//! PERF-2 P3 go/no-go (`docs/perf2_campaign.md`): the batched f32 red-black //! V-cycle on the device against the CPU one. Runs only with //! `--features cuda` on a CUDA host, and only when asked (`--ignored`): //! //! `RTX_CUDA_ARCH=sm_120 cargo test --release -p rtx-cfd --features cuda --test gpu_vcycle_bench -- --ignored --nocapture` //! //! Checks first that the K = 1 device V-cycle reproduces the CPU f32 //! red-black V-cycle (same algorithm; FMA contraction and summation order //! differ, so to 1e-4 of the correction's scale), then times one V-cycle //! per march at K = 1, 8, 16 (including the residual upload and the //! correction download) against the CPU's serial f64 red-black V-cycle. #![cfg(feature = "cuda")] use cudarc::driver::{CudaContext, CudaSlice, LaunchConfig, PushKernelArg}; use cudarc::nvrtc::{CompileOptions, compile_ptx_with_opts}; use rtx_cfd::solvers::incompressible::{ LevelExport, MgSmoother, MultigridParameters, PoissonProblem, export_hierarchy, vcycle_f32_reference, }; use std::sync::Arc; use std::time::Instant; const KERNELS: &str = include_str!("../src/kernels/cuda/mg_vcycle.cu"); /// The anchor-sized masked operator (ny 62 over the 2.5 × 0.41 channel with /// a cylinder-sized hole), the same construction as the Poisson pins. fn problem(nx: usize, ny: usize, seed: u64) -> PoissonProblem { let mut p = PoissonProblem::new(nx, ny); let (dx, dy, dt) = (2.5 / nx as f64, 0.41 / ny as f64, 3.24e-4); let (ae, an) = (dt * dy / dx, dt * dx / dy); let hole = |i: usize, j: usize| { let (x, y) = ((i as f64 + 0.5) * dx, (j as f64 + 0.5) * dy); (x - 0.2).powi(2) + (y - 0.2).powi(2) < 0.08 * 0.08 }; for j in 0..ny { for i in 0..nx { let idx = j * nx + i; if hole(i, j) { p.active[idx] = false; continue; } if i + 1 < nx && !hole(i + 1, j) { p.ae[idx] = ae; } if i > 0 && !hole(i - 1, j) { p.aw[idx] = ae; } if j + 1 < ny && !hole(i, j + 1) { p.an[idx] = an; } if j > 0 && !hole(i, j - 1) { p.as_[idx] = an; } if i + 1 == nx { p.extra_diag[idx] = 2.0 * ae; } } } let mut state = seed | 1; for idx in 0..nx * ny { state ^= state << 13; state ^= state >> 7; state ^= state << 17; p.rhs[idx] = if p.active[idx] { 1e-3 * ((state >> 11) as f64 / (1u64 << 53) as f64 - 0.5) } else { 0.0 }; } p } struct DeviceLevel { n: usize, nx: i32, cells: CudaSlice, red: CudaSlice, black: CudaSlice, coarse_of: CudaSlice, children_ptr: CudaSlice, children_idx: CudaSlice, n_cells: usize, n_red: usize, n_black: usize, ae: CudaSlice, aw: CudaSlice, an: CudaSlice, as_: CudaSlice, ap: CudaSlice, b: CudaSlice, x: CudaSlice, r: CudaSlice, } fn cfg(n_items: usize, k: usize) -> LaunchConfig { LaunchConfig { grid_dim: ((n_items as u32).div_ceil(256).max(1), k as u32, 1), block_dim: (256, 1, 1), shared_mem_bytes: 0, } } #[test] #[ignore] fn batched_device_vcycle_go_no_go() { let (nx, ny) = (372usize, 62usize); let prob = problem(nx, ny, 3); let params = MultigridParameters { smoother: MgSmoother::RedBlack, ..MultigridParameters::default() }; let levels: Vec = export_hierarchy(&prob, ¶ms); let depth = levels.len(); println!( " hierarchy: {depth} levels, cells per level {:?