3#ifndef DUNE_AMG_MATRIXHIERARCHY_HH
4#define DUNE_AMG_MATRIXHIERARCHY_HH
11#include "renumberer.hh"
12#include "graphcreator.hh"
57 template<
class M,
class PI,
class A=std::allocator<M> >
65 typedef typename MatrixOperator::matrix_type
Matrix;
83 using AAllocator =
typename std::allocator_traits<Allocator>::template rebind_alloc<AggregatesMap*>;
92 using RILAllocator =
typename std::allocator_traits<Allocator>::template rebind_alloc<RedistributeInfoType>;
103 std::shared_ptr<ParallelInformation> pinfo = std::make_shared<ParallelInformation>());
112 template<
typename O,
typename T>
113 void build(
const T& criterion);
129 template<
class V,
class BA,
class TA>
137 template<
class S,
class TA>
145 std::size_t
levels()
const;
153 bool hasCoarsest()
const;
186 double getProlongationDampingFactor()
const
226 template<
class Matrix,
bool pr
int>
233 static void stats([[maybe_unused]]
const Matrix& matrix)
237 template<
class Matrix>
238 struct MatrixStats<
Matrix,true>
252 void operator()(
const matrix_row& row)
266 static void stats(
const Matrix& matrix)
268 calc c= for_each(matrix.begin(), matrix.end(), calc());
269 dinfo<<
"Matrix row: min="<<c.min<<
" max="<<c.max
270 <<
" average="<<
static_cast<double>(c.sum)/matrix.N()
310 template<
typename M,
typename C1>
311 bool repartitionAndDistributeMatrix([[maybe_unused]]
const M& origMatrix,
312 [[maybe_unused]] std::shared_ptr<M> newMatrix,
313 [[maybe_unused]] SequentialInformation& origComm,
314 [[maybe_unused]] std::shared_ptr<SequentialInformation>& newComm,
315 [[maybe_unused]] RedistributeInformation<SequentialInformation>& ri,
316 [[maybe_unused]]
int nparts,
317 [[maybe_unused]] C1& criterion)
319 DUNE_THROW(NotImplemented,
"Redistribution does not make sense in sequential code!");
323 template<
typename M,
typename C,
typename C1>
324 bool repartitionAndDistributeMatrix(
const M& origMatrix,
325 std::shared_ptr<M> newMatrix,
327 std::shared_ptr<C>& newComm,
328 RedistributeInformation<C>& ri,
329 int nparts, C1& criterion)
332#ifdef AMG_REPART_ON_COMM_GRAPH
334 bool existentOnRedist=Dune::commGraphRepartition(origMatrix, origComm, nparts, newComm,
336 criterion.debugLevel()>1);
344 IdentityMap> PropertiesGraph;
345 MatrixGraph graph(origMatrix);
346 PropertiesGraph pgraph(graph);
350 if(origComm.communicator().rank()==0)
351 std::cout<<
"Original matrix"<<std::endl;
352 origComm.communicator().barrier();
353 printGlobalSparseMatrix(origMatrix, origComm, std::cout);
356 newComm, ri.getInterface(),
357 criterion.debugLevel()>1);
360 if(origComm.communicator().rank()==0 && criterion.debugLevel()>1)
361 std::cout<<
"Repartitioning took "<<time.elapsed()<<
" seconds."<<std::endl;
366 ri.checkInterface(origComm.indexSet(), newComm->indexSet(), origComm.communicator());
372 if(origComm.communicator().rank()==0)
373 std::cout<<
"Original matrix"<<std::endl;
374 origComm.communicator().barrier();
375 if(newComm->communicator().size()>0)
376 printGlobalSparseMatrix(*newMatrix, *newComm, std::cout);
377 origComm.communicator().barrier();
380 if(origComm.communicator().rank()==0 && criterion.debugLevel()>1)
381 std::cout<<
"Redistributing matrix took "<<time.elapsed()<<
" seconds."<<std::endl;
