_ps, min_z_v); + + // Deltas + let dxs = _mm256_sub_ps(particle_xs, grid_xs); + let dys = _mm256_sub_ps(particle_ys, grid_ys); + let dzs = _mm256_sub_ps(particle_zs, grid_zs); + + // Distance squared + let dist_sq = { + let t = _mm256_fmadd_ps(dxs, dxs, _mm256_mul_ps(dys, dys)); + _mm256_fmadd_ps(dzs, dzs, t) + }; + + // Cheap mask to skip work if all lanes are outside support + let inside_mask = _mm256_cmp_ps::<_CMP_LT_OQ>(dist_sq, support_sq_v); + if _mm256_movemask_ps(inside_mask) == 0 { + return _mm256_set1_ps(0.0); + } + + // Compute weights, then mask out lanes outside support + let dist = _mm256_sqrt_ps(dist_sq); + let w = kernel_avx.evaluate(dist); + _mm256_and_ps(w, inside_mask) + }; + + // Loop over grid points in support region of the particle + for i in lower[0]..upper[0] { + for j in lower[1]..upper[1] { + let flat_index_base = (i * dim_y + j) * dim_z; + + let global_i = subdomain_ijk_i32[0] * mc_cells[0] + i as i32; + let global_j = subdomain_ijk_i32[1] * mc_cells[1] + j as i32; + + let grid_x = global_i as f32 * cube_size + global_min[0]; + let grid_y = global_j as f32 * cube_size + global_min[1]; + let grid_xs = _mm256_set1_ps(grid_x); + let grid_ys = _mm256_set1_ps(grid_y); + + for k in (lower[2]..upper_k_aligned).step_by(LANES) { + let flat_point_idx = flat_index_base + k; + let w_ij = evaluate_contribution(k, grid_xs, grid_ys); + + unsafe { + let prev_val = _mm256_loadu_ps(levelset_grid.as_ptr().add(flat_point_idx)); + let val = _mm256_fmadd_ps(w_ij, v_i_ps, prev_val); + _mm256_storeu_ps(levelset_grid.as_mut_ptr().add(flat_point_idx), val); + } + } + + // Handle remainder + if remainder > 0 { + let flat_point_idx = flat_index_base + upper_k_aligned; + let w_ij = evaluate_contribution(upper_k_aligned, grid_xs, grid_ys); + unsafe { + let val = _mm256_mul_ps(w_ij, v_i_ps); + let mut tmp: [f32; LANES] = [0.0; LANES]; + _mm256_storeu_ps(tmp.as_mut_ptr(), val); + for rr in 0..remainder { + levelset_grid[flat_point_idx + rr] += tmp[rr]; + } + } + } + } + } + } +} + +pub fn density_grid_loop_sparse>( + levelset_grid: &mut [R], + index_cache: &mut Vec, + subdomain_particles: &[Vector3], + subdomain_particle_densities: &[R], + subdomain_mc_grid: &UniformCartesianCubeGrid3d, + subdomain_ijk: &[I; 3], + global_mc_grid: &UniformCartesianCubeGrid3d, + cube_radius: I, + squared_support_with_margin: R, + particle_rest_mass: R, + surface_threshold: R, + kernel: &K, +) { + profile!("density grid loop (sparse)"); + let mc_grid = subdomain_mc_grid; + + for (p_i, rho_i) in subdomain_particles + .iter() + .copied() + .zip(subdomain_particle_densities.iter().copied()) + { + let (lower, upper) = particle_influence_aabb(&p_i, &mc_grid, cube_radius); + + // Loop over all grid points around the enclosing cell + for i in I::range(lower[0], upper[0]).iter() { + for j in I::range(lower[1], upper[1]).iter() { + for k in I::range(lower[2], upper[2]).iter() { + let point_ijk = [i, j, k]; + let local_point = mc_grid + .get_point(point_ijk) + .expect("point has to be part of the subdomain grid"); + + let mc_cells_per_subdomain = mc_grid.cells_per_dim(); + + // Use global coordinate calculation for consistency with neighboring domains + let global_point_ijk = local_to_global_point_ijk( + point_ijk, + *subdomain_ijk, + *mc_cells_per_subdomain, + ); + let global_point = global_mc_grid + .get_point(global_point_ijk) + .expect("point has to be part of the global mc grid"); + let point_coordinates = global_mc_grid.point_coordinates(&global_point); + + let dx = p_i - point_coordinates; + let dx_norm_sq = dx.norm_squared(); + + if dx_norm_sq < squared_support_with_margin { + let v_i = particle_rest_mass / rho_i; + let r = dx_norm_sq.sqrt(); + let w_ij = kernel.evaluate(r); + //let w_ij = kernel.evaluate(dx_norm_sq); + + let interpolated_value = v_i * w_ij; + + let flat_point_idx = mc_grid.flatten_point_index(&local_point); + let flat_point_idx = flat_point_idx.to_usize().unwrap(); + levelset_grid[flat_point_idx] += interpolated_value; + + if levelset_grid[flat_point_idx] > surface_threshold { + for c in mc_grid + .cells_adjacent_to_point( + &mc_grid.get_point_neighborhood(&local_point), + ) + .iter() + .flatten() + { + let flat_cell_index = mc_grid.flatten_cell_index(c); + index_cache.push(flat_cell_index); + } + } + } + } + } + } + } +} + pub(crate) fn reconstruction( parameters: &ParametersSubdomainGrid, global_particles: &[Vector3], global_particle_densities: &[R], subdomains: &Subdomains, + enable_simd: bool, ) -> Vec> { profile!(parent, "reconstruction"); @@ -787,7 +1344,9 @@ pub(crate) fn reconstruction( let workspace_tls = ThreadLocal::>>::new(); - let reconstruct_dense = |flat_subdomain_idx: I, subdomain_particle_indices: &Vec| { + let reconstruct_patch = |flat_subdomain_idx: I, + subdomain_particle_indices: &Vec, + sparse: bool| { // Obtain thread local workspace and clear it let mut workspace = workspace_tls.get_or_default().borrow_mut(); @@ -795,7 +1354,7 @@ pub(crate) fn reconstruction( subdomain_particles, subdomain_particle_densities, levelset_grid, - index_cache: _index_cache, + index_cache, } = &mut *workspace; let flat_subdomain_idx: I = flat_subdomain_idx; @@ -833,105 +1392,67 @@ pub(crate) fn reconstruction( levelset_grid.fill(R::zero()); levelset_grid.resize(mc_total_points.to_usize().unwrap(), R::zero()); - { - profile!