}", levels.iter().map(|l| l.cells.len()).collect::>() ); // Device. let ctx = CudaContext::new(0).expect("CUDA context"); let stream = ctx.default_stream(); let arch = std::env::var("RTX_CUDA_ARCH").unwrap_or_else(|_| "sm_120".to_string()); let ptx = compile_ptx_with_opts( KERNELS, CompileOptions { arch: Some(Box::leak(arch.clone().into_boxed_str())), ..Default::default() }, ) .expect("nvrtc"); let module = ctx.load_module(ptx).expect("module"); let f_half = module.load_function("mg_rb_half").unwrap(); let f_res = module.load_function("mg_residual").unwrap(); let f_restrict = module.load_function("mg_restrict").unwrap(); let f_prolong = module.load_function("mg_prolong").unwrap(); let f_zero = module.load_function("mg_zero").unwrap(); let f_coarsest = module.load_function("mg_coarsest").unwrap(); // The CPU reference V-cycle on the fine right-hand side. let n0 = nx * ny; let r_host: Vec = prob.rhs.clone(); let mut z_ref = vec![0.0; n0]; vcycle_f32_reference(&prob, ¶ms, &r_host, &mut z_ref); let z_scale = z_ref.iter().fold(0.0_f64, |m, v| m.max(v.abs())); // The CPU f64 serial red-black V-cycle's wall time (the comparison point). let t0 = Instant::now(); let reps = 20; for _ in 0..reps { let mut z = vec![0.0; n0]; vcycle_f32_reference(&prob, ¶ms, &r_host, &mut z); } let cpu_ms = t0.elapsed().as_secs_f64() * 1e3 / reps as f64; println!(" CPU f32 red-black V-cycle (incl. hierarchy build): {cpu_ms:.3} ms"); let sweeps = 2usize; for &k in &[1usize, 8, 16] { // Upload: coefficients replicated K times, index lists shared. let mut dev: Vec = Vec::with_capacity(depth); for l in &levels { let n = l.nx * l.ny; let rep = |v: &[f32]| -> Vec { let mut out = Vec::with_capacity(v.len() * k); for _ in 0..k { out.extend_from_slice(v); } out }; let up_u = |v: &[u32]| stream.memcpy_stod(v).unwrap(); let up_f = |v: &[f32]| stream.memcpy_stod(v).unwrap(); dev.push(DeviceLevel { n, nx: l.nx as i32, cells: up_u(&l.cells), red: up_u(&l.red), black: up_u(&l.black), coarse_of: up_u(if l.coarse_of.is_empty() { &[0u32][..] } else { &l.coarse_of }), children_ptr: up_u(if l.children_ptr.is_empty() { &[0u32][..] } else { &l.children_ptr }), children_idx: up_u(if l.children_idx.is_empty() { &[0u32][..] } else { &l.children_idx }), n_cells: l.cells.len(), n_red: l.red.len(), n_black: l.black.len(), ae: up_f(&rep(&l.ae)), aw: up_f(&rep(&l.aw)), an: up_f(&rep(&l.an)), as_: up_f(&rep(&l.as_)), ap: up_f(&rep(&l.ap)), b: stream.alloc_zeros::(n * k).unwrap(), x: stream.alloc_zeros::(n * k).unwrap(), r: stream.alloc_zeros::(n * k).unwrap(), }); } stream.synchronize().unwrap(); let r_f32: Vec = { let one: Vec = r_host.iter().map(|&v| v as f32).collect(); let mut out = Vec::with_capacity(n0 * k); for _ in 0..k { out.extend_from_slice(&one); } out }; let mut z_out = vec![0.0f32; n0 * k]; let vcycle = |dev: &mut Vec, r_f32: &[f32], z_out: &mut [f32]| { // Upload the residual into level 0's b. stream.memcpy_htod(r_f32, &mut dev[0].b).unwrap(); let half = |lv: &mut DeviceLevel, colour: u8| { let (list, n_list) = if colour == 0 { (&lv.red, lv.n_red) } else { (&lv.black, lv.n_black) }; let