int main() {
typedef Kokkos::DefaultNode::DefaultNodeType Node;
typedef KokkosExamples::EmptySparseKernel<void,Node> SOBASE;
typedef SOBASE::graph<int,Node>::graph_type Graph;
typedef SOBASE::bind_scalar<float>::other_type FloatOps;
typedef FloatOps::matrix< float,int,Node>::matrix_type FMatrix;
typedef SOBASE::bind_scalar<double>::other_type DoubleOps;
typedef DoubleOps::matrix<double,int,Node>::matrix_type DMatrix;
typedef Kokkos::MultiVector<double,Node> DoubleVec;
typedef Kokkos::MultiVector<float,Node> FloatVec;
std::cout << "Note, this class doesn't actually do anything. We are only testing that it compiles." << std::endl;
// get a pointer to the default node
Teuchos::RCP<Node> node = Kokkos::DefaultNode::getDefaultNode();
// create the graph G
const int numRows = 5,
numCols = 5;
Teuchos::RCP<Graph> G = Teuchos::rcp(new Graph(numRows,numCols,node,Teuchos::null));
// create a double-valued matrix dM using the graph G
Teuchos::RCP<DMatrix> dM = Teuchos::rcp(new DMatrix(G,Teuchos::null));
DoubleOps doubleKernel(node);
// initialize it with G and dM
DoubleOps::finalizeGraphAndMatrix(Teuchos::UNDEF_TRI,Teuchos::NON_UNIT_DIAG,*G,*dM,Teuchos::null);
doubleKernel.setGraphAndMatrix(G,dM);
// create double-valued vectors and initialize them
DoubleVec dx(node), dy(node);
// call the sparse kernel operator interfaces
doubleKernel.multiply( Teuchos::NO_TRANS, 1.0, dx, dy);
doubleKernel.multiply( Teuchos::NO_TRANS, 1.0, dx, 1.0, dy);
doubleKernel.solve( Teuchos::NO_TRANS, dy, dx);
// create a float-valued matrix fM using the graph G
Teuchos::RCP<FMatrix> fM = Teuchos::rcp(new FMatrix(G,Teuchos::null));
// create a double-valued sparse kernel using the rebind functionality
FloatOps floatKernel(node);
// initialize it with G and fM
FloatOps::finalizeMatrix(*G,*fM,Teuchos::null);
floatKernel.setGraphAndMatrix(G,fM);
// create float-valued vectors and initialize them
FloatVec fx(node), fy(node);
// call the sparse kernel operator interfaces
floatKernel.multiply( Teuchos::NO_TRANS, 1.0f, fx, fy);
floatKernel.multiply( Teuchos::NO_TRANS, 1.0f, fx, 1.0f, fy);
floatKernel.solve( Teuchos::NO_TRANS, fy, fx);
std::cout << "End Result: TEST PASSED" << std::endl;
return 0;
}
int main() {
typedef Kokkos::DefaultNode::DefaultNodeType Node;
typedef KokkosExamples::DummySparseKernel<Node> SparseOps;
typedef Kokkos::CrsGraph < int,Node,SparseOps> Graph;
typedef Kokkos::CrsMatrix<double,int,Node,SparseOps> DoubleMat;
typedef Kokkos::CrsMatrix< float,int,Node,SparseOps> FloatMat;
typedef Kokkos::MultiVector<double,Node> DoubleVec;
typedef Kokkos::MultiVector<float,Node> FloatVec;
std::cout << "Note, this class doesn't actually do anything. We are only testing that it compiles." << std::endl;
// get a pointer to the default node
Teuchos::RCP<Node> node = Kokkos::DefaultNode::getDefaultNode();
// create the graph G
const size_t numRows = 5;
Graph G(numRows,node);
// create a double-valued matrix dM using the graph G
DoubleMat dM(G);
// create a double-valued sparse kernel using the rebind functionality
SparseOps::rebind<double>::other doubleKernel(node);
// initialize it with G and dM
doubleKernel.initializeStructure(G);
doubleKernel.initializeValues(dM);
// create double-valued vectors and initialize them
DoubleVec dx(node), dy(node);
// test the sparse kernel operator interfaces
doubleKernel.multiply( Teuchos::NO_TRANS, 1.0, dx, dy);
doubleKernel.multiply( Teuchos::NO_TRANS, 1.0, dx, 1.0, dy);
doubleKernel.solve( Teuchos::NO_TRANS, Teuchos::UPPER_TRI, Teuchos::UNIT_DIAG, dy, dx);
// create a float-valued matrix fM using the graph G
FloatMat fM(G);