("density grid loop"); - - let extents = mc_grid.points_per_dim(); + index_cache.clear(); - for (p_i, rho_i) in subdomain_particles - .iter() - .copied() - .zip(subdomain_particle_densities.iter().copied()) + if sparse { + density_grid_loop_sparse( + levelset_grid.as_mut_slice(), + index_cache, + subdomain_particles.as_slice(), + subdomain_particle_densities.as_slice(), + &mc_grid, + &subdomain_idx.index(), + ¶meters.global_marching_cubes_grid, + cube_radius, + squared_support_with_margin, + parameters.particle_rest_mass, + parameters.surface_threshold, + &kernel, + ); + } else { + use std::any::TypeId; + use std::mem::transmute; + if enable_simd + && TypeId::of::() == TypeId::of::() + && TypeId::of::() == TypeId::of::() { - // Note: this loop assumes that enclosing_cell can return negative indices for ghost particles - - // Get grid cell containing particle - let particle_cell = mc_grid.enclosing_cell(&p_i); - - // Compute lower and upper bounds of the grid points possibly affected by the particle - // We want to loop over the vertices of the enclosing cells plus all points in `cube_radius` distance from the cell - - let lower = [0, 1, 2].map(|i| { - particle_cell[i] - .saturating_sub(&cube_radius) - .max(I::zero()) - .min(extents[i]) - }); - - let upper = [0, 1, 2].map(|i| { - // We add 2 because - // - we want to loop over all grid points of the cell (+1 for upper points) + the radius - // - the upper range limit is exclusive (+1) - (particle_cell[i] + cube_radius + I::two()) - .min(extents[i]) - .max(I::zero()) - }); - - // Loop over all grid points around the enclosing cell - for i in I::range(lower[0], upper[0]).iter() { - for j in I::range(lower[1], upper[1]).iter() { - for k in I::range(lower[2], upper[2]).iter() { - let point_ijk = [i, j, k]; - let local_point = mc_grid - .get_point(point_ijk) - .expect("point has to be part of the subdomain grid"); - //let point_coordinates = mc_grid.point_coordinates(&point); - - let subdomain_ijk = subdomain_idx.index(); - let mc_cells_per_subdomain = mc_grid.cells_per_dim(); - - fn local_to_global_point_ijk( - local_point_ijk: [I; 3], - subdomain_ijk: [I; 3], - cells_per_subdomain: [I; 3], - ) -> [GlobalIndex; 3] { - let local_point_ijk = local_point_ijk - .map(|i| ::from(i).unwrap()); - let subdomain_ijk = subdomain_ijk - .map(|i| ::from(i).unwrap()); - let cells_per_subdomain = cells_per_subdomain - .map(|i| ::from(i).unwrap()); - let [i, j, k] = local_point_ijk; - - [ - subdomain_ijk[0] * cells_per_subdomain[0] + i, - subdomain_ijk[1] * cells_per_subdomain[1] + j, - subdomain_ijk[2] * cells_per_subdomain[2] + k, - ] - } - - // Use global coordinate calculation for consistency with neighboring domains - let global_point_ijk = local_to_global_point_ijk( - point_ijk, - *subdomain_ijk, - *mc_cells_per_subdomain, - ); - let global_point = parameters - .global_marching_cubes_grid - .get_point(global_point_ijk) - .expect("point has to be part of the global mc grid"); - let point_coordinates = parameters - .global_marching_cubes_grid - .point_coordinates(&global_point); - - let dx = p_i - point_coordinates; - let dx_norm_sq = dx.norm_squared(); - - if dx_norm_sq < squared_support_with_margin { - let v_i = parameters.particle_rest_mass / rho_i; - let r = dx_norm_sq.sqrt(); - let w_ij = kernel.evaluate(r); - //let w_ij = kernel.evaluate(dx_norm_sq); - - let interpolated_value = v_i * w_ij; - - let flat_point_idx = mc_grid.flatten_point_index(&local_point); - let flat_point_idx = flat_point_idx.to_usize().unwrap(); - levelset_grid[flat_point_idx] += interpolated_value; - } - } - } - } + density_grid_loop_auto( + unsafe { transmute::<&mut [R], &mut [f32]>(levelset_grid.as_mut_slice()) }, + unsafe { + transmute::<&[Vector3], &[Vector3]>(subdomain_particles.as_slice()) + }, + unsafe { transmute::<&[R], &[f32]>(subdomain_particle_densities.as_slice()) }, + unsafe { + transmute::< + &UniformCartesianCubeGrid3d, + &UniformCartesianCubeGrid3d, + >(&mc_grid) + }, + &subdomain_idx.index().map(|i| i.to_i64().unwrap()), + unsafe { + transmute::< + &UniformCartesianCubeGrid3d, + &UniformCartesianCubeGrid3d, + >(¶meters.global_marching_cubes_grid) + }, + cube_radius.to_i64().unwrap(), + squared_support_with_margin.to_f32().unwrap(), + parameters.particle_rest_mass.to_f32().unwrap(), + &CubicSplineKernel::new(parameters.compact_support_radius.to_f32().unwrap()), + ); + } else { + density_grid_loop_scalar( + levelset_grid.as_mut_slice(), + subdomain_particles.as_slice(), + subdomain_particle_densities.as_slice(), + &mc_grid, + &subdomain_idx.index(), + ¶meters.global_marching_cubes_grid, + cube_radius, + squared_support_with_margin, + parameters.particle_rest_mass, + &kernel, + ); } } @@ -948,354 +1469,94 @@ pub(crate) fn reconstruction( let mut edge_to_vertex = new_map(); - { - profile!