KOKKOS_INLINE_FUNCTION
static Scalar draw(Generator& gen, const Scalar& start, const Scalar& end) {
return BaseRand::draw(gen, start.coeff(0), end.coeff(0));
}
void run_samples(
const Teuchos::Comm<int>& comm ,
Kokkos::Example::FENL::Problem< Sacado::MP::Vector<Storage>, Device, ElemOrder>& problem ,
const CoeffFunctionType & coeff_function,
const Teuchos::RCP<Kokkos::Example::FENL::SampleGrouping<double> >& grouper,
const Teuchos::RCP<Teuchos::ParameterList>& fenlParams,
const CMD & cmd ,
const double bc_lower_value,
const double bc_upper_value,
const Teuchos::Array< Teuchos::Array<double> >& points,
Teuchos::Array<double>& responses,
Teuchos::Array<int>& iterations,
Kokkos::Example::FENL::Perf& perf_total)
{
using Teuchos::Array;
using Teuchos::Ordinal;
typedef typename Sacado::MP::Vector<Storage> Scalar;
typedef typename CoeffFunctionType::RandomVariableView RV;
typedef typename RV::HostMirror HRV;
static const int VectorSize = Storage::static_size;
// Group points into ensembles
Array< Array<Ordinal> > groups;
Ordinal num_duplicate = 0;
grouper->group(VectorSize, points, groups, num_duplicate);
const int num_groups = groups.size();
RV rv = coeff_function.getRandomVariables();
HRV hrv = Kokkos::create_mirror_view(rv);
const int dim = rv.dimension_0();
// Loop over quadrature point groups
for (int group=0; group<num_groups; ++group) {
// Set random variables
for (int qp=0; qp<VectorSize; ++qp)
for (int i=0; i<dim; ++i)
hrv(i).fastAccessCoeff(qp) = points[groups[group][qp]][i];
Kokkos::deep_copy( rv, hrv );
// Evaluate response at quadrature point
Scalar response = 0;
Kokkos::Example::FENL::Perf perf =
fenl( problem , fenlParams ,
cmd.PRINT , cmd.USE_TRIALS , cmd.USE_ATOMIC ,
cmd.USE_BELOS , cmd.USE_MUELU , cmd.USE_MEANBASED ,
coeff_function , cmd.USE_ISOTROPIC ,
cmd.USE_COEFF_SRC , cmd.USE_COEFF_ADV ,
bc_lower_value , bc_upper_value ,
response);
// Save response -- note currently all samples within an ensemble
// get the same number of iterations
for (int qp=0; qp<VectorSize; ++qp) {
responses[groups[group][qp]] = response.coeff(qp);
iterations[groups[group][qp]] = perf.cg_iter_count;
}
if (cmd.PRINT_ITS && 0 == comm.getRank()) {
std::cout << group << " : " << perf.cg_iter_count << " ( ";
for (int qp=0; qp<VectorSize; ++qp)
std::cout << groups[group][qp] << " ";
std::cout << ")";
std::cout << " ( ";
for (int i=0; i<dim; ++i)
std::cout << hrv(i) << " ";
std::cout << ")" << std::endl;
}
// Adjust timing statistics for ensemble size
perf.newton_iter_count *= VectorSize;
perf.cg_iter_count *= VectorSize;
perf.map_ratio *= VectorSize;
perf.fill_node_set *= VectorSize;
perf.scan_node_count *= VectorSize;
perf.fill_graph_entries *= VectorSize;
perf.sort_graph_entries *= VectorSize;
perf.fill_element_graph *= VectorSize;
// Increment timing statistics
perf_total.increment(perf, !cmd.USE_BELOS);
}
}
KOKKOS_INLINE_FUNCTION
static Scalar draw(Generator& gen, const Scalar& range) {
return BaseRand::draw(gen, range.coeff(0));
}
//
// Test Belos GMRES solve for a simple banded upper-triangular matrix
//
TEUCHOS_UNIT_TEST_TEMPLATE_4_DECL(
Tpetra_CrsMatrix_MP, BelosGMRES, BaseScalar, LocalOrdinal, GlobalOrdinal, Node )
{
using Teuchos::RCP;
using Teuchos::rcp;
using Teuchos::ArrayView;
using Teuchos::Array;
using Teuchos::ArrayRCP;
using Teuchos::ParameterList;
const LocalOrdinal VectorSize = 3;
typedef typename DeviceForNode<Node>::type Device;
typedef Stokhos::StaticFixedStorage<LocalOrdinal,BaseScalar,VectorSize,Device> Storage;
typedef Sacado::MP::Vector<Storage> Scalar;
typedef Teuchos::Comm<int> Tpetra_Comm;
typedef Tpetra::Map<LocalOrdinal,GlobalOrdinal,Node> Tpetra_Map;
typedef Tpetra::Vector<Scalar,LocalOrdinal,GlobalOrdinal,Node> Tpetra_Vector;
typedef Tpetra::CrsMatrix<Scalar,LocalOrdinal,GlobalOrdinal,Node> Tpetra_CrsMatrix;
