DUNE PDELab (git)

parallelhelper.hh
1// -*- tab-width: 8; indent-tabs-mode: nil; c-basic-offset: 2 -*-
2// vi: set et ts=8 sw=2 sts=2:
3#ifndef DUNE_PDELAB_BACKEND_ISTL_PARALLELHELPER_HH
4#define DUNE_PDELAB_BACKEND_ISTL_PARALLELHELPER_HH
5
6#include <limits>
7
11
12#if HAVE_DUNE_UGGRID && PDELAB_SEQUENTIAL_UG
13// We need the UGGrid declaration for the assertion
14#include <dune/grid/uggrid.hh>
15#endif
16
18#include <dune/istl/solvercategory.hh>
20#include <dune/istl/solvers.hh>
24#include <dune/istl/paamg/pinfo.hh>
25#include <dune/istl/io.hh>
26#include <dune/istl/superlu.hh>
27
28#include <dune/pdelab/constraints/common/constraints.hh>
29#include <dune/pdelab/gridfunctionspace/genericdatahandle.hh>
30#include <dune/pdelab/backend/interface.hh>
31#include <dune/pdelab/backend/istl/vector.hh>
32#include <dune/pdelab/backend/istl/utility.hh>
33#include <dune/pdelab/gridfunctionspace/tags.hh>
34
35namespace Dune {
36 namespace PDELab {
37 namespace ISTL {
38
42
43
44 //========================================================
45 // A parallel helper class providing a nonoverlapping
46 // decomposition of all degrees of freedom
47 //========================================================
48
49 template<typename GFS>
50 class ParallelHelper
51 {
52
54 typedef int RankIndex;
55
57 using RankVector = Dune::PDELab::Backend::Vector<GFS,RankIndex>;
59 using GhostVector = Dune::PDELab::Backend::Vector<GFS,bool>;
60
62 typedef typename GFS::Ordering::Traits::ContainerIndex ContainerIndex;
63
64 public:
65
66 ParallelHelper (const GFS& gfs, int verbose = 1)
67 : _gfs(gfs)
68 , _rank(gfs.gridView().comm().rank())
69 , _rank_partition(gfs,_rank)
70 , _ghosts(gfs,false)
71 , _verbose(verbose)
72 {
73
74 // Let's try to be clever and reduce the communication overhead by picking the smallest
75 // possible communication interface depending on the overlap structure of the GFS.
76 // FIXME: Switch to simple comparison as soon as dune-grid:1b3e83ec0 is reliably available!
77 if (gfs.entitySet().partitions().value == Partitions::interiorBorder.value)
78 {
79 // The GFS only spans the interior and border partitions, so we can skip sending or
80 // receiving anything else.
81 _interiorBorder_all_interface = InteriorBorder_InteriorBorder_Interface;
82 _all_all_interface = InteriorBorder_InteriorBorder_Interface;
83 }
84 else
85 {
86 // In general, we have to transmit more.
87 _interiorBorder_all_interface = InteriorBorder_All_Interface;
88 _all_all_interface = All_All_Interface;
89 }
90
91 if (_gfs.gridView().comm().size()>1)
92 {
93
94 // find out about ghosts
95 //GFSDataHandle<GFS,GhostVector,GhostGatherScatter>
96 GhostDataHandle<GFS,GhostVector>
97 gdh(_gfs,_ghosts,false);
98 _gfs.gridView().communicate(gdh,_interiorBorder_all_interface,Dune::ForwardCommunication);
99
100 // create disjoint DOF partitioning
101 // GFSDataHandle<GFS,RankVector,DisjointPartitioningGatherScatter<RankIndex> >
102 // ibdh(_gfs,_rank_partition,DisjointPartitioningGatherScatter<RankIndex>(_rank));
103 DisjointPartitioningDataHandle<GFS,RankVector> pdh(_gfs,_rank_partition);
104 _gfs.gridView().communicate(pdh,_interiorBorder_all_interface,Dune::ForwardCommunication);
105
106 }
107
108 // Generate list of neighbors' ranks
109 std::set<RankIndex> rank_set;
110 for (RankIndex rank : _rank_partition)
111 if (rank != _rank)
112 rank_set.insert(rank);
113
114 for (RankIndex rank : rank_set)
115 _neighbor_ranks.push_back(rank);
116 }
117
119 const std::vector<RankIndex>& getNeighborRanks() const
120 {
121 return _neighbor_ranks;
122 }
123
125 template<typename X>
126 void maskForeignDOFs(X& x) const
127 {
128 using Backend::native;
129 // dispatch to implementation.
