pMultiGrid_example.cpp

After reading the command line arguments, we define the problem specification (domain, right-hand side, function for boundary conditions, functions for CDR equation) for the chosen benchmark problem (option –Benchmark).

    gsFunctionExpr<> sol_exact, rhs_exact, coeff_diff, coeff_conv, coeff_reac;
    gsMultiPatch<> mp;
    gsInfo << "|| Benchmark information ||\n";
    switch (numBenchmark)
    {
        case 1:
            gsInfo << "1) CDR-equation the unit square\n";
            mp = gsMultiPatch<>(*gsNurbsCreator<>::BSplineSquare(1.0, 0.0, 0.0));
            sol_exact = gsFunctionExpr<>("sin(pi*x)*sin(pi*y)",2);
            rhs_exact = gsFunctionExpr<>("1.2*pi*pi*sin(pi*x)*sin(pi*y)+0.9*pi*pi*sin(pi*x)*sin(pi*y)+0.7*pi*pi*cos(pi*x)*cos(pi*y)"
                            " + 0.4*pi*pi*cos(pi*x)*cos(pi*y) +0.4*pi*cos(pi*x)*sin(pi*y)-0.2*pi*sin(pi*x)*cos(pi*y)+0.3*sin(pi*x)*sin(pi*y)", 2);
            coeff_diff = gsFunctionExpr<>("1.2","-0.7","-0.4","0.9",2);
            coeff_conv = gsFunctionExpr<>("0.4","-0.2",2);
            coeff_reac = gsFunctionExpr<>("0.3",2);
            break;

        case 2:
            gsInfo << "2) Poisson equation on the quarter annulus\n";
            mp = gsMultiPatch<>(*gsNurbsCreator<>::BSplineFatQuarterAnnulus(1.0, 2.0));
            sol_exact = gsFunctionExpr<>( "-(x*x+y*y-1)*(x*x+y*y-4)*x*y*y", 2);
            rhs_exact = gsFunctionExpr<>( "2*x*(22*x*x*y*y+21*y*y*y*y-45*y*y+x*x*x*x-5*x*x+4)", 2);
            coeff_diff = gsFunctionExpr<>("1","0","0","1",2);
            coeff_conv = gsFunctionExpr<>("0","0",2);
            coeff_reac = gsFunctionExpr<>("0",2);
            break;

        case 3:
            gsInfo << "3) Poisson equation on the quarter annulus\n";
            mp = gsMultiPatch<>(*gsNurbsCreator<>::BSplineFatQuarterAnnulus(1.0, 2.0));
            sol_exact = gsFunctionExpr<>( "(x^2+y^2-3*sqrt(x^2+y^2)+2)*sin(2*atan(y/x))", 2);
            rhs_exact = gsFunctionExpr<>( "(8-9*sqrt(x^2 + y^2))*sin(2*atan(y/x))/(x^2+y^2)", 2);
            coeff_diff = gsFunctionExpr<>("1","0","0","1",2);
            coeff_conv = gsFunctionExpr<>("0","0",2);
            coeff_reac = gsFunctionExpr<>("0",2);
            break;

        case 4:
            gsInfo << "4) Poisson equation on an L-shaped domain\n";
            mp = gsMultiPatch<>(*gsNurbsCreator<>::BSplineLShape_p1());
            sol_exact = gsFunctionExpr<>( "if ( y>0, ( (x^2+y^2)^(1.0/3.0) )*sin( (2*atan2(y,x) - pi)/3.0 ), ( (x^2+y^2)^(1.0/3.0) )*sin( (2*atan2(y,x) +3*pi)/3.0 ) )", 2);
            rhs_exact = gsFunctionExpr<>( "0", 2);
            coeff_diff = gsFunctionExpr<>("1","0","0","1",2);
            coeff_conv = gsFunctionExpr<>("0","0",2);
            coeff_reac = gsFunctionExpr<>("0",2);
            break;

        case 5:
            gsInfo << "5) Poisson equation on the unit cube\n";
            mp = gsMultiPatch<>(*gsNurbsCreator<>::BSplineCube((real_t)1));
            sol_exact = gsFunctionExpr<>( "sin(pi*x)*sin(pi*y)*sin(pi*z)", 3);
            rhs_exact = gsFunctionExpr<>( "(3*pi^2)*sin(pi*x)*sin(pi*y)*sin(pi*z)", 3);
            coeff_diff = gsFunctionExpr<>("1","0","0","0","1","0","0","0","1",3);
            coeff_conv = gsFunctionExpr<>("0","0","0",3);
            coeff_reac = gsFunctionExpr<>("0",3);
            break;

        case 6:
            gsInfo << "6) Poisson's equation on Yeti footprint\n";
            mp = *static_cast<gsMultiPatch<>::uPtr>(gsReadFile<>("domain2d/yeti_mp2.xml"));
            sol_exact = gsFunctionExpr<>( "sin(5*pi*x)*sin(5*pi*y)", 2);
            rhs_exact = gsFunctionExpr<>( "(50*pi^2)*sin(5*pi*x)*sin(5*pi*y)", 2);
            coeff_diff = gsFunctionExpr<>("1","0","0","1",2);
            coeff_conv = gsFunctionExpr<>("0","0",2);
            coeff_reac = gsFunctionExpr<>("0",2);
            break;

        default:
            gsInfo << "Unknown benchmark case chosen.\n";
            return EXIT_FAILURE;
    }

The command line option –PatchSplits \(i\) allows to apply \(i\) uniform splits of each patch into \( 2^d \) sub-patches.

    for (index_t i=0; i<numSplits; ++i)
        mp = mp.uniformSplit();

We define the boundary conditions object with the function containing the corresponding Dirichlet data.

    gsBoundaryConditions<> bcInfo;
    gsFunctionExpr<> zero("0", mp.geoDim());
    for (gsMultiPatch<>::const_biterator bit = mp.bBegin(); bit != mp.bEnd(); ++bit)
        bcInfo.addCondition(*bit, condition_type::dirichlet, &sol_exact);
    bcInfo.setGeoMap(mp);

The setup of the multigrid hierarchy is given by the command line parameters –Levels, –Projection and –Coarsening.

With –Levels, the number of levels \(L\) is specified.

Using –Coarsening, one can specify \(L-1\) values for the coarsening (the leftmost entry corresponds to the coarsest level): h: standard grid coarsening (as by uniform grid refinement; increase grid size by factor 2) p: reduce spline degree and smoothness (keep grid as-is) z: reduce spline degree and smoothness and grid coarsening

The choice –Projection 1 means that p and z refer to a direct coarsening from degree \(p\) to degree 1. The choice –Projection 2 means that p and z refer to a reduction of the spline degree by 1, like from \(p\) to \(p-1\).

If –Projection 1, there can only be one single p or z coarsening.

