void DropNegativeEntriesFactory<Scalar, LocalOrdinal, GlobalOrdinal, Node>::Build(Level& currentLevel) const {
FactoryMonitor m(*this, "Matrix filtering (springs)", currentLevel);
RCP<Matrix> Ain = Get< RCP<Matrix> >(currentLevel, "A");
LocalOrdinal nDofsPerNode = Ain->GetFixedBlockSize();
// create new empty Operator
Teuchos::RCP<Matrix> Aout = MatrixFactory::Build(Ain->getRowMap(), Ain->getGlobalMaxNumRowEntries(), Xpetra::StaticProfile);
size_t numLocalRows = Ain->getNodeNumRows();
for(size_t row=0; row<numLocalRows; row++) {
GlobalOrdinal grid = Ain->getRowMap()->getGlobalElement(row);
int rDofID = Teuchos::as<int>(grid % nDofsPerNode);
// extract row information from input matrix
Teuchos::ArrayView<const LocalOrdinal> indices;
Teuchos::ArrayView<const Scalar> vals;
Ain->getLocalRowView(row, indices, vals);
// just copy all values in output
Teuchos::ArrayRCP<GlobalOrdinal> indout(indices.size(),Teuchos::ScalarTraits<GlobalOrdinal>::zero());
Teuchos::ArrayRCP<Scalar> valout(indices.size(),Teuchos::ScalarTraits<Scalar>::zero());
size_t nNonzeros = 0;
for(size_t i=0; i<(size_t)indices.size(); i++) {
GlobalOrdinal gcid = Ain->getColMap()->getGlobalElement(indices[i]); // global column id
int cDofID = Teuchos::as<int>(gcid % nDofsPerNode);
if(rDofID == cDofID && Teuchos::ScalarTraits<Scalar>::magnitude(vals[i]) >= Teuchos::ScalarTraits<Scalar>::magnitude(Teuchos::ScalarTraits<Scalar>::zero())) {
indout [nNonzeros] = gcid;
valout [nNonzeros] = vals[i];
nNonzeros++;
}
}
indout.resize(nNonzeros);
valout.resize(nNonzeros);
Aout->insertGlobalValues(Ain->getRowMap()->getGlobalElement(row), indout.view(0,indout.size()), valout.view(0,valout.size()));
}
Aout->fillComplete(Ain->getDomainMap(), Ain->getRangeMap());
// copy block size information
Aout->SetFixedBlockSize(nDofsPerNode);
GetOStream(Statistics0, 0) << "Nonzeros in A (input): " << Ain->getGlobalNumEntries() << ", Nonzeros after filtering A: " << Aout->getGlobalNumEntries() << std::endl;
Set(currentLevel, "A", Aout);
}
void UserPFactory<Scalar, LocalOrdinal, GlobalOrdinal, Node, LocalMatOps>::BuildP(Level& fineLevel, Level& coarseLevel) const {
FactoryMonitor m(*this, "Build", coarseLevel);
RCP<Matrix> A = Get< RCP<Matrix> > (fineLevel, "A");
RCP<MultiVector> fineNullspace = Get< RCP<MultiVector> > (fineLevel, "Nullspace");
TEUCHOS_TEST_FOR_EXCEPTION(A->GetFixedBlockSize() != 1, Exceptions::RuntimeError, "Block size > 1 has not been implemented");
const Teuchos::ParameterList& pL = GetParameterList();
std::string mapFile = pL.get<std::string>("mapFileName");
RCP<const Map> rowMap = A->getRowMap();
RCP<const Map> coarseMap = Utils2::ReadMap(mapFile, rowMap->lib(), rowMap->getComm());
Set(coarseLevel, "CoarseMap", coarseMap);
std::string matrixFile = pL.get<std::string>("matrixFileName");
RCP<Matrix> P = Utils::Read(matrixFile, rowMap, coarseMap, coarseMap, rowMap);
#if 1
Set(coarseLevel, "P", P);
#else
// Expand column map by 1
RCP<Matrix> P1 = Utils::Multiply(*A, false, *P, false);
P = Utils::Read(matrixFile, rowMap, P1->getColMap(), coarseMap, rowMap);
Set(coarseLevel, "P", P);
#endif
RCP<MultiVector> coarseNullspace = MultiVectorFactory::Build(coarseMap, fineNullspace->getNumVectors());
P->apply(*fineNullspace, *coarseNullspace, Teuchos::TRANS, Teuchos::ScalarTraits<SC>::one(), Teuchos::ScalarTraits<SC>::zero());
Set(coarseLevel, "Nullspace", coarseNullspace);
// Coordinates transfer
size_t n = Teuchos::as<size_t>(sqrt(coarseMap->getGlobalNumElements()));
TEUCHOS_TEST_FOR_EXCEPTION(n*n != coarseMap->getGlobalNumElements(), Exceptions::RuntimeError, "Unfortunately, this is not the case, don't know what to do");
RCP<MultiVector> coarseCoords = MultiVectorFactory::Build(coarseMap, 2);
ArrayRCP<Scalar> x = coarseCoords->getDataNonConst(0), y = coarseCoords->getDataNonConst(1);
for (size_t LID = 0; LID < coarseMap->getNodeNumElements(); ++LID) {
GlobalOrdinal GID = coarseMap->getGlobalElement(LID) - coarseMap->getIndexBase();
GlobalOrdinal i = GID % n, j = GID/n;
x[LID] = i;
y[LID] = j;
}
Set(coarseLevel, "Coordinates", coarseCoords);
if (IsPrint(Statistics1)) {
RCP<ParameterList> params = rcp(new ParameterList());
params->set("printLoadBalancingInfo", true);
GetOStream(Statistics1) << PerfUtils::PrintMatrixInfo(*P, "P", params);
}
}
void RebalanceAcFactory<Scalar, LocalOrdinal, GlobalOrdinal, Node, LocalMatOps>::Build(Level &fineLevel, Level &coarseLevel) const {
FactoryMonitor m(*this, "Computing Ac", coarseLevel);
RCP<Matrix> originalAc = Get< RCP<Matrix> >(coarseLevel, "A");
RCP<const Import> rebalanceImporter = Get< RCP<const Import> >(coarseLevel, "Importer");
if (rebalanceImporter != Teuchos::null) {
RCP<Matrix> rebalancedAc;
{
SubFactoryMonitor subM(*this, "Rebalancing existing Ac", coarseLevel);
RCP<const Map> targetMap = rebalanceImporter->getTargetMap();
const ParameterList & pL = GetParameterList();
ParameterList XpetraList;
if (pL.get<bool>("useSubcomm") == true) {
GetOStream(Runtime0,0) << "Replacing maps with a subcommunicator" << std::endl;
XpetraList.set("Restrict Communicator",true);
}
// NOTE: If the communicator is restricted away, Build returns Teuchos::null.
rebalancedAc = MatrixFactory::Build(originalAc, *rebalanceImporter, targetMap, targetMap, rcp(&XpetraList,false));
if (!rebalancedAc.is_null())
rebalancedAc->SetFixedBlockSize(originalAc->GetFixedBlockSize());
Set(coarseLevel, "A", rebalancedAc);
}
if (!rebalancedAc.is_null()) {
RCP<ParameterList> params = rcp(new ParameterList());
params->set("printLoadBalancingInfo", true);
GetOStream(Statistics0, 0) << Utils::PrintMatrixInfo(*rebalancedAc, "Ac (rebalanced)", params);
}
} else {
// Ac already built by the load balancing process and no load balancing needed
GetOStream(Warnings0, 0) << "No rebalancing" << std::endl;
GetOStream(Warnings0, 0) << "Jamming A into Level " << coarseLevel.GetLevelID() << " w/ generating factory "
<< this << std::endl;
Set(coarseLevel, "A", originalAc);
}
} //Build()
void FilteredAFactory<Scalar, LocalOrdinal, GlobalOrdinal, Node, LocalMatOps>::Build(Level& currentLevel) const {
FactoryMonitor m(*this, "Matrix filtering", currentLevel);
RCP<Matrix> A = Get< RCP<Matrix> >(currentLevel, "A");
if (currentLevel.Get<bool>("Filtering", currentLevel.GetFactoryManager()->GetFactory("Filtering").get()) == false) {
GetOStream(Runtime0) << "Filtered matrix is not being constructed as no filtering is being done" << std::endl;
Set(currentLevel, "A", A);
return;
}
size_t blkSize = A->GetFixedBlockSize();
const ParameterList& pL = GetParameterList();
bool lumping = pL.get<bool>("lumping");
if (lumping)
GetOStream(Runtime0) << "Lumping dropped entries" << std::endl;
RCP<GraphBase> G = Get< RCP<GraphBase> >(currentLevel, "Graph");
SC zero = Teuchos::ScalarTraits<SC>::zero();
// Both Epetra and Tpetra matrix-matrix multiply use the following trick:
// if an entry of the left matrix is zero, it does not compute or store the
// zero value.