("mc triangulation loop"); - - for flat_cell_idx in I::range(I::zero(), mc_total_cells).iter() { - let cell = mc_grid.try_unflatten_cell_index(flat_cell_idx).unwrap(); - - let mut vertices_inside = [true; 8]; - for local_point_index in 0..8 { - let point = cell.global_point_index_of(local_point_index).unwrap(); - let flat_point_idx = mc_grid.flatten_point_index(&point); - let flat_point_idx = flat_point_idx.to_usize().unwrap(); - // Get value of density map - let density_value = levelset_grid[flat_point_idx]; - // Update inside/outside surface flag - vertices_inside[local_point_index] = - density_value > parameters.surface_threshold; - } + let mut triangulate_cell = |flat_cell_idx: I| { + let cell = mc_grid.try_unflatten_cell_index(flat_cell_idx).unwrap(); + + let mut vertices_inside = [true; 8]; + for local_point_index in 0..8 { + let point = cell.global_point_index_of(local_point_index).unwrap(); + let flat_point_idx = mc_grid.flatten_point_index(&point); + let flat_point_idx = flat_point_idx.to_usize().unwrap(); + // Get value of density map + let density_value = levelset_grid[flat_point_idx]; + // Update inside/outside surface flag + vertices_inside[local_point_index] = density_value > parameters.surface_threshold; + } - for triangle in marching_cubes_triangulation_iter(&vertices_inside) { - let mut global_triangle = [0; 3]; - for (v_idx, local_edge_index) in triangle.iter().copied().enumerate() { - let edge = cell - .global_edge_index_of(local_edge_index as usize) + for triangle in marching_cubes_triangulation_iter(&vertices_inside) { + let mut global_triangle = [0; 3]; + for (v_idx, local_edge_index) in triangle.iter().copied().enumerate() { + let edge = cell + .global_edge_index_of(local_edge_index as usize) + .unwrap(); + let vertex_index = *edge_to_vertex.entry(edge).or_insert_with(|| { + // TODO: Nonlinear interpolation + + let origin_coords = mc_grid.point_coordinates(edge.origin()); + let target_coords = mc_grid.point_coordinates(&edge.target()); + + let flat_origin_idx = mc_grid + .flatten_point_index(edge.origin()) + .to_usize() + .unwrap(); + let flat_target_idx = mc_grid + .flatten_point_index(&edge.target()) + .to_usize() .unwrap(); - let vertex_index = *edge_to_vertex.entry(edge).or_insert_with(|| { - // TODO: Nonlinear interpolation - - let origin_coords = mc_grid.point_coordinates(edge.origin()); - let target_coords = mc_grid.point_coordinates(&edge.target()); - - let flat_origin_idx = mc_grid - .flatten_point_index(edge.origin()) - .to_usize() - .unwrap(); - let flat_target_idx = mc_grid - .flatten_point_index(&edge.target()) - .to_usize() - .unwrap(); - - let origin_value = levelset_grid[flat_origin_idx]; - let target_value = levelset_grid[flat_target_idx]; - - let alpha = (parameters.surface_threshold - origin_value) - / (target_value - origin_value); - let interpolated_coords = - origin_coords * (R::one() - alpha) + target_coords * alpha; - let vertex_coords = interpolated_coords; - - vertices.push(vertex_coords); - let vertex_index = vertices.len() - 1; - - let is_interior_vertex = !mc_grid.is_boundary_edge(&edge); - vertex_inside_count += is_interior_vertex as usize; - vertex_inside_flags.push(is_interior_vertex); - - if !is_interior_vertex { - exterior_vertex_edge_indices.push(globalize_local_edge( - &mc_grid, - ¶meters.subdomain_grid, - flat_subdomain_idx, - &edge, - )); - } - - vertex_index - }); - global_triangle[v_idx] = vertex_index; - } + let origin_value = levelset_grid[flat_origin_idx]; + let target_value = levelset_grid[flat_target_idx]; + + let alpha = (parameters.surface_threshold - origin_value) + / (target_value - origin_value); + let interpolated_coords = + origin_coords * (R::one() - alpha) + target_coords * alpha; + let vertex_coords = interpolated_coords; + + vertices.push(vertex_coords); + let vertex_index = vertices.len() - 1; + + let is_interior_vertex = !mc_grid.is_boundary_edge(&edge); + vertex_inside_count += is_interior_vertex as usize; + vertex_inside_flags.push(is_interior_vertex); + + if !is_interior_vertex { + exterior_vertex_edge_indices.push(globalize_local_edge( + &mc_grid, + ¶meters.subdomain_grid, + flat_subdomain_idx, + &edge, + )); + } - let all_tri_vertices_inside = global_triangle - .iter() - .copied() - .all(|v_idx| vertex_inside_flags[v_idx]); + vertex_index + }); - triangles.push(global_triangle); - triangle_inside_count += all_tri_vertices_inside as usize; - triangle_inside_flags.push(all_tri_vertices_inside); + global_triangle[v_idx] = vertex_index; } - } - } - - SurfacePatch { - vertices, - triangles, - vertex_inside_count, - triangle_inside_count, - vertex_inside_flags, - triangle_inside_flags, - exterior_vertex_edge_indices, - } - }; - - let reconstruct_sparse = |flat_subdomain_idx: I, subdomain_particle_indices: &Vec| { - // Obtain thread local workspace and clear it - let mut workspace = workspace_tls.get_or_default().borrow_mut(); - - let SubdomainWorkspace { - subdomain_particles, - subdomain_particle_densities, - levelset_grid, - index_cache, - } = &mut *workspace; - - let flat_subdomain_idx: I = flat_subdomain_idx; - let subdomain_particle_indices: &[usize] = subdomain_particle_indices.as_slice(); - - // Collect all particle positions and densities of this subdomain - { - //profile!("collect subdomain data"); - gather_subdomain_data( - global_particles, - subdomain_particle_indices, - subdomain_particles, - ); - gather_subdomain_data( - global_particle_densities, - subdomain_particle_indices, - subdomain_particle_densities, - ); - } - - // Get the cell index and AABB of the subdomain - let subdomain_idx = parameters - .subdomain_grid - .try_unflatten_cell_index(flat_subdomain_idx) - .expect("Subdomain cell does not exist"); - let subdomain_aabb = parameters.subdomain_grid.cell_aabb(&subdomain_idx); - - let mc_grid = UniformCartesianCubeGrid3d::new( - subdomain_aabb.min(), - &[parameters.subdomain_cubes; 3], - parameters.cube_size, - ) - .unwrap(); - - levelset_grid.fill(R::zero()); - levelset_grid.resize(mc_total_points.to_usize().unwrap(), R::zero()); - - index_cache.clear(); - - { - profile!