If –Coarsening is not specified: in case of –Projection 1, the default is h...hz, meaning that we have degree 1 for the levels \(\ell=1,\ldots,L-1\) and the degree specified by –Degree for the finest level \(L\). All levels refer to different grid sizes. in case of –Projection 2, the default is h...hz...z, meaning that we have the degree specified by –Degree for the finest level \(L\). On each next coarser level, the degree is reduced by 1. After reaching degree 1, further coarsening (if still necessary) is only of type h. All levels refer to different grid sizes.

    if (typeCoarsening.empty())
    {
        // Just setup some defaults
        if (typeProjection==1)
        {
            // If we have a transition from degree p to degree 1, we only need
            // a single refinement where the degree is changed. We apply this
            // between the finest and the second finest levels.
            typeCoarsening = std::string(numLevels-2, 'h') + "z";
        }
        else //if (typeProjection==2)
        {
            // If we have a transition where the degree is changed by only one,
            // we need up to p-1 transitions. The remainder needs to by of type h.
            if (numLevels>numDegree)
                typeCoarsening = std::string(numLevels-numDegree, 'h') + std::string(numDegree-1, 'z');
            else
                // It can happen that the coarsest problem does not have degree 1 (if there
                // are not enough levels).
                typeCoarsening = std::string(numLevels-1, 'z');
        }
    }

We now compute the parameters for the coarsest grid such that the finest grid is as prescribed using the parameters –Degree and –Refinement.

    // Index 0 refers to coarsest level; we first setup that basis
    std::vector<gsMultiBasis<>> bases;
    bases.emplace_back(mp);

    // Adjust spline degree for coarsest level
    const index_t degreeOffset = numDegree - (numRefP+numRefZ) * (typeProjection==1?(numDegree-1):1) - bases[0].degree();
    if (degreeOffset>0)
        bases[0].degreeIncrease(degreeOffset);
    else if (degreeOffset<0)
        bases[0].degreeReduce(-degreeOffset);

    // Apply refinement in h for the coarses level
    for (index_t i = 0; i < numRefine - numRefH - numRefZ; ++i)
        bases[0].uniformRefine();

The finer grids are then constructed as indicated using the parameters –Coarsening and –Projection.

    for (index_t i = 1; i < numLevels; i++)
    {
        // New basis object, which is just a copy
        bases.push_back(bases.back());
        if (typeCoarsening[i-1] == 'p')
        {
            if (typeProjection == 1)
                bases.back().degreeIncrease(numDegree-1);
            else
                bases.back().degreeIncrease();
        }
        else if (typeCoarsening[i-1] == 'h')
        {
            bases.back().uniformRefine();
        }
        else //if (typeCoarsening[i-1] == 'z')
        {
            bases.back().uniformRefine();
            if (typeProjection == 1)
                bases.back().degreeIncrease(numDegree-1);
            else
                bases.back().degreeIncrease();
        }
    }

The next step is the setup of the refinement and prolongation operators. In case of h-coarsening, the prolongation is the canonical embedding matrix and the restriction is its transpose.

In case of p- and z-coarsening, the method depends on the lumping type specified by –Lumping.

In case of lumping type 1, the restriction and the prolongation are the corresponding \(L_2\)-orthogonal projectors, given by

\[ M_{\ell-1}^{-1} M_{\ell-1,\ell} \quad\mbox{and}\quad M_{\ell}^{-1} M_{\ell,\ell-1} \]

respectively. Here, \( M_{\ell} \) and \( M_{\ell-1} \) are the mass matrices on those grid levels (assembleMass). \( M_{\ell-1,\ell} = M_{\ell,\ell-1}^\top \) is obtained by deriving a mass matrix with the basis functions for the level \(\ell-1\) as trial functions and the basis functions for the level \(\ell\) as test functions (assembleMixedMass). The realization of the inverses is done by applying a conjugate gradient solver.

In case of lumping type 2, the matrices \( M_{\ell} \) and \( M_{\ell-1} \) are replaced by diagonal matrices, where the diagonal entries coincide with the row-sum of the \( M_{\ell} \) or \( M_{\ell-1} \), respectively. Using the partition-of-unity property, these diagonal entries are obtained by evaluating \( (\cdot,1)_{L_2(\Omega)} \) for the basis functions (assembleLumpedMass).

    gsInfo << "|| Multigrid hierarchy ||\n";
    for (index_t i=1; i<numLevels; i++)
    {
        if (typeCoarsening[i-1] != 'h')
        {
            if (typeLumping == 1)
            {
                gsInfo << "Restriction and prolongation between levels " << i << " and " << i-1 << ": L2-projection with lumped mass.\n";
                gsSparseMatrix<> mixedMass = assembleMixedMass(mp, bases[i], bases[i-1], bcInfo, opt);
                gsSparseMatrix<real_t> prolongationMatrix
                      = assembleLumpedMass(mp, bases[i], bcInfo, opt).asDiagonal().inverse()
                      * mixedMass;
                gsSparseMatrix<real_t> restrictionMatrix
                      = assembleLumpedMass(mp, bases[i-1], bcInfo, opt).asDiagonal().inverse()
                      * mixedMass.transpose();
                prolongation[i-1] = makeMatrixOp(prolongationMatrix.moveToPtr());
                restriction[i-1] = makeMatrixOp(restrictionMatrix.moveToPtr());
            }
            else
            {
                gsInfo << "Restriction and prolongation between levels " << i << " and " << i-1 << ": exact L2-projection.\n";
                gsSparseMatrix<> prolongationP = assembleMixedMass(mp, bases[i], bases[i-1], bcInfo, opt);
                gsSparseMatrix<> restrictionP = prolongationP.transpose();
                gsSparseMatrix<> prolongationM = assembleMass(mp, bases[i], bcInfo, opt);
                gsSparseMatrix<> restrictionM = assembleMass(mp, bases[i-1], bcInfo, opt);

                prolongation[i-1] = makeLinearOp(
                    [prolongationP=give(prolongationP),prolongationM=give(prolongationM)]
                    (const gsMatrix<>& Xcoarse, gsMatrix<>& Xfine)
                    {
                        gsConjugateGradient<> CGSolver(prolongationM);
                        CGSolver.setTolerance(1e-12);
                        CGSolver.solve(prolongationP*Xcoarse,Xfine);
                    },
                    prolongationP.rows(), prolongationP.cols()
                );
                restriction[i-1] = makeLinearOp(
                    [restrictionP=give(restrictionP),restrictionM=give(restrictionM)]
                    (const gsMatrix<>& Xfine, gsMatrix<>& Xcoarse)
                    {
                        gsConjugateGradient<> CGSolver(restrictionM);
                        CGSolver.setTolerance(1e-12);
                        CGSolver.solve(restrictionP*Xfine,Xcoarse);
                    },
                    restrictionP.rows(), restrictionP.cols()
                );

            }
        }
        else //if (typeCoarsening[i-1] == 'h')
        {
            gsInfo << "Restriction and prolongation between levels " << i << " and " << i-1 << ": canonical embedding and its transpose.\n";
            bases[i].clone()->uniformCoarsen_withTransfer(prolongation_H[i-1],bcInfo,opt);
            prolongation[i-1] = makeMatrixOp(prolongation_H[i-1]);
            restriction[i-1] = makeMatrixOp(prolongation_H[i-1].transpose());

        }
    }

For a p-multigrid method, one has to assemble the problem for the individual levels. The assembler is used to derive the stiffness matrix for the finest level, the spline degree on the corresponding level is different to the level on the next finer level, or rediscretization is explicitly requested (using –CoarseOperator 1). Otherwise, Galerkin projections are used.