382 return existentOnRedist;
386 template<
class M,
class IS,
class A>
388 std::shared_ptr<ParallelInformation> pinfo)
389 : matrices_(fineMatrix),
390 parallelInformation_(pinfo)
393 DUNE_THROW(
ISTLError,
"MatrixOperator and ParallelInformation must belong to the same category!");
396 template<
class M,
class IS,
class A>
397 template<
typename O,
typename T>
400 prolongDamp_ = criterion.getProlongationDampingFactor();
401 typedef O OverlapFlags;
408 GalerkinProduct<ParallelInformation> productBuilder;
409 MatIterator mlevel = matrices_.finest();
410 MatrixStats<typename M::matrix_type,MINIMAL_DEBUG_LEVEL<=INFO_DEBUG_LEVEL>::stats(mlevel->getmat());
412 PInfoIterator infoLevel = parallelInformation_.finest();
414 finenonzeros = infoLevel->communicator().sum(finenonzeros);
415 BIGINT allnonzeros = finenonzeros;
421 BIGINT unknowns = mlevel->getmat().N();
423 unknowns = infoLevel->communicator().sum(unknowns);
424 double dunknowns=unknowns.todouble();
425 infoLevel->buildGlobalLookup(mlevel->getmat().N());
428 for(; level < criterion.maxLevel(); ++level, ++mlevel) {
429 assert(matrices_.levels()==redistributes_.size());
430 rank = infoLevel->communicator().rank();
431 if(rank==0 && criterion.debugLevel()>1)
432 std::cout<<
"Level "<<level<<
" has "<<dunknowns<<
" unknowns, "<<dunknowns/infoLevel->communicator().size()
433 <<
" unknowns per proc (procs="<<infoLevel->communicator().size()<<
")"<<std::endl;
445 && dunknowns < 30*infoLevel->communicator().size()))
446 && infoLevel->communicator().size()>1 &&
447 dunknowns/infoLevel->communicator().size() <= criterion.coarsenTarget())
450 std::shared_ptr<Matrix> redistMat = std::make_shared<Matrix>();
451 std::shared_ptr<ParallelInformation> redistComm;
452 std::size_t nodomains = (std::size_t)std::ceil(dunknowns/(criterion.minAggregateSize()
453 *criterion.coarsenTarget()));
454 if( nodomains<=criterion.minAggregateSize()/2 ||
455 dunknowns <= criterion.coarsenTarget() )
458 bool existentOnNextLevel =
459 repartitionAndDistributeMatrix(mlevel->getmat(), redistMat, *infoLevel,
460 redistComm, redistributes_.back(), nodomains,
462 BIGINT unknownsRedist = redistMat->N();
463 unknownsRedist = infoLevel->communicator().sum(unknownsRedist);
464 dunknowns= unknownsRedist.todouble();
465 if(redistComm->communicator().rank()==0 && criterion.debugLevel()>1)
466 std::cout<<
"Level "<<level<<
" (redistributed) has "<<dunknowns<<
" unknowns, "<<dunknowns/redistComm->communicator().size()
467 <<
" unknowns per proc (procs="<<redistComm->communicator().size()<<
")"<<std::endl;
468 MatrixArgs args(redistMat, *redistComm);
470 assert(mlevel.isRedistributed());
471 infoLevel.addRedistributed(redistComm);
472 infoLevel->freeGlobalLookup();
474 if(!existentOnNextLevel)
479 matrix = &(mlevel.getRedistributed());
480 info = &(infoLevel.getRedistributed());
481 info->buildGlobalLookup(matrix->getmat().N());
484 rank = info->communicator().rank();
485 if(dunknowns <= criterion.coarsenTarget())
489 typedef PropertiesGraphCreator<MatrixOperator,ParallelInformation> GraphCreator;
491 typedef typename GraphCreator::GraphTuple GraphTuple;
495 std::vector<bool> excluded(matrix->getmat().N(),
false);