//
// This trick allows us to bypass constructing a new matrix. Instead, we
// make a deep copy of the original one, and fill it in with zeros, which
// are ignored during the prolongator smoothing.
RCP<Matrix> filteredA = MatrixFactory::Build(A->getCrsGraph());
filteredA->resumeFill();
ArrayView<const LO> inds;
ArrayView<const SC> valsA;
#ifdef ASSUME_DIRECT_ACCESS_TO_ROW
ArrayView<SC> vals;
#else
Array<SC> vals;
#endif
Array<char> filter(blkSize * G->GetImportMap()->getNodeNumElements(), 0);
size_t numGRows = G->GetNodeNumVertices();
for (size_t i = 0; i < numGRows; i++) {
// Set up filtering array
ArrayView<const LO> indsG = G->getNeighborVertices(i);
for (size_t j = 0; j < as<size_t>(indsG.size()); j++)
for (size_t k = 0; k < blkSize; k++)
filter[indsG[j]*blkSize+k] = 1;
for (size_t k = 0; k < blkSize; k++) {
LO row = i*blkSize + k;
A->getLocalRowView(row, inds, valsA);
size_t nnz = inds.size();
if (nnz == 0)
continue;
#ifdef ASSUME_DIRECT_ACCESS_TO_ROW
// Transform ArrayView<const SC> into ArrayView<SC>
ArrayView<const SC> vals1;
filteredA->getLocalRowView(row, inds, vals1);
vals = ArrayView<SC>(const_cast<SC*>(vals1.getRawPtr()), nnz);
memcpy(vals.getRawPtr(), valsA.getRawPtr(), nnz*sizeof(SC));
#else
vals = Array<SC>(valsA);
#endif
if (lumping == false) {
for (size_t j = 0; j < nnz; j++)
if (!filter[inds[j]])
vals[j] = zero;
} else {
LO diagIndex = -1;
SC diagExtra = zero;
for (size_t j = 0; j < nnz; j++) {
if (filter[inds[j]])
continue;
if (inds[j] == row) {
// Remember diagonal position
diagIndex = j;
} else {
diagExtra += vals[j];
}
vals[j] = zero;
}
// Lump dropped entries
// NOTE
// * Does it make sense to lump for elasticity?
// * Is it different for diffusion and elasticity?
if (diagIndex != -1)
vals[diagIndex] += diagExtra;
}
#ifndef ASSUME_DIRECT_ACCESS_TO_ROW
// Because we used a column map in the construction of the matrix
// we can just use insertLocalValues here instead of insertGlobalValues
filteredA->replaceLocalValues(row, inds, vals);
#endif
}
// Reset filtering array
for (size_t j = 0; j < as<size_t> (indsG.size()); j++)
for (size_t k = 0; k < blkSize; k++)
filter[indsG[j]*blkSize+k] = 0;
}
RCP<ParameterList> fillCompleteParams(new ParameterList);
fillCompleteParams->set("No Nonlocal Changes", true);
filteredA->fillComplete(fillCompleteParams);
filteredA->SetFixedBlockSize(blkSize);
if (pL.get<bool>("filtered matrix: reuse eigenvalue")) {
// Reuse max eigenvalue from A
// It is unclear what eigenvalue is the best for the smoothing, but we already may have
// the D^{-1}A estimate in A, may as well use it.
// NOTE: ML does that too
filteredA->SetMaxEigenvalueEstimate(A->GetMaxEigenvalueEstimate());
}
Set(currentLevel, "A", filteredA);
}
int main(int argc, char *argv[]) {
#include <MueLu_UseShortNames.hpp>
using Teuchos::RCP; // reference count pointers
using Teuchos::rcp;
using Teuchos::TimeMonitor;
// =========================================================================
// MPI initialization using Teuchos
// =========================================================================
Teuchos::GlobalMPISession mpiSession(&argc, &argv, NULL);
bool success = false;
bool verbose = true;
try {
RCP< const Teuchos::Comm<int> > comm = Teuchos::DefaultComm<int>::getComm();
// =========================================================================
// Convenient definitions
// =========================================================================
SC zero = Teuchos::ScalarTraits<SC>::zero(), one = Teuchos::ScalarTraits<SC>::one();
// Instead of checking each time for rank, create a rank 0 stream
RCP<Teuchos::FancyOStream> fancy = Teuchos::fancyOStream(Teuchos::rcpFromRef(std::cout));
Teuchos::FancyOStream& fancyout = *fancy;
fancyout.setOutputToRootOnly(0);
// =========================================================================
// Parameters initialization
// =========================================================================
Teuchos::CommandLineProcessor clp(false);
//GO nx = 100, ny = 100, nz = 100;
//Galeri::Xpetra::Parameters<GO> matrixParameters(clp, nx, ny, nz, "Laplace2D"); // manage parameters of the test case
Xpetra::Parameters xpetraParameters(clp); // manage parameters of Xpetra
std::string xmlFileName = "driver.xml"; clp.setOption("xml", &xmlFileName, "read parameters from a file. Otherwise, this example uses by default 'scalingTest.xml'");
int amgAsPrecond = 1; clp.setOption("precond", &amgAsPrecond, "apply multigrid as preconditioner");
int amgAsSolver = 0; clp.setOption("fixPoint", &amgAsSolver, "apply multigrid as solver");
bool printTimings = true; clp.setOption("timings", "notimings", &printTimings, "print timings to screen");
int writeMatricesOPT = -2; clp.setOption("write", &writeMatricesOPT, "write matrices to file (-1 means all; i>=0 means level i)");
double tol = 1e-6; clp.setOption("tol", &tol, "solver convergence tolerance");
std::string krylovMethod = "gmres"; clp.setOption("krylov", &krylovMethod, "outer Krylov method");
int maxIts = 100; clp.setOption("maxits", &maxIts, "maximum number of Krylov iterations");
int output = 1; clp.setOption("output", &output, "how often to print Krylov residual history");
std::string matrixFileName = "crada1/crada_A.mm"; clp.setOption("matrixfile", &matrixFileName, "matrix market file containing matrix");
std::string rhsFileName = "crada1/crada_b.mm"; clp.setOption("rhsfile", &rhsFileName, "matrix market file containing right-hand side");
std::string nspFileName = "crada1/crada_ns.mm"; clp.setOption("nspfile", &nspFileName, "matrix market file containing fine level null space");
std::string cooFileName = "crada1/crada_coordinates.mm"; clp.setOption("coordinatesfile",&cooFileName, "matrix market file containing fine level coordinates");
std::string spcFileName = "crada1/crada_special.mm"; clp.setOption("specialfile", &spcFileName, "matrix market file containing fine level special dofs");
int nPDE = 3; clp.setOption("numpdes", &nPDE, "number of PDE equations");
int nNspVectors = 3; clp.setOption("numnsp", &nNspVectors, "number of nullspace vectors. Only used if null space is read from file. Must be smaller or equal than the number of null space vectors read in from file.");
std::string convType = "r0"; clp.setOption("convtype", &convType, "convergence type (r0 or none)");
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;
}
// =========================================================================
// Problem construction
// =========================================================================
RCP<TimeMonitor> globalTimeMonitor = rcp(new TimeMonitor(*TimeMonitor::getNewTimer("MatrixRead: S - Global Time"))), tm;
comm->barrier();
