5#ifndef DUNE_AMG_MATRIXHIERARCHY_HH
6#define DUNE_AMG_MATRIXHIERARCHY_HH
13#include "renumberer.hh"
14#include "graphcreator.hh"
59 template<
class M,
class PI,
class A=std::allocator<M> >
67 typedef typename MatrixOperator::matrix_type
Matrix;
85 using AAllocator =
typename std::allocator_traits<Allocator>::template rebind_alloc<AggregatesMap*>;
94 using RILAllocator =
typename std::allocator_traits<Allocator>::template rebind_alloc<RedistributeInfoType>;
105 std::shared_ptr<ParallelInformation> pinfo = std::make_shared<ParallelInformation>());
114 template<
typename O,
typename T>
115 void build(
const T& criterion);
131 template<
class V,
class BA,
class TA>
139 template<
class S,
class TA>
147 std::size_t
levels()
const;
155 bool hasCoarsest()
const;
188 double getProlongationDampingFactor()
const
228 template<
class Matrix,
bool pr
int>
235 static void stats([[maybe_unused]]
const Matrix& matrix)
239 template<
class Matrix>
240 struct MatrixStats<
Matrix,true>
254 void operator()(
const matrix_row& row)
268 static void stats(
const Matrix& matrix)
270 calc c= for_each(matrix.begin(), matrix.end(), calc());
271 dinfo<<
"Matrix row: min="<<c.min<<
" max="<<c.max
272 <<
" average="<<
static_cast<double>(c.sum)/matrix.N()
315 template<
typename M,
typename C1>
316 bool repartitionAndDistributeMatrix([[maybe_unused]]
const M& origMatrix,
317 [[maybe_unused]] std::shared_ptr<M> newMatrix,
318 [[maybe_unused]] SequentialInformation& origComm,
319 [[maybe_unused]] std::shared_ptr<SequentialInformation>& newComm,
320 [[maybe_unused]] RedistributeInformation<SequentialInformation>& ri,
321 [[maybe_unused]]
int nparts,
322 [[maybe_unused]] C1& criterion)
324 DUNE_THROW(NotImplemented,
"Redistribution does not make sense in sequential code!");
328 template<
typename M,
typename C,
typename C1>
329 bool repartitionAndDistributeMatrix(
const M& origMatrix,
330 std::shared_ptr<M> newMatrix,
332 std::shared_ptr<C>& newComm,
333 RedistributeInformation<C>& ri,
334 int nparts, C1& criterion)
337#ifdef AMG_REPART_ON_COMM_GRAPH
339 bool existentOnRedist=Dune::commGraphRepartition(origMatrix, origComm, nparts, newComm,
341 criterion.debugLevel()>1);
349 IdentityMap> PropertiesGraph;
350 MatrixGraph graph(origMatrix);
351 PropertiesGraph pgraph(graph);
355 if(origComm.communicator().rank()==0)
356 std::cout<<
"Original matrix"<<std::endl;
357 origComm.communicator().barrier();
358 printGlobalSparseMatrix(origMatrix, origComm, std::cout);
361 newComm, ri.getInterface(),
362 criterion.debugLevel()>1);
365 if(origComm.communicator().rank()==0 && criterion.debugLevel()>1)
366 std::cout<<
"Repartitioning took "<<time.elapsed()<<
" seconds."<<std::endl;
371 ri.checkInterface(origComm.indexSet(), newComm->indexSet(), origComm.communicator());
377 if(origComm.communicator().rank()==0)
378 std::cout<<
"Original matrix"<<std::endl;
379 origComm.communicator().barrier();
380 if(newComm->communicator().size()>0)
381 printGlobalSparseMatrix(*newMatrix, *newComm, std::cout);
382 origComm.communicator().barrier();
385 if(origComm.communicator().rank()==0 && criterion.debugLevel()>1)
386 std::cout<<
"Redistributing matrix took "<<time.elapsed()<<
" seconds."<<std::endl;
387 return existentOnRedist;
391 template<
class M,
class IS,
class A>
393 std::shared_ptr<ParallelInformation> pinfo)
394 : matrices_(fineMatrix),
395 parallelInformation_(pinfo)
398 DUNE_THROW(
ISTLError,
