Windows下可用！开源高性能稀疏矩阵迭代法C++求解库amgcl

#include <vector>#include <iostream>

#include <amgcl/backend/builtin.hpp>#include <amgcl/adapter/crs_tuple.hpp>#include <amgcl/make_solver.hpp>#include <amgcl/amg.hpp>#include <amgcl/coarsening/smoothed_aggregation.hpp>#include <amgcl/relaxation/spai0.hpp>#include <amgcl/solver/bicgstab.hpp>

#include <amgcl/io/mm.hpp>#include <amgcl/profiler.hpp>

int main(int argc, char *argv[]) {// The matrix and the RHS file names should be in the command line options:if (argc < 3) {std::cerr << "Usage: " << argv[0] << " <matrix.mtx> <rhs.mtx>" << std::endl;return 1;}

// The profiler:amgcl::profiler<> prof("poisson3Db");

// Read the system matrix and the RHS:ptrdiff_t rows, cols;std::vector<ptrdiff_t> ptr, col;std::vector<double> val, rhs;

prof.tic("read");std::tie(rows, cols) = amgcl::io::mm_reader(argv[1])(ptr, col, val);std::cout << "Matrix " << argv[1] << ": " << rows << "x" << cols << std::endl;

std::tie(rows, cols) = amgcl::io::mm_reader(argv[2])(rhs);std::cout << "RHS " << argv[2] << ": " << rows << "x" << cols << std::endl;prof.toc("read");

// We use the tuple of CRS arrays to represent the system matrix.// Note that std::tie creates a tuple of references, so no data is actually// copied here:auto A = std::tie(rows, ptr, col, val);

// Compose the solver type//   the solver backend:typedef amgcl::backend::builtin<double> SBackend;//   the preconditioner backend:#ifdef MIXED_PRECISIONtypedef amgcl::backend::builtin<float> PBackend;#elsetypedef amgcl::backend::builtin<double> PBackend;#endif

typedef amgcl::make_solver<amgcl::amg<PBackend,amgcl::coarsening::smoothed_aggregation,amgcl::relaxation::spai0>,amgcl::solver::bicgstab<SBackend>> Solver;

// Initialize the solver with the system matrix:prof.tic("setup");Solver solve(A);prof.toc("setup");

// Show the mini-report on the constructed solver:std::cout << solve << std::endl;

// Solve the system with the zero initial approximation:int iters;double error;std::vector<double> x(rows, 0.0);

prof.tic("solve");std::tie(iters, error) = solve(A, rhs, x);prof.toc("solve");

// Output the number of iterations, the relative error,// and the profiling data:std::cout << "Iters: " << iters << std::endl<< "Error: " << error << std::endl<< prof << std::endl;}

typedef amgcl::backend::builtin<double> SBackend;//   the preconditioner backend:#ifdef MIXED_PRECISIONtypedef amgcl::backend::builtin<float> PBackend;#elsetypedef amgcl::backend::builtin<double> PBackend;#endif

typedef amgcl::make_solver<amgcl::amg<PBackend,amgcl::coarsening::smoothed_aggregation,amgcl::relaxation::spai0>,amgcl::solver::bicgstab<SBackend>> Solver;

// Initialize the solver with the system matrix:prof.tic("setup");Solver solve(A);prof.toc("setup");