tm = rcp(new TimeMonitor(*TimeMonitor::getNewTimer("Driver: 1 - Matrix Build")));
RCP<Matrix> A = Teuchos::null;
if (matrixFileName != "") {
fancyout << "Read matrix from file " << matrixFileName << std::endl;
A = Xpetra::IO<SC,LO,GO,Node>::Read(std::string(matrixFileName), xpetraParameters.GetLib(), comm);
}
RCP<const Map> map = A->getRowMap();
RCP<MultiVector> nullspace = MultiVectorFactory::Build(A->getDomainMap(),nPDE);
A->SetFixedBlockSize(nPDE);
fancyout << "#pdes = " << A->GetFixedBlockSize() << std::endl;
if (nspFileName != "") {
fancyout << "Read null space from file " << nspFileName << std::endl;
nullspace = Xpetra::IO<SC,LO,GO,Node>::ReadMultiVector(std::string(nspFileName), A->getRowMap());
fancyout << "Found " << nullspace->getNumVectors() << " null space vectors" << std::endl;
if (nNspVectors > Teuchos::as<int>(nullspace->getNumVectors())) {
fancyout << "Set number of null space vectors from " << nNspVectors << " to " << nullspace->getNumVectors() << " as only " << nullspace->getNumVectors() << " are provided by " << nspFileName << std::endl;
nNspVectors = nullspace->getNumVectors();
}
if (nNspVectors < 1) {
fancyout << "Set number of null space vectors from " << nNspVectors << " to " << nullspace->getNumVectors() << ". Note: we need at least one null space vector!!!" << std::endl;
nNspVectors = nullspace->getNumVectors();
}
if (nNspVectors < Teuchos::as<int>(nullspace->getNumVectors())) {
RCP<MultiVector> temp = MultiVectorFactory::Build(A->getDomainMap(),nNspVectors);
for(int j=0; j<nNspVectors; j++) {
Teuchos::ArrayRCP<SC> tempData = temp->getDataNonConst(j);
Teuchos::ArrayRCP<const SC> nsData = nullspace->getData(j);
for (int i=0; i<nsData.size(); ++i) {
tempData[i] = nsData[i];
}
}
nullspace = Teuchos::null;
nullspace = temp;
}
} else {
if (nPDE == 1)
nullspace->putScalar( Teuchos::ScalarTraits<SC>::one() );
else {
for (int i=0; i<nPDE; ++i) {
Teuchos::ArrayRCP<SC> nsData = nullspace->getDataNonConst(i);
for (int j=0; j<nsData.size(); ++j) {
GO gel = A->getDomainMap()->getGlobalElement(j) - A->getDomainMap()->getIndexBase();
if ((gel-i) % nPDE == 0)
nsData[j] = Teuchos::ScalarTraits<SC>::one();
}
}
}
}
RCP<MultiVector> coordinates = Teuchos::null; //MultiVectorFactory::Build(A->getDomainMap(),1);
if (cooFileName != "") {
std::vector<GO> myGIDs (map->getNodeNumElements() / A->GetFixedBlockSize());
// reconstruct map for coordinates
for(LO r = 0; r < Teuchos::as<LO>(map->getNodeNumElements() / A->GetFixedBlockSize()); ++r) {
GO gid = map->getGlobalElement(r * A->GetFixedBlockSize());
myGIDs[r] = gid;
}
GO gCntGIDs = 0;
GO glCntGIDs = Teuchos::as<GlobalOrdinal>(myGIDs.size());
MueLu_sumAll(comm,glCntGIDs,gCntGIDs);
Teuchos::Array<GlobalOrdinal> eltList(myGIDs);
RCP<const Map> myCoordMap = MapFactory::Build (xpetraParameters.GetLib(),gCntGIDs,eltList(),0,comm);
fancyout << "Read fine level coordinates from file " << cooFileName << std::endl;
coordinates = Xpetra::IO<SC,LO,GO,Node>::ReadMultiVector(std::string(cooFileName), myCoordMap);
fancyout << "Found " << nullspace->getNumVectors() << " null space vectors of length " << myCoordMap->getGlobalNumElements() << std::endl;
}
RCP<Map> mySpecialMap = Teuchos::null;
if (spcFileName != "") {
// read file on each processor and pick out the special dof numbers which belong to the current proc
std::ifstream infile(spcFileName);
std::string line;
std::vector<GlobalOrdinal> mySpecialGids;
GlobalOrdinal cnt = 0; // count overall number of gids
GlobalOrdinal mycnt = 0; // count only local gids
while ( std::getline(infile, line)) {
if(0 == line.find("%")) continue;
if(0 == line.find(" ")) {
cnt++;
GlobalOrdinal gid;
std::istringstream iss(line);
iss >> gid;
gid--; // note, that the matlab vector starts counting at 1 and not 0!
if(map->isNodeGlobalElement(gid)) {
mySpecialGids.push_back(gid);
mycnt++;
}
}
}
Teuchos::Array<GlobalOrdinal> eltList(mySpecialGids);
mySpecialMap = MapFactory::Build (xpetraParameters.GetLib(),cnt,eltList(),0,comm);
// empty processors
std::vector<size_t> lelePerProc(comm->getSize(),0);
std::vector<size_t> gelePerProc(comm->getSize(),0);
lelePerProc[comm->getRank()] = mySpecialMap->getNodeNumElements();
Teuchos::reduceAll(*comm,Teuchos::REDUCE_MAX,comm->getSize(),&lelePerProc[0],&gelePerProc[0]);
if(comm->getRank() == 0) {
fancyout << "Distribution of " << cnt << " special dofs over processors:" << std::endl;
fancyout << "Proc #DOFs" << std::endl;
for(int i=0; i<comm->getSize(); i++) {
fancyout << i << " " << gelePerProc[i] << std::endl;
}
}
}
int main(int argc, char *argv[]) {
#include <MueLu_UseShortNames.hpp>
using Teuchos::RCP; // reference count pointers
using Teuchos::rcp;
using Teuchos::TimeMonitor;
// =========================================================================
// MPI initialization using Teuchos
// =========================================================================
Teuchos::GlobalMPISession mpiSession(&argc, &argv, NULL);
RCP< const Teuchos::Comm<int> > comm = Teuchos::DefaultComm<int>::getComm();
// =========================================================================
// Convenient definitions
// =========================================================================
SC zero = Teuchos::ScalarTraits<SC>::zero(), one = Teuchos::ScalarTraits<SC>::one();
// Instead of checking each time for rank, create a rank 0 stream
RCP<Teuchos::FancyOStream> fancy = Teuchos::fancyOStream(Teuchos::rcpFromRef(std::cout));
Teuchos::FancyOStream& fancyout = *fancy;
fancyout.setOutputToRootOnly(0);
// =========================================================================
// Parameters initialization
// =========================================================================
Teuchos::CommandLineProcessor clp(false);
GO nx = 100, ny = 100, nz = 100;
Galeri::Xpetra::Parameters<GO> matrixParameters(clp, nx, ny, nz, "Laplace2D"); // manage parameters of the test case
Xpetra::Parameters xpetraParameters(clp); // manage parameters of Xpetra
std::string xmlFileName = "scalingTest.xml"; clp.setOption("xml", &xmlFileName, "read parameters from a file. Otherwise, this example uses by default 'scalingTest.xml'");
int amgAsPrecond = 1; clp.setOption("precond", &amgAsPrecond, "apply multigrid as preconditioner");
int amgAsSolver = 0; clp.setOption("fixPoint", &amgAsSolver, "apply multigrid as solver");
bool printTimings = true; clp.setOption("timings", "notimings", &printTimings, "print timings to screen");
int writeMatricesOPT = -2; clp.setOption("write", &writeMatricesOPT, "write matrices to file (-1 means all; i>=0 means level i)");
double tol = 1e-12; clp.setOption("tol", &tol, "solver convergence tolerance");
std::string krylovMethod = "cg"; clp.setOption("krylov", &krylovMethod, "outer Krylov method");