("density grid loop"); - - let extents = mc_grid.points_per_dim(); - - for (p_i, rho_i) in subdomain_particles - .iter() - .copied() - .zip(subdomain_particle_densities.iter().copied()) - { - // Note: this loop assumes that enclosing_cell can return negative indices for ghost particles - - // Get grid cell containing particle - let particle_cell = mc_grid.enclosing_cell(&p_i); - - // Compute lower and upper bounds of the grid points possibly affected by the particle - // We want to loop over the vertices of the enclosing cells plus all points in `cube_radius` distance from the cell - - let lower = [0, 1, 2].map(|i| { - particle_cell[i] - .saturating_sub(&cube_radius) - .max(I::zero()) - .min(extents[i]) - }); - - let upper = [0, 1, 2].map(|i| { - // We add 2 because - // - we want to loop over all grid points of the cell (+1 for upper points) + the radius - // - the upper range limit is exclusive (+1) - (particle_cell[i] + cube_radius + I::two()) - .min(extents[i]) - .max(I::zero()) - }); - // Loop over all grid points around the enclosing cell - for i in I::range(lower[0], upper[0]).iter() { - for j in I::range(lower[1], upper[1]).iter() { - for k in I::range(lower[2], upper[2]).iter() { - let point_ijk = [i, j, k]; - let local_point = mc_grid - .get_point(point_ijk) - .expect("point has to be part of the subdomain grid"); - //let point_coordinates = mc_grid.point_coordinates(&point); - - let subdomain_ijk = subdomain_idx.index(); - let mc_cells_per_subdomain = mc_grid.cells_per_dim(); - - fn local_to_global_point_ijk( - local_point_ijk: [I; 3], - subdomain_ijk: [I; 3], - cells_per_subdomain: [I; 3], - ) -> [GlobalIndex; 3] { - let local_point_ijk = local_point_ijk - .map(|i| ::from(i).unwrap()); - let subdomain_ijk = subdomain_ijk - .map(|i| ::from(i).unwrap()); - let cells_per_subdomain = cells_per_subdomain - .map(|i| ::from(i).unwrap()); - let [i, j, k] = local_point_ijk; - - [ - subdomain_ijk[0] * cells_per_subdomain[0] + i, - subdomain_ijk[1] * cells_per_subdomain[1] + j, - subdomain_ijk[2] * cells_per_subdomain[2] + k, - ] - } + let all_tri_vertices_inside = global_triangle + .iter() + .copied() + .all(|v_idx| vertex_inside_flags[v_idx]); - // Use global coordinate calculation for consistency with neighboring domains - let global_point_ijk = local_to_global_point_ijk( - point_ijk, - *subdomain_ijk, - *mc_cells_per_subdomain, - ); - let global_point = parameters - .global_marching_cubes_grid - .get_point(global_point_ijk) - .expect("point has to be part of the global mc grid"); - let point_coordinates = parameters - .global_marching_cubes_grid - .point_coordinates(&global_point); - - let dx = p_i - point_coordinates; - let dx_norm_sq = dx.norm_squared(); - - if dx_norm_sq < squared_support_with_margin { - let v_i = parameters.particle_rest_mass / rho_i; - let r = dx_norm_sq.sqrt(); - let w_ij = kernel.evaluate(r); - //let w_ij = kernel.evaluate(dx_norm_sq); - - let interpolated_value = v_i * w_ij; - - let flat_point_idx = mc_grid.flatten_point_index(&local_point); - let flat_point_idx = flat_point_idx.to_usize().unwrap(); - levelset_grid[flat_point_idx] += interpolated_value; - - if levelset_grid[flat_point_idx] > parameters.surface_threshold { - for c in mc_grid - .cells_adjacent_to_point( - &mc_grid.get_point_neighborhood(&local_point), - ) - .iter() - .flatten() - { - let flat_cell_index = mc_grid.flatten_cell_index(c); - index_cache.push(flat_cell_index); - } - } - } - } - } - } + triangles.push(global_triangle); + triangle_inside_count += all_tri_vertices_inside as usize; + triangle_inside_flags.push(all_tri_vertices_inside); } - } - - let mut vertices = Vec::new(); - let mut triangles = Vec::new(); - - let mut vertex_inside_count = 0; - let mut triangle_inside_count = 0; - - let mut vertex_inside_flags = Vec::new(); - let mut triangle_inside_flags = Vec::new(); - - let mut exterior_vertex_edge_indices = Vec::new(); - - let mut edge_to_vertex = new_map(); + }; { profile!("mc triangulation loop"); - index_cache.sort_unstable(); - for flat_cell_idx in index_cache.iter().copied().dedup() { - let cell = mc_grid.try_unflatten_cell_index(flat_cell_idx).unwrap(); - - let mut vertices_inside = [true; 8]; - for local_point_index in 0..8 { - let point = cell.global_point_index_of(local_point_index).unwrap(); - let flat_point_idx = mc_grid.flatten_point_index(&point); - let flat_point_idx = flat_point_idx.to_usize().unwrap(); - // Get value of density map - let density_value = levelset_grid[flat_point_idx]; - // Update inside/outside surface flag - vertices_inside[local_point_index] = - density_value > parameters.surface_threshold; + if sparse { + index_cache.sort_unstable(); + for flat_cell_idx in index_cache.iter().copied().dedup() { + triangulate_cell(flat_cell_idx); } - - for triangle in marching_cubes_triangulation_iter(&vertices_inside) { - let mut global_triangle = [0; 3]; - for (v_idx, local_edge_index) in triangle.iter().copied().enumerate() { - let edge = cell - .global_edge_index_of(local_edge_index as usize) - .unwrap(); - let vertex_index = *edge_to_vertex.entry(edge).or_insert_with(|| { - // TODO: Nonlinear interpolation - - let origin_coords = mc_grid.point_coordinates(edge.origin()); - let target_coords = mc_grid.point_coordinates(&edge.target()); - - let flat_origin_idx = mc_grid - .flatten_point_index(edge.origin()) - .to_usize() - .unwrap(); - let flat_target_idx = mc_grid - .flatten_point_index(&edge.target()) - .to_usize() - .unwrap(); - - let origin_value = levelset_grid[flat_origin_idx]; - let target_value = levelset_grid[flat_target_idx]; - - let alpha = (parameters.surface_threshold - origin_value) - / (target_value - origin_value); - let interpolated_coords = - origin_coords * (R::one() - alpha) + target_coords * alpha; - let vertex_coords = interpolated_coords; - - vertices.push(vertex_coords); - let vertex_index = vertices.len() - 1; - - let is_interior_vertex = !mc_grid.is_boundary_edge(&edge); - vertex_inside_count += is_interior_vertex as usize; - vertex_inside_flags.push(is_interior_vertex); - - if !is_interior_vertex { - exterior_vertex_edge_indices.push(globalize_local_edge( - &mc_grid, - ¶meters.subdomain_grid, - flat_subdomain_idx, - &edge, - )); - } - - vertex_index - }); - - global_triangle[v_idx] = vertex_index; - } - - let all_tri_vertices_inside = global_triangle - .iter() - .copied() - .all(|v_idx| vertex_inside_flags[v_idx]); - - triangles.push(global_triangle); - triangle_inside_count += all_tri_vertices_inside as usize; - triangle_inside_flags.push(all_tri_vertices_inside); + } else { + for flat_cell_idx in I::range(I::zero(), mc_total_cells).iter() { + triangulate_cell(flat_cell_idx); } } } @@ -1322,10 +1583,10 @@ pub(crate) fn reconstruction( // If support radius is huge, the dense method might be better even for few particles if subdomain_particle_indices.len() <= sparse_limit { profile!("subdomain reconstruction (sparse)", parent = parent); - reconstruct_sparse(flat_subdomain_idx, subdomain_particle_indices) + reconstruct_patch(flat_subdomain_idx, subdomain_particle_indices, true) } else { profile!("subdomain reconstruction (dense)", parent = parent); - reconstruct_dense(flat_subdomain_idx, subdomain_particle_indices) + reconstruct_patch(flat_subdomain_idx, subdomain_particle_indices, false) } }) .collect_into_vec(&mut surface_patches); diff --git a/splashsurf_lib/src/kernel.rs b/splashsurf_lib/src/kernel.rs index 2b79ab5a..3b3c84a7 100644 --- a/splashsurf_lib/src/kernel.rs +++ b/splashsurf_lib/src/kernel.rs @@ -1,9 +1,23 @@ //! SPH kernel function implementations +//! +//! Currently, the following SIMD implementations are provided: +//! - `CubicSplineKernelAvxF32`: Only available on `x86` and `x86_64` targets, requires AVX2 and FMA support +//! - `CubicSplineKernelNeonF32`: Only available on `aarch64` targets, requires NEON support +//! +//! Note that documentation of the SIMD kernels is only available on the respective target architectures. use crate::{Real, RealConvert}; use nalgebra::Vector3; use numeric_literals::replace_float_literals; +#[cfg(all(target_arch = "aarch64"))] +use core::arch::aarch64::float32x4_t; + +#[cfg(target_arch = "x86")] +use core::arch::x86::__m256; +#[cfg(target_arch = "x86_64")] +use core::arch::x86_64::__m256; + // TODO: Add reference for the kernel function, document formula /// Utility functions for computing the volume of fluid particles @@ -23,6 +37,8 @@ impl Volume { /// Trait for symmetric kernel functions in three dimensions pub trait SymmetricKernel3d { + /// Returns the compact support radius of the kernel + fn compact_support_radius(&self) -> R; /// Evaluates the kernel at the radial distance `r` relative to the origin fn evaluate(&self, r: R) -> R; /// Evaluates the kernel gradient at the position `x` relative to the origin @@ -80,6 +96,10 @@ impl CubicSplineKernel { } impl SymmetricKernel3d for CubicSplineKernel { + fn compact_support_radius(&self) -> R { + self.compact_support_radius + } + /// Evaluates the cubic spline kernel at the radial distance `r` fn evaluate(&self, r: R) -> R { let q = (r + r) / self.compact_support_radius; @@ -159,6 +179,307 @@ fn test_cubic_kernel_r_integral() { } } +/// Vectorized implementation of the cubic spline kernel using NEON instructions. Only available on `aarch64` targets. +#[cfg(target_arch = "aarch64")] +pub struct CubicSplineKernelNeonF32 { + compact_support_inv: f32, + sigma: f32, +} + +#[cfg(target_arch = "aarch64")] +impl CubicSplineKernelNeonF32 { + /// Initializes a cubic spline kernel with the given compact support radius + pub fn new(compact_support_radius: f32) -> Self { + let r = compact_support_radius; + let compact_support_inv = 1.0 / r; + let rrr = r * r * r; + let sigma = 8.0 / (std::f32::consts::PI * rrr); + Self { + compact_support_inv, + sigma, + } + } + + /// Evaluates the cubic spline kernel at the specified radial distances + #[target_feature(enable = "neon")] + pub fn evaluate(&self, r: float32x4_t) -> float32x4_t { + use core::arch::aarch64::*; + + let one = vdupq_n_f32(1.0); + let half = vdupq_n_f32(0.5); + let zero = vdupq_n_f32(0.0); + + // q = r / h, v = 1 - q + let q = vmulq_n_f32(r, self.compact_support_inv); + let v = vsubq_f32(one, q); + // Clamp v to [0, 1] to implicitly zero-out contributions with q > 1 + let v = vmaxq_f32(v, zero); + + // Reuse v^2 and v^3 for both branches + let v2 = vmulq_f32(v, v); + let v3 = vmulq_f32(v2, v); + + // Outer branch (0.5 < q <= 1.0): 2*sigma*(1 - q)^3 = 2*sigma*v^3 + let res_outer = vmulq_n_f32(v3, 2.0 * self.sigma); + + // Inner branch (q <= 0.5) rewritten in terms of v to avoid computing q^2: + // sigma * (1 - 6q^2 + 6q^3) == sigma * (1 - 6v + 12v^2 - 6v^3) + let mut