int main(int argc, char *argv[]) {
#include "MueLu_UseShortNames.hpp"
Teuchos::oblackholestream blackhole;
Teuchos::GlobalMPISession mpiSession(&argc,&argv,&blackhole);
RCP<const Teuchos::Comm<int> > comm = Teuchos::DefaultComm<int>::getComm();
/**********************************************************************************/
/* SET TEST PARAMETERS */
/**********************************************************************************/
// Note: use --help to list available options.
Teuchos::CommandLineProcessor clp(false);
// Default is Laplace1D with nx = 8748.
// It's a nice size for 1D and perfect aggregation. (6561=3^8)
//Nice size for 1D and perfect aggregation on small numbers of processors. (8748=4*3^7)
Galeri::Xpetra::Parameters<GO> matrixParameters(clp, 8748); // manage parameters of the test case
Xpetra::Parameters xpetraParameters(clp); // manage parameters of xpetra
// custom parameters
int nSmoothers=2;
LO maxLevels = 3;
LO its=10;
std::string coarseSolver="ifpack2";
// std::string coarseSolver="amesos2";
int pauseForDebugger=0;
clp.setOption("nSmoothers",&nSmoothers,"number of Gauss-Seidel smoothers in the MergedSmootehrs");
clp.setOption("maxLevels",&maxLevels,"maximum number of levels allowed. If 1, then a MergedSmoother is used on the coarse grid");
clp.setOption("its",&its,"number of multigrid cycles");
clp.setOption("coarseSolver",&coarseSolver,"amesos2 or ifpack2 (Tpetra specific. Ignored for Epetra)");
clp.setOption("debug",&pauseForDebugger,"pause to attach debugger");
switch (clp.parse(argc,argv)) {
case Teuchos::CommandLineProcessor::PARSE_HELP_PRINTED: return EXIT_SUCCESS; break;
case Teuchos::CommandLineProcessor::PARSE_ERROR:
case Teuchos::CommandLineProcessor::PARSE_UNRECOGNIZED_OPTION: return EXIT_FAILURE; break;
case Teuchos::CommandLineProcessor::PARSE_SUCCESSFUL: break;
}
matrixParameters.check();
xpetraParameters.check();
// TODO: check custom parameters
if (comm->getRank() == 0) {
// matrixParameters.print();
// xpetraParameters.print();
// TODO: print custom parameters
}
if (pauseForDebugger) {
Utils::PauseForDebugger();
}
/**********************************************************************************/
/* CREATE INITIAL MATRIX */
/**********************************************************************************/
const RCP<const Map> map = MapFactory::Build(xpetraParameters.GetLib(), matrixParameters.GetNumGlobalElements(), 0, comm);
RCP<Galeri::Xpetra::Problem<Map,CrsMatrixWrap,MultiVector> > Pr =
Galeri::Xpetra::BuildProblem<SC,LO,GO,Map,CrsMatrixWrap,MultiVector>(matrixParameters.GetMatrixType(), map, matrixParameters.GetParameterList()); //TODO: Matrix vs. CrsMatrixWrap
RCP<Matrix> Op = Pr->BuildMatrix();
#ifdef NEUMANN
// Tranform matrix to Neumann b.c.
// Essentially, we need to update two diagonal elements
// TODO: calls to getLocalRowView not really needed
Op->resumeFill();
Teuchos::ArrayView<const LO> indices;
Teuchos::ArrayView<const SC> values;
Teuchos::Array<SC> newValues(2, 0.0);
size_t myRank = Op->getRowMap()->getComm()->getRank();
size_t nCpus = Op->getRowMap()->getComm()->getSize();
if (myRank == 0) { // JG TODO: can we use rowMap->isNodeLocalElement(0) instead for more genericity?
//LO firstRow = 0;
newValues[0] = 1.0; newValues[1] = -1.0;
Op->getLocalRowView(0, indices, values);
Op->replaceLocalValues(0, indices, newValues);
}
if (myRank == nCpus-1) { // JG TODO: can we use rowMap->isNodeLocalElement(lastRow) instead for more genericity?
