10 #ifndef MUELU_CLASSICALDROPPING_HPP
11 #define MUELU_CLASSICALDROPPING_HPP
14 #include "Kokkos_Core.hpp"
15 #include "Kokkos_ArithTraits.hpp"
17 #include "MueLu_Utilities.hpp"
19 namespace MueLu::ClassicalDropping {
45 template <
class Scalar,
class LocalOrdinal,
class GlobalOrdinal,
class Node, Misc::StrengthMeasure measure>
54 using diag_view_type =
typename Kokkos::DualView<const scalar_type*, Kokkos::LayoutStride, typename Node::device_type, Kokkos::MemoryUnmanaged>::t_dev;
58 using ATS = Kokkos::ArithTraits<scalar_type>;
60 using mATS = Kokkos::ArithTraits<magnitudeType>;
72 :
A(A_.getLocalMatrixDevice())
78 auto lclDiag2d =
diagVec->getLocalViewDevice(Xpetra::Access::ReadOnly);
79 diag = Kokkos::subview(lclDiag2d, Kokkos::ALL(), 0);
82 auto lcl2d =
diagVec->getLocalViewDevice(Xpetra::Access::ReadOnly);
83 diag = Kokkos::subview(lcl2d, Kokkos::ALL(), 0);
87 KOKKOS_FORCEINLINE_FUNCTION
89 auto row =
A.rowConst(rlid);
90 size_t offset =
A.graph.row_map(rlid);
92 #ifdef MUELU_COALESCE_DROP_DEBUG
94 Kokkos::printf(
"SoC: ");
96 auto clid = row.colidx(k);
98 auto val = row.value(k);
101 auto aiiajj = ATS::magnitude(
diag(rlid)) * ATS::magnitude(
diag(clid));
102 auto aij2 = ATS::magnitude(val) * ATS::magnitude(val);
104 Kokkos::printf(
"%5f ", ATS::sqrt(aij2 / aiiajj));
106 auto neg_aij = -ATS::real(val);
107 auto max_neg_aik =
eps * ATS::real(
diag(rlid));
108 results(offset + k) = Kokkos::max((neg_aij < max_neg_aik) ?
DROP :
KEEP,
110 Kokkos::printf(
"%5f ", neg_aij / max_neg_aik);
112 auto aiiajj = ATS::magnitude(
diag(rlid)) * ATS::magnitude(
diag(clid));
113 const bool is_nonpositive = ATS::real(val) <= mATS::zero();
114 magnitudeType aij2 = ATS::magnitude(val) * ATS::magnitude(val);
118 Kokkos::printf(
"%5f ", ATS::sqrt(aij2 / aiiajj));
121 Kokkos::printf(
"\n");
126 auto clid = row.colidx(k);
128 auto val = row.value(k);
131 auto aiiajj = ATS::magnitude(
diag(rlid)) * ATS::magnitude(
diag(clid));
132 auto aij2 = ATS::magnitude(val) * ATS::magnitude(val);
137 auto neg_aij = -ATS::real(val);
138 auto max_neg_aik =
eps * ATS::real(
diag(rlid));
139 results(offset + k) = Kokkos::max((neg_aij < max_neg_aik) ?
DROP :
KEEP,
142 auto aiiajj = ATS::magnitude(
diag(rlid)) * ATS::magnitude(
diag(clid));
143 const bool is_nonpositive = ATS::real(val) <= mATS::zero();
144 magnitudeType aij2 = ATS::magnitude(val) * ATS::magnitude(val);
156 template <Misc::StrengthMeasure measure,
class Scalar,
class LocalOrdinal,
class GlobalOrdinal,
class Node>
static Teuchos::RCP< Vector > GetMatrixMaxMinusOffDiagonal(const Xpetra::Matrix< Scalar, LocalOrdinal, GlobalOrdinal, Node > &A)
Return vector containing: max_{i=k}(-a_ik), for each for i in the matrix.
Kokkos::View< const bool *, memory_space > boundary_nodes_view
Kokkos::ArithTraits< magnitudeType > mATS
typename local_matrix_type::value_type scalar_type
typename local_matrix_type::memory_space memory_space
DropFunctor(matrix_type &A_, magnitudeType threshold, results_view &results_)
typename matrix_type::local_matrix_type local_matrix_type
typename ATS::magnitudeType magnitudeType
Kokkos::View< DecisionType *, memory_space > results_view
typename Kokkos::DualView< const scalar_type *, Kokkos::LayoutStride, typename Node::device_type, Kokkos::MemoryUnmanaged >::t_dev diag_view_type
KOKKOS_FORCEINLINE_FUNCTION void operator()(const local_ordinal_type rlid) const
auto make_drop_functor(Xpetra::Matrix< Scalar, LocalOrdinal, GlobalOrdinal, Node > &A_, typename DropFunctor< Scalar, LocalOrdinal, GlobalOrdinal, Node, measure >::magnitudeType threshold, typename DropFunctor< Scalar, LocalOrdinal, GlobalOrdinal, Node, measure >::results_view &results_)
static RCP< Vector > GetMatrixOverlappedDiagonal(const Matrix &A)
Extract Overlapped Matrix Diagonal.
Kokkos::ArithTraits< scalar_type > ATS
typename local_matrix_type::ordinal_type local_ordinal_type
Teuchos::RCP< diag_vec_type > diagVec
Classical dropping criterion.