    for (index_t i=numLevels-1; i>=0; --i)
    {
        if (typeCoarseOperator == 1 || i == numLevels-1 || typeCoarsening[i] != 'h')
        {
            gsInfo << "Assemble on level " << i << ": ";
            clock.restart();
            gsCDRAssembler<real_t> assembler(
                mp,
                bases[i],
                bcInfo,
                rhs_exact,
                coeff_diff, coeff_conv, coeff_reac,
                (dirichlet::strategy)opt.getInt("DirichletStrategy"),
                iFace::glue
            );
            assembler.assemble();
            matrices[i] = assembler.matrix();
            if (i==numLevels-1)
                rhs = assembler.rhs();
            Time_Assembly += clock.stop();
            gsInfo << "Degree: " << bases[i].degree()  << ", Ndof: " << matrices[i].rows() << "\n";
        }
        else
        {
            gsInfo << "Apply Galerkin projection on level " << i << ": ";
            clock.restart();
            matrices[i] = prolongation_H[i].transpose() * matrices[i+1] * prolongation_H[i];
            Time_Galerkin += clock.stop();
            gsInfo << "Ndof: " << matrices[i].rows() << "\n";
        }
        operators[i] = makeMatrixOp(matrices[i]);
    }
    gsSparseMatrix<>& matrix = matrices.back();

Now, we are able to setup the gsMultiGrid object. This class has two kinds of constructors: stiffness matrix on the finest grid and vector of prolongation matrices (all as gsSparseMatrix) vectors of all the stiffness matrices, the restriction operators and the prolongation operators (all as gsLinearOperator::Ptr).

In the first case, the stiffness matrices on the finer grids are derived automatically using a Galerkin projection.

Since we have a vector of stiffness matrices and since our restrictions and prolongations might not be just matrices, we need to use the second option.

    gsMultiGridOp<>::Ptr mg = gsMultiGridOp<>::make(operators, prolongation, restriction);

We setup the coarse solver exactly since the "matrix-free" version of gsMultiGridOp does not setup the coarse solver automatically.

    mg->setCoarseSolver(makeSparseLUSolver(matrices[0]));

Next, we choose the type of the cycle (1=V-cycle, 2=W-cycle). Here, we can use different options, depending if the coarsening is a h-coarsening or a coarsening which involves a change of the degree (p- or z-coarsening).

    if (typeCycle_p == typeCycle_h)
        gsInfo << "Multigrid cycle type: " << typeCycle_h << "\n";
    else
        gsInfo << "Multigrid cycle type: " << typeCycle_h << " for h-refinement and " << typeCycle_p << " for p- and z-refinement\n";
    for (index_t i=1; i<numLevels-1; i++)
    {
        if (typeCoarsening[i] != 'h')
            mg->setNumCycles(i,typeCycle_p);
        else
            mg->setNumCycles(i,typeCycle_h);
    }

The next step is the setup of the smoothers. As smoothers, one can choose an incomplete LU smoother (–Smoother 1), a blockwise incomplete LU smoother (–Smoother 4), the subspace corrected mass smoother (–Smoother 3; see multiGrid_example.cpp) the Gauss-Seidel smoother (–Smoother 2). For the levels with spline degree 1, always the Gauss-Seidel smoother is used. For the setup, we use a for loop over the levels 1,...,numLevels. On level 0, we use a direct solver.

Moreover, we specify the number of pre and post smoothing steps (default: 1), as given via command –Smoothing.

If a conjugate gradient solver (–Solver 3) is used, the post smoothing operator is the transpose of the pre smoothing. Otherwise, we choose the post smoothing to be equal to the pre smoothing. This is obtained with by setting setSymmSmooth to false.

    for (index_t i=1; i<numLevels; i++)
    {
        if (bases[i].degree()==1)
        {
            mg->setSmoother(i,makeGaussSeidelOp(matrices[i]));
            gsInfo << "Smoother for level " << i << ": Gauss-Seidel\n";
        }
        else switch (typeSmoother)
        {
            case 1:
                mg->setSmoother(i,makeIncompleteLUOp(matrices[i]));
                gsInfo << "Smoother for level " << i << ": Incomplete LU\n";
                break;
            case 2:
                mg->setSmoother(i,makeGaussSeidelOp(matrices[i]));
                gsInfo << "Smoother for level " << i << ": Gauss-Seidel\n";
                break;
            case 3:
                mg->setSmoother(i,setupSubspaceCorrectedMassSmoother(matrices[i], bases[i], bcInfo, opt));
                gsInfo << "Smoother for level " << i << ": Subspace corrected mass smoother (damping = "<<dampingSCMS<<")\n";
                break;
            case 4:
                mg->setSmoother(i,setupBlockILUT(matrices[i], bases[i], bcInfo, opt));
                gsInfo << "Smoother for level " << i << ": Blockwise Incomplete LU\n";
                break;
            default:
                gsInfo << "Unknown smoother chosen.\n";
                return EXIT_FAILURE;
        }
    }
    gsInfo << "Number of smoothing steps: " << numSmoothing << "\n";
    mg->setNumPreSmooth(numSmoothing);
    mg->setNumPostSmooth(numSmoothing);
    // For the conjugate Gradient solver, the post smoother needs to be the transpose of the
    // pre smoother. For all other iterative solvers, it does not matter. So, we choose
    // pre smoothing and post smoothing to be the same.
    gsInfo << "Post smoothing is transpose of pre smoothing: " << (typeSolver == 3?"yes":"no") << "\n";
    mg->setSymmSmooth(typeSolver == 3);

Next, we initialize the chosen iterative solver.

    gsIterativeSolver<>::Ptr solver;
    switch (typeSolver)
    {
        case 1:
            gsInfo << "\n|| Solver information ||\np-multigrid is applied as stand-alone solver\n";
            // The preconditioned gradient method is noting but applying p-multigrid as a stand-alone solver.
            // We have to set step size = 1 to deactivate automatic stepsize control.
            solver = gsGradientMethod<>::make(matrix, mg, 1);
            break;
        case 2:
            gsInfo << "\n|| Solver information ||\nBiCGStab is applied as solver, p-multigrid as a preconditioner\n";
            solver = gsBiCgStab<>::make(matrix, mg);
            break;
        case 3:
            gsInfo << "\n|| Solver information ||\nCG is applied as solver, p-multigrid as a preconditioner\n";
            solver = gsConjugateGradient<>::make(matrix, mg);
            break;
        default:
            gsInfo << "Unknown iterative solver chosen.\n";
            return EXIT_FAILURE;
    }

We choose a random initial guess.

    gsMatrix<> x = gsMatrix<>::Random(matrix.rows(),1);

Finally, we use the iterative solver to solve the problem. We use solveDetailed with an errorHistory in order to be able to give the convergence behavior.

    solver->solveDetailed( rhs, x, error_history );

Annotated source file

Here is the full file examples/pMultiGrid_example.cpp. Clicking on a function or class name will lead you to its reference documentation.