497 GraphTuple graphs = GraphCreator::create(*matrix, excluded, *info, OverlapFlags());
501 aggregatesMaps_.push_back(aggregatesMap);
505 int noAggregates, isoAggregates, oneAggregates, skippedAggregates;
507 std::tie(noAggregates, isoAggregates, oneAggregates, skippedAggregates) =
508 aggregatesMap->
buildAggregates(matrix->getmat(), *(std::get<1>(graphs)), criterion, level==0);
510 if(rank==0 && criterion.debugLevel()>2)
511 std::cout<<
" Have built "<<noAggregates<<
" aggregates totally ("<<isoAggregates<<
" isolated aggregates, "<<
512 oneAggregates<<
" aggregates of one vertex, and skipped "<<
513 skippedAggregates<<
" aggregates)."<<std::endl;
517 int start, end, overlapStart, overlapEnd;
518 int procs=info->communicator().rank();
519 int n = UNKNOWNS/procs;
520 int bigger = UNKNOWNS%procs;
525 end = (rank+1)*(n+1);
527 start = bigger + rank * n;
528 end = bigger + (rank + 1) * n;
533 overlapStart = start - 1;
535 overlapStart = start;
538 overlapEnd = end + 1;
542 assert((UNKNOWNS)*(overlapEnd-overlapStart)==aggregatesMap->
noVertices());
543 for(
int j=0; j< UNKNOWNS; ++j)
544 for(
int i=0; i < UNKNOWNS; ++i)
546 if(i>=overlapStart && i<overlapEnd)
548 int no = (j/2)*((UNKNOWNS)/2)+i/2;
549 (*aggregatesMap)[j*(overlapEnd-overlapStart)+i-overlapStart]=no;
554 if(criterion.debugLevel()>1 && info->communicator().rank()==0)
555 std::cout<<
"aggregating finished."<<std::endl;
557 BIGINT gnoAggregates=noAggregates;
558 gnoAggregates = info->communicator().sum(gnoAggregates);
559 double dgnoAggregates = gnoAggregates.todouble();
561 BIGINT gnoAggregates=((UNKNOWNS)/2)*((UNKNOWNS)/2);
564 if(criterion.debugLevel()>2 && rank==0)
565 std::cout <<
"Building "<<dgnoAggregates<<
" aggregates took "<<watch.
elapsed()<<
" seconds."<<std::endl;
567 if(dgnoAggregates==0 || dunknowns/dgnoAggregates<criterion.minCoarsenRate())
572 std::cerr <<
"Stopped coarsening because of rate breakdown "<<dunknowns<<
"/"<<dgnoAggregates
573 <<
"="<<dunknowns/dgnoAggregates<<
"<"
574 <<criterion.minCoarsenRate()<<std::endl;
576 std::cerr<<
"Could not build any aggregates. Probably no connected nodes."<<std::endl;
578 aggregatesMap->
free();
579 delete aggregatesMap;
580 aggregatesMaps_.pop_back();
582 if(criterion.accumulate() && mlevel.isRedistributed() && info->communicator().size()>1) {
586 delete &(mlevel.getRedistributed().getmat());
587 mlevel.deleteRedistributed();
588 delete &(infoLevel.getRedistributed());
589 infoLevel.deleteRedistributed();
590 redistributes_.back().resetSetup();
595 unknowns = noAggregates;
596 dunknowns = dgnoAggregates;
598 CommunicationArgs commargs(info->communicator(),info->category());
599 parallelInformation_.addCoarser(commargs);
607 int aggregates = IndicesCoarsener<ParallelInformation,OverlapFlags>
609 *(std::get<1>(graphs)),
614 GraphCreator::free(graphs);
616 if(criterion.debugLevel()>2) {
618 std::cout<<
"Coarsening of index sets took "<<watch.
elapsed()<<
" seconds."<<std::endl;
623 infoLevel->buildGlobalLookup(aggregates);
624 AggregatesPublisher<Vertex,OverlapFlags,ParallelInformation>::publish(*aggregatesMap,
626 infoLevel->globalLookup());
629 if(criterion.debugLevel()>2) {
631 std::cout<<
"Communicating global aggregate numbers took "<<watch.