int maxIts = 100; clp.setOption("maxits", &maxIts, "maximum number of Krylov iterations");
int output = 1; clp.setOption("output", &output, "how often to print Krylov residual history");
std::string matrixFileName = "A.mm"; clp.setOption("matrixfile", &matrixFileName, "matrix market file containing matrix");
std::string rhsFileName = ""; clp.setOption("rhsfile", &rhsFileName, "matrix market file containing right-hand side");
int nPDE = 1; clp.setOption("numpdes", &nPDE, "number of PDE equations");
std::string convType = "r0"; clp.setOption("convtype", &convType, "convergence type (r0 or none)");
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;
}
fancyout << "========================================================\n" << xpetraParameters << matrixParameters;
// =========================================================================
// Problem construction
// =========================================================================
RCP<TimeMonitor> globalTimeMonitor = rcp(new TimeMonitor(*TimeMonitor::getNewTimer("MatrixRead: S - Global Time"))), tm;
comm->barrier();
tm = rcp(new TimeMonitor(*TimeMonitor::getNewTimer("ScalingTest: 1 - Matrix Build")));
RCP<Matrix> A = Utils::Read(string(matrixFileName), xpetraParameters.GetLib(), comm);
RCP<const Map> map = A->getRowMap();
RCP<MultiVector> nullspace = MultiVectorFactory::Build(A->getDomainMap(),nPDE);
//RCP<MultiVector> fakeCoordinates = MultiVectorFactory::Build(A->getDomainMap(),1);
A->SetFixedBlockSize(nPDE);
std::cout << "#pdes = " << A->GetFixedBlockSize() << std::endl;
if (nPDE == 1)
nullspace->putScalar( Teuchos::ScalarTraits<SC>::one() );
else {
for (int i=0; i<nPDE; ++i) {
Teuchos::ArrayRCP<SC> nsData = nullspace->getDataNonConst(i);
for (int j=0; j<nsData.size(); ++j) {
GO gel = A->getDomainMap()->getGlobalElement(j) - A->getDomainMap()->getIndexBase();
if ((gel-i) % nPDE == 0)
nsData[j] = Teuchos::ScalarTraits<SC>::one();
}
}
}
comm->barrier();
tm = Teuchos::null;
fancyout << "Galeri complete.\n========================================================" << std::endl;
// =========================================================================
// Preconditioner construction
// =========================================================================
comm->barrier();
tm = rcp(new TimeMonitor(*TimeMonitor::getNewTimer("ScalingTest: 1.5 - MueLu read XML")));
ParameterListInterpreter mueLuFactory(xmlFileName, *comm);
comm->barrier();
tm = rcp(new TimeMonitor(*TimeMonitor::getNewTimer("ScalingTest: 2 - MueLu Setup")));
RCP<Hierarchy> H = mueLuFactory.CreateHierarchy();
// By default, we use Extreme. However, typically the xml file contains verbosity parameter
// which is used instead
H->SetDefaultVerbLevel(MueLu::Extreme);
H->GetLevel(0)->Set("A", A);
H->GetLevel(0)->Set("Nullspace", nullspace);
//H->GetLevel(0)->Set("Coordinates", fakeCoordinates);
mueLuFactory.SetupHierarchy(*H);
comm->barrier();
tm = Teuchos::null;
// Print out the hierarchy stats. We should not need this line, but for some reason the
// print out in the hierarchy construction does not work.
H->print(fancyout);
// =========================================================================
// System solution (Ax = b)
// =========================================================================
comm->barrier();
tm = rcp (new TimeMonitor(*TimeMonitor::getNewTimer("ScalingTest: 3 - LHS and RHS initialization")));
RCP<Vector> X = VectorFactory::Build(map,1);
RCP<MultiVector> B = VectorFactory::Build(map,1);
if (rhsFileName != "")
B = Utils2::ReadMultiVector(string(rhsFileName), A->getRowMap());
else
{
// we set seed for reproducibility
X->setSeed(846930886);
bool useSameRandomGen = false;
X->randomize(useSameRandomGen);
A->apply(*X, *B, Teuchos::NO_TRANS, one, zero);
Teuchos::Array<Teuchos::ScalarTraits<SC>::magnitudeType> norms(1);
B->norm2(norms);
//B->scale(1.0/norms[0]);
}
X->putScalar(zero);
tm = Teuchos::null;
if (writeMatricesOPT > -2)
H->Write(writeMatricesOPT, writeMatricesOPT);
comm->barrier();
if (amgAsSolver) {
tm = rcp (new TimeMonitor(*TimeMonitor::getNewTimer("ScalingTest: 4 - Fixed Point Solve")));
H->IsPreconditioner(false);
Teuchos::Array<Teuchos::ScalarTraits<SC>::magnitudeType> norms(1);
norms = Utils::ResidualNorm(*A,*X,*B);
std::cout << " iter: 0 residual = " << norms[0] << std::endl;
for (int i=0; i< maxIts; ++i) {
H->Iterate(*B, *X);
norms = Utils::ResidualNorm(*A,*X,*B);
std::cout << " iter: " << i+1 << " residual = " << norms[0] << std::endl;
}
} else if (amgAsPrecond) {
#ifdef HAVE_MUELU_BELOS
tm = rcp(new TimeMonitor(*TimeMonitor::getNewTimer("ScalingTest: 5 - Belos Solve")));
// Operator and Multivector type that will be used with Belos
typedef MultiVector MV;
typedef Belos::OperatorT<MV> OP;
H->IsPreconditioner(true);
// Define Operator and Preconditioner
Teuchos::RCP<OP> belosOp = Teuchos::rcp(new Belos::XpetraOp<SC, LO, GO, NO, LMO>(A)); // Turns a Xpetra::Matrix object into a Belos operator
Teuchos::RCP<OP> belosPrec = Teuchos::rcp(new Belos::MueLuOp<SC, LO, GO, NO, LMO>(H)); // Turns a MueLu::Hierarchy object into a Belos operator
// Construct a Belos LinearProblem object
RCP< Belos::LinearProblem<SC, MV, OP> > belosProblem = rcp(new Belos::LinearProblem<SC, MV, OP>(belosOp, X, B));
belosProblem->setRightPrec(belosPrec);
bool set = belosProblem->setProblem();
if (set == false) {
fancyout << "\nERROR: Belos::LinearProblem failed to set up correctly!" << std::endl;
return EXIT_FAILURE;
}
// Belos parameter list
Teuchos::ParameterList belosList;
belosList.set("Maximum Iterations", maxIts); // Maximum number of iterations allowed
belosList.set("Convergence Tolerance", tol); // Relative convergence tolerance requested
belosList.set("Verbosity", Belos::Errors + Belos::Warnings + Belos::StatusTestDetails);
belosList.set("Output Frequency", output);
belosList.set("Output Style", Belos::Brief);
//belosList.set("Orthogonalization", "ICGS");
if (convType == "none") {
belosList.set("Explicit Residual Scaling", "None");
belosList.set("Implicit Residual Scaling", "None");
}
// Create an iterative solver manager
RCP< Belos::SolverManager<SC, MV, OP> > solver;
if (krylovMethod == "cg") {
solver = rcp(new Belos::BlockCGSolMgr<SC, MV, OP>(belosProblem, rcp(&belosList, false)));
} else if (krylovMethod == "gmres") {
solver = rcp(new Belos::BlockGmresSolMgr<SC, MV, OP>(belosProblem, rcp(&belosList, false)));
} else {
TEUCHOS_TEST_FOR_EXCEPTION(true, MueLu::Exceptions::RuntimeError, "Invalid Krylov method. Options are \"cg\" or \" gmres\".");
}
// Perform solve
Belos::ReturnType ret = Belos::Unconverged;
try {
ret = solver->solve();
// Get the number of iterations for this solve.