#include <gismo.h>
#include <string>

using namespace gismo;

gsPreconditionerOp<>::Ptr setupSubspaceCorrectedMassSmoother(
    const gsSparseMatrix<>&,
    const gsMultiBasis<>&,
    const gsBoundaryConditions<>&,
    const gsOptionList&
);

gsPreconditionerOp<>::Ptr setupBlockILUT(
    const gsSparseMatrix<>&,
    const gsMultiBasis<>&,
    const gsBoundaryConditions<>&,
    const gsOptionList&
);

gsMatrix<> assembleLumpedMass(
    const gsMultiPatch<>& mp,
    const gsMultiBasis<>& basis,
    const gsBoundaryConditions<>& bcInfo,
    const gsOptionList&
);

gsSparseMatrix<> assembleMass(
    const gsMultiPatch<>& mp,
    const gsMultiBasis<>& basis,
    const gsBoundaryConditions<>& bcInfo,
    const gsOptionList&
);

gsSparseMatrix<> assembleMixedMass(
    const gsMultiPatch<>& mp,
    const gsMultiBasis<>& basisU,
    const gsMultiBasis<>& basisV,
    const gsBoundaryConditions<>& bcInfo,
    const gsOptionList&
);

int main(int argc, char* argv[])
{
    index_t numBenchmark = 3;
    index_t numSplits = 0;
    index_t numDegree = 2;
    index_t numRefine = 6;
    index_t typeBCHandling = 2;
    index_t numLevels = 2;
    index_t typeProjection = 2;
    std::string typeCoarsening;
    index_t typeLumping = 1;
    index_t typeCoarseOperator = 2;
    index_t typeCycle_p = 1;
    index_t typeCycle_h = 2;
    index_t typeSmoother = 1;
    index_t numSmoothing = 1;
    real_t dampingSCMS = 1;
    index_t typeSolver = 2;
    real_t tol = 1e-8;
    index_t maxIter = 20;

    // Command line argument parser
    gsCmdLine cmd("This program solves the CDR-equation with a p-multigrid or h-multigrid method");

    // Add command line arguments
    cmd.addInt("b", "Benchmark", "Number of the benchmark problem", numBenchmark);
    cmd.addInt("P", "PatchSplits", "Number of patch splittings: split each patch that many times into 2^d patches", numSplits);
    cmd.addInt("p", "Degree", "Spline degree for finest grid", numDegree);
    cmd.addInt("r", "Refinement", "Number of global refinements to obtain finest grid", numRefine);
    cmd.addInt("d", "BCHandling", "Handle Dirichlet BC's by (1) elimination or (2) Nitsche's method", typeBCHandling);
    cmd.addInt("l", "Levels", "Number of levels for multigrid", numLevels);
    cmd.addInt("D", "Projection", "A p or z coarsening refers to (1) changing the degree directly to 1 or (2) reducing the degree by 1", typeProjection);
    cmd.addString("z", "Coarsening", "Coarsening strategy for each of the levels: (h) coarser grid, (p) reduced spline degree or (z) both", typeCoarsening);
    cmd.addInt("L", "Lumping", "Restriction and prolongation performed with the (1) lumped or (2) full mass matrix", typeLumping);
    cmd.addInt("G", "CoarseOperator", "Derive coarse stiffness matrix (1) by rediscretization or (2) using Galerkin projection if possible", typeCoarseOperator);
    cmd.addInt("m", "Cycle_p", "Type of cycle where p or z-coarsening is applied: (1) V-cycle or (2) W-cycle", typeCycle_p);
    cmd.addInt("M", "Cycle_h", "Type of cycle where h-coarsening is applied: (1) V-cycle or (2) W-cycle", typeCycle_h);
    cmd.addInt("S", "Smoother", "Smoother: (1) ILUT, (2) Gauss-Seidel, (3) subspace corrected mass smoother or (4) Block ILUT", typeSmoother);
    cmd.addInt("v", "Smoothing", "Number of pre and post smoothing steps", numSmoothing);
    cmd.addReal("", "DampingSCMS", "Damping for subspace corrected mass smoother (otherwise ignored)", dampingSCMS);
    cmd.addInt("s", "Solver", "Solver: (1) mg as stand-alone solver, (2) BiCGStab prec. with mg or (3) CG prec. with mg", typeSolver);
    cmd.addReal("", "Tolerance", "Threshold for iterative solver", tol);
    cmd.addInt("", "MaxIter", "Maximum number of iterations for iterative solver", maxIter);

    // Read parameters from command line
    try { cmd.getValues(argc,argv);  } catch (int rv) { return rv; }

    gsOptionList opt;

    // Check validity of input
    if (numDegree<=0)
    {
        gsInfo << "--Degree has to be a positive value.\n";
        return EXIT_FAILURE;
    }

    if (numRefine<0)
    {
        gsInfo << "--Refinement has to be a non-negative value.\n";
        return EXIT_FAILURE;
    }

    if (numSmoothing<0)
    {
        gsInfo << "--Smoothing has to be a non-negative value.\n";
        return EXIT_FAILURE;
    }

    if (numLevels<=0)
    {
        gsInfo << "--Levels has to be a positive value.\n";
        return EXIT_FAILURE;
    }

    if (numSplits<0)
    {
        gsInfo << "--PatchSplits has to be a non-negative value.\n";
        return EXIT_FAILURE;
    }

    if (typeCycle_p<=0 || typeCycle_h<=0)
    {
        gsInfo << "--Cycle_p and Cycle_h have to be a positvie value.\n";
        return EXIT_FAILURE;
    }

    switch (typeBCHandling)
    {
        case 1:
            opt.addInt("DirichletStrategy","",dirichlet::elimination); break;
        case 2:
            opt.addInt("DirichletStrategy","",dirichlet::nitsche    ); break;
        default:
            gsInfo << "Unknown boundary condition handling type chosen.\n";
            return EXIT_FAILURE;
    }

    if (typeLumping < 1 || typeLumping > 2)
    {
        gsInfo << "Unknown lumping type chosen.\n";
        return -1;
    }

    if (typeProjection < 1 || typeProjection > 2)
    {
        gsInfo << "Unknown projection type chosen.\n";
        return -1;
    }

    if (typeCoarseOperator < 1 || typeCoarseOperator > 2)
    {
        gsInfo << "Unknown coarse operator chosen.\n";
        return -1;
    }

    // Initialize solution, rhs and geometry
    gsFunctionExpr<> sol_exact, rhs_exact, coeff_diff, coeff_conv, coeff_reac;
    gsMultiPatch<> mp;
    gsInfo << "|| Benchmark information ||\n";
    switch (numBenchmark)
    {
        case 1:
            gsInfo << "1) CDR-equation the unit square\n";
            mp = gsMultiPatch<>(*gsNurbsCreator<>::BSplineSquare(1.0, 0.0, 0.0));
            sol_exact = gsFunctionExpr<>("sin(pi*x)*sin(pi*y)",2);
            rhs_exact = gsFunctionExpr<>("1.2*pi*pi*sin(pi*x)*sin(pi*y)+0.9*pi*pi*sin(pi*x)*sin(pi*y)+0.7*pi*pi*cos(pi*x)*cos(pi*y)"
                            " + 0.4*pi*pi*cos(pi*x)*cos(pi*y) +0.4*pi*cos(pi*x)*sin(pi*y)-0.2*pi*sin(pi*x)*cos(pi*y)+0.3*sin(pi*x)*sin(pi*y)", 2);
            coeff_diff = gsFunctionExpr<>("1.2","-0.7","-0.4","0.9",2);
            coeff_conv = gsFunctionExpr<>("0.4","-0.2",2);
            coeff_reac = gsFunctionExpr<>("0.3",2);
            break;

        case 2:
            gsInfo << "2) Poisson equation on the quarter annulus\n";
            mp = gsMultiPatch<>(*gsNurbsCreator<>::BSplineFatQuarterAnnulus(1.0, 2.0));
            sol_exact = gsFunctionExpr<>( "-(x*x+y*y-1)*(x*x+y*y-4)*x*y*y", 2);
            rhs_exact = gsFunctionExpr<>( "2*x*(22*x*x*y*y+21*y*y*y*y-45*y*y+x*x*x*x-5*x*x+4)", 2);
            coeff_diff = gsFunctionExpr<>("1","0","0","1",2);
            coeff_conv = gsFunctionExpr<>("0","0",2);
            coeff_reac = gsFunctionExpr<>("0",2);
            break;