elapsed()<<
" seconds."<<std::endl;
635 std::vector<bool>& visited=excluded;
637 typedef std::vector<bool>::iterator Iterator;
639 Iterator end = visited.end();
640 for(Iterator iter= visited.begin(); iter != end; ++iter)
645 std::shared_ptr<typename MatrixOperator::matrix_type>
646 coarseMatrix(productBuilder.build(*(std::get<0>(graphs)), visitedMap2,
651 dverb<<
"Building of sparsity pattern took "<<watch.
elapsed()<<std::endl;
653 info->freeGlobalLookup();
655 delete std::get<0>(graphs);
656 productBuilder.calculate(matrix->getmat(), *aggregatesMap, *coarseMatrix, *infoLevel, OverlapFlags());
658 if(criterion.debugLevel()>2) {
660 std::cout<<
"Calculation entries of Galerkin product took "<<watch.
elapsed()<<
" seconds."<<std::endl;
664 allnonzeros = allnonzeros + infoLevel->communicator().sum(nonzeros);
665 MatrixArgs args(coarseMatrix, *infoLevel);
667 matrices_.addCoarser(args);
672 infoLevel->freeGlobalLookup();
676 aggregatesMaps_.push_back(aggregatesMap);
678 if(criterion.debugLevel()>0) {
679 if(level==criterion.maxLevel()) {
680 BIGINT unknownsLevel = mlevel->getmat().N();
681 unknownsLevel = infoLevel->communicator().sum(unknownsLevel);
682 double dunknownsLevel = unknownsLevel.todouble();
683 if(rank==0 && criterion.debugLevel()>1) {
684 std::cout<<
"Level "<<level<<
" has "<<dunknownsLevel<<
" unknowns, "<<dunknownsLevel/infoLevel->communicator().size()
685 <<
" unknowns per proc (procs="<<infoLevel->communicator().size()<<
")"<<std::endl;
690 if(criterion.accumulate() && !redistributes_.back().isSetup() &&
691 infoLevel->communicator().size()>1) {
692#if HAVE_MPI && !HAVE_PARMETIS
694 infoLevel->communicator().rank()==0)
695 std::cerr<<
"Successive accumulation of data on coarse levels only works with ParMETIS installed."
696 <<
" Fell back to accumulation to one domain on coarsest level"<<std::endl;
700 std::shared_ptr<Matrix> redistMat = std::make_shared<Matrix>();
701 std::shared_ptr<ParallelInformation> redistComm;
704 repartitionAndDistributeMatrix(mlevel->getmat(), redistMat, *infoLevel,
705 redistComm, redistributes_.back(), nodomains,criterion);
706 MatrixArgs args(redistMat, *redistComm);
707 BIGINT unknownsRedist = redistMat->N();
708 unknownsRedist = infoLevel->communicator().sum(unknownsRedist);
710 if(redistComm->communicator().rank()==0 && criterion.debugLevel()>1) {
711 double dunknownsRedist = unknownsRedist.todouble();
712 std::cout<<
"Level "<<level<<
" redistributed has "<<dunknownsRedist<<
" unknowns, "<<dunknownsRedist/redistComm->communicator().size()
713 <<
" unknowns per proc (procs="<<redistComm->communicator().size()<<
")"<<std::endl;
716 infoLevel.addRedistributed(redistComm);
717 infoLevel->freeGlobalLookup();
720 int levels = matrices_.levels();
721 maxlevels_ = parallelInformation_.finest()->communicator().max(levels);
722 assert(matrices_.levels()==redistributes_.size());
723 if(hasCoarsest() && rank==0 && criterion.debugLevel()>1)
724 std::cout<<
"operator complexity: "<<allnonzeros.todouble()/finenonzeros.todouble()<<std::endl;
728 template<
class M,
class IS,
class A>
735 template<
class M,