fancyout << "Number of iterations performed for this solve: " << solver->getNumIters() << std::endl;
} catch(...) {
fancyout << std::endl << "ERROR: Belos threw an error! " << std::endl;
}
// Check convergence
if (ret != Belos::Converged)
fancyout << std::endl << "ERROR: Belos did not converge! " << std::endl;
else
fancyout << std::endl << "SUCCESS: Belos converged!" << std::endl;
#endif //ifdef HAVE_MUELU_BELOS
}
comm->barrier();
tm = Teuchos::null;
globalTimeMonitor = Teuchos::null;
if (printTimings) {
TimeMonitor::summarize(A->getRowMap()->getComm().ptr(), std::cout, false, true, false, Teuchos::Union);
MueLu::MutuallyExclusiveTime<MueLu::BaseClass>::PrintParentChildPairs();
}
return 0;
} //main
void Zoltan2Interface<Scalar, LocalOrdinal, GlobalOrdinal, Node>::Build(Level& level) const {
FactoryMonitor m(*this, "Build", level);
RCP<Matrix> A = Get<RCP<Matrix> >(level, "A");
RCP<const Map> rowMap = A->getRowMap();
typedef Xpetra::MultiVector<double, LocalOrdinal, GlobalOrdinal, Node> dMultiVector;
RCP<dMultiVector> coords = Get<RCP<dMultiVector> >(level, "Coordinates");
RCP<const Map> map = coords->getMap();
GO numElements = map->getNodeNumElements();
LO blkSize = A->GetFixedBlockSize();
// Check that the number of local coordinates is consistent with the #rows in A
TEUCHOS_TEST_FOR_EXCEPTION(rowMap->getNodeNumElements()/blkSize != coords->getLocalLength(), Exceptions::Incompatible,
"Coordinate vector length (" + toString(coords->getLocalLength()) << " is incompatible with number of block rows in A ("
+ toString(rowMap->getNodeNumElements()/blkSize) + "The vector length should be the same as the number of mesh points.");
#ifdef HAVE_MUELU_DEBUG
GO indexBase = rowMap->getIndexBase();
GetOStream(Runtime0) << "Checking consistence of row and coordinates maps" << std::endl;
// Make sure that logical blocks in row map coincide with logical nodes in coordinates map
ArrayView<const GO> rowElements = rowMap->getNodeElementList();
ArrayView<const GO> coordsElements = map ->getNodeElementList();
for (LO i = 0; i < Teuchos::as<LO>(numElements); i++)
TEUCHOS_TEST_FOR_EXCEPTION((coordsElements[i]-indexBase)*blkSize + indexBase != rowElements[i*blkSize],
Exceptions::RuntimeError, "i = " << i << ", coords GID = " << coordsElements[i]
<< ", row GID = " << rowElements[i*blkSize] << ", blkSize = " << blkSize << std::endl);
#endif
int numParts = Get<int>(level, "number of partitions");
if (numParts == 1) {
// Single processor, decomposition is trivial: all zeros
RCP<Xpetra::Vector<GO,LO,GO,NO> > decomposition = Xpetra::VectorFactory<GO, LO, GO, NO>::Build(rowMap, true);
Set(level, "Partition", decomposition);
return;
} else if (numParts == -1) {
// No repartitioning
RCP<Xpetra::Vector<GO,LO,GO,NO> > decomposition = Teuchos::null; //Xpetra::VectorFactory<GO, LO, GO, NO>::Build(rowMap, true);
//decomposition->putScalar(Teuchos::as<Scalar>(rowMap->getComm()->getRank()));
Set(level, "Partition", decomposition);
return;
}
const ParameterList& pL = GetParameterList();
RCP<const ParameterList> providedList = pL.get<RCP<const ParameterList> >("ParameterList");
ParameterList Zoltan2Params;
if (providedList != Teuchos::null)
Zoltan2Params = *providedList;
// Merge defalt Zoltan2 parameters with user provided
// If default and user parameters contain the same parameter name, user one is always preferred
for (ParameterList::ConstIterator param = defaultZoltan2Params->begin(); param != defaultZoltan2Params->end(); param++) {
const std::string& pName = defaultZoltan2Params->name(param);
if (!Zoltan2Params.isParameter(pName))
Zoltan2Params.set(pName, defaultZoltan2Params->get<std::string>(pName));
}
Zoltan2Params.set("num_global_parts", Teuchos::as<int>(numParts));
GetOStream(Runtime0) << "Zoltan2 parameters:\n----------\n" << Zoltan2Params << "----------" << std::endl;
const std::string& algo = Zoltan2Params.get<std::string>("algorithm");
TEUCHOS_TEST_FOR_EXCEPTION(algo != "multijagged" && algo != "rcb", Exceptions::RuntimeError,
"Unknown partitioning algorithm: \"" << algo << "\"");
typedef Zoltan2::XpetraMultiVectorAdapter<dMultiVector> InputAdapterType;
typedef Zoltan2::PartitioningProblem<InputAdapterType> ProblemType;
int rowWeight = pL.get<int>("rowWeight");
GetOStream(Runtime0) << "Using weights formula: nnz + " << rowWeight << std::endl;
Array<double> weightsPerRow(numElements);
for (LO i = 0; i < numElements; i++) {
weightsPerRow[i] = 0.0;
for (LO j = 0; j < blkSize; j++) {
weightsPerRow[i] += A->getNumEntriesInLocalRow(i*blkSize+j);
// Zoltan2 pqJagged gets as good partitioning as Zoltan RCB in terms of nnz
// but Zoltan also gets a good partioning in rows, which sometimes does not
// happen for Zoltan2. So here is an attempt to get a better row partitioning
// without significantly screwing up nnz partitioning
// NOTE: no good heuristic here, the value was chosen almost randomly
weightsPerRow[i] += rowWeight;
}
}
std::vector<int> strides;
std::vector<const double*> weights(1, weightsPerRow.getRawPtr());
RCP<const Teuchos::MpiComm<int> > dupMpiComm = rcp_dynamic_cast<const Teuchos::MpiComm<int> >(rowMap->getComm()->duplicate());
RCP<const Teuchos::OpaqueWrapper<MPI_Comm> > zoltanComm = dupMpiComm->getRawMpiComm();
InputAdapterType adapter(coords, weights, strides);
RCP<ProblemType> problem(new ProblemType(&adapter, &Zoltan2Params, (*zoltanComm)()));
{
SubFactoryMonitor m1(*this, "Zoltan2 " + toString(algo), level);
problem->solve();
}
RCP<Xpetra::Vector<GO,LO,GO,NO> > decomposition = Xpetra::VectorFactory<GO,LO,GO,NO>::Build(rowMap, false);
ArrayRCP<GO> decompEntries = decomposition->getDataNonConst(0);
const typename InputAdapterType::part_t * parts = problem->getSolution().getPartListView();
for (GO i = 0; i < numElements; i++) {
int partNum = parts[i];
for (LO j = 0; j < blkSize; j++)
decompEntries[i*blkSize + j] = partNum;
}
Set(level, "Partition", decomposition);
}
void ZoltanInterface<LocalOrdinal, GlobalOrdinal, Node, LocalMatOps>::Build(Level& level) const {
FactoryMonitor m(*this, "Build", level);
RCP<Matrix> A = Get< RCP<Matrix> > (level, "A");
RCP<const Map> rowMap = A->getRowMap();
RCP<MultiVector> Coords = Get< RCP<MultiVector> >(level, "Coordinates");
size_t dim = Coords->getNumVectors();
GO numParts = level.Get<GO>("number of partitions");
if (numParts == 1) {
// Running on one processor, so decomposition is the trivial one, all zeros.