"MatrixOperator and ParallelInformation must belong to the same category!");
401 template<
class M,
class IS,
class A>
402 template<
typename O,
typename T>
405 prolongDamp_ = criterion.getProlongationDampingFactor();
406 typedef O OverlapFlags;
413 GalerkinProduct<ParallelInformation> productBuilder;
414 MatIterator mlevel = matrices_.finest();
415 MatrixStats<typename M::matrix_type,MINIMAL_DEBUG_LEVEL<=INFO_DEBUG_LEVEL>::stats(mlevel->getmat());
417 PInfoIterator infoLevel = parallelInformation_.finest();
419 finenonzeros = infoLevel->communicator().sum(finenonzeros);
420 BIGINT allnonzeros = finenonzeros;
426 BIGINT unknowns = mlevel->getmat().N();
428 unknowns = infoLevel->communicator().sum(unknowns);
429 double dunknowns=unknowns.todouble();
430 infoLevel->buildGlobalLookup(mlevel->getmat().N());
433 for(; level < criterion.maxLevel(); ++level, ++mlevel) {
434 assert(matrices_.levels()==redistributes_.size());
435 rank = infoLevel->communicator().rank();
436 if(rank==0 && criterion.debugLevel()>1)
437 std::cout<<
"Level "<<level<<
" has "<<dunknowns<<
" unknowns, "<<dunknowns/infoLevel->communicator().size()
438 <<
" unknowns per proc (procs="<<infoLevel->communicator().size()<<
")"<<std::endl;
450 && dunknowns < 30*infoLevel->communicator().
size()))
451 && infoLevel->communicator().size()>1 &&
452 dunknowns/infoLevel->communicator().size() <= criterion.coarsenTarget())
455 std::shared_ptr<Matrix> redistMat = std::make_shared<Matrix>();
456 std::shared_ptr<ParallelInformation> redistComm;
457 std::size_t nodomains = (std::size_t)std::ceil(dunknowns/(criterion.minAggregateSize()
458 *criterion.coarsenTarget()));
459 if( nodomains<=criterion.minAggregateSize()/2 ||
460 dunknowns <= criterion.coarsenTarget() )
463 bool existentOnNextLevel =
464 repartitionAndDistributeMatrix(mlevel->getmat(), redistMat, *infoLevel,
465 redistComm, redistributes_.back(), nodomains,
467 BIGINT unknownsRedist = redistMat->N();
468 unknownsRedist = infoLevel->communicator().sum(unknownsRedist);
469 dunknowns= unknownsRedist.todouble();
470 if(redistComm->communicator().rank()==0 && criterion.debugLevel()>1)
471 std::cout<<
"Level "<<level<<
" (redistributed) has "<<dunknowns<<
" unknowns, "<<dunknowns/redistComm->communicator().size()
472 <<
" unknowns per proc (procs="<<redistComm->communicator().size()<<
")"<<std::endl;
473 MatrixArgs args(redistMat, *redistComm);
475 assert(mlevel.isRedistributed());
476 infoLevel.addRedistributed(redistComm);
477 infoLevel->freeGlobalLookup();
479 if(!existentOnNextLevel)
484 matrix = &(mlevel.getRedistributed());
485 info = &(infoLevel.getRedistributed());
486 info->buildGlobalLookup(matrix->getmat().N());
489 rank = info->communicator().rank();
490 if(dunknowns <= criterion.coarsenTarget())
494 typedef PropertiesGraphCreator<MatrixOperator,ParallelInformation> GraphCreator;
496 typedef typename GraphCreator::GraphTuple GraphTuple;
500 std::vector<bool> excluded(matrix->getmat().N(),
false);
502 GraphTuple graphs = GraphCreator::create(*matrix, excluded, *info, OverlapFlags());
506 aggregatesMaps_.push_back(aggregatesMap);
510 auto [noAggregates, isoAggregates, oneAggregates, skippedAggregates] =
511 aggregatesMap->
buildAggregates(matrix->getmat(), *(std::get<1>(graphs)), criterion, level==0);
513 if(rank==0 && criterion.debugLevel()>2)
514 std::cout<<
" Have built "<<noAggregates<<
" aggregates totally ("<<isoAggregates<<
" isolated aggregates, "<<