class IS,
class A>
739 return parallelInformation_;
742 template<
class M,
class IS,
class A>
745 int levels=aggregatesMaps().size();
746 int maxlevels=parallelInformation_.finest()->communicator().max(levels);
747 std::size_t size=(*(aggregatesMaps().begin()))->noVertices();
749 std::vector<std::size_t> tmp;
750 std::vector<std::size_t> *coarse, *fine;
767 if(levels==maxlevels) {
768 const AggregatesMap& map = *(*(++aggregatesMaps().rbegin()));
771 for(
typename AggregatesMap::const_iterator iter = map.begin(); iter != map.end(); ++iter)
777 srand((
unsigned)std::clock());
778 std::set<size_t> used;
779 for(
typename std::vector<std::size_t>::iterator iter=coarse->begin(); iter != coarse->end();
782 std::pair<std::set<std::size_t>::iterator,
bool> ibpair
783 = used.insert(
static_cast<std::size_t
>((((
double)rand())/(RAND_MAX+1.0)))*coarse->size());
785 while(!ibpair.second)
786 ibpair = used.insert(
static_cast<std::size_t
>((((
double)rand())/(RAND_MAX+1.0))*coarse->size()));
787 *iter=*(ibpair.first);
795 for(
typename AggregatesMapList::const_reverse_iterator aggregates=++aggregatesMaps().rbegin();
796 aggregates != aggregatesMaps().rend(); ++aggregates,--levels) {
798 fine->resize((*aggregates)->noVertices());
799 fine->assign(fine->size(), 0);
800 Transfer<typename AggregatesMap::AggregateDescriptor, std::vector<std::size_t>,
ParallelInformation>
801 ::prolongateVector(*(*aggregates), *coarse, *fine,
static_cast<std::size_t
>(1), *pinfo);
803 std::swap(coarse, fine);
807 assert(coarse==&data);
810 template<
class M,
class IS,
class A>
814 return aggregatesMaps_;
816 template<
class M,
class IS,
class A>
820 return redistributes_;
823 template<
class M,
class IS,
class A>
826 typedef typename AggregatesMapList::reverse_iterator AggregatesMapIterator;
827 typedef typename ParallelMatrixHierarchy::Iterator Iterator;
828 typedef typename ParallelInformationHierarchy::Iterator InfoIterator;
830 AggregatesMapIterator amap = aggregatesMaps_.rbegin();
831 InfoIterator info = parallelInformation_.coarsest();
832 for(Iterator level=matrices_.coarsest(), finest=matrices_.finest(); level != finest; --level, --info, ++amap) {
839 template<
class M,
class IS,
class A>
840 template<
class V,
class BA,
class TA>
843 assert(hierarchy.levels()==1);
845 typedef typename RedistributeInfoList::const_iterator RIter;
846 RIter redist = redistributes_.begin();
848 Iterator matrix = matrices_.finest(), coarsest = matrices_.coarsest();
850 if(redist->isSetup())
851 hierarchy.addRedistributedOnCoarsest(matrix.getRedistributed().getmat().N());
852 Dune::dvverb<<
"Level "<<level<<
" has "<<matrices_.finest()->getmat().N()<<
" unknowns!"<<std::endl;
854 while(matrix != coarsest) {
855 ++matrix; ++level; ++redist;
856 Dune::dvverb<<
"Level "<<level<<
" has "<<matrix->getmat().N()<<
" unknowns!"<<std::endl;
858 hierarchy.addCoarser(matrix->getmat().N());
859 if(redist->isSetup())
860 hierarchy.addRedistributedOnCoarsest(matrix.getRedistributed().getmat().N());
866 template<
class M,
class IS,
class A>
867 template<
class S,
class TA>
871 assert(smoothers.