res_inner = vdupq_n_f32(self.sigma); + res_inner = vmlsq_n_f32(res_inner, v, 6.0 * self.sigma); // -6*sigma*v + res_inner = vmlaq_n_f32(res_inner, v2, 12.0 * self.sigma); // +12*sigma*v^2 + res_inner = vmlsq_n_f32(res_inner, v3, 6.0 * self.sigma); // -6*sigma*v^3 + + // Select inner for q <= 0.5, else outer; v was clamped so q > 1 yields 0 automatically + let leq_than_half = vcleq_f32(q, half); + vbslq_f32(leq_than_half, res_inner, res_outer) + } +} + +#[test] +#[cfg_attr( + not(all(target_arch = "aarch64", target_feature = "neon")), + ignore = "Skipped on non-aarch64 targets" +)] +fn test_cubic_spline_kernel_neon() { + #[cfg(all(target_arch = "aarch64", target_feature = "neon"))] + { + use core::arch::aarch64::*; + + // Test a few representative compact support radii + let hs: [f32; 3] = [0.025, 0.1, 2.0]; + for &h in hs.iter() { + let scalar = CubicSplineKernel::new(h); + let neon = CubicSplineKernelNeonF32::new(h); + + // Sample radii from 0 to 2h (beyond support should be 0) + let n: usize = 1024; + let mut r0: f32 = 0.0; + let dr: f32 = (2.0 * h) / (n as f32); + + for _chunk in 0..(n / 4) { + // Prepare 4 lanes of radii + let rs = [r0, r0 + dr, r0 + 2.0 * dr, r0 + 3.0 * dr]; + let r_vec = unsafe { vld1q_f32(rs.as_ptr()) }; + + // Evaluate NEON and store back to array + let w_vec = unsafe { neon.evaluate(r_vec) }; + let mut w_neon = [0.0f32; 4]; + unsafe { vst1q_f32(w_neon.as_mut_ptr(), w_vec) }; + + // Compare against scalar lane-wise + for lane in 0..4 { + let r_lane = rs[lane]; + let w_scalar = scalar.evaluate(r_lane); + let diff = (w_neon[lane] - w_scalar).abs(); + + // Absolute tolerance with mild relative component to be robust across scales + let tol = 5e-6_f32.max(2e-5_f32 * w_scalar.abs()); + assert!( + diff <= tol, + "NEON kernel mismatch (h={}, r={}, lane={}): neon={}, scalar={}, diff={}, tol={}", + h, + r_lane, + lane, + w_neon[lane], + w_scalar, + diff, + tol + ); + } + + r0 += 4.0 * dr; + } + + // Also check a couple of out-of-support points explicitly + for &r in &[h * 1.01, h * 1.5, h * 2.0, h * 2.5] { + let w_scalar = scalar.evaluate(r); + let w_neon = { + let v = unsafe { vld1q_f32([r, r, r, r].as_ptr()) }; + let w = unsafe { neon.evaluate(v) }; + let mut tmp = [0.0f32; 4]; + unsafe { vst1q_f32(tmp.as_mut_ptr(), w) }; + tmp[0] + }; + let diff = (w_neon - w_scalar).abs(); + let tol = 5e-6_f32.max(1e-5_f32 * w_scalar.abs()); + assert!( + diff <= tol, + "NEON kernel mismatch outside support (h={}, r={}): neon={}, scalar={}, diff={}, tol={}", + h, + r, + w_neon, + w_scalar, + diff, + tol + ); + } + } + } +} + +/// Vectorized implementation of the cubic spline kernel using AVX2 and FMA instructions. Only available on `x86` and `x86_64` targets. +#[cfg(any(target_arch = "x86_64", target_arch = "x86"))] +pub struct CubicSplineKernelAvxF32 { + compact_support_inv: f32, + sigma: f32, +} + +#[cfg(any(target_arch = "x86_64", target_arch = "x86"))] +impl CubicSplineKernelAvxF32 { + /// Initializes a cubic spline kernel with the given compact support radius + pub fn new(compact_support_radius: f32) -> Self { + let r = compact_support_radius; + let compact_support_inv = 1.0 / r; + let rrr = r * r * r; + let sigma = 8.0 / (std::f32::consts::PI * rrr); + Self { + compact_support_inv, + sigma, + } + } + + /// Evaluates the cubic spline kernel at the specified radial distances + #[target_feature(enable = "avx2,fma")] + pub fn evaluate(&self, r: __m256) -> __m256 { + #[cfg(target_arch = "x86")] + use core::arch::x86::*; + #[cfg(target_arch = "x86_64")] + use core::arch::x86_64::*; + + let one = _mm256_set1_ps(1.0); + let half = _mm256_set1_ps(0.5); + let zero = _mm256_set1_ps(0.0); + + // q = r / h, v = 1 - q + let q = _mm256_mul_ps(r, _mm256_set1_ps(self.compact_support_inv)); + let mut v = _mm256_sub_ps(one, q); + // Clamp v to [0, 1] to implicitly zero-out contributions with q > 1 + v = _mm256_max_ps(v, zero); + + // v^2 and v^3 + let v2 = _mm256_mul_ps(v, v); + let v3 = _mm256_mul_ps(v2, v); + + // Outer: 2*sigma*v^3 + let res_outer = _mm256_mul_ps(v3, _mm256_set1_ps(2.0 * self.sigma)); + + // Inner: sigma * (1 - 6v + 12v^2 - 6v^3) + let mut res_inner = _mm256_set1_ps(self.sigma); + // res_inner = res_inner - 6*sigma*v + res_inner = _mm256_fnmadd_ps(v, _mm256_set1_ps(6.0 * self.sigma), res_inner); + // res_inner = res_inner + 12*sigma*v^2 + res_inner = _mm256_fmadd_ps(v2, _mm256_set1_ps(12.0 * self.sigma), res_inner); + // res_inner = res_inner - 6*sigma*v^3 + res_inner = _mm256_fnmadd_ps(v3, _mm256_set1_ps(6.0 * self.sigma), res_inner); + + // Select inner for q <= 0.5, else outer + let leq_than_half = _mm256_cmp_ps::<_CMP_LE_OQ>(q, half); + _mm256_blendv_ps(res_outer, res_inner, leq_than_half) + } +} + +#[test] +#[cfg_attr( + not(all( + any(target_arch = "x86_64", target_arch = "x86"), + target_feature = "avx2", + target_feature = "fma" + )), + ignore = "Skipped on non-x86 targets" +)] +fn test_cubic_spline_kernel_avx() { + #[cfg(all( + any(target_arch = "x86_64", target_arch = "x86"), + target_feature = "avx2", + target_feature = "fma" + ))] + { + #[cfg(target_arch = "x86")] + use core::arch::x86::*; + #[cfg(target_arch = "x86_64")] + use core::arch::x86_64::*; + + // Test a few representative compact support radii + let hs: [f32; 3] = [0.025, 0.1, 2.0]; + for &h in hs.iter() { + let scalar = CubicSplineKernel::new(h); + let avx = CubicSplineKernelAvxF32::new(h); + + // Sample radii from 0 to 2h (beyond support should be 0) + let n: usize = 1024; + let mut r0: f32 = 0.0; + let dr: f32 = (2.0 * h) / (n as f32); + + for _chunk in 0..