515 oneAggregates<<
" aggregates of one vertex, and skipped "<<
516 skippedAggregates<<
" aggregates)."<<std::endl;
520 int start, end, overlapStart, overlapEnd;
521 int procs=info->communicator().rank();
522 int n = UNKNOWNS/procs;
523 int bigger = UNKNOWNS%procs;
528 end = (rank+1)*(n+1);
530 start = bigger + rank * n;
531 end = bigger + (rank + 1) * n;
536 overlapStart = start - 1;
538 overlapStart = start;
541 overlapEnd = end + 1;
545 assert((UNKNOWNS)*(overlapEnd-overlapStart)==aggregatesMap->
noVertices());
546 for(
int j=0; j< UNKNOWNS; ++j)
547 for(
int i=0; i < UNKNOWNS; ++i)
549 if(i>=overlapStart && i<overlapEnd)
551 int no = (j/2)*((UNKNOWNS)/2)+i/2;
552 (*aggregatesMap)[j*(overlapEnd-overlapStart)+i-overlapStart]=no;
557 if(criterion.debugLevel()>1 && info->communicator().rank()==0)
558 std::cout<<
"aggregating finished."<<std::endl;
560 BIGINT gnoAggregates=noAggregates;
561 gnoAggregates = info->communicator().sum(gnoAggregates);
562 double dgnoAggregates = gnoAggregates.todouble();
564 BIGINT gnoAggregates=((UNKNOWNS)/2)*((UNKNOWNS)/2);
567 if(criterion.debugLevel()>2 && rank==0)
568 std::cout <<
"Building "<<dgnoAggregates<<
" aggregates took "<<watch.
elapsed()<<
" seconds."<<std::endl;
570 if(dgnoAggregates==0 || dunknowns/dgnoAggregates<criterion.minCoarsenRate())
575 std::cerr <<
"Stopped coarsening because of rate breakdown "<<dunknowns<<
"/"<<dgnoAggregates
576 <<
"="<<dunknowns/dgnoAggregates<<
"<"
577 <<criterion.minCoarsenRate()<<std::endl;
579 std::cerr<<
"Could not build any aggregates. Probably no connected nodes."<<std::endl;
581 aggregatesMap->
free();
582 delete aggregatesMap;
583 aggregatesMaps_.pop_back();
585 if(criterion.accumulate() && mlevel.isRedistributed() && info->communicator().size()>1) {
589 delete &(mlevel.getRedistributed().getmat());
590 mlevel.deleteRedistributed();
591 delete &(infoLevel.getRedistributed());
592 infoLevel.deleteRedistributed();
593 redistributes_.back().resetSetup();
598 unknowns = noAggregates;
599 dunknowns = dgnoAggregates;
601 CommunicationArgs commargs(info->communicator(),info->category());
602 parallelInformation_.addCoarser(commargs);
610 int aggregates = IndicesCoarsener<ParallelInformation,OverlapFlags>
612 *(std::get<1>(graphs)),
617 criterion.useFixedOrder());
618 GraphCreator::free(graphs);
620 if(criterion.debugLevel()>2) {
622 std::cout<<
"Coarsening of index sets took "<<watch.
elapsed()<<
" seconds."<<std::endl;
627 infoLevel->buildGlobalLookup(aggregates);
628 AggregatesPublisher<Vertex,OverlapFlags,ParallelInformation>::publish(*aggregatesMap,
630 infoLevel->globalLookup());
633 if(criterion.debugLevel()>2) {
635 std::cout<<
"Communicating global aggregate numbers took "<<watch.
elapsed()<<
" seconds."<<std::endl;
639 std::vector<bool>& visited=excluded;
641 typedef std::vector<bool>::iterator Iterator;
643 Iterator end = visited.end();
644 for(Iterator iter= visited.begin(); iter != end; ++iter)
649 std::shared_ptr<typename MatrixOperator::matrix_type>
650 coarseMatrix(productBuilder.build(*(std::get<0>(graphs)), visitedMap2,
655 dverb<<
"Building of sparsity pattern took "<<watch.
elapsed()<<std::endl;
657 info->freeGlobalLookup();
659 delete std::get<0>(graphs);
660 productBuilder.calculate(matrix->getmat(), *aggregatesMap, *coarseMatrix, *infoLevel, OverlapFlags());
662 if(criterion.debugLevel()>2) {
664 std::cout<<
"Calculation entries of Galerkin product took "<<watch.