levels()==0);
874 typedef typename AggregatesMapList::const_iterator AggregatesIterator;
877 cargs.setArgs(sargs);
878 PinfoIterator pinfo = parallelInformation_.finest();
879 AggregatesIterator aggregates = aggregatesMaps_.begin();
881 for(MatrixIterator matrix = matrices_.finest(), coarsest = matrices_.coarsest();
882 matrix != coarsest; ++matrix, ++pinfo, ++aggregates, ++level) {
883 cargs.setMatrix(matrix->getmat(), **aggregates);
884 cargs.setComm(*pinfo);
887 if(maxlevels()>levels()) {
889 cargs.setMatrix(matrices_.coarsest()->getmat(), **aggregates);
890 cargs.setComm(*pinfo);
896 template<
class M,
class IS,
class A>
900 typedef typename AggregatesMapList::iterator AggregatesMapIterator;
904 AggregatesMapIterator amap = aggregatesMaps_.begin();
905 BaseGalerkinProduct productBuilder;
906 InfoIterator info = parallelInformation_.finest();
907 typename RedistributeInfoList::iterator riIter = redistributes_.begin();
908 Iterator level = matrices_.finest(), coarsest=matrices_.coarsest();
909 if(level.isRedistributed()) {
910 info->buildGlobalLookup(level->getmat().N());
911 redistributeMatrixEntries(
const_cast<Matrix&
>(level->getmat()),
912 const_cast<Matrix&
>(level.getRedistributed().getmat()),
913 *info,info.getRedistributed(), *riIter);
914 info->freeGlobalLookup();
917 for(; level!=coarsest; ++amap) {
918 const Matrix& fine = (level.isRedistributed() ? level.getRedistributed() : *level).getmat();
922 productBuilder.calculate(fine, *(*amap),
const_cast<Matrix&
>(level->getmat()), *info, copyFlags);
923 if(level.isRedistributed()) {
924 info->buildGlobalLookup(level->getmat().N());
925 redistributeMatrixEntries(
const_cast<Matrix&
>(level->getmat()),
926 const_cast<Matrix&
>(level.getRedistributed().getmat()), *info,
927 info.getRedistributed(), *riIter);
928 info->freeGlobalLookup();
933 template<
class M,
class IS,
class A>
936 return matrices_.levels();
939 template<
class M,
class IS,
class A>
945 template<
class M,
class IS,
class A>
948 return levels()==maxlevels() &&
949 (!matrices_.coarsest().isRedistributed() ||matrices_.coarsest()->getmat().N()>0);
952 template<
class M,
class IS,
class A>
Provides classes for the Coloring process of AMG.
This file implements a vector space as a tensor product of a given vector space. The number of compon...
Class providing information about the mapping of the vertices onto aggregates.
Definition: aggregates.hh:558
Base class of all aggregation criterions.
Definition: aggregates.hh:47
The criterion describing the stop criteria for the coarsening process.
Definition: matrixhierarchy.hh:281
T AggregationCriterion
The criterion for tagging connections as strong and nodes as isolated. This might be e....
Definition: matrixhierarchy.hh:287
CoarsenCriterion(int maxLevel=100, int coarsenTarget=1000, double minCoarsenRate=1.2, double prolongDamp=1.6, AccumulationMode accumulate=successiveAccu)
Constructor.
Definition: matrixhierarchy.hh:299
LevelIterator< Hierarchy< MatrixOperator, Allocator >, MatrixOperator > Iterator
Type of the mutable iterator.
Definition: hierarchy.hh:214
LevelIterator< const Hierarchy< MatrixOperator, Allocator >, const MatrixOperator > ConstIterator
Type of the const iterator.
Definition: hierarchy.hh:217
The hierarchies build by the coarsening process.
Definition: matrixhierarchy.hh:59
typename std::allocator_traits< Allocator >::template rebind_alloc< AggregatesMap * > AAllocator
Allocator for pointers.
Definition: matrixhierarchy.hh:83
Dune::Amg::Hierarchy< ParallelInformation, Allocator > ParallelInformationHierarchy
The type of the parallel informarion hierarchy.
Definition: matrixhierarchy.hh:80
std::list< AggregatesMap *, AAllocator > AggregatesMapList
The type of the aggregates maps list.
Definition: matrixhierarchy.hh:86
PI ParallelInformation
The type of the index set.
Definition: matrixhierarchy.hh:68
Dune::Amg::Hierarchy< MatrixOperator, Allocator > ParallelMatrixHierarchy
The type of the parallel matrix hierarchy.
Definition: matrixhierarchy.hh:77
A Allocator
The allocator to use.