        case 3:
            gsInfo << "3) Poisson equation on the quarter annulus\n";
            mp = gsMultiPatch<>(*gsNurbsCreator<>::BSplineFatQuarterAnnulus(1.0, 2.0));
            sol_exact = gsFunctionExpr<>( "(x^2+y^2-3*sqrt(x^2+y^2)+2)*sin(2*atan(y/x))", 2);
            rhs_exact = gsFunctionExpr<>( "(8-9*sqrt(x^2 + y^2))*sin(2*atan(y/x))/(x^2+y^2)", 2);
            coeff_diff = gsFunctionExpr<>("1","0","0","1",2);
            coeff_conv = gsFunctionExpr<>("0","0",2);
            coeff_reac = gsFunctionExpr<>("0",2);
            break;

        case 4:
            gsInfo << "4) Poisson equation on an L-shaped domain\n";
            mp = gsMultiPatch<>(*gsNurbsCreator<>::BSplineLShape_p1());
            sol_exact = gsFunctionExpr<>( "if ( y>0, ( (x^2+y^2)^(1.0/3.0) )*sin( (2*atan2(y,x) - pi)/3.0 ), ( (x^2+y^2)^(1.0/3.0) )*sin( (2*atan2(y,x) +3*pi)/3.0 ) )", 2);
            rhs_exact = gsFunctionExpr<>( "0", 2);
            coeff_diff = gsFunctionExpr<>("1","0","0","1",2);
            coeff_conv = gsFunctionExpr<>("0","0",2);
            coeff_reac = gsFunctionExpr<>("0",2);
            break;

        case 5:
            gsInfo << "5) Poisson equation on the unit cube\n";
            mp = gsMultiPatch<>(*gsNurbsCreator<>::BSplineCube((real_t)1));
            sol_exact = gsFunctionExpr<>( "sin(pi*x)*sin(pi*y)*sin(pi*z)", 3);
            rhs_exact = gsFunctionExpr<>( "(3*pi^2)*sin(pi*x)*sin(pi*y)*sin(pi*z)", 3);
            coeff_diff = gsFunctionExpr<>("1","0","0","0","1","0","0","0","1",3);
            coeff_conv = gsFunctionExpr<>("0","0","0",3);
            coeff_reac = gsFunctionExpr<>("0",3);
            break;

        case 6:
            gsInfo << "6) Poisson's equation on Yeti footprint\n";
            mp = *static_cast<gsMultiPatch<>::uPtr>(gsReadFile<>("domain2d/yeti_mp2.xml"));
            sol_exact = gsFunctionExpr<>( "sin(5*pi*x)*sin(5*pi*y)", 2);
            rhs_exact = gsFunctionExpr<>( "(50*pi^2)*sin(5*pi*x)*sin(5*pi*y)", 2);
            coeff_diff = gsFunctionExpr<>("1","0","0","1",2);
            coeff_conv = gsFunctionExpr<>("0","0",2);
            coeff_reac = gsFunctionExpr<>("0",2);
            break;

        default:
            gsInfo << "Unknown benchmark case chosen.\n";
            return EXIT_FAILURE;
    }

    // Print information about benchmark
    gsInfo << "Exact solution: " << sol_exact << "\n";
    gsInfo << "Right hand side: " << rhs_exact << "\n";
    gsInfo << "Handling of boundary conditions: " << (typeBCHandling==1 ? "elimination" : "Nitsche") << "\n";

    // Handle the uniform splitting
    for (index_t i=0; i<numSplits; ++i)
        mp = mp.uniformSplit();
    gsInfo << "Number of patches: " << mp.nPatches() << "\n\n";

    // Define boundary conditions
    gsBoundaryConditions<> bcInfo;
    gsFunctionExpr<> zero("0", mp.geoDim());
    for (gsMultiPatch<>::const_biterator bit = mp.bBegin(); bit != mp.bEnd(); ++bit)
        bcInfo.addCondition(*bit, condition_type::dirichlet, &sol_exact);
    bcInfo.setGeoMap(mp);

    // Setup of vector of bases
    if (typeCoarsening.empty())
    {
        // Just setup some defaults
        if (typeProjection==1)
        {
            // If we have a transition from degree p to degree 1, we only need
            // a single refinement where the degree is changed. We apply this
            // between the finest and the second finest levels.
            typeCoarsening = std::string(numLevels-2, 'h') + "z";
        }
        else //if (typeProjection==2)
        {
            // If we have a transition where the degree is changed by only one,
            // we need up to p-1 transitions. The remainder needs to by of type h.
            if (numLevels>numDegree)
                typeCoarsening = std::string(numLevels-numDegree, 'h') + std::string(numDegree-1, 'z');
            else
                // It can happen that the coarsest problem does not have degree 1 (if there
                // are not enough levels).
                typeCoarsening = std::string(numLevels-1, 'z');
        }
    }
    if (typeCoarsening.size() != (size_t)numLevels-1)
    {
        gsInfo << "The string provided to --Coarsening should have length " << numLevels-1 << "\n";
        return EXIT_FAILURE;
    }
    // Now, we count the coarsening type informations
    index_t numRefH = 0, numRefP = 0, numRefZ = 0;
    for (index_t i = 0; i < numLevels-1; ++i)
    {
        if ( typeCoarsening[i] == 'h')
            numRefH++;
        else if ( typeCoarsening[i] == 'p')
            numRefP++;
        else if ( typeCoarsening[i] == 'z')
            numRefZ++;
        else
        {
            gsInfo << "Unknown type given in --Coarsening.\n";
            return EXIT_FAILURE;
        }
    }

    if (typeProjection==1 && numRefP+numRefZ > 1)
    {
        gsInfo << "If --Projection 1, there should be only one coarsening of type p or z in --Coarsening.\n";
        return EXIT_FAILURE;
    }

    if (numRefine - numRefH - numRefZ<0)
    {
        gsInfo << "Cannot have more h or z refinements in --Coarsening than overall number of refinement steps.\n";
        return EXIT_FAILURE;
    }

    // Vector of multibasis objects
    // Index 0 refers to coarsest level; we first setup that basis
    std::vector<gsMultiBasis<>> bases;
    bases.emplace_back(mp);

    // Adjust spline degree for coarsest level
    const index_t degreeOffset = numDegree - (numRefP+numRefZ) * (typeProjection==1?(numDegree-1):1) - bases[0].degree();
    if (degreeOffset>0)
        bases[0].degreeIncrease(degreeOffset);
    else if (degreeOffset<0)
        bases[0].degreeReduce(-degreeOffset);

    // Apply refinement in h for the coarses level
    for (index_t i = 0; i < numRefine - numRefH - numRefZ; ++i)
        bases[0].uniformRefine();

    // Now, we setup the remaining levels
    for (index_t i = 1; i < numLevels; i++)
    {
        // New basis object, which is just a copy
        bases.push_back(bases.back());
        if (typeCoarsening[i-1] == 'p')
        {
            if (typeProjection == 1)
                bases.back().degreeIncrease(numDegree-1);
            else
                bases.back().degreeIncrease();
        }
        else if (typeCoarsening[i-1] == 'h')
        {
            bases.back().uniformRefine();
        }
        else //if (typeCoarsening[i-1] == 'z')
        {
            bases.back().uniformRefine();
            if (typeProjection == 1)
                bases.back().degreeIncrease(numDegree-1);
            else
                bases.back().degreeIncrease();
        }
    }

    gsStopwatch clock;

