File: smoothed_aggregation.cu

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#include <cusp/precond/aggregation/smoothed_aggregation.h>
#include <cusp/krylov/cg.h>
#include <cusp/gallery/poisson.h>
#include <cusp/csr_matrix.h>

#include <iostream>

template <typename Monitor>
void report_status(Monitor& monitor)
{
    if (monitor.converged())
    {
        std::cout << "  Solver converged to " << monitor.tolerance() << " tolerance";
        std::cout << " after " << monitor.iteration_count() << " iterations";
        std::cout << " (" << monitor.residual_norm() << " final residual)" << std::endl;
    }
    else
    {
        std::cout << "  Solver reached iteration limit " << monitor.iteration_limit() << " before converging";
        std::cout << " to " << monitor.tolerance() << " tolerance ";
        std::cout << " (" << monitor.residual_norm() << " final residual)" << std::endl;
    }
}

int main(void)
{
    typedef int                 IndexType;
    typedef float               ValueType;
    typedef cusp::device_memory MemorySpace;

    // create an empty sparse matrix structure
    cusp::coo_matrix<IndexType, ValueType, MemorySpace> A;

    // create 2D Poisson problem
    cusp::gallery::poisson5pt(A, 256, 256);

    // solve without preconditioning
    {
        std::cout << "\nSolving with no preconditioner..." << std::endl;
    
        // allocate storage for solution (x) and right hand side (b)
        cusp::array1d<ValueType, MemorySpace> x(A.num_rows, 0);
        cusp::array1d<ValueType, MemorySpace> b(A.num_rows, 1);

        // set stopping criteria (iteration_limit = 1000, relative_tolerance = 1e-6)
        cusp::default_monitor<ValueType> monitor(b, 1000, 1e-6);
        
        // solve
        cusp::krylov::cg(A, x, b, monitor);

        // report status
        report_status(monitor);
    }

    // solve with smoothed aggregation algebraic multigrid preconditioner
    {
        std::cout << "\nSolving with smoothed aggregation preconditioner..." << std::endl;
        
        // allocate storage for solution (x) and right hand side (b)
        cusp::array1d<ValueType, MemorySpace> x(A.num_rows, 0);
        cusp::array1d<ValueType, MemorySpace> b(A.num_rows, 1);

        // set stopping criteria (iteration_limit = 1000, relative_tolerance = 1e-6)
        cusp::default_monitor<ValueType> monitor(b, 1000, 1e-6);

        // setup preconditioner
        cusp::precond::aggregation::smoothed_aggregation<IndexType, ValueType, MemorySpace> M(A);
        
        // solve
        cusp::krylov::cg(A, x, b, monitor, M);
        
        // report status
        report_status(monitor);
        
        // print hierarchy information
        std::cout << "\nPreconditioner statistics" << std::endl;
        M.print();
    }

    return 0;
}