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MueLu_MatrixFreeTentativeP_kokkos_def.hpp
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46#ifndef MUELU_MATRIXFREETENTATIVEP_KOKKOS_DEF_HPP
47#define MUELU_MATRIXFREETENTATIVEP_KOKKOS_DEF_HPP
48
50
51#include "MueLu_Aggregates_kokkos.hpp"
52#include "MueLu_Level.hpp"
53#include "MueLu_MasterList.hpp"
54#include "MueLu_PerfUtils.hpp"
55#include "MueLu_PFactory.hpp"
56#include "MueLu_Monitor.hpp"
57#include "MueLu_Utilities_kokkos.hpp"
58
59#include <KokkosCompat_ClassicNodeAPI_Wrapper.hpp>
60
61#include "Teuchos_ScalarTraits.hpp"
62
63namespace MueLu {
64
65 // compute Y = alpha*R*X + beta*Y
66 template <class Scalar, class LocalOrdinal, class GlobalOrdinal, class DeviceType>
68 MultiVector &Y,
69 Teuchos::ETransp mode,
70 Scalar alpha,
71 Scalar beta) const {
72
73 using impl_scalar_type = typename Kokkos::ArithTraits<Scalar>::val_type;
74 impl_scalar_type implAlpha = alpha;
75
76 // Step 1: Y*=beta*Y, setup necessary structures
77 Y.scale(beta);
78
79 // TODO: probably smarter to sqrt the whole aggSizes once, but may be slower if it's done in a separate kernel launch?
80 typename Aggregates_kokkos::aggregates_sizes_type::const_type aggSizes = aggregates_->ComputeAggregateSizes();
81
82 auto kokkos_view_X = X.getDeviceLocalView(Xpetra::Access::ReadOnly);
83 auto kokkos_view_Y = Y.getDeviceLocalView(Xpetra::Access::ReadWrite);
84 LO numCols = kokkos_view_X.extent(1);
85
86 if(mode == Teuchos::TRANS) { // if we're in restrictor mode
87 auto vertex2AggId = aggregates_->GetVertex2AggId();
88 auto vertex2AggIdView = vertex2AggId->getDeviceLocalView(Xpetra::Access::ReadOnly);
89 LO numNodes = kokkos_view_X.extent(0);
90
91 // Step 2: Compute Y=Y+alpha*R*X
92 // recall R*X is an average of X over aggregates
93 Kokkos::parallel_for("MueLu:MatrixFreeTentativeR_kokkos:apply", md_range_type({0,0},{numCols,numNodes}),
94 KOKKOS_LAMBDA(const int colIdx, const int NodeIdx) {
95 LO aggIdx = vertex2AggIdView(NodeIdx,0);
96 if(aggIdx != -1) { // depending on maps, vertex2agg
97 Kokkos::atomic_add(&kokkos_view_Y(aggIdx,colIdx),implAlpha*kokkos_view_X(NodeIdx,colIdx)/Kokkos::sqrt(aggSizes(aggIdx)));
98 }
99 });
100 } else { // if we're in prolongator mode
101 const auto vertex2Agg = aggregates_->GetVertex2AggId();
102 auto vertex2AggView = vertex2Agg->getDeviceLocalView(Xpetra::Access::ReadOnly);
103 LO numNodes = kokkos_view_Y.extent(0);
104
105 // Step 2: Compute Y=Y+alpha*P*X
106 // recall P*X is essentially injection of X, but sum if a node belongs to multiple aggregates
107 Kokkos::parallel_for("MueLu:MatrixFreeTentativeP_kokkos:apply", md_range_type({0,0},{numCols,numNodes}),
108 KOKKOS_LAMBDA(const int colIdx, const int fineIdx) {
109 LO aggIdx = vertex2AggView(fineIdx,0);
110 kokkos_view_Y(fineIdx,colIdx) += implAlpha*kokkos_view_X(aggIdx,colIdx)/Kokkos::sqrt(aggSizes(aggIdx));
111 });
112 }
113 }
114
115 // I don't care
116 template <class Scalar, class LocalOrdinal, class GlobalOrdinal, class DeviceType>
117 void MatrixFreeTentativeP_kokkos<Scalar,LocalOrdinal,GlobalOrdinal,Kokkos::Compat::KokkosDeviceWrapperNode<DeviceType>>::residual(const MultiVector &X, const MultiVector &B, MultiVector &R) const {
118 TEUCHOS_TEST_FOR_EXCEPTION(true,Exceptions::RuntimeError,"MatrixFreeTentativeP residual would make no sense as the operator is not square!");
119 }
120
121} //namespace MueLu
122
123#define MUELU_MATRIXFREETENTATIVEP_KOKKOS_SHORT
124#endif // MUELU_MATRIXFREETENTATIVEP_KOKKOS_DEF_HPP
MueLu::DefaultScalar Scalar
Exception throws to report errors in the internal logical of the program.
Namespace for MueLu classes and methods.