    // Determine prolongation/restriction operators
    std::vector<gsSparseMatrix<real_t,RowMajor>> prolongation_H(numLevels-1);
    std::vector<gsLinearOperator<>::Ptr> restriction(numLevels-1);
    std::vector<gsLinearOperator<>::Ptr> prolongation(numLevels-1);

    clock.restart();
    gsInfo << "|| Multigrid hierarchy ||\n";
    for (index_t i=1; i<numLevels; i++)
    {
        if (typeCoarsening[i-1] != 'h')
        {
            if (typeLumping == 1)
            {
                gsInfo << "Restriction and prolongation between levels " << i << " and " << i-1 << ": L2-projection with lumped mass.\n";
                gsSparseMatrix<> mixedMass = assembleMixedMass(mp, bases[i], bases[i-1], bcInfo, opt);
                gsSparseMatrix<real_t> prolongationMatrix
                      = assembleLumpedMass(mp, bases[i], bcInfo, opt).asDiagonal().inverse()
                      * mixedMass;
                gsSparseMatrix<real_t> restrictionMatrix
                      = assembleLumpedMass(mp, bases[i-1], bcInfo, opt).asDiagonal().inverse()
                      * mixedMass.transpose();
                prolongation[i-1] = makeMatrixOp(prolongationMatrix.moveToPtr());
                restriction[i-1] = makeMatrixOp(restrictionMatrix.moveToPtr());
            }
            else
            {
                gsInfo << "Restriction and prolongation between levels " << i << " and " << i-1 << ": exact L2-projection.\n";
                gsSparseMatrix<> prolongationP = assembleMixedMass(mp, bases[i], bases[i-1], bcInfo, opt);
                gsSparseMatrix<> restrictionP = prolongationP.transpose();
                gsSparseMatrix<> prolongationM = assembleMass(mp, bases[i], bcInfo, opt);
                gsSparseMatrix<> restrictionM = assembleMass(mp, bases[i-1], bcInfo, opt);

                prolongation[i-1] = makeLinearOp(
                    [prolongationP=give(prolongationP),prolongationM=give(prolongationM)]
                    (const gsMatrix<>& Xcoarse, gsMatrix<>& Xfine)
                    {
                        gsConjugateGradient<> CGSolver(prolongationM);
                        CGSolver.setTolerance(1e-12);
                        CGSolver.solve(prolongationP*Xcoarse,Xfine);
                    },
                    prolongationP.rows(), prolongationP.cols()
                );
                restriction[i-1] = makeLinearOp(
                    [restrictionP=give(restrictionP),restrictionM=give(restrictionM)]
                    (const gsMatrix<>& Xfine, gsMatrix<>& Xcoarse)
                    {
                        gsConjugateGradient<> CGSolver(restrictionM);
                        CGSolver.setTolerance(1e-12);
                        CGSolver.solve(restrictionP*Xfine,Xcoarse);
                    },
                    restrictionP.rows(), restrictionP.cols()
                );

            }
        }
        else //if (typeCoarsening[i-1] == 'h')
        {
            gsInfo << "Restriction and prolongation between levels " << i << " and " << i-1 << ": canonical embedding and its transpose.\n";
            bases[i].clone()->uniformCoarsen_withTransfer(prolongation_H[i-1],bcInfo,opt);
            prolongation[i-1] = makeMatrixOp(prolongation_H[i-1]);
            restriction[i-1] = makeMatrixOp(prolongation_H[i-1].transpose());

        }
    }
    double Time_Transfer = clock.stop();

    // Determine stiffness matrices (assembling or Galerkin projection)
    gsInfo << "\n|| Assembling ||\n";
    std::vector<gsSparseMatrix<>> matrices(numLevels);
    std::vector<gsLinearOperator<>::Ptr> operators(numLevels);
    gsMatrix<> rhs;
    double Time_Assembly = 0, Time_Galerkin = 0;
    for (index_t i=numLevels-1; i>=0; --i)
    {
        if (typeCoarseOperator == 1 || i == numLevels-1 || typeCoarsening[i] != 'h')
        {
            gsInfo << "Assemble on level " << i << ": ";
            clock.restart();
            gsCDRAssembler<real_t> assembler(
                mp,
                bases[i],
                bcInfo,
                rhs_exact,
                coeff_diff, coeff_conv, coeff_reac,
                (dirichlet::strategy)opt.getInt("DirichletStrategy"),
                iFace::glue
            );
            assembler.assemble();
            matrices[i] = assembler.matrix();
            if (i==numLevels-1)
                rhs = assembler.rhs();
            Time_Assembly += clock.stop();
            gsInfo << "Degree: " << bases[i].degree()  << ", Ndof: " << matrices[i].rows() << "\n";
        }
        else
        {
            gsInfo << "Apply Galerkin projection on level " << i << ": ";
            clock.restart();
            matrices[i] = prolongation_H[i].transpose() * matrices[i+1] * prolongation_H[i];
            Time_Galerkin += clock.stop();
            gsInfo << "Ndof: " << matrices[i].rows() << "\n";
        }
        operators[i] = makeMatrixOp(matrices[i]);
    }
    gsSparseMatrix<>& matrix = matrices.back();

    // Setup of multigrid object
    gsMultiGridOp<>::Ptr mg = gsMultiGridOp<>::make(operators, prolongation, restriction);

    // Setup of solver for coarsest grid level
    clock.restart();
    mg->setCoarseSolver(makeSparseLUSolver(matrices[0]));
    double Time_Coarse_Solver_Setup = clock.stop();

    // Specify the number of cycles
    // For coarsest level, we stick to 1 in any case (exact solver is never cycled)
    if (typeCycle_p == typeCycle_h)
        gsInfo << "Multigrid cycle type: " << typeCycle_h << "\n";
    else
        gsInfo << "Multigrid cycle type: " << typeCycle_h << " for h-refinement and " << typeCycle_p << " for p- and z-refinement\n";
    for (index_t i=1; i<numLevels-1; i++)
    {
        if (typeCoarsening[i] != 'h')
            mg->setNumCycles(i,typeCycle_p);
        else
            mg->setNumCycles(i,typeCycle_h);
    }

    // Setup of smoothers
    gsInfo << "\n|| Smoother ||\n";
    opt.addReal("Scaling","",0.12);           // only used for SCMS
    opt.addReal("Damping","",dampingSCMS);    // only used for SCMS
    clock.restart();
    for (index_t i=1; i<numLevels; i++)
    {
        if (bases[i].degree()==1)
        {
            mg->setSmoother(i,makeGaussSeidelOp(matrices[i]));
            gsInfo << "Smoother for level " << i << ": Gauss-Seidel\n";
        }
        else switch (typeSmoother)
        {
            case 1:
                mg->setSmoother(i,makeIncompleteLUOp(matrices[i]));
                gsInfo << "Smoother for level " << i << ": Incomplete LU\n";
                break;
            case 2:
                mg->setSmoother(i,makeGaussSeidelOp(matrices[i]));
                gsInfo << "Smoother for level " << i << ": Gauss-Seidel\n";
                break;
            case 3:
                mg->setSmoother(i,setupSubspaceCorrectedMassSmoother(matrices[i], bases[i], bcInfo, opt));
                gsInfo << "Smoother for level " << i << ": Subspace corrected mass smoother (damping = "<<dampingSCMS<<")\n";
                break;
            case 4:
                mg->setSmoother(i,setupBlockILUT(matrices[i], bases[i], bcInfo, opt));
                gsInfo << "Smoother for level " << i << ": Blockwise Incomplete LU\n";
                break;
            default:
                gsInfo << "Unknown smoother chosen.\n";
                return EXIT_FAILURE;
        }
    }
    gsInfo << "Number of smoothing steps: " << numSmoothing << "\n";
    mg->setNumPreSmooth(numSmoothing);
    mg->setNumPostSmooth(numSmoothing);
    // For the conjugate Gradient solver, the post smoother needs to be the transpose of the
    // pre smoother. For all other iterative solvers, it does not matter. So, we choose
    // pre smoothing and post smoothing to be the same.
    gsInfo << "Post smoothing is transpose of pre smoothing: " << (typeSolver == 3?"yes":"no") << "\n";
    mg->setSymmSmooth(typeSolver == 3);
    double Time_Smoother_Setup = clock.stop();

