CCCL (CUDA C++ Core Libraries) provides: - CUB: device/block/warp-level GPU primitives (reduce, scan, sort, topk) - Thrust: high-level parallel algorithms (transform_reduce, sort, scan) - libcudacxx: CUDA C++ standard library (atomics, barriers, memory) - cudax: experimental features (memory resources, allocators) - Tuning policies: per-SM hardware-specific algorithm parameters Competition optimization vectors mapped to CCCL: - Output TPS (83% weight): warp_reduce, block_reduce, device_topk - Input TPS (14% weight): device_scan, block_load, prefetch - Cache TPS (3% weight): prefix caching strategy patterns - Memory (0.9 util): pooled/cached/buddy allocators Source: https://github.com/NVIDIA/cccl (shallow clone, HEAD only) License: Apache-2.0
187 lines
6.9 KiB
Plaintext
187 lines
6.9 KiB
Plaintext
//===----------------------------------------------------------------------===//
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//
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// Part of CUDASTF in CUDA C++ Core Libraries,
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// under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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// SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES.
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//
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//===----------------------------------------------------------------------===//
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/**
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* @file
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*
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* @brief FDTD example using the repeat_n helper function
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*
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* This shows how to refactor the original fdtd_while.cu example
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* to use the new repeat_n helper for cleaner loop patterns.
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*/
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#include <cuda/experimental/stf.cuh>
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#include <iostream>
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#include <stdlib.h>
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using namespace cuda::experimental::stf;
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// Define the source function
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_CCCL_DEVICE double Source(double t, double x, double y, double z)
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{
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constexpr double pi = 3.14159265358979323846;
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constexpr double freq = 1e9;
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constexpr double omega = (2 * pi * freq);
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constexpr double wavelength = 3e8 / freq;
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constexpr double k = 2 * pi / wavelength;
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return sin(k * x - omega * t);
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}
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int main([[maybe_unused]] int argc, [[maybe_unused]] char** argv)
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{
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#if _CCCL_CTK_BELOW(12, 4)
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fprintf(stderr, "Waiving test: conditional nodes are only available since CUDA 12.4.\n");
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return 0;
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#else
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stackable_ctx ctx;
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// Initialize the time loop
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size_t timesteps = 10;
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if (argc > 1)
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{
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timesteps = (size_t) atol(argv[1]);
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}
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// Domain dimensions (smaller for this example)
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const size_t SIZE_X = 50;
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const size_t SIZE_Y = 50;
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const size_t SIZE_Z = 50;
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// Grid spacing
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const double DX = 0.01;
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const double DY = 0.01;
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const double DZ = 0.01;
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// Define the electric and magnetic fields
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auto data_shape = shape_of<slice<double, 3>>(SIZE_X, SIZE_Y, SIZE_Z);
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auto lEx = ctx.logical_data(data_shape);
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auto lEy = ctx.logical_data(data_shape);
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auto lEz = ctx.logical_data(data_shape);
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auto lHx = ctx.logical_data(data_shape);
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auto lHy = ctx.logical_data(data_shape);
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auto lHz = ctx.logical_data(data_shape);
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// Define the permittivity and permeability of the medium
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auto lepsilon = ctx.logical_data(data_shape);
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auto lmu = ctx.logical_data(data_shape);
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const double EPSILON = 8.85e-12; // Permittivity of free space
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const double MU = 1.256e-6; // Permeability of free space
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// CFL condition DT <= min(DX, DY, DZ) * sqrt(epsilon_max * mu_max)
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double DT = 0.25 * min(min(DX, DY), DZ) * sqrt(EPSILON * MU);
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// Initialize E fields
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ctx.parallel_for(data_shape, lEx.write(), lEy.write(), lEz.write())
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->*[] _CCCL_DEVICE(size_t i, size_t j, size_t k, auto Ex, auto Ey, auto Ez) {
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Ex(i, j, k) = 0.0;
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Ey(i, j, k) = 0.0;
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Ez(i, j, k) = 0.0;
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};
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// Initialize H fields
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ctx.parallel_for(data_shape, lHx.write(), lHy.write(), lHz.write())
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->*[] _CCCL_DEVICE(size_t i, size_t j, size_t k, auto Hx, auto Hy, auto Hz) {
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Hx(i, j, k) = 0.0;