Definition: matrixhierarchy.hh:71
RedistributeInformation< ParallelInformation > RedistributeInfoType
The type of the redistribute information.
Definition: matrixhierarchy.hh:89
typename std::allocator_traits< Allocator >::template rebind_alloc< RedistributeInfoType > RILAllocator
Allocator for RedistributeInfoType.
Definition: matrixhierarchy.hh:92
std::list< RedistributeInfoType, RILAllocator > RedistributeInfoList
The type of the list of redistribute information.
Definition: matrixhierarchy.hh:95
Dune::Amg::AggregatesMap< typename MatrixGraph< Matrix >::VertexDescriptor > AggregatesMap
The type of the aggregates map we use.
Definition: matrixhierarchy.hh:74
MatrixOperator::matrix_type Matrix
The type of the matrix.
Definition: matrixhierarchy.hh:65
M MatrixOperator
The type of the matrix operator.
Definition: matrixhierarchy.hh:62
All parameters for AMG.
Definition: parameters.hh:391
Attaches properties to the edges and vertices of a graph.
Definition: graph.hh:976
Graph::VertexDescriptor VertexDescriptor
The vertex descriptor.
Definition: graph.hh:986
A vector of blocks with memory management.
Definition: bvector.hh:393
derive error class from the base class in common
Definition: istlexception.hh:17
Adapter to turn a random access iterator into a property map.
Definition: propertymap.hh:106
A generic dynamic dense matrix.
Definition: matrix.hh:559
A::size_type size_type
Type for indices and sizes.
Definition: matrix.hh:575
MatrixImp::DenseMatrixBase< T, A >::window_type row_type
The type implementing a matrix row.
Definition: matrix.hh:572
A simple stop watch.
Definition: timer.hh:41
void reset() noexcept
Reset timer while keeping the running/stopped state.
Definition: timer.hh:55
double elapsed() const noexcept
Get elapsed user-time from last reset until now/last stop in seconds.
Definition: timer.hh:75
Portable very large unsigned integers.
Definition: bigunsignedint.hh:71
Helper classes for the construction of classes without empty constructor.
Provides classes for initializing the link attributes of a matrix graph.
Provides a class for building the galerkin product based on a aggregation scheme.
Provdes class for identifying aggregates globally.
Provides classes for building the matrix graph.
#define DUNE_THROW(E, m)
Definition: exceptions.hh:216
constexpr T accumulate(Range &&range, T value, F &&f)
Accumulate values.
Definition: hybridutilities.hh:289
const AggregatesMapList & aggregatesMaps() const
Get the hierarchy of the mappings of the nodes onto aggregates.
Definition: matrixhierarchy.hh:812
bool isBuilt() const
Whether the hierarchy was built.
Definition: matrixhierarchy.hh:953
std::size_t levels() const
Get the number of levels in the hierarchy.
Definition: hierarchy.hh:320
std::size_t levels() const
Get the number of levels in the hierarchy.
Definition: matrixhierarchy.hh:934
void addCoarser(Arguments &args)
Add an element on a coarser level.
Definition: hierarchy.hh:332
const RedistributeInfoList & redistributeInformation() const
Get the hierarchy of the information about redistributions,.
Definition: matrixhierarchy.hh:818
const ParallelInformationHierarchy & parallelInformation() const
Get the hierarchy of the parallel data distribution information.
Definition: matrixhierarchy.hh:737
const ParallelMatrixHierarchy & matrices() const
Get the matrix hierarchy.
Definition: matrixhierarchy.hh:730
std::size_t maxlevels() const
Get the max number of levels in the hierarchy of processors.
Definition: matrixhierarchy.hh:940
static const V ISOLATED
Identifier of isolated vertices.
Definition: aggregates.hh:569
void recalculateGalerkin(const F ©Flags)
Recalculate the galerkin products.
Definition: matrixhierarchy.hh:898
const void * Arguments
A type holding all the arguments needed to call the constructor.
Definition: construction.hh:42
std::size_t noVertices() const
Get the number of vertices.
void coarsenVector(Hierarchy< BlockVector< V, BA >, TA > &hierarchy) const
Coarsen the vector hierarchy according to the matrix hierarchy.