elapsed()<<
" seconds."<<std::endl;
668 allnonzeros = allnonzeros + infoLevel->communicator().sum(nonzeros);
669 MatrixArgs args(coarseMatrix, *infoLevel);
671 matrices_.addCoarser(args);
676 infoLevel->freeGlobalLookup();
680 aggregatesMaps_.push_back(aggregatesMap);
682 if(criterion.debugLevel()>0) {
683 if(level==criterion.maxLevel()) {
684 BIGINT unknownsLevel = mlevel->getmat().N();
685 unknownsLevel = infoLevel->communicator().sum(unknownsLevel);
686 if(rank==0 && criterion.debugLevel()>1) {
687 double dunknownsLevel = unknownsLevel.todouble();
688 std::cout<<
"Level "<<level<<
" has "<<dunknownsLevel<<
" unknowns, "<<dunknownsLevel/infoLevel->communicator().size()
689 <<
" unknowns per proc (procs="<<infoLevel->communicator().size()<<
")"<<std::endl;
694 if(criterion.accumulate() && !redistributes_.back().isSetup() &&
695 infoLevel->communicator().size()>1) {
696#if HAVE_MPI && !HAVE_PARMETIS
698 infoLevel->communicator().rank()==0)
699 std::cerr<<
"Successive accumulation of data on coarse levels only works with ParMETIS installed."
700 <<
" Fell back to accumulation to one domain on coarsest level"<<std::endl;
704 std::shared_ptr<Matrix> redistMat = std::make_shared<Matrix>();
705 std::shared_ptr<ParallelInformation> redistComm;
708 repartitionAndDistributeMatrix(mlevel->getmat(), redistMat, *infoLevel,
709 redistComm, redistributes_.back(), nodomains,criterion);
710 MatrixArgs args(redistMat, *redistComm);
711 BIGINT unknownsRedist = redistMat->N();
712 unknownsRedist = infoLevel->communicator().sum(unknownsRedist);
714 if(redistComm->communicator().rank()==0 && criterion.debugLevel()>1) {
715 double dunknownsRedist = unknownsRedist.todouble();
716 std::cout<<
"Level "<<level<<
" redistributed has "<<dunknownsRedist<<
" unknowns, "<<dunknownsRedist/redistComm->communicator().size()
717 <<
" unknowns per proc (procs="<<redistComm->communicator().size()<<
")"<<std::endl;
720 infoLevel.addRedistributed(redistComm);
721 infoLevel->freeGlobalLookup();
724 int levels = matrices_.levels();
725 maxlevels_ = parallelInformation_.finest()->communicator().max(levels);
726 assert(matrices_.levels()==redistributes_.size());
727 if(hasCoarsest() && rank==0 && criterion.debugLevel()>1)
728 std::cout<<
"operator complexity: "<<allnonzeros.todouble()/finenonzeros.todouble()<<std::endl;
732 template<
class M,
class IS,
class A>
739 template<
class M,
class IS,
class A>
743 return parallelInformation_;
746 template<
class M,
class IS,
class A>
749 int levels=aggregatesMaps().size();
750 int maxlevels=parallelInformation_.finest()->communicator().max(levels);
751 std::size_t
size=(*(aggregatesMaps().begin()))->noVertices();
753 std::vector<std::size_t> tmp;
754 std::vector<std::size_t> *coarse, *fine;
771 if(levels==maxlevels) {
772 const AggregatesMap& map = *(*(++aggregatesMaps().rbegin()));
775 for(
typename AggregatesMap::const_iterator iter = map.begin(); iter != map.end(); ++iter)
781 srand((
unsigned)std::clock());
782 std::set<size_t> used;
783 for(
typename std::vector<std::size_t>::iterator iter=coarse->begin(); iter != coarse->end();
786 std::pair<std::set<std::size_t>::iterator,
bool> ibpair
787 = used.insert(
static_cast<std::size_t
>((((
double)rand())/(RAND_MAX+1.0)))*coarse->size());
789 while(!ibpair.second)
790 ibpair = used.insert(
static_cast<std::size_t
>((((
double)rand())/(RAND_MAX+1.0))*coarse->size()));
791 *iter=*(ibpair.first);
799 for(
typename AggregatesMapList::const_reverse_iterator aggregates=++aggregatesMaps().rbegin();
800 aggregates != aggregatesMaps().rend(); ++aggregates,--levels) {
802 fine->resize((*aggregates)->noVertices());
803 fine->assign(fine->size(), 0);
804 Transfer<typename AggregatesMap::AggregateDescriptor, std::vector<std::size_t>,
ParallelInformation>
805 ::prolongateVector(*(*aggregates), *coarse, *fine,
static_cast<std::size_t