RCP<Xpetra::Vector<GO, LO, GO, NO> > decomposition = Xpetra::VectorFactory<GO, LO, GO, NO>::Build(rowMap, true);
Set(level, "Partition", decomposition);
return;
}
float zoltanVersion_;
Zoltan_Initialize(0, NULL, &zoltanVersion_);
RCP<const Teuchos::MpiComm<int> > dupMpiComm = rcp_dynamic_cast<const Teuchos::MpiComm<int> >(rowMap->getComm()->duplicate());
RCP<const Teuchos::OpaqueWrapper<MPI_Comm> > zoltanComm = dupMpiComm->getRawMpiComm();
RCP<Zoltan> zoltanObj_ = rcp(new Zoltan((*zoltanComm)())); //extract the underlying MPI_Comm handle and create a Zoltan object
if (zoltanObj_ == Teuchos::null)
throw Exceptions::RuntimeError("MueLu::Zoltan : Unable to create Zoltan data structure");
// Tell Zoltan what kind of local/global IDs we will use.
// In our case, each GID is two ints and there are no local ids.
// One can skip this step if the IDs are just single ints.
int rv;
if ((rv = zoltanObj_->Set_Param("num_gid_entries", "1")) != ZOLTAN_OK)
throw Exceptions::RuntimeError("MueLu::Zoltan::Setup : setting parameter 'num_gid_entries' returned error code " + Teuchos::toString(rv));
if ((rv = zoltanObj_->Set_Param("num_lid_entries", "0") ) != ZOLTAN_OK)
throw Exceptions::RuntimeError("MueLu::Zoltan::Setup : setting parameter 'num_lid_entries' returned error code " + Teuchos::toString(rv));
if ((rv = zoltanObj_->Set_Param("obj_weight_dim", "1") ) != ZOLTAN_OK)
throw Exceptions::RuntimeError("MueLu::Zoltan::Setup : setting parameter 'obj_weight_dim' returned error code " + Teuchos::toString(rv));
if (GetVerbLevel() & Statistics1) zoltanObj_->Set_Param("debug_level", "1");
else zoltanObj_->Set_Param("debug_level", "0");
zoltanObj_->Set_Param("num_global_partitions", toString(numParts));
zoltanObj_->Set_Num_Obj_Fn(GetLocalNumberOfRows, (void *) &*A);
zoltanObj_->Set_Obj_List_Fn(GetLocalNumberOfNonzeros, (void *) &*A);
zoltanObj_->Set_Num_Geom_Fn(GetProblemDimension, (void *) &dim);
zoltanObj_->Set_Geom_Multi_Fn(GetProblemGeometry, (void *) Coords.get());
// Data pointers that Zoltan requires.
ZOLTAN_ID_PTR import_gids = NULL; // Global nums of objs to be imported
ZOLTAN_ID_PTR import_lids = NULL; // Local indices to objs to be imported
int *import_procs = NULL; // Proc IDs of procs owning objs to be imported.
int *import_to_part = NULL; // Partition #s to which imported objs should be assigned.
ZOLTAN_ID_PTR export_gids = NULL; // Global nums of objs to be exported
ZOLTAN_ID_PTR export_lids = NULL; // local indices to objs to be exported
int *export_procs = NULL; // Proc IDs of destination procs for objs to be exported.
int *export_to_part = NULL; // Partition #s for objs to be exported.
int num_imported; // Number of objs to be imported.
int num_exported; // Number of objs to be exported.
int newDecomp; // Flag indicating whether the decomposition has changed
int num_gid_entries; // Number of array entries in a global ID.
int num_lid_entries;
{
SubFactoryMonitor m1(*this, "Zoltan RCB", level);
rv = zoltanObj_->LB_Partition(newDecomp, num_gid_entries, num_lid_entries,
num_imported, import_gids, import_lids, import_procs, import_to_part,
num_exported, export_gids, export_lids, export_procs, export_to_part);
if (rv == ZOLTAN_FATAL)
throw Exceptions::RuntimeError("Zoltan::LB_Partition() returned error code");
}
// TODO check that A's row map is 1-1. Zoltan requires this.
RCP<Xpetra::Vector<GO, LO, GO, NO> > decomposition;
if (newDecomp) {
decomposition = Xpetra::VectorFactory<GO, LO, GO, NO>::Build(rowMap, false); // Don't initialize, will be overwritten
ArrayRCP<GO> decompEntries = decomposition->getDataNonConst(0);
int mypid = rowMap->getComm()->getRank();
for (typename ArrayRCP<GO>::iterator i = decompEntries.begin(); i != decompEntries.end(); ++i)
*i = mypid;
LO blockSize = A->GetFixedBlockSize();
for (int i = 0; i < num_exported; ++i) {
// We have assigned Zoltan gids to first row GID in the block
// NOTE: Zoltan GIDs are different from GIDs in the Coordinates vector
LO localEl = rowMap->getLocalElement(export_gids[i]);
int partNum = export_to_part[i];
for (LO j = 0; j < blockSize; ++j)
decompEntries[localEl + j] = partNum;
}
}
Set(level, "Partition", decomposition);
zoltanObj_->LB_Free_Part(&import_gids, &import_lids, &import_procs, &import_to_part);
zoltanObj_->LB_Free_Part(&export_gids, &export_lids, &export_procs, &export_to_part);
} //Build()
TEUCHOS_UNIT_TEST(Zoltan, Build3PDEs)
{
typedef Teuchos::ScalarTraits<Scalar> ST;
out << "version: " << MueLu::Version() << std::endl;
out << std::endl;
out << "This tests that the partitioning produced by Zoltan is \"reasonable\" for a matrix" << std::endl;
out << "that has a random number of nonzeros per row and 3 DOFs per mesh point. Good results have been precomputed" << std::endl;
out << "for up to 5 processors. The results are the number of nonzeros in the local matrix" << std::endl;
out << "once the Zoltan repartitioning has been applied." << std::endl;
out << "The results can be viewed in Paraview by enabling code guarded by the macro MUELU_VISUALIZE_REPARTITIONING" << std::endl;
RCP<const Teuchos::Comm<int> > comm = TestHelpers::Parameters::getDefaultComm();
if (comm->getSize() > 5) {
out << std::endl;
out << "This test must be run on 1 to 5 processes." << std::endl;
TEST_EQUALITY(true, true);
return;
}
Level level;
RCP<FactoryManagerBase> factoryHandler = rcp(new FactoryManager());
level.SetFactoryManager(factoryHandler);
int nx=9;
int ny=nx;
int dofsPerNode = 3;
GO numGlobalElements = nx*ny*dofsPerNode;
size_t maxEntriesPerRow=30;
RCP<const Map> map;
int numMyNodes = numGlobalElements / dofsPerNode;
if (comm->getSize() > 1) {
// In parallel, make sure that the dof's associated with a node all
// reside on the same processor.
int numNodes = numGlobalElements / dofsPerNode;
TEUCHOS_TEST_FOR_EXCEPTION( (numGlobalElements - numNodes * dofsPerNode) != 0, MueLu::Exceptions::RuntimeError,
"Number of matrix rows is not divisible by #dofs" );
int nproc = comm->getSize();
if (comm->getRank() < nproc-1) numMyNodes = numNodes / nproc;
else numMyNodes = numNodes - (numNodes/nproc) * (nproc-1);
map = MapFactory::createContigMap(TestHelpers::Parameters::getLib(), numGlobalElements, numMyNodes*dofsPerNode, comm);
} else {
map = MapFactory::createUniformContigMap(TestHelpers::Parameters::getLib(), numGlobalElements, comm);
}
const size_t numMyElements = map->getNodeNumElements();
Teuchos::ArrayView<const GlobalOrdinal> myGlobalElements = map->getNodeElementList();
RCP<Matrix> A = rcp(new CrsMatrixWrap(map, 1)); // Force underlying linear algebra library to allocate more
// memory on the fly. While not super efficient, this
// ensures that no zeros are being stored. Thus, from
// Zoltan's perspective the matrix is imbalanced.