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Hy(i, j, k) = 0.0;
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Hz(i, j, k) = 0.0;
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};
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// Initialize permittivity and permeability fields
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ctx.parallel_for(data_shape, lepsilon.write(), lmu.write())
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->*[=] _CCCL_DEVICE(size_t i, size_t j, size_t k, auto epsilon, auto mu) {
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epsilon(i, j, k) = EPSILON;
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mu(i, j, k) = MU;
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};
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// Set the source location
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const size_t center_x = SIZE_X / 2;
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const size_t center_y = SIZE_Y / 2;
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const size_t center_z = SIZE_Z / 2;
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// Index shapes for Electric fields, Magnetic fields, and the source
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box Es({1ul, SIZE_X - 1}, {1ul, SIZE_Y - 1}, {1ul, SIZE_Z - 1});
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box Hs({0ul, SIZE_X - 1}, {0ul, SIZE_Y - 1}, {0ul, SIZE_Z - 1});
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box source_s({center_x, center_x + 1}, {center_y, center_y + 1}, {center_z, center_z + 1});
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std::cout << "Running FDTD simulation for " << timesteps << " timesteps" << '\n';
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std::cout << "Grid size: " << SIZE_X << "x" << SIZE_Y << "x" << SIZE_Z << '\n';
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{
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auto repeat_guard = ctx.repeat_graph_scope(timesteps);
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// Update Ex
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ctx.parallel_for(Es, lEx.rw(), lHy.read(), lHz.read(), lepsilon.read())
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->*[=]
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_CCCL_DEVICE(size_t i, size_t j, size_t k, auto Ex, auto Hy, auto Hz, auto epsilon) {
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Ex(i, j, k) = Ex(i, j, k)
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+ (DT / (epsilon(i, j, k) * DX)) * (Hz(i, j, k) - Hz(i, j - 1, k) - Hy(i, j, k) + Hy(i, j, k - 1));
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};
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// Update Ey
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ctx.parallel_for(Es, lEy.rw(), lHx.read(), lHz.read(), lepsilon.read())
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->*[=]
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_CCCL_DEVICE(size_t i, size_t j, size_t k, auto Ey, auto Hx, auto Hz, auto epsilon) {
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Ey(i, j, k) = Ey(i, j, k)
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+ (DT / (epsilon(i, j, k) * DY)) * (Hx(i, j, k) - Hx(i, j, k - 1) - Hz(i, j, k) + Hz(i - 1, j, k));
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};
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// Update Ez
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ctx.parallel_for(Es, lEz.rw(), lHx.read(), lHy.read(), lepsilon.read())
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->*[=]
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_CCCL_DEVICE(size_t i, size_t j, size_t k, auto Ez, auto Hx, auto Hy, auto epsilon) {
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Ez(i, j, k) = Ez(i, j, k)
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+ (DT / (epsilon(i, j, k) * DZ)) * (Hy(i, j, k) - Hy(i - 1, j, k) - Hx(i, j, k) + Hx(i, j - 1, k));
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};
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// Add the source function at the center of the grid
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// Note: We could add a current iteration tracker if needed for time-dependent sources
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ctx.parallel_for(source_s, lEz.rw())->*[=] _CCCL_DEVICE(size_t i, size_t j, size_t k, auto Ez) {
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// For simplicity, using a constant source in this example
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// In the full version, you'd want to track the current timestep
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Ez(i, j, k) = Ez(i, j, k) + 0.1 * sin(0.1 * (i + j + k));
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};
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// Update Hx
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ctx.parallel_for(Hs, lHx.rw(), lEy.read(), lEz.read(), lmu.read())
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->*[=] _CCCL_DEVICE(size_t i, size_t j, size_t k, auto Hx, auto Ey, auto Ez, auto mu) {
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Hx(i, j, k) = Hx(i, j, k)
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- (DT / (mu(i, j, k) * DY)) * (Ez(i, j + 1, k) - Ez(i, j, k) - Ey(i, j, k + 1) + Ey(i, j, k));
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};
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// Update Hy
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ctx.parallel_for(Hs, lHy.rw(), lEx.read(), lEz.read(), lmu.read())
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->*[=] _CCCL_DEVICE(size_t i, size_t j, size_t k, auto Hy, auto Ex, auto Ez, auto mu) {
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Hy(i, j, k) = Hy(i, j, k)
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- (DT / (mu(i, j, k) * DZ)) * (Ex(i, j, k + 1) - Ex(i, j, k) - Ez(i + 1, j, k) + Ez(i, j, k));
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};
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// Update Hz
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ctx.parallel_for(Hs, lHz.rw(), lEx.read(), lEy.read(), lmu.read())
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->*[=] _CCCL_DEVICE(size_t i, size_t j, size_t k, auto Hz, auto Ex, auto Ey, auto mu) {
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Hz(i, j, k) = Hz(i, j, k)
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- (DT / (mu(i, j, k) * DX)) * (Ey(i + 1, j, k) - Ey(i, j, k) - Ex(i, j + 1, k) + Ex(i, j, k));
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};
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} // repeat_guard
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// Print final result at center
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ctx.host_launch(lEz.read())->*[=](auto Ez) {
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std::cout << "Final Ez at center: " << Ez(center_x, center_y, center_z) << '\n';
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};
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ctx.finalize();
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std::cout << "FDTD simulation completed!" << '\n';
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return 0;
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#endif
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}
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