>(1), *pinfo);
807 std::swap(coarse, fine);
811 assert(coarse==&data);
814 template<
class M,
class IS,
class A>
818 return aggregatesMaps_;
820 template<
class M,
class IS,
class A>
824 return redistributes_;
827 template<
class M,
class IS,
class A>
830 typedef typename AggregatesMapList::reverse_iterator AggregatesMapIterator;
831 typedef typename ParallelMatrixHierarchy::Iterator Iterator;
832 typedef typename ParallelInformationHierarchy::Iterator InfoIterator;
834 AggregatesMapIterator amap = aggregatesMaps_.rbegin();
835 InfoIterator info = parallelInformation_.coarsest();
836 for(Iterator level=matrices_.coarsest(), finest=matrices_.finest(); level != finest; --level, --info, ++amap) {
843 template<
class M,
class IS,
class A>
844 template<
class V,
class BA,
class TA>
847 assert(hierarchy.levels()==1);
849 typedef typename RedistributeInfoList::const_iterator RIter;
850 RIter redist = redistributes_.begin();
852 Iterator matrix = matrices_.finest(), coarsest = matrices_.coarsest();
854 if(redist->isSetup())
855 hierarchy.addRedistributedOnCoarsest(matrix.getRedistributed().getmat().N());
856 Dune::dvverb<<
"Level "<<level<<
" has "<<matrices_.finest()->getmat().N()<<
" unknowns!"<<std::endl;
858 while(matrix != coarsest) {
859 ++matrix; ++level; ++redist;
860 Dune::dvverb<<
"Level "<<level<<
" has "<<matrix->getmat().N()<<
" unknowns!"<<std::endl;
862 hierarchy.addCoarser(matrix->getmat().N());
863 if(redist->isSetup())
864 hierarchy.addRedistributedOnCoarsest(matrix.getRedistributed().getmat().N());
870 template<
class M,
class IS,
class A>
871 template<
class S,
class TA>
875 assert(smoothers.
levels()==0);
878 typedef typename AggregatesMapList::const_iterator AggregatesIterator;
881 cargs.setArgs(sargs);
882 PinfoIterator pinfo = parallelInformation_.finest();
883 AggregatesIterator aggregates = aggregatesMaps_.begin();
885 for(MatrixIterator matrix = matrices_.finest(), coarsest = matrices_.coarsest();
886 matrix != coarsest; ++matrix, ++pinfo, ++aggregates, ++level) {
887 cargs.setMatrix(matrix->getmat(), **aggregates);
888 cargs.setComm(*pinfo);
891 if(maxlevels()>levels()) {
893 cargs.setMatrix(matrices_.coarsest()->getmat(), **aggregates);
894 cargs.setComm(*pinfo);
900 template<
class M,
class IS,
class A>
904 typedef typename AggregatesMapList::iterator AggregatesMapIterator;
908 AggregatesMapIterator amap = aggregatesMaps_.begin();
909 BaseGalerkinProduct productBuilder;
910 InfoIterator info = parallelInformation_.finest();
911 typename RedistributeInfoList::iterator riIter = redistributes_.begin();
912 Iterator level = matrices_.finest(), coarsest=matrices_.coarsest();
913 if(level.isRedistributed()) {
914 info->buildGlobalLookup(level->getmat().N());
915 redistributeMatrixEntries(
const_cast<Matrix&
>(level->getmat()),
916 const_cast<Matrix&
>(level.getRedistributed().getmat()),
917 *info,info.getRedistributed(), *riIter);
918 info->freeGlobalLookup();
921 for(; level!=coarsest; ++amap) {
922 const Matrix& fine = (level.isRedistributed() ? level.getRedistributed() : *level).getmat();
926 productBuilder.calculate(fine, *(*amap),
const_cast<Matrix&
>(level->getmat()), *info, copyFlags);
927 if(level.isRedistributed()) {
928 info->buildGlobalLookup(level->getmat().N());
929 redistributeMatrixEntries(
const_cast<Matrix&
>(level->getmat()),
930 const_cast<Matrix&
>(level.getRedistributed().getmat()), *info,
931 info.getRedistributed(), *riIter);
932 info->freeGlobalLookup();
937 template<
class M,
class IS,
class A>
940 return matrices_.levels();
943 template<
class M,
class IS,
class A>
949 template<
class M,
class IS,
class A>
952 return levels()==maxlevels() &&
953 (!matrices_.coarsest().isRedistributed() ||matrices_.coarsest()->getmat().N()>0);
956 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:560
Base class of all aggregation criterions.