    gsInfo << "\n|| Setup Timings || \n";
    gsInfo << "Total transfer setup time: " << Time_Transfer << "\n";
    gsInfo << "Total Assembly time: " << Time_Assembly << "\n";
    gsInfo << "Total Galerkin projections: " << Time_Galerkin << "\n";
    gsInfo << "Coarse solver setup time: " << Time_Coarse_Solver_Setup << "\n";
    gsInfo << "Smoother setup time: " << Time_Smoother_Setup << "\n";
    gsInfo << "Total setup time: " << Time_Assembly + Time_Galerkin + Time_Transfer
        + Time_Coarse_Solver_Setup + Time_Smoother_Setup << "\n";

    // Setup of iterative solver
    gsIterativeSolver<>::Ptr solver;
    switch (typeSolver)
    {
        case 1:
            gsInfo << "\n|| Solver information ||\np-multigrid is applied as stand-alone solver\n";
            // The preconditioned gradient method is noting but applying p-multigrid as a stand-alone solver.
            // We have to set step size = 1 to deactivate automatic stepsize control.
            solver = gsGradientMethod<>::make(matrix, mg, 1);
            break;
        case 2:
            gsInfo << "\n|| Solver information ||\nBiCGStab is applied as solver, p-multigrid as a preconditioner\n";
            solver = gsBiCgStab<>::make(matrix, mg);
            break;
        case 3:
            gsInfo << "\n|| Solver information ||\nCG is applied as solver, p-multigrid as a preconditioner\n";
            solver = gsConjugateGradient<>::make(matrix, mg);
            break;
        default:
            gsInfo << "Unknown iterative solver chosen.\n";
            return EXIT_FAILURE;
    }

    gsMatrix<> x = gsMatrix<>::Random(matrix.rows(),1);

    // Unfortunately, the stopping criterion is relative to the rhs not to the initial residual (not yet configurable)
    const real_t rhs_norm = rhs.norm();
    solver->setTolerance( tol * (rhs-matrix*x).norm() / rhs_norm );
    solver->setMaxIterations(maxIter);
    gsMatrix<> error_history;
    clock.restart();
    solver->solveDetailed( rhs, x, error_history );
    double Time_Solve = clock.stop();

    gsInfo << "   0  |  Residual norm: " << std::setprecision(6) << (error_history(0,0) * rhs_norm) << "\n";
    for (index_t i=1; i<error_history.rows(); ++i)
        gsInfo << std::right << std::setw(4) << i
               << "  |  Residual norm: "
               << std::setprecision(6) << std::left << std::setw(15) << (error_history(i,0) * rhs_norm)
               << "  reduction:  1 / "
               << std::setprecision(3) << (error_history(i-1,0)/error_history(i,0))
               << "\n";

    const bool success = solver->error() <= solver->tolerance();
    if (success)
        gsInfo << "Solver reached accuracy goal after " << solver->iterations() << " iterations.\n";
    else
        gsInfo << "Solver did not reach accuracy goal within " << solver->iterations() << " iterations.\n";
    gsInfo << "The iteration took " << Time_Solve << " seconds.\n";
    // Determine residual and l2 error
    gsInfo << "Residual after solving: "  << (rhs-matrix*x).norm() << "\n";

    return success ? EXIT_SUCCESS : EXIT_FAILURE;
}

// Create the subspace corrected mass smoother
gsPreconditionerOp<>::Ptr setupSubspaceCorrectedMassSmoother(
    const gsSparseMatrix<>& matrix,
    const gsMultiBasis<>& mb,
    const gsBoundaryConditions<>& bc,
    const gsOptionList& opt
)
{
    const short_t dim = mb.topology().dim();

    // Setup dof mapper
    gsDofMapper dm;
    mb.getMapper(
       (dirichlet::strategy)opt.getInt("DirichletStrategy"),
       iFace::glue,
       bc,
       dm,
       0
    );
    const index_t nTotalDofs = dm.freeSize();

    // Decompose the whole domain into components
    std::vector< std::vector<patchComponent> > components = mb.topology().allComponents(true);
    const index_t nr_components = components.size();

    // Setup Dirichlet boundary conditions
    gsBoundaryConditions<> dir_bc;
    for ( index_t ps=0; ps < 2*dim; ++ps )
        dir_bc.addCondition( 0, 1+ps, condition_type::dirichlet, NULL );

    // Setup transfer matrices and local preconditioners
    std::vector< gsSparseMatrix<real_t,RowMajor> > transfers;
    transfers.reserve(nr_components);
    std::vector< gsLinearOperator<>::Ptr > ops;
    ops.reserve(nr_components);

    for (index_t i=0; i<nr_components; ++i)
    {
        gsMatrix<index_t> indices;
        std::vector<gsBasis<>::uPtr> bases = mb.componentBasis_withIndices(components[i],dm,indices,true);
        index_t sz = indices.rows();
        gsSparseEntries<> se;
        se.reserve(sz);
        for (index_t l=0; l<sz; ++l)
            se.add(indices(l,0),l,(real_t)(1));
        gsSparseMatrix<real_t,RowMajor> transfer(nTotalDofs,sz);
        transfer.setFrom(se);
        if (sz>0)
        {
            if (bases[0]->dim() == dim)
            {
                GISMO_ASSERT ( bases.size() == 1, "Only one basis is expected for each patch." );
                ops.push_back(
                    gsPatchPreconditionersCreator<>::subspaceCorrectedMassSmootherOp(
                        *(bases[0]),
                        dir_bc,
                        gsOptionList(),
                        opt.getReal("Scaling")
                    )
                );
            }
            else
            {
                gsSparseMatrix<> mat = transfer.transpose() * matrix * transfer;
                ops.push_back( makeSparseCholeskySolver(mat) );
            }
            transfers.push_back(give(transfer));
        }
    }
    gsPreconditionerOp<>::uPtr result = gsPreconditionerFromOp<>::make(makeMatrixOp(matrix), gsAdditiveOp<>::make(transfers, ops));
    result->setOptions(opt);
    return give(result);
}

gsPreconditionerOp<>::Ptr setupBlockILUT(
    const gsSparseMatrix<>& A,
    const gsMultiBasis<>& mb,
    const gsBoundaryConditions<>& bc,
    const gsOptionList& opt
)
{
    const index_t nPatches = mb.nPieces();