LO lastRow = Op->getNodeNumRows()-1;
newValues[0] = -1.0; newValues[1] = 1.0;
Op->getLocalRowView(lastRow, indices, values);
Op->replaceLocalValues(lastRow, indices, newValues);
}
Op->fillComplete();
#endif // NEUMANN
/**********************************************************************************/
/* */
/**********************************************************************************/
RCP<MultiVector> nullSpace = MultiVectorFactory::Build(map,1);
nullSpace->putScalar( (SC) 1.0);
Teuchos::Array<Teuchos::ScalarTraits<SC>::magnitudeType> norms(1);
nullSpace->norm1(norms);
if (comm->getRank() == 0)
std::cout << "||NS|| = " << norms[0] << std::endl;
RCP<MueLu::Hierarchy<SC,LO,GO,NO,LMO> > H = rcp( new Hierarchy() );
H->SetDefaultVerbLevel(MueLu::Extreme);
H->IsPreconditioner(false);
RCP<MueLu::Level> Finest = H->GetLevel();
Finest->setDefaultVerbLevel(Teuchos::VERB_HIGH);
Finest->Set("A", Op);
Finest->Set("Nullspace", nullSpace);
FactoryManager M;
M.SetFactory("Aggregates", rcp(new CoupledAggregationFactory()));
M.SetFactory("Ptent", rcp(new TentativePFactory()));
M.SetFactory("P", rcp(new SaPFactory()));
#ifdef EMIN
// Energy-minimization
RCP<PatternFactory> PatternFact = rcp(new PatternFactory());
#if 0
PatternFact->SetFactory("P", M.GetFactory("Ptent"));
#else
PatternFact->SetFactory("P", M.GetFactory("P"));
#endif
M.SetFactory("Ppattern", PatternFact);
RCP<EminPFactory> EminPFact = rcp(new EminPFactory());
EminPFact->SetFactory("P", M.GetFactory("Ptent"));
M.SetFactory("P", EminPFact);
RCP<NullspacePresmoothFactory> NullPreFact = rcp(new NullspacePresmoothFactory());
NullPreFact->SetFactory("Nullspace", M.GetFactory("Nullspace"));
M.SetFactory("Nullspace", NullPreFact);
#endif
RCP<SmootherPrototype> smooProto = gimmeMergedSmoother(nSmoothers, xpetraParameters.GetLib(), coarseSolver, comm->getRank());
M.SetFactory("Smoother", rcp(new SmootherFactory(smooProto)));
Teuchos::ParameterList status;
RCP<SmootherPrototype> coarseProto;
if (maxLevels != 1)
coarseProto = gimmeCoarseProto(xpetraParameters.GetLib(), coarseSolver, comm->getRank());
else
coarseProto = gimmeMergedSmoother(nSmoothers, xpetraParameters.GetLib(), coarseSolver, comm->getRank());
if (coarseProto == Teuchos::null)
return EXIT_FAILURE;
#ifdef NEUMANN
// Use coarse level projection solver
RCP<SmootherPrototype> projectedSolver = rcp(new ProjectorSmoother(coarseProto));
RCP<SmootherFactory> coarseSolveFact = rcp(new SmootherFactory(projectedSolver));
#else
RCP<SmootherFactory> coarseSolveFact = rcp(new SmootherFactory(coarseProto));
#endif
M.SetFactory("CoarseSolver", coarseSolveFact);
H->EnableGraphDumping("graph.dot", 2);
H->Setup(M, 0, maxLevels);
//if (comm->getRank() == 0) {
// std::cout << "======================\n Multigrid statistics \n======================" << std::endl;
// status.print(std::cout,Teuchos::ParameterList::PrintOptions().indent(2));
//}
// Define RHS
RCP<MultiVector> X = MultiVectorFactory::Build(map,1);
RCP<MultiVector> RHS = MultiVectorFactory::Build(map,1);
X->setSeed(846930886);
X->randomize();
X->norm2(norms);
if (comm->getRank() == 0)
std::cout << "||X_true|| = " << std::setiosflags(std::ios::fixed) << std::setprecision(10) << norms[0] << std::endl;
Op->apply(*X,*RHS,Teuchos::NO_TRANS,(SC)1.0,(SC)0.0);
// Use AMG directly as an iterative method
{
X->putScalar( (SC) 0.0);
H->Iterate(*RHS,its,*X);
X->norm2(norms);
if (comm->getRank() == 0)
std::cout << "||X_" << std::setprecision(2) << its << "|| = " << std::setiosflags(std::ios::fixed) << std::setprecision(10) << norms[0] << std::endl;
}
return EXIT_SUCCESS;
}