Definition: aggregates.hh:49
The criterion describing the stop criteria for the coarsening process.
Definition: matrixhierarchy.hh:283
T AggregationCriterion
The criterion for tagging connections as strong and nodes as isolated. This might be e....
Definition: matrixhierarchy.hh:289
CoarsenCriterion(int maxLevel=100, int coarsenTarget=1000, double minCoarsenRate=1.2, double prolongDamp=1.6, AccumulationMode accumulate=successiveAccu, bool useFixedOrder=false)
Constructor.
Definition: matrixhierarchy.hh:304
LevelIterator< Hierarchy< MatrixOperator, Allocator >, MatrixOperator > Iterator
Type of the mutable iterator.
Definition: hierarchy.hh:220
LevelIterator< const Hierarchy< MatrixOperator, Allocator >, const MatrixOperator > ConstIterator
Type of the const iterator.
Definition: hierarchy.hh:223
The hierarchies build by the coarsening process.
Definition: matrixhierarchy.hh:61
typename std::allocator_traits< Allocator >::template rebind_alloc< AggregatesMap * > AAllocator
Allocator for pointers.
Definition: matrixhierarchy.hh:85
Dune::Amg::Hierarchy< ParallelInformation, Allocator > ParallelInformationHierarchy
The type of the parallel informarion hierarchy.
Definition: matrixhierarchy.hh:82
std::list< AggregatesMap *, AAllocator > AggregatesMapList
The type of the aggregates maps list.
Definition: matrixhierarchy.hh:88
PI ParallelInformation
The type of the index set.
Definition: matrixhierarchy.hh:70
Dune::Amg::Hierarchy< MatrixOperator, Allocator > ParallelMatrixHierarchy
The type of the parallel matrix hierarchy.
Definition: matrixhierarchy.hh:79
A Allocator
The allocator to use.
Definition: matrixhierarchy.hh:73
RedistributeInformation< ParallelInformation > RedistributeInfoType
The type of the redistribute information.
Definition: matrixhierarchy.hh:91
typename std::allocator_traits< Allocator >::template rebind_alloc< RedistributeInfoType > RILAllocator
Allocator for RedistributeInfoType.
Definition: matrixhierarchy.hh:94
std::list< RedistributeInfoType, RILAllocator > RedistributeInfoList
The type of the list of redistribute information.
Definition: matrixhierarchy.hh:97
Dune::Amg::AggregatesMap< typename MatrixGraph< Matrix >::VertexDescriptor > AggregatesMap
The type of the aggregates map we use.
Definition: matrixhierarchy.hh:76
MatrixOperator::matrix_type Matrix
The type of the matrix.
Definition: matrixhierarchy.hh:67
M MatrixOperator
The type of the matrix operator.
Definition: matrixhierarchy.hh:64
All parameters for AMG.
Definition: parameters.hh:416
Attaches properties to the edges and vertices of a graph.
Definition: graph.hh:978
Graph::VertexDescriptor VertexDescriptor
The vertex descriptor.
Definition: graph.hh:988
A vector of blocks with memory management.
Definition: bvector.hh:392
derive error class from the base class in common
Definition: istlexception.hh:19
Adapter to turn a random access iterator into a property map.
Definition: propertymap.hh:108
A generic dynamic dense matrix.
Definition: matrix.hh:561
A::size_type size_type
Type for indices and sizes.
Definition: matrix.hh:577
MatrixImp::DenseMatrixBase< T, A >::window_type row_type
The type implementing a matrix row.
Definition: matrix.hh:574
A simple stop watch.
Definition: timer.hh:43
void reset() noexcept
Reset timer while keeping the running/stopped state.
