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#include <cusp/hyb_matrix.h>
#include <cusp/gallery/poisson.h>
#include <cusp/krylov/cg_m.h>
// where to perform the computation
typedef cusp::device_memory MemorySpace;
// which floating point type to use
typedef float ValueType;
int main(void)
{
// create an empty sparse matrix structure (HYB format)
cusp::hyb_matrix<int, ValueType, MemorySpace> A;
// create a 2d Poisson problem on a 10x10 mesh
cusp::gallery::poisson5pt(A, 10, 10);
// allocate storage for solution (x) and right hand side (b)
size_t N_s = 4;
cusp::array1d<ValueType, MemorySpace> x(A.num_rows*N_s, ValueType(0)); // TODO replace with array2d when cg_m supports it
cusp::array1d<ValueType, MemorySpace> b(A.num_rows, ValueType(1));
// set sigma values
cusp::array1d<ValueType, MemorySpace> sigma(N_s);
sigma[0] = ValueType(0.1);
sigma[1] = ValueType(0.5);
sigma[2] = ValueType(1.0);
sigma[3] = ValueType(5.0);
// set stopping criteria:
// iteration_limit = 100
// relative_tolerance = 1e-6
cusp::verbose_monitor<ValueType> monitor(b, 100, 1e-6);
// solve the linear systems (A + \sigma_i * I) * x = b for each
// sigma_i with the Conjugate Gradient method
cusp::krylov::cg_m(A, x, b, sigma, monitor);
return 0;
}
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