130 maskForeignDOFs(ISTL::container_tag(native(x)),native(x),native(_rank_partition));
131 }
132
133 private:
134
135 // Implementation for block vector; recursively masks blocks.
136 template<typename X, typename Mask>
137 void maskForeignDOFs(ISTL::tags::block_vector, X& x, const Mask& mask) const
138 {
139 typename Mask::const_iterator mask_it = mask.begin();
140 for (typename X::iterator it = x.begin(),
141 end_it = x.end();
142 it != end_it;
143 ++it, ++mask_it)
144 maskForeignDOFs(ISTL::container_tag(*it),*it,*mask_it);
145 }
146
147 // Implementation for field vector, iterates over entries and masks them individually.
148 template<typename X, typename Mask>
149 void maskForeignDOFs(ISTL::tags::field_vector, X& x, const Mask& mask) const
150 {
151 typename Mask::const_iterator mask_it = mask.begin();
152 for (typename X::iterator it = x.begin(),
153 end_it = x.end();
154 it != end_it;
155 ++it, ++mask_it)
156 *it = (*mask_it == _rank ? *it : typename X::field_type(0));
157 }
158
159 public:
160
162 bool owned(const ContainerIndex& i) const
163 {
164 return _rank_partition[i] == _rank;
165 }
166
168 bool isGhost(const ContainerIndex& i) const
169 {
170 return _ghosts[i];
171 }
172
174 template<typename X, typename Y>
175 typename PromotionTraits<
176 typename X::field_type,
177 typename Y::field_type
178 >::PromotedType
179 disjointDot(const X& x, const Y& y) const
180 {
181 using Backend::native;
182 return disjointDot(ISTL::container_tag(native(x)),
183 native(x),
184 native(y),
185 native(_rank_partition)
186 );
187 }
188
189 private:
190
191 // Implementation for BlockVector, collects the result of recursively
192 // invoking the algorithm on the vector blocks.
193 template<typename X, typename Y, typename Mask>
194 typename PromotionTraits<
195 typename X::field_type,
196 typename Y::field_type
197 >::PromotedType
198 disjointDot(ISTL::tags::block_vector, const X& x, const Y& y, const Mask& mask) const
199 {
200 typedef typename PromotionTraits<
201 typename X::field_type,
202 typename Y::field_type
203 >::PromotedType result_type;
204
205 result_type r(0);
206
207 typename Y::const_iterator y_it = y.begin();
208 typename Mask::const_iterator mask_it = mask.begin();
209 for (typename X::const_iterator x_it = x.begin(),
210 end_it = x.end();
211 x_it != end_it;
212 ++x_it, ++y_it, ++mask_it)
213 r += disjointDot(ISTL::container_tag(*x_it),*x_it,*y_it,*mask_it);
214
215 return r;
216 }
217
218 // Implementation for FieldVector, iterates over the entries and calls Dune::dot() for DOFs
219 // associated with the current rank.
220 template<typename X, typename Y, typename Mask>
221 typename PromotionTraits<
222 typename X::field_type,
223 typename Y::field_type
224 >::PromotedType
225 disjointDot(ISTL::tags::field_vector, const X& x, const Y& y, const Mask& mask) const
226 {
227 typedef typename PromotionTraits<
228 typename X::field_type,
229 typename Y::field_type
230 >::PromotedType result_type;
231
232 result_type r(0);
233
234 typename Y::const_iterator y_it = y.begin();
235 typename Mask::const_iterator mask_it = mask.begin();
236 for (typename X::const_iterator x_it = x.begin(),
237 end_it = x.end();
238 x_it != end_it;
239 ++x_it, ++y_it, ++mask_it)
240 r += (*mask_it == _rank ? Dune::dot(*x_it,*y_it) : result_type(0));
241
242 return r;
243 }
244
245 public:
246
248 RankIndex rank() const
249 {
250 return _rank;
251 }
252
253#if HAVE_MPI
254
256
272 template<typename MatrixType, typename Comm>
273 void createIndexSetAndProjectForAMG(MatrixType& m, Comm& c);
274
275 private:
276
277 // Checks whether a matrix block is owned by the current process. Used for the AMG
278 // construction and thus assumes a single level of blocking and blocks with ownership
279 // restricted to a single DOF.