(n / 8) { + // Prepare 8 lanes of radii + let rs = [ + r0, + r0 + dr, + r0 + 2.0 * dr, + r0 + 3.0 * dr, + r0 + 4.0 * dr, + r0 + 5.0 * dr, + r0 + 6.0 * dr, + r0 + 7.0 * dr, + ]; + + // Evaluate AVX and store back to array + let r_vec = unsafe { _mm256_loadu_ps(rs.as_ptr()) }; + let w_vec = unsafe { avx.evaluate(r_vec) }; + let mut w_avx = [0.0f32; 8]; + unsafe { _mm256_storeu_ps(w_avx.as_mut_ptr(), w_vec) }; + + // Compare against scalar lane-wise + for lane in 0..8 { + let r_lane = rs[lane]; + let w_scalar = scalar.evaluate(r_lane); + let diff = (w_avx[lane] - w_scalar).abs(); + + // Absolute tolerance with mild relative component to be robust across scales + let tol = 1e-6_f32.max(1e-5_f32 * w_scalar.abs()); + assert!( + diff <= tol, + "AVX kernel mismatch (h={}, r={}, lane={}): avx={}, scalar={}, diff={}, tol={}", + h, + r_lane, + lane, + w_avx[lane], + w_scalar, + diff, + tol + ); + } + + r0 += 8.0 * dr; + } + + // Also check a couple of out-of-support points explicitly + for &r in &[h * 1.01, h * 1.5, h * 2.0, h * 2.5] { + let w_scalar = scalar.evaluate(r); + let w_avx = { + let v = unsafe { _mm256_set1_ps(r) }; + let w = unsafe { avx.evaluate(v) }; + let mut tmp = [0.0f32; 8]; + unsafe { _mm256_storeu_ps(tmp.as_mut_ptr(), w) }; + tmp[0] + }; + let diff = (w_avx - w_scalar).abs(); + let tol = 1e-6_f32.max(1e-5_f32 * w_scalar.abs()); + assert!( + diff <= tol, + "AVX kernel mismatch outside support (h={}, r={}): avx={}, scalar={}, diff={}, tol={}", + h, + r, + w_avx, + w_scalar, + diff, + tol + ); + } + } + } +} + /// Accelerator for efficient evaluation of a precomputed cubic kernel /// /// This structure is used to pre-compute a discrete representation of the cubic kernel function. diff --git a/splashsurf_lib/src/lib.rs b/splashsurf_lib/src/lib.rs index 7d7ec155..e5da862b 100644 --- a/splashsurf_lib/src/lib.rs +++ b/splashsurf_lib/src/lib.rs @@ -21,9 +21,10 @@ //! by binary crates calling into this library to add their own profiling scopes to the measurements. //! If this features is not enabled, the macro will just expend to a no-op and remove the (small) //! performance overhead of the profiling. +//! - **`serde-serialize`**: Enables `Serialize` and `Deserialize` impls for some types using `serde`. //! -use log::info; +use log::{info, warn}; /// Re-export the version of `nalgebra` used by this crate pub use nalgebra; use nalgebra::Scalar; @@ -53,7 +54,7 @@ pub mod profiling; pub mod profiling_macro; mod aabb; -pub(crate) mod dense_subdomains; +pub mod dense_subdomains; pub mod density_map; pub mod generic_tree; pub mod halfedge_mesh; @@ -74,7 +75,6 @@ pub mod uniform_grid; mod utils; pub(crate) mod workspace; -// TODO: Add documentation of feature flags // TODO: Feature flag for multi threading // TODO: Feature flag to disable (debug level) logging? @@ -175,6 +175,10 @@ pub struct Parameters { pub particle_aabb: Option>, /// Whether to allow multi threading within the surface reconstruction procedure pub enable_multi_threading: bool, + /// Whether to enable SIMD vectorization for some computations if supported by the target architecture + /// + /// Currently only supported on x86/x86_64 (AVX2 + FMA) and aarch64 (NEON) for single precision (f32) reconstructions. + pub enable_simd: bool, /// Parameters for the spatial decomposition of the surface reconstruction /// If not provided, no spatial decomposition is performed and a global approach is used instead. pub spatial_decomposition: SpatialDecomposition, @@ -199,6 +203,7 @@ impl Parameters { iso_surface_threshold: R::from_float(0.6), particle_aabb: None, enable_multi_threading: true, + enable_simd: true, spatial_decomposition: Default::default(), global_neighborhood_list: false, } @@ -230,6 +235,7 @@ impl Parameters { iso_surface_threshold: self.iso_surface_threshold.try_convert()?, particle_aabb: map_option!(&self.particle_aabb, aabb => aabb.try_convert()?), enable_multi_threading: self.enable_multi_threading, + enable_simd: self.enable_simd, spatial_decomposition: self.spatial_decomposition.clone(), global_neighborhood_list: self.global_neighborhood_list, }) @@ -336,6 +342,26 @@ pub fn reconstruct_surface_inplace( // Clear the existing mesh output_surface.mesh.clear(); + if parameters.enable_simd { + if let Some(simd) = utils::detect_simd_support() { + let simd_str = match simd { + utils::SimdFeatures::Avx2Fma => "AVX2 and FMA", + utils::SimdFeatures::Neon => "NEON", + }; + info!("Vectorization enabled with support detected for {simd_str} instructions."); + } else { + warn!( + "Vectorization was enabled, but no SIMD support was detected on this CPU. Falling back to non-vectorized code." + ); + } + + if std::any::TypeId::of::() != std::any::TypeId::of::() { + warn!( + "Vectorization is currently only supported for single-precision (f32) reconstructions. Falling back to non-vectorized code." + ); + } + } + // Filter out particles let filtered_particle_positions = if let Some(particle_aabb) = ¶meters.particle_aabb { profile!