// Populate CrsMatrix with random number of entries (up to maxEntriesPerRow) per row.
// Create a vector with random integer entries in [1,maxEntriesPerRow].
ST::seedrandom(666*comm->getRank());
RCP<Xpetra::Vector<LO,LO,GO,NO> > entriesPerRow = Xpetra::VectorFactory<LO,LO,GO,NO>::Build(map,false);
Teuchos::ArrayRCP<LO> eprData = entriesPerRow->getDataNonConst(0);
for (Teuchos::ArrayRCP<LO>::iterator i=eprData.begin(); i!=eprData.end(); ++i) {
*i = (LO)(std::floor(((ST::random()+1)*0.5*maxEntriesPerRow)+1));
}
RCP<Teuchos::FancyOStream> fos = Teuchos::fancyOStream(Teuchos::rcpFromRef(std::cout));
fos->setOutputToRootOnly(-1);
Teuchos::Array<Scalar> vals(maxEntriesPerRow);
Teuchos::Array<GO> cols(maxEntriesPerRow);
for (size_t i = 0; i < numMyElements; ++i) {
Teuchos::ArrayView<SC> av(&vals[0],eprData[i]);
Teuchos::ArrayView<GO> iv(&cols[0],eprData[i]);
//stick in ones for values
for (LO j=0; j< eprData[i]; ++j) vals[j] = ST::one();
//figure out valid column indices
GO start = std::max(myGlobalElements[i]-eprData[i]+1,0);
for (LO j=0; j< eprData[i]; ++j) cols[j] = start+j;
A->insertGlobalValues(myGlobalElements[i], iv, av);
}
A->fillComplete();
// Now treat the matrix as if it has 3 DOFs per node.
A->SetFixedBlockSize(dofsPerNode);
level.Set("A",A);
//build coordinates
Teuchos::ParameterList list;
list.set("nx",nx);
list.set("ny",ny);
RCP<const Map> coalescedMap = MapFactory::createContigMap(TestHelpers::Parameters::getLib(), numGlobalElements/dofsPerNode, numMyNodes, comm);
RCP<MultiVector> XYZ = Galeri::Xpetra::Utils::CreateCartesianCoordinates<SC,LO,GO,Map,MultiVector>("2D",coalescedMap,list);
// XYZ are the "coalesce" coordinates as it has been generated for 1 DOF/node and we are using them for 3 DOFS/node
// level.Set("Coordinates",XYZ); "Coordinates" == uncoalesce. "X,Y,ZCoordinates" == coalesce
{
RCP<MultiVector> coordinates = XYZ;
// making a copy because I don't want to keep 'open' the Xpetra_MultiVector
if (coordinates->getNumVectors() >= 1) {
Teuchos::ArrayRCP<const SC> coord = coordinates->getData(0);
Teuchos::ArrayRCP<SC> coordCpy(coord.size());
for(int i=0; i<coord.size(); i++) {
coordCpy[i] = coord[i];
}
level.Set("XCoordinates", coordCpy);
//std::cout << coordCpy << std::endl;
}
if (coordinates->getNumVectors() >= 2) {
Teuchos::ArrayRCP<const SC> coord = coordinates->getData(1);
Teuchos::ArrayRCP<SC> coordCpy(coord.size());
for(int i=0; i<coord.size(); i++) {
coordCpy[i] = coord[i];
}
level.Set("YCoordinates", coordCpy);
}
/*if (coordinates->getNumVectors() >= 3) {
Teuchos::ArrayRCP<const SC> coord = coordinates->getData(2);
Teuchos::ArrayRCP<SC> coordCpy(coord.size());
for(int i=0; i<coord.size(); i++) {
coordCpy[i] = coord[i];
}
level.Set("ZCoordinates", coordCpy);
}*/
}
//coalescedMap->describe(*fos,Teuchos::VERB_EXTREME);
//sleep(1); comm->barrier();
//XYZ->describe(*fos,Teuchos::VERB_EXTREME);
LO numPartitions = comm->getSize();
level.Set("number of partitions",numPartitions);
RCP<ZoltanInterface> zoltan = rcp(new ZoltanInterface());
//zoltan->SetOutputLevel(0); //options are 0=none, 1=summary, 2=every pid prints
level.Request("Partition",zoltan.get());
zoltan->Build(level);
RCP<Xpetra::Vector<GO,LO,GO,NO> > decomposition = level.Get<RCP<Xpetra::Vector<GO,LO,GO,NO> > >("Partition",zoltan.get());
/* //temporary code to have the trivial decomposition (no change)
ArrayRCP<GO> decompEntries = decomposition->getDataNonConst(0);
for (ArrayRCP<GO>::iterator i = decompEntries.begin(); i != decompEntries.end(); ++i)
*i = comm->getRank();
decompEntries=Teuchos::null;
*/
//Create vector whose local length is the global number of partitions.
//This vector will record the local number of nonzeros associated with each partition.
Teuchos::Array<GO> parts(numPartitions);
for (int i=0; i<numPartitions; ++i) parts[i] = i;
Teuchos::ArrayView<GO> partsView(&parts[0],numPartitions);
RCP<const Map> partitionMap = MapFactory::Build(TestHelpers::Parameters::getLib(),
Teuchos::OrdinalTraits<global_size_t>::invalid(), partsView,
map->getIndexBase(),comm);
RCP<Xpetra::Vector<LO,LO,GO,NO> > localPartsVec = Xpetra::VectorFactory<LO,LO,GO,NO>::Build(partitionMap);
RCP<Xpetra::Vector<LO,LO,GO,NO> > nnzPerRow = Xpetra::VectorFactory<LO,LO,GO,NO>::Build(A->getRowMap());
Teuchos::ArrayRCP<GO> nnzData = nnzPerRow->getDataNonConst(0);
//For the local rows in each partition, tally up the number of nonzeros. This is what
//Zoltan should be load-balancing.
Teuchos::ArrayRCP<GO> lpvData = localPartsVec->getDataNonConst(0);
Teuchos::ArrayRCP<const GO> decompData = decomposition->getData(0);
for (size_t i=0; i<decomposition->getLocalLength();++i) {
Teuchos::ArrayView<const LO> c;
Teuchos::ArrayView<const SC> v;
A->getLocalRowView(i,c,v);
lpvData[decompData[i]] += v.size();
nnzData[i] = v.size();
}
lpvData = Teuchos::null;
decompData = Teuchos::null;
nnzData = Teuchos::null;
/*
if (comm->getRank() == 0)
std::cout << "nnz per row" << std::endl;
nnzPerRow->describe(*fos,Teuchos::VERB_EXTREME);
if (comm->getRank() == 0)
std::cout << "Row-to-partition assignment (from Zoltan)" << std::endl;
decomposition->describe(*fos,Teuchos::VERB_EXTREME);
if (comm->getRank() == 0)
std::cout << "#nonzeros per partition" << std::endl;
localPartsVec->describe(*fos,Teuchos::VERB_EXTREME);
*/
//Send the local nnz tallies to pid 0, which can report the global sums.
