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smoothed_aggregation.cu
#include <cusp/krylov/cg.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
// create 2D Poisson problem
cusp::monitor<ValueType> monitor(b, 1000, 1e-6);
// solve without preconditioning
{
std::cout << "\nSolving with no preconditioner..." << std::endl;
// allocate storage for solution (x)
// solve
cusp::krylov::cg(A, x, b, monitor);
// report status
monitor.print();
}
// solve with smoothed aggregation algebraic multigrid preconditioner
{
std::cout << "\nSolving with smoothed aggregation preconditioner..." << std::endl;
// allocate storage for solution (x)
// reset the monitor
monitor.reset(b);
// setup preconditioner
// solve
cusp::krylov::cg(A, x, b, monitor, M);
// report status
monitor.print();
// print hierarchy information
std::cout << "\nPreconditioner statistics" << std::endl;
M.print();
}
return 0;
}