Definition: timer.hh:57
double elapsed() const noexcept
Get elapsed user-time from last reset until now/last stop in seconds.
Definition: timer.hh:77
Portable very large unsigned integers.
Definition: bigunsignedint.hh:73
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,...)
Definition: exceptions.hh:312
constexpr auto max
Function object that returns the greater of the given values.
Definition: hybridutilities.hh:484
constexpr auto min
Function object that returns the smaller of the given values.
Definition: hybridutilities.hh:506
constexpr T accumulate(Range &&range, T value, F &&f)
Accumulate values.
Definition: hybridutilities.hh:279
const AggregatesMapList & aggregatesMaps() const
Get the hierarchy of the mappings of the nodes onto aggregates.
Definition: matrixhierarchy.hh:816
bool isBuilt() const
Whether the hierarchy was built.
Definition: matrixhierarchy.hh:957
std::size_t levels() const
Get the number of levels in the hierarchy.
Definition: hierarchy.hh:326
std::size_t levels() const
Get the number of levels in the hierarchy.
Definition: matrixhierarchy.hh:938
void addCoarser(Arguments &args)
Add an element on a coarser level.
Definition: hierarchy.hh:338
const RedistributeInfoList & redistributeInformation() const
Get the hierarchy of the information about redistributions,.
Definition: matrixhierarchy.hh:822
const ParallelInformationHierarchy & parallelInformation() const
Get the hierarchy of the parallel data distribution information.
Definition: matrixhierarchy.hh:741
const ParallelMatrixHierarchy & matrices() const
Get the matrix hierarchy.
Definition: matrixhierarchy.hh:734
std::size_t maxlevels() const
Get the max number of levels in the hierarchy of processors.
Definition: matrixhierarchy.hh:944
static const V ISOLATED
Identifier of isolated vertices.
Definition: aggregates.hh:571
void recalculateGalerkin(const F ©Flags)
Recalculate the galerkin products.
Definition: matrixhierarchy.hh:902
const void * Arguments
A type holding all the arguments needed to call the constructor.
Definition: construction.hh:44
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:845
MatrixHierarchy(std::shared_ptr< MatrixOperator > fineMatrix, std::shared_ptr< ParallelInformation > pinfo=std::make_shared< ParallelInformation >())
Constructor.
Definition: matrixhierarchy.hh:392
AccumulationMode
Identifiers for the different accumulation modes.
Definition: parameters.hh:231
void build(const T &criterion)
Build the matrix hierarchy using aggregation.
Definition: matrixhierarchy.hh:403
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:872
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:747
@ MAX_PROCESSES
Hard limit for the number of processes allowed.
Definition: matrixhierarchy.hh:50
@ atOnceAccu
Accumulate data to one process at once.
Definition: parameters.hh:243
@ successiveAccu
Successively accumulate to fewer processes.
Definition: parameters.hh:247
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:119
DVVerbType dvverb(std::cout)
stream for very verbose output.
Definition: stdstreams.hh:96
DInfoType dinfo(std::cout)
Stream for informative output.
Definition: stdstreams.hh:141
DVerbType dverb(std::cout)
Singleton of verbose debug stream.
Definition: stdstreams.hh:117
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:13
constexpr std::integral_constant< std::size_t, sizeof...(II)> size(std::integer_sequence< T, II... >)
Return the size of the sequence.
Definition: integersequence.hh:75
void redistributeMatrix(M &origMatrix, M &newMatrix, C &origComm, C &newComm, RedistributeInformation< C > &ri)
Redistribute a matrix according to given domain decompositions.
Definition: matrixredistribute.hh:820
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:1228
constexpr auto get(std::integer_sequence< T, II... >, std::integral_constant< std::size_t, pos >={})
Return the entry at position pos of the given sequence.
Definition: integersequence.hh:22
Classes for the generic construction and application of the smoothers.
Traits class for generically constructing non default constructable types.
Definition: construction.hh:39
Traits class for getting the attribute class of a smoother.
Definition: smoother.hh:66
Tag idnetifying the visited property of a vertex.
Definition: properties.hh:29
A property map that applies the identity function to integers.
Definition: propertymap.hh:293
Selector for the property map type.
Definition: propertymap.hh:320
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:34
Prolongation and restriction for amg.