n_i = lv.n as i32; let n_list_i = n_list as i32; unsafe { stream .launch_builder(&f_half) .arg(&n_list_i) .arg(list) .arg(&n_i) .arg(&lv.ae) .arg(&lv.aw) .arg(&lv.an) .arg(&lv.as_) .arg(&lv.ap) .arg(&lv.b) .arg(&mut lv.x) .arg(&lv.nx) .launch(cfg(n_list, k)) .unwrap(); } }; let smooth = |lv: &mut DeviceLevel| { for _ in 0..sweeps { half(lv, 0); half(lv, 1); half(lv, 1); half(lv, 0); } }; // Down. for l in 0..depth - 1 { { let lv = &mut dev[l]; let (n_i, n_cells_i) = (lv.n as i32, lv.n_cells as i32); unsafe { stream .launch_builder(&f_zero) .arg(&n_cells_i) .arg(&lv.cells) .arg(&n_i) .arg(&mut lv.x) .launch(cfg(lv.n_cells, k)) .unwrap(); } smooth(lv); unsafe { stream .launch_builder(&f_res) .arg(&n_cells_i) .arg(&lv.cells) .arg(&n_i) .arg(&lv.ae) .arg(&lv.aw) .arg(&lv.an) .arg(&lv.as_) .arg(&lv.ap) .arg(&lv.b) .arg(&lv.x) .arg(&mut lv.r) .arg(&lv.nx) .launch(cfg(lv.n_cells, k)) .unwrap(); } } let (fine, coarse) = dev.split_at_mut(l + 1); let (lf, lc) = (&fine[l], &mut coarse[0]); let (n_c_cells_i, n_f_i, n_c_i) = (lc.n_cells as i32, lf.n as i32, lc.n as i32); unsafe { stream .launch_builder(&f_restrict) .arg(&n_c_cells_i) .arg(&lc.cells) .arg(&lf.children_ptr) .arg(&lf.children_idx) .arg(&n_f_i) .arg(&n_c_i) .arg(&lf.r) .arg(&mut lc.b) .launch(cfg(lc.n_cells, k)) .unwrap(); } } // Coarsest. { let lv = &mut dev[depth - 1]; let (k_i, n_cells_i, n_i, sw_i) = (k as i32, lv.n_cells as i32, lv.n as i32, 50i32); unsafe { stream .launch_builder(&f_coarsest) .arg(&k_i) .arg(&n_cells_i) .arg(&lv.cells) .arg(&n_i) .arg(&lv.ae) .arg(&lv.aw) .arg(&lv.an) .arg(&lv.as_) .arg(&lv.ap) .arg(&lv.b) .arg(&mut lv.x) .arg(&lv.nx) .arg(&sw_i) .launch(LaunchConfig { grid_dim: ((k as u32).div_ceil(32), 1, 1), block_dim: (32, 1, 1), shared_mem_bytes: 0, }) .unwrap(); } } // Up. for l in (0..depth - 1).rev() { let (fine, coarse) = dev.split_at_mut(l + 1); let (lf, lc) = (&mut fine[l], &coarse[0]); let (n_cells_i, n_f_i, n_c_i) = (lf.n_cells as i32, lf.n as i32, lc.n as i32); unsafe { stream .launch_builder(&f_prolong) .arg(&n_cells_i) .arg(&lf.cells) .arg(&lf.coarse_of) .arg(&n_f_i) .arg(&n_c_i) .arg(&mut lf.x) .arg(&lc.x) .launch(cfg(lf.n_cells, k)) .unwrap(); } smooth(lf); } stream.memcpy_dtoh(&dev[0].x, z_out).unwrap(); stream.synchronize().unwrap(); }; // Correctness at K = 1 (and every batch member at K > 1). vcycle(&mut dev, &r_f32, &mut z_out); let mut worst = 0.0_f64; for m in 0..k { for idx in 0..n0 { let d = (z_out[m * n0 + idx] as f64 - z_ref[idx]).abs(); worst = worst.max(d); } } println!(" K = {k}: device V-cycle vs CPU f32 reference: max |Δz| {worst:.3e} on a scale of {z_scale:.3e}"); assert!(worst < 1e-4 * z_scale, "device V-cycle disagrees with the CPU one"); // Timing: 50 V-cycles, per march. let reps = 50; vcycle(&mut dev, &r_f32, &mut z_out); let t0 = Instant::now(); for _ in 0..reps { vcycle(&mut dev, &r_f32, &mut z_out); } let ms = t0.elapsed().as_secs_f64() * 1e3 / reps as f64; println!( " K = {k}: {ms:.3} ms per batched V-cycle = {:.3} ms per march (CPU serial {cpu_ms:.3} ms; ratio {:.2}×)", ms / k as f64, cpu_ms / (ms / k as f64) ); } }