    // Setup dof mapper
    gsDofMapper dm;
    mb.getMapper(
       (dirichlet::strategy)opt.getInt("DirichletStrategy"),
       iFace::glue,
       bc,
       dm,
       0
    );
    // Subdivide the overal dofs into
    //   a) the patch-local dofs (l=0,...,nPatches-1)
    //   b) the coupled dofs (l=nPatches)
    std::vector<index_t> sizes(nPatches+1);
    std::vector<index_t> shifts(nPatches+1);
    shifts[0] = 0;
    for (index_t k=0; k<nPatches; k++)
    {
        sizes[k] = dm.findFreeUncoupled(k).rows();
        shifts[k+1] = shifts[k] + sizes[k];
    }
    sizes[nPatches] = A.rows() - shifts[nPatches];

    // Vector of factorized operators
    std::vector< gsEigen::PermutationMatrix<Dynamic,Dynamic,index_t> > P(nPatches+1);
    // Vector of factorized operators
    std::vector< gsEigen::PermutationMatrix<Dynamic,Dynamic,index_t> > Pinv(nPatches+1);
    // Define the A_aprox matrix
    // Inefficient since it does not use a sparse matrix
    gsMatrix<> A_aprox(A.rows(),A.cols());
    A_aprox.setZero();

    gsSparseMatrix<> S = A.block(shifts[nPatches],shifts[nPatches],sizes[nPatches],sizes[nPatches]);

    for (index_t k=0 ; k<nPatches; k++)
    {
        // Diagonal entries
        gsSparseMatrix<> block = A.block(shifts[k],shifts[k],sizes[k],sizes[k]);
        gsEigen::IncompleteLUT<real_t> ilu;
        ilu.setFillfactor(1);
        ilu.compute(block);
        P[k] = ilu.fillReducingPermutation();
        Pinv[k] = ilu.inversePermutation();
        A_aprox.block(shifts[k],shifts[k],sizes[k],sizes[k]) = ilu.factors();

        // Schur complement and off-diagonal contributions
        if (sizes[nPatches]>0)
        {
            gsMatrix<> ddB = A.block(shifts[nPatches],shifts[k],sizes[nPatches],sizes[k]);
            gsMatrix<> ddC = A.block(shifts[k],shifts[nPatches],sizes[k],sizes[nPatches]);
            gsMatrix<> ddBtilde = ilu.factors().triangularView<gsEigen::Upper>().transpose().solve((ddB*P[k]).transpose()).transpose();
            gsMatrix<> ddCtilde = ilu.factors().triangularView<gsEigen::UnitLower>().solve(Pinv[k]*ddC);

            S -= (ddBtilde*ddCtilde).sparseView();
            A_aprox.block(shifts[k],shifts[nPatches],sizes[k],sizes[nPatches]) = ddCtilde;
            A_aprox.block(shifts[nPatches],shifts[k],sizes[nPatches],sizes[k]) = ddBtilde;
        }
    }

    // If there is no coupling (for example if there is only one patch), the work
    // is done. We should not try to compute the ilu factorization then.
    if (sizes[nPatches]>0)
    {
        // Preform ILUT on the S-matrix.
        gsEigen::IncompleteLUT<real_t> ilu;
        ilu.setFillfactor(1);
        ilu.compute(S);
        P[nPatches] = ilu.fillReducingPermutation();
        Pinv[nPatches] = ilu.inversePermutation();
        A_aprox.block(shifts[nPatches],shifts[nPatches],sizes[nPatches],sizes[nPatches]) = ilu.factors();
    }

    return gsPreconditionerFromOp<>::make(
        makeMatrixOp(A),
        makeLinearOp(
            [m_A_aprox=give(A_aprox), m_P=give(P), m_Pinv=give(Pinv),m_shifts=give(shifts),m_sizes=give(sizes),
                m_nPatches=nPatches](const gsMatrix<>& rhs, gsMatrix<>& x)
            {
                x.setZero(rhs.rows(),rhs.cols());
                for (index_t k=0; k<=m_nPatches; ++k)
                    x.block(m_shifts[k],0,m_sizes[k],1) = m_Pinv[k]*rhs.block(m_shifts[k],0,m_sizes[k],1);
                x = m_A_aprox.template triangularView<gsEigen::UnitLower>().solve(x);
                x = m_A_aprox.template triangularView<gsEigen::Upper>().solve(x);
                for (index_t k=0; k<=m_nPatches; ++k)
                    x.block(m_shifts[k],0,m_sizes[k],1) = m_P[k]*x.block(m_shifts[k],0,m_sizes[k],1);
            },
            A.rows(),
            A.cols()
        )
    );
}

gsMatrix<> assembleLumpedMass(
    const gsMultiPatch<>& mp,
    const gsMultiBasis<>& basis,
    const gsBoundaryConditions<>& bcInfo,
    const gsOptionList& opt
)
{
    typedef gsExprAssembler<real_t>::geometryMap geometryMap;
    typedef gsExprAssembler<real_t>::variable variable;
    typedef gsExprAssembler<real_t>::space space;

    gsExprAssembler<real_t> ex(1,1);
    geometryMap G = ex.getMap(mp);
    space w_n = ex.getSpace(basis, 1, 0);
    w_n.setInterfaceCont(0);
    if ((dirichlet::strategy)opt.getInt("DirichletStrategy") == dirichlet::elimination)
    {
        w_n.setup(bcInfo, dirichlet::interpolation, 0);
    }
    ex.setIntegrationElements(basis);
    ex.initSystem();
    ex.assemble(w_n * meas(G));
    return ex.rhs();
}

gsSparseMatrix<> assembleMass(
    const gsMultiPatch<>& mp,
    const gsMultiBasis<>& basis,
    const gsBoundaryConditions<>& bcInfo,
    const gsOptionList& opt
)
{
    typedef gsExprAssembler<real_t>::geometryMap geometryMap;
    typedef gsExprAssembler<real_t>::variable variable;
    typedef gsExprAssembler<real_t>::space space;

    gsExprAssembler<real_t> ex(1,1);
    geometryMap G = ex.getMap(mp);
    space w_n = ex.getSpace(basis, 1, 0);
    if ((dirichlet::strategy)opt.getInt("DirichletStrategy") == dirichlet::elimination)
    {
        w_n.setup(bcInfo, dirichlet::interpolation, 0);
    }
    ex.setIntegrationElements(basis);
    ex.initSystem();
    ex.assemble(w_n * meas(G) * w_n.tr());
    return ex.matrix();
}

gsSparseMatrix<> assembleMixedMass(
    const gsMultiPatch<>& mp,
    const gsMultiBasis<>& basisU,
    const gsMultiBasis<>& basisV,
    const gsBoundaryConditions<>& bcInfo,
    const gsOptionList& opt
)
{
    typedef gsExprAssembler<real_t>::geometryMap geometryMap;
    typedef gsExprAssembler<real_t>::variable variable;
    typedef gsExprAssembler<real_t>::space space;

    gsExprAssembler<real_t> ex(1,1);
    geometryMap G = ex.getMap(mp);
    space v_n = ex.getSpace(basisU, 1, 0);
    space u_n = ex.getTestSpace(v_n, basisV);
    if ((dirichlet::strategy)opt.getInt("DirichletStrategy") == dirichlet::elimination)
    {
        v_n.setup(bcInfo, dirichlet::interpolation, 0);
        u_n.setup(bcInfo, dirichlet::interpolation, 0);
    }
    ex.setIntegrationElements(basisU);
    ex.initSystem();
    ex.assemble(u_n * meas(G) * v_n.tr());
    return ex.matrix().transpose();
}