("filtering particles"); diff --git a/splashsurf_lib/src/mesh.rs b/splashsurf_lib/src/mesh.rs index 69695308..0d30781e 100644 --- a/splashsurf_lib/src/mesh.rs +++ b/splashsurf_lib/src/mesh.rs @@ -15,9 +15,9 @@ //! - [`IntoVtkUnstructuredGridPiece`] to convert basic meshes and meshes with attached attributes to the //! - [`IntoVtkDataSet`] for all meshes implementing [`IntoVtkUnstructuredGridPiece`] to directly save a mesh as a VTK file -use crate::{Aabb3d, MapType, Real, RealConvert, Scalar, new_map, profile}; +use crate::{Aabb3d, MapType, Real, RealConvert, new_map, profile}; use bytemuck_derive::{Pod, Zeroable}; -use nalgebra::{Unit, Vector3}; +use nalgebra::{Scalar, Unit, Vector3}; use rayon::prelude::*; use std::borrow::Cow; use std::cell::RefCell; diff --git a/splashsurf_lib/src/reconstruction.rs b/splashsurf_lib/src/reconstruction.rs index eaceab4f..1ac7dbd9 100644 --- a/splashsurf_lib/src/reconstruction.rs +++ b/splashsurf_lib/src/reconstruction.rs @@ -41,6 +41,7 @@ pub(crate) fn reconstruct_surface_subdomain_grid( particle_positions, &particle_densities, &subdomains, + parameters.enable_simd, ); let global_mesh = stitching(surface_patches); diff --git a/splashsurf_lib/src/traits.rs b/splashsurf_lib/src/traits.rs index 28a08096..a55b61bd 100644 --- a/splashsurf_lib/src/traits.rs +++ b/splashsurf_lib/src/traits.rs @@ -5,6 +5,7 @@ use num_traits::{ Bounded, CheckedAdd, CheckedMul, CheckedSub, FromPrimitive, NumCast, SaturatingSub, Signed, ToPrimitive, }; +//use serde::{Serialize, de::DeserializeOwned}; use simba::scalar::SupersetOf; use std::fmt::{Debug, Display}; use std::hash::Hash; @@ -62,6 +63,8 @@ pub trait Index: + Display + Pod + ThreadSafe +// + Serialize +// + DeserializeOwned + 'static { #[inline] @@ -124,6 +127,8 @@ pub trait Real: + Default + Pod + ThreadSafe +// + Serialize +// + DeserializeOwned { /// Converts the given float value to this Real type #[inline(always)] @@ -172,6 +177,8 @@ impl Index for I where + Display + Pod + ThreadSafe + // + Serialize + // + DeserializeOwned + 'static { } @@ -187,6 +194,8 @@ impl Real for R where + Default + Pod + ThreadSafe + // + Serialize + // + DeserializeOwned + 'static { } diff --git a/splashsurf_lib/src/uniform_grid.rs b/splashsurf_lib/src/uniform_grid.rs index a859cd33..cb285d17 100644 --- a/splashsurf_lib/src/uniform_grid.rs +++ b/splashsurf_lib/src/uniform_grid.rs @@ -7,9 +7,10 @@ use itertools::iproduct; use log::trace; use nalgebra::{Scalar, Vector3}; use num_traits::Bounded; +#[cfg(feature = "serde-serialize")] +use serde_derive::{Deserialize, Serialize}; use std::iter::Iterator; use thiserror::Error as ThisError; - // TODO: Reduce mess with all array and scalar indexing functions /* @@ -126,7 +127,8 @@ pub type UniformGrid = UniformCartesianCubeGrid3d; /// obtained using the [`get_point`](UniformCartesianCubeGrid3d::get_point) and [`get_cell`](UniformCartesianCubeGrid3d::get_cell) /// functions respectively. These functions check if the specified indices are in the valid index range /// of the grid (as computed during construction based on the extents of the grid). -#[derive(Clone, PartialEq, Debug)] +#[derive(Clone, Debug, PartialEq)] +#[cfg_attr(feature = "serde-serialize", derive(Serialize, Deserialize))] pub struct UniformCartesianCubeGrid3d { /// AABB of the grid. Note that the grid may extend beyond the max coordinate of the AABB by less than the `cell_size`. aabb: Aabb3d, diff --git a/splashsurf_lib/src/utils.rs b/splashsurf_lib/src/utils.rs index a39224c8..71d0a36b 100644 --- a/splashsurf_lib/src/utils.rs +++ b/splashsurf_lib/src/utils.rs @@ -177,3 +177,29 @@ impl ChunkSize { self } } + +#[allow(dead_code)] +#[derive(Copy, Clone, Debug, PartialEq, Eq)] +pub(crate) enum SimdFeatures { + Avx2Fma, + Neon, +} + +/// Returns the SIMD +pub(crate) fn detect_simd_support() -> Option { + #[cfg(any(target_arch = "x86_64", target_arch = "x86"))] + { + if is_x86_feature_detected!("avx2") && is_x86_feature_detected!("fma") { + return Some(SimdFeatures::Avx2Fma); + } + } + + #[cfg(target_arch = "aarch64")] + { + if std::arch::is_aarch64_feature_detected!("neon") { + return Some(SimdFeatures::Neon); + } + } + + None +} diff --git a/splashsurf_lib/src/workspace.rs b/splashsurf_lib/src/workspace.rs index dbbe8cb2..8341c8ed 100644 --- a/splashsurf_lib/src/workspace.rs +++ b/splashsurf_lib/src/workspace.rs @@ -1,7 +1,7 @@ //! Workspace for reusing allocated memory between multiple surface reconstructions -use crate::{Real, Scalar}; -use nalgebra::Vector3; +use crate::Real; +use nalgebra::{Scalar, Vector3}; use std::cell::RefCell; use std::fmt; use std::fmt::Debug; diff --git a/splashsurf_lib/tests/integration_tests/test_full.rs b/splashsurf_lib/tests/integration_tests/test_full.rs index bd08f761..751d786d 100644 --- a/splashsurf_lib/tests/integration_tests/test_full.rs +++ b/splashsurf_lib/tests/integration_tests/test_full.rs @@ -35,6 +35,7 @@ fn params_with_aabb( iso_surface_threshold, particle_aabb: domain_aabb, enable_multi_threading: false, + enable_simd: false, spatial_decomposition: SpatialDecomposition::None, global_neighborhood_list: false, }; diff --git a/splashsurf_lib/tests/integration_tests/test_simple.rs b/splashsurf_lib/tests/integration_tests/test_simple.rs index 6b86aa23..b15ca9c3 100644 --- a/splashsurf_lib/tests/integration_tests/test_simple.rs +++ b/splashsurf_lib/tests/integration_tests/test_simple.rs @@ -29,6 +29,7 @@ fn params_with_aabb( iso_surface_threshold, particle_aabb: domain_aabb, enable_multi_threading: false, + enable_simd: false, spatial_decomposition: SpatialDecomposition::None, global_neighborhood_list: false, };