280 bool owned_for_amg(std::size_t i) const
281 {
282 return Backend::native(_rank_partition)[i][0] == _rank;
283 }
284
285#endif // HAVE_MPI
286
287 private:
288
289 const GFS& _gfs;
290 const RankIndex _rank;
291 RankVector _rank_partition; // vector to identify unique decomposition
292 std::vector<RankIndex> _neighbor_ranks; // list of neighbors' ranks
293 GhostVector _ghosts; //vector to identify ghost dofs
294 int _verbose; //verbosity
295
297 InterfaceType _interiorBorder_all_interface;
298
300 InterfaceType _all_all_interface;
301 };
302
303#if HAVE_MPI
304
305 template<typename GFS>
306 template<typename M, typename C>
307 void ParallelHelper<GFS>::createIndexSetAndProjectForAMG(M& m, C& c)
308 {
309
310 using Backend::native;
311
312 const bool is_bcrs_matrix =
313 std::is_same<
314 typename ISTL::tags::container<
315 Backend::Native<M>
316 >::type::base_tag,
317 ISTL::tags::bcrs_matrix
318 >::value;
319
320 const bool block_type_is_field_matrix =
321 std::is_same<
322 typename ISTL::tags::container<
323 typename Backend::Native<M>::block_type
324 >::type::base_tag,
325 ISTL::tags::field_matrix
326 >::value;
327
328 // We assume M to be a BCRSMatrix in the following, so better check for that
329 static_assert(is_bcrs_matrix && block_type_is_field_matrix, "matrix structure not compatible with AMG");
330
331 // ********************************************************************************
332 // In the following, the code will always assume that all DOFs stored in a single
333 // block of the BCRSMatrix are attached to the same entity and can be handled
334 // identically. For that reason, the code often restricts itself to inspecting the
335 // first entry of the blocks in the diverse BlockVectors.
336 // ********************************************************************************
337
338 typedef typename GFS::Traits::GridViewType GV;
339 typedef typename RankVector::size_type size_type;
340 const GV& gv = _gfs.gridView();
341
342 // Do we need to communicate at all?
343 const bool need_communication = _gfs.gridView().comm().size() > 1;
344
345 // First find out which dofs we share with other processors
346 using BoolVector = Backend::Vector<GFS,bool>;
347 BoolVector sharedDOF(_gfs, false);
348
349 if (need_communication)
350 {
351 SharedDOFDataHandle<GFS,BoolVector> data_handle(_gfs,sharedDOF,false);
352 _gfs.gridView().communicate(data_handle,_all_all_interface,Dune::ForwardCommunication);
353 }
354
355 // Count shared dofs that we own
356 typedef typename C::ParallelIndexSet::GlobalIndex GlobalIndex;
357 GlobalIndex count = 0;
358
359 for (size_type i = 0; i < sharedDOF.N(); ++i)
360 if (owned_for_amg(i) && native(sharedDOF)[i][0])
361 ++count;
362
363 dverb << gv.comm().rank() << ": shared block count is " << count.touint() << std::endl;
364
365 // Communicate per-rank count of owned and shared DOFs to all processes.
366 std::vector<GlobalIndex> counts(_gfs.gridView().comm().size());
367 _gfs.gridView().comm().allgather(&count, 1, &(counts[0]));
368
369 // Compute start index start_p = \sum_{i=0}^{i<p} counts_i
370 GlobalIndex start = std::accumulate(counts.begin(),counts.begin() + _rank,GlobalIndex(0));
371
372 using GIVector = Dune::PDELab::Backend::Vector<GFS,GlobalIndex>;
373 GIVector scalarIndices(_gfs, std::numeric_limits<GlobalIndex>::max());
374
375 for (size_type i = 0; i < sharedDOF.N(); ++i)
376 if (owned_for_amg(i) && native(sharedDOF)[i][0])
377 {
378 native(scalarIndices)[i][0] = start;
379 ++start;
380 }
381
382 // Publish global indices for the shared DOFS to other processors.
383 if (need_communication)
384 {
385 MinDataHandle<GFS,GIVector> data_handle(_gfs,scalarIndices);
386 _gfs.gridView().communicate(data_handle,_interiorBorder_all_interface,Dune::ForwardCommunication);
387 }
388
389 // Setup the index set
390 c.indexSet().beginResize();
391 for (size_type i=0; i<scalarIndices.N(); ++i)
392 {
393 Dune::OwnerOverlapCopyAttributeSet::AttributeSet attr;
394 if(native(scalarIndices)[i][0] != std::numeric_limits<GlobalIndex>::max())
395 {
396 // global index exist in index set
397 if (owned_for_amg(i))
398 {
399 // This dof is managed by us.