size_t mysize=1;
if (comm->getRank() == 0) mysize = numPartitions;
RCP<const Map> globalTallyMap = MapFactory::Build(TestHelpers::Parameters::getLib(),
Teuchos::OrdinalTraits<global_size_t>::invalid(),
mysize,
map->getIndexBase(),
comm);
RCP<Xpetra::Vector<LO,LO,GO,NO> > globalTallyVec = Xpetra::VectorFactory<LO,LO,GO,NO>::Build(globalTallyMap);
RCP<const Export> exporter = ExportFactory::Build( partitionMap, globalTallyMap);
globalTallyVec->doExport(*localPartsVec,*exporter,Xpetra::ADD);
ArrayRCP<GO> expectedResults(numPartitions);
switch (comm->getSize()) {
case 1:
expectedResults[0] = 3951;
break;
case 2:
expectedResults[0] = 1955;
expectedResults[1] = 1910;
break;
case 3:
expectedResults[0] = 1326;
expectedResults[1] = 1340;
expectedResults[2] = 1321;
break;
case 4:
expectedResults[0] = 950;
expectedResults[1] = 922;
expectedResults[2] = 908;
expectedResults[3] = 936;
break;
case 5:
expectedResults[0] = 774;
expectedResults[1] = 735;
expectedResults[2] = 726;
expectedResults[3] = 771;
expectedResults[4] = 759;
break;
default:
break;
};
ArrayRCP<const LO> gtvData = globalTallyVec->getData(0);
#ifdef __linux__
out << "Checking results..." << std::endl;
for (int i=0; i<numPartitions; ++i) {
if (comm->getRank() == 0) TEST_EQUALITY( expectedResults[i], gtvData[i]);
}
#endif
#ifdef MUELU_VISUALIZE_REPARTITIONING
//
//Now write everything to a comma-separate list that ParaView can grok
//
Teuchos::ArrayRCP<const Scalar> X = XYZ->getData(0);
Teuchos::ArrayRCP<const Scalar> Y = XYZ->getData(1);
Teuchos::ArrayRCP<const GO> D = decomposition->getData(0);
RCP<std::ofstream> outFile;
std::string fileName = "zoltanResults.csv";
//write header information
if (comm->getRank() == 0) {
outFile = rcp(new std::ofstream(fileName.c_str()));
*outFile << "x coord, y coord, z coord, partition, row weight" << std::endl;
}
comm->barrier();
//append coordinates
nnzData = nnzPerRow->getDataNonConst(0);
for (int j=0; j<comm->getSize(); ++j) {
int mypid = comm->getRank();
if (mypid == j) {
outFile = rcp(new std::ofstream(fileName.c_str(),std::ios::app));
int blockSize = A->GetFixedBlockSize();
//Coordinates are for coalesced system, D is for uncoalesced
for (int i=0; i < D.size()/blockSize; ++i) {
int nnz=0;
for (int k=0; k<blockSize; ++k) nnz += nnzData[i*blockSize+k];
*outFile << X[i] << ", " << Y[i] << ", " << ST::zero() << ", "
<< D[i*blockSize] << ", " << nnz << std::endl;
}
}
} //for (int i=0; i<comm->getSize(); ++i)
out << std::endl;
out << "You can view the Zoltan decomposition in ParaView 3.10.1 or later:" << std::endl;
out << " 1) Load the data file " << fileName << "." << std::endl;
out << " 2) Run the filter Filters/ Alphabetical/ Table To Points." << std::endl;
out << " 3) Tell ParaView what columns are the X, Y and Z coordinates." << std::endl;
out << " 4) Split screen horizontally (Icon, top right)." << std::endl;
out << " 5) Click on the eyeball in the Pipeline Browser to see the points." << std::endl;
out << " 6) Under the Display tab, you can color points by scalar value and resize them." << std::endl;
out << std::endl;
out << " To display row weights next to each point:" << std::endl;
out << " 1) Click the \"Select Points Through\" button (2nd row) and select all points." << std::endl;
out << " 2) Under View pull-down menu, choose the \"Selection Inspector\"." << std::endl;
out << " 3) Under the Point Label, check the Visible box and set the Label Mode to \"row weight\"." << std::endl;
#endif
} //Build3PDEs
void FilteredAFactory<Scalar, LocalOrdinal, GlobalOrdinal, Node, LocalMatOps>::Build(Level& currentLevel) const {
using Teuchos::as;
FactoryMonitor m(*this, "Matrix filtering", currentLevel);
RCP<Matrix> A = Get< RCP<Matrix> >(currentLevel, "A");
if (currentLevel.Get<bool>("Filtering", currentLevel.GetFactoryManager()->GetFactory("Filtering").get()) == false) {
GetOStream(Runtime0,0) << "Filtered matrix is not being constructed as no filtering is being done" << std::endl;
Set(currentLevel, "A", A);
return;
}
const ParameterList& pL = GetParameterList();
RCP<GraphBase> G = Get< RCP<GraphBase> >(currentLevel, "Graph");
bool lumping = pL.get<bool>("lumping");
size_t blkSize = A->GetFixedBlockSize();
if (lumping)
GetOStream(Runtime0,0) << "Lumping dropped entries" << std::endl;
// Calculate max entries per row
RCP<Matrix> filteredA = MatrixFactory::Build(A->getRowMap(), A->getColMap(), A->getNodeMaxNumRowEntries(), Xpetra::StaticProfile);
Array<LO> newInds;
Array<SC> newVals;
Array<char> filter(blkSize*G->GetImportMap()->getNodeNumElements(), 0);
size_t numGRows = G->GetNodeNumVertices(), numInds = 0, diagIndex;
SC diagExtra;
for (size_t i = 0; i < numGRows; i++) {
// Set up filtering array
Teuchos::ArrayView<const LO> indsG = G->getNeighborVertices(i);
for (size_t j = 0; j < as<size_t> (indsG.size()); j++)
for (size_t k = 0; k < blkSize; k++)
filter[indsG[j]*blkSize+k] = 1;
for (size_t k = 0; k < blkSize; k++) {
LocalOrdinal row = i*blkSize+k;
ArrayView<const LO> oldInds;
ArrayView<const SC> oldVals;
A->getLocalRowView(row, oldInds, oldVals);
diagIndex = as<size_t>(-1);
diagExtra = Teuchos::ScalarTraits<SC>::zero();
newInds.resize(oldInds.size());
newVals.resize(oldVals.size());
numInds = 0;
for (size_t j = 0; j < as<size_t> (oldInds.size()); j++)
if (filter[oldInds[j]]) {
newInds[numInds] = oldInds[j];
newVals[numInds] = oldVals[j];
// Remember diagonal position
if (newInds[numInds] == row)
diagIndex = numInds;
numInds++;
} else {
diagExtra += oldVals[j];
}
// Lump dropped entries
// NOTE
// * Does it make sense to lump for elasticity?
// * Is it different for diffusion and elasticity?
if (lumping)
newVals[diagIndex] += diagExtra;
newInds.resize(numInds);
newVals.resize(numInds);
// Because we used a column map in the construction of the matrix
// we can just use insertLocalValues here instead of insertGlobalValues
filteredA->insertLocalValues(row, newInds, newVals);
}
// Clean up filtering array
for (size_t j = 0; j < as<size_t> (indsG.size()); j++)
for (size_t k = 0; k < blkSize; k++)
filter[indsG[j]*blkSize+k] = 0;
}
RCP<ParameterList> fillCompleteParams(new ParameterList);
fillCompleteParams->set("No Nonlocal Changes", true);
filteredA->fillComplete(A->getDomainMap(), A->getRangeMap(), fillCompleteParams);
filteredA->SetFixedBlockSize(blkSize);
// TODO: Can we reuse max eigenvalue from A?
// filteredA->SetMaxEigenvalueEstimate(A->GetMaxEigenvalueEstimate());
Set(currentLevel, "A", filteredA);
}