// create a double-valued sparse kernel using the rebind functionality
SparseOps::rebind<float>::other floatKernel(node);
// initialize it with G and fM
floatKernel.initializeStructure(G);
floatKernel.initializeValues(fM);
// create float-valued vectors and initialize them
FloatVec fx(node), fy(node);
// test the sparse kernel operator interfaces
floatKernel.multiply( Teuchos::NO_TRANS, 1.0f, fx, fy);
floatKernel.multiply( Teuchos::NO_TRANS, 1.0f, fx, 1.0f, fy);
floatKernel.solve( Teuchos::NO_TRANS, Teuchos::UPPER_TRI, Teuchos::UNIT_DIAG, fy, fx);
std::cout << "End Result: TEST PASSED" << std::endl;
return 0;
}
int main() {
typedef Kokkos::DefaultNode::DefaultNodeType Node;
typedef KokkosExamples::EmptySparseKernel<void,Node> SOBASE;
typedef SOBASE::graph<int,Node>::graph_type Graph;
typedef SOBASE::bind_scalar<float>::other_type FloatOps;
typedef FloatOps::matrix< float,int,Node>::matrix_type FMatrix;
typedef SOBASE::bind_scalar<double>::other_type DoubleOps;
typedef DoubleOps::matrix<double,int,Node>::matrix_type DMatrix;
typedef Kokkos::MultiVector<double,Node> DoubleVec;
typedef Kokkos::MultiVector<float,Node> FloatVec;
std::cout << "Note, this class doesn't actually do anything. We are only testing that it compiles." << std::endl;
// get a pointer to the default node
Teuchos::RCP<Node> node = Kokkos::DefaultNode::getDefaultNode();
// create the graph G
const int numRows = 5,
numCols = 5;
Teuchos::RCP<Graph> G = Teuchos::rcp(new Graph(numRows,numCols,node,Teuchos::null));
// create a double-valued matrix dM using the graph G
Teuchos::RCP<DMatrix> dM = Teuchos::rcp(new DMatrix(G,Teuchos::null));
DoubleOps doubleKernel(node);
// initialize it with G and dM
DoubleOps::finalizeGraphAndMatrix(Teuchos::UNDEF_TRI,Teuchos::NON_UNIT_DIAG,*G,*dM,Teuchos::null);
doubleKernel.setGraphAndMatrix(G,dM);
// create double-valued vectors and initialize them
DoubleVec dx(node), dy(node);
// call the sparse kernel operator interfaces
doubleKernel.multiply( Teuchos::NO_TRANS, 1.0, dx, dy);
doubleKernel.multiply( Teuchos::NO_TRANS, 1.0, dx, 1.0, dy);
doubleKernel.solve( Teuchos::NO_TRANS, dy, dx);
// The Gauss-Seidel kernel asks the user to precompute the inverse
// diagonal entries of the matrix (here, the vector D). We
// demonstrate both sweep directions here. The local kernels don't
// implement a "Symmetric" direction; Tpetra handles that. (This is
// because for a matrix distributed over multiple processes,
// symmetric Gauss-Seidel requires interprocess communication
// between the forward and backward sweeps.)
DoubleVec dd (node);
doubleKernel.gaussSeidel (dy, dx, dd, 1.0, Kokkos::Forward);
doubleKernel.gaussSeidel (dy, dx, dd, 1.0, Kokkos::Backward);
// create a float-valued matrix fM using the graph G
Teuchos::RCP<FMatrix> fM = Teuchos::rcp(new FMatrix(G,Teuchos::null));
// create a double-valued sparse kernel using the rebind functionality
FloatOps floatKernel(node);
// initialize it with G and fM
FloatOps::finalizeMatrix(*G,*fM,Teuchos::null);
floatKernel.setGraphAndMatrix(G,fM);
// create float-valued vectors and initialize them
FloatVec fx(node), fy(node);
// call the sparse kernel operator interfaces
floatKernel.multiply( Teuchos::NO_TRANS, 1.0f, fx, fy);
floatKernel.multiply( Teuchos::NO_TRANS, 1.0f, fx, 1.0f, fy);
floatKernel.solve( Teuchos::NO_TRANS, fy, fx);
// Precomputed inverse diagonal entries of the sparse matrix.
FloatVec fd (node);
floatKernel.gaussSeidel (fy, fx, fd, (float) 1.0, Kokkos::Forward);
floatKernel.gaussSeidel (fy, fx, fd, (float) 1.0, Kokkos::Backward);
std::cout << "End Result: TEST PASSED" << std::endl;
return 0;
}