Definition: matrixhierarchy.hh:841
MatrixHierarchy(std::shared_ptr< MatrixOperator > fineMatrix, std::shared_ptr< ParallelInformation > pinfo=std::make_shared< ParallelInformation >())
Constructor.
Definition: matrixhierarchy.hh:387
AccumulationMode
Identifiers for the different accumulation modes.
Definition: parameters.hh:230
void build(const T &criterion)
Build the matrix hierarchy using aggregation.
Definition: matrixhierarchy.hh:398
void free()
Free the allocated memory.
void coarsenSmoother(Hierarchy< S, TA > &smoothers, const typename SmootherTraits< S >::Arguments &args) const
Coarsen the smoother hierarchy according to the matrix hierarchy.
Definition: matrixhierarchy.hh:868
void buildDependency(G &graph, const typename C::Matrix &matrix, C criterion, bool finestLevel)
Build the dependency of the matrix graph.
std::tuple< int, int, int, int > buildAggregates(const M &matrix, G &graph, const C &criterion, bool finestLevel)
Build the aggregates.
void getCoarsestAggregatesOnFinest(std::vector< std::size_t > &data) const
Get the mapping of fine level unknowns to coarse level aggregates.
Definition: matrixhierarchy.hh:743
@ atOnceAccu
Accumulate data to one process at once.
Definition: parameters.hh:242
@ successiveAccu
Successively accumulate to fewer processes.
Definition: parameters.hh:246
@ MAX_PROCESSES
Hard limit for the number of processes allowed.
Definition: matrixhierarchy.hh:48
auto countNonZeros(const M &, typename std::enable_if_t< Dune::IsNumber< M >::value > *sfinae=nullptr)
Get the number of nonzero fields in the matrix.
Definition: matrixutils.hh:117
auto min(ADLTag< 0 >, const V &v1, const V &v2)
implements binary Simd::min()
Definition: defaults.hh:87
auto max(ADLTag< 0 >, const V &v1, const V &v2)
implements binary Simd::max()
Definition: defaults.hh:79
DVVerbType dvverb(std::cout)
stream for very verbose output.
Definition: stdstreams.hh:93
DInfoType dinfo(std::cout)
Stream for informative output.
Definition: stdstreams.hh:138
DVerbType dverb(std::cout)
Singleton of verbose debug stream.
Definition: stdstreams.hh:114
Provides a classes representing the hierarchies in AMG.
Provides a map between global and local indices.
Provides a class for building the index set and remote indices on the coarse level.
Functionality for redistributing a sparse matrix.
Some handy generic functions for ISTL matrices.
Dune namespace.
Definition: alignedallocator.hh:11
void redistributeMatrix(M &origMatrix, M &newMatrix, C &origComm, C &newComm, RedistributeInformation< C > &ri)
Redistribute a matrix according to given domain decompositions.
Definition: matrixredistribute.hh:818
bool graphRepartition(const G &graph, Dune::OwnerOverlapCopyCommunication< T1, T2 > &oocomm, Metis::idx_t nparts, std::shared_ptr< Dune::OwnerOverlapCopyCommunication< T1, T2 > > &outcomm, RedistributeInterface &redistInf, bool verbose=false)
execute a graph repartition for a giving graph and indexset.
Definition: repartition.hh:1233
Classes for the generic construction and application of the smoothers.
Traits class for generically constructing non default constructable types.
Definition: construction.hh:37
Traits class for getting the attribute class of a smoother.
Definition: smoother.hh:64
Tag idnetifying the visited property of a vertex.
Definition: properties.hh:27
A property map that applies the identity function to integers.
Definition: propertymap.hh:291
Selector for the property map type.
Definition: propertymap.hh:318
static Category category(const OP &op, decltype(op.category()) *=nullptr)
Helperfunction to extract the solver category either from an enum, or from the newly introduced virtu...
Definition: solvercategory.hh:32
Prolongation and restriction for amg.