400 attr = Dune::OwnerOverlapCopyAttributeSet::owner;
401 }
402 else
403 {
404 attr = Dune::OwnerOverlapCopyAttributeSet::copy;
405 }
406 c.indexSet().add(native(scalarIndices)[i][0], typename C::ParallelIndexSet::LocalIndex(i,attr));
407 }
408 }
409 c.indexSet().endResize();
410
411 // Compute neighbors using communication
412 std::set<int> neighbors;
413
414 if (need_communication)
415 {
416 GFSNeighborDataHandle<GFS,int> data_handle(_gfs,_rank,neighbors);
417 _gfs.gridView().communicate(data_handle,_all_all_interface,Dune::ForwardCommunication);
418 }
419
420 c.remoteIndices().setNeighbours(neighbors);
421 c.remoteIndices().template rebuild<false>();
422 }
423
424#endif // HAVE_MPI
425
426 template<int s, bool isFakeMPIHelper>
427 struct CommSelector
428 {
429 typedef Dune::Amg::SequentialInformation type;
430 };
431
432
433#if HAVE_MPI
434
435 // Need MPI for OwnerOverlapCopyCommunication
436 template<int s>
437 struct CommSelector<s,false>
438 {
439 typedef OwnerOverlapCopyCommunication<bigunsignedint<s>,int> type;
440 };
441
442#endif // HAVE_MPI
443
444 template<typename T>
445 void assertParallelUG(T comm)
446 {}
447
448#if HAVE_DUNE_UGGRID && PDELAB_SEQUENTIAL_UG
449 template<int dim>
450 void assertParallelUG(Dune::Communication<Dune::UGGrid<dim> > comm)
451 {
452 static_assert(Dune::AlwaysFalse<Dune::UGGrid<dim> >::value, "Using sequential UG in parallel environment");
453 };
454#endif
456
457 } // namespace ISTL
458 } // namespace PDELab
459} // namespace Dune
460
461#endif // DUNE_PDELAB_BACKEND_ISTL_PARALLELHELPER_HH
The AMG preconditioner.
Collective communication interface and sequential default implementation.
Definition: communication.hh:100
Front-end for the grid manager of the finite element toolbox UG3.
Definition: uggrid.hh:208
Traits for type conversions and type information.
Some generic functions for pretty printing vectors and matrices.
Implementations of the inverse operator interface.
auto dot(const A &a, const B &b) -> typename std::enable_if< IsNumber< A >::value &&!IsVector< A >::value &&!std::is_same< typename FieldTraits< A >::field_type, typename FieldTraits< A >::real_type > ::value, decltype(conj(a) *b)>::type
computes the dot product for fundamental data types according to Petsc's VectDot function: dot(a,...
Definition: dotproduct.hh:42
InterfaceType
Parameter to be used for the communication functions.
Definition: gridenums.hh:86
@ ForwardCommunication
communicate as given in InterfaceType
Definition: gridenums.hh:171
@ InteriorBorder_All_Interface
send interior and border, receive all entities
Definition: gridenums.hh:88
@ All_All_Interface
send all and receive all entities
Definition: gridenums.hh:91
@ InteriorBorder_InteriorBorder_Interface
send/receive interior and border entities
Definition: gridenums.hh:87
constexpr auto max
Function object that returns the greater of the given values.
Definition: hybridutilities.hh:484
constexpr T accumulate(Range &&range, T value, F &&f)
Accumulate values.
Definition: hybridutilities.hh:279
Mask< V > mask(ADLTag< 0, std::is_same< V, Mask< V > >::value >, const V &v)
implements Simd::mask()
Definition: defaults.hh:153
Rebind< bool, V > Mask
Mask type type of some SIMD type.
Definition: interface.hh:289
DVerbType dverb(std::cout)
Singleton of verbose debug stream.
Definition: stdstreams.hh:117
Helpers for dealing with MPI.
constexpr InteriorBorder interiorBorder
PartitionSet for the interior and border partitions.
Definition: partitionset.hh:286
Dune namespace.
Definition: alignedallocator.hh:13
Define general, extensible interface for operators. The available implementation wraps a matrix.
Classes providing communication interfaces for overlapping Schwarz methods.
Define general preconditioner interface.
Define base class for scalar product and norm.
Standard Dune debug streams.
template which always yields a false value
Definition: typetraits.hh:124
Classes for using SuperLU with ISTL matrices.
The UGGrid class.
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