typedef Tpetra::CrsGraph<LocalOrdinal,GlobalOrdinal,Node> Tpetra_CrsGraph;
// Ensure device is initialized
if (!Device::is_initialized())
Device::initialize();
// Build banded matrix
GlobalOrdinal nrow = 10;
RCP<const Tpetra_Comm> comm =
Tpetra::DefaultPlatform::getDefaultPlatform().getComm();
RCP<Node> node = rcp(new Node);
RCP<const Tpetra_Map> map =
Tpetra::createUniformContigMapWithNode<LocalOrdinal,GlobalOrdinal>(
nrow, comm, node);
RCP<Tpetra_CrsGraph> graph = Tpetra::createCrsGraph(map, size_t(2));
Array<GlobalOrdinal> columnIndices(2);
ArrayView<const GlobalOrdinal> myGIDs = map->getNodeElementList();
const size_t num_my_row = myGIDs.size();
for (size_t i=0; i<num_my_row; ++i) {
const GlobalOrdinal row = myGIDs[i];
columnIndices[0] = row;
size_t ncol = 1;
if (row != nrow-1) {
columnIndices[1] = row+1;
ncol = 2;
}
graph->insertGlobalIndices(row, columnIndices(0,ncol));
}
graph->fillComplete();
RCP<Tpetra_CrsMatrix> matrix = rcp(new Tpetra_CrsMatrix(graph));
// Set values in matrix
Array<Scalar> vals(2);
Scalar val(VectorSize, BaseScalar(0.0));
for (size_t i=0; i<num_my_row; ++i) {
const GlobalOrdinal row = myGIDs[i];
columnIndices[0] = row;
for (LocalOrdinal j=0; j<VectorSize; ++j)
val.fastAccessCoeff(j) = j+1;
vals[0] = val;
size_t ncol = 1;
if (row != nrow-1) {
columnIndices[1] = row+1;
for (LocalOrdinal j=0; j<VectorSize; ++j)
val.fastAccessCoeff(j) = j+1;
vals[1] = val;
ncol = 2;
}
matrix->replaceGlobalValues(row, columnIndices(0,ncol), vals(0,ncol));
}
matrix->fillComplete();
// Fill RHS vector
RCP<Tpetra_Vector> b = Tpetra::createVector<Scalar>(map);
ArrayRCP<Scalar> b_view = b->get1dViewNonConst();
for (size_t i=0; i<num_my_row; ++i) {
b_view[i] = Scalar(1.0);
}
// Solve
typedef Teuchos::ScalarTraits<BaseScalar> ST;
typedef BaseScalar BelosScalar;
typedef Tpetra::MultiVector<Scalar,LocalOrdinal,GlobalOrdinal,Node> MV;
typedef Tpetra::Operator<Scalar,LocalOrdinal,GlobalOrdinal,Node> OP;
typedef Belos::OperatorTraits<BelosScalar,MV,OP> BOPT;
typedef Belos::MultiVecTraits<BelosScalar,MV> BMVT;
typedef Belos::LinearProblem<BelosScalar,MV,OP> BLinProb;
RCP<Tpetra_Vector> x = Tpetra::createVector<Scalar>(map);
RCP< BLinProb > problem = rcp(new BLinProb(matrix, x, b));
RCP<ParameterList> belosParams = rcp(new ParameterList);
typename ST::magnitudeType tol = 1e-12;
belosParams->set("Flexible Gmres", false);
belosParams->set("Num Blocks", 100);
belosParams->set("Convergence Tolerance", BelosScalar(tol));
belosParams->set("Maximum Iterations", 100);
belosParams->set("Verbosity", 33);
belosParams->set("Output Style", 1);
belosParams->set("Output Frequency", 1);
belosParams->set("Output Stream", out.getOStream());
RCP<Belos::SolverManager<BelosScalar,MV,OP> > solver =
rcp(new Belos::PseudoBlockGmresSolMgr<BelosScalar,MV,OP>(problem, belosParams));
problem->setProblem();
Belos::ReturnType ret = solver->solve();
TEST_EQUALITY_CONST( ret, Belos::Converged );
// x->describe(*(Teuchos::fancyOStream(rcp(&std::cout,false))),
// Teuchos::VERB_EXTREME);
// Check -- Correct answer is:
// [ 0, 0, ..., 0 ]
// [ 1, 1/2, ..., 1/VectorSize ]
// [ 0, 0, ..., 0 ]
// [ 1, 1/2, ..., 1/VectorSize ]
// ....
ArrayRCP<Scalar> x_view = x->get1dViewNonConst();
for (size_t i=0; i<num_my_row; ++i) {
const GlobalOrdinal row = myGIDs[i];
if (row % 2) {
for (LocalOrdinal j=0; j<VectorSize; ++j) {
val.fastAccessCoeff(j) = BaseScalar(1.0) / BaseScalar(j+1);
}
}
else
val = Scalar(0.0);
TEST_EQUALITY( x_view[i].size(), VectorSize );
// Set small values to zero
Scalar v = x_view[i];
for (LocalOrdinal j=0; j<VectorSize; ++j) {
if (ST::magnitude(v.coeff(j)) < tol)
v.fastAccessCoeff(j) = BaseScalar(0.0);
}
for (LocalOrdinal j=0; j<VectorSize; ++j)
TEST_FLOATING_EQUALITY(v.coeff(j), val.coeff(j), tol);
}
}
