void EmergencyAggregationAlgorithm<LocalOrdinal, GlobalOrdinal, Node, LocalMatOps>::BuildAggregates(const ParameterList& params, const GraphBase& graph, Aggregates& aggregates, std::vector<unsigned>& aggStat, LO& numNonAggregatedNodes) const {
Monitor m(*this, "BuildAggregates");
// vertex ids for output
ArrayRCP<LO> vertex2AggId = aggregates.GetVertex2AggId()->getDataNonConst(0);
ArrayRCP<LO> procWinner = aggregates.GetProcWinner() ->getDataNonConst(0);
const LO nRows = graph.GetNodeNumVertices();
const int myRank = graph.GetComm()->getRank();
int aggIndex = -1;
size_t aggSize = 0;
std::vector<int> aggList(graph.getNodeMaxNumRowEntries());
LO nLocalAggregates = aggregates.GetNumAggregates();
for (LO iNode = 0; iNode < nRows; iNode++) {
if (aggStat[iNode] != NodeStats::AGGREGATED) {
aggSize = 0;
aggregates.SetIsRoot(iNode);
aggList[aggSize++] = iNode;
aggIndex = nLocalAggregates++;
ArrayView<const LO> neighOfINode = graph.getNeighborVertices(iNode);
for (LO j = 0; j < neighOfINode.size(); j++) {
LO neigh = neighOfINode[j];
if (neigh != iNode && graph.isLocalNeighborVertex(neigh) && aggStat[neigh] != NodeStats::AGGREGATED)
aggList[aggSize++] = neigh;
}
// finalize aggregate
for (size_t k = 0; k < aggSize; k++) {
aggStat [aggList[k]] = NodeStats::AGGREGATED;
vertex2AggId[aggList[k]] = aggIndex;
procWinner [aggList[k]] = myRank;
}
numNonAggregatedNodes -= aggSize;
}
}
aggregates.SetNumAggregates(nLocalAggregates);
}
void AggregationPhase1Algorithm_kokkos<LocalOrdinal, GlobalOrdinal, Node>::
BuildAggregates(const ParameterList& params, const LWGraph_kokkos& graph, Aggregates_kokkos& aggregates, std::vector<unsigned>& aggStat,
LO& numNonAggregatedNodes) const {
Monitor m(*this, "BuildAggregates");
std::string ordering = params.get<std::string>("aggregation: ordering");
int maxNeighAlreadySelected = params.get<int> ("aggregation: max selected neighbors");
int minNodesPerAggregate = params.get<int> ("aggregation: min agg size");
int maxNodesPerAggregate = params.get<int> ("aggregation: max agg size");
TEUCHOS_TEST_FOR_EXCEPTION(maxNodesPerAggregate < minNodesPerAggregate, Exceptions::RuntimeError,
"MueLu::UncoupledAggregationAlgorithm::BuildAggregates: minNodesPerAggregate must be smaller or equal to MaxNodePerAggregate!");
const LO numRows = graph.GetNodeNumVertices();
const int myRank = graph.GetComm()->getRank();
ArrayRCP<LO> vertex2AggId = aggregates.GetVertex2AggId()->getDataNonConst(0);
ArrayRCP<LO> procWinner = aggregates.GetProcWinner() ->getDataNonConst(0);
LO numLocalAggregates = aggregates.GetNumAggregates();
ArrayRCP<LO> randomVector;
if (ordering == "random") {
randomVector = arcp<LO>(numRows);
for (LO i = 0; i < numRows; i++)
randomVector[i] = i;
RandomReorder(randomVector);
}
int aggIndex = -1;
size_t aggSize = 0;
std::vector<int> aggList(graph.getNodeMaxNumRowEntries());
std::queue<LO> graphOrderQueue;
// Main loop over all local rows of graph(A)
for (LO i = 0; i < numRows; i++) {
// Step 1: pick the next node to aggregate
LO rootCandidate = 0;
if (ordering == "natural") rootCandidate = i;
else if (ordering == "random") rootCandidate = randomVector[i];
else if (ordering == "graph") {
if (graphOrderQueue.size() == 0) {
// Current queue is empty for "graph" ordering, populate with one READY node
for (LO jnode = 0; jnode < numRows; jnode++)
if (aggStat[jnode] == READY) {
graphOrderQueue.push(jnode);
break;
}
}
if (graphOrderQueue.size() == 0) {
// There are no more ready nodes, end the phase
break;
}
rootCandidate = graphOrderQueue.front(); // take next node from graph ordering queue
graphOrderQueue.pop(); // delete this node in list
}
if (aggStat[rootCandidate] != READY)
continue;
// Step 2: build tentative aggregate
aggSize = 0;
aggList[aggSize++] = rootCandidate;
// TODO replace me
//ArrayView<const LO> neighOfINode = graph.getNeighborVertices(rootCandidate);
ArrayView<const LO> neighOfINode;
// If the number of neighbors is less than the minimum number of nodes
// per aggregate, we know this is not going to be a valid root, and we
// may skip it, but only for "natural" and "random" (for "graph" we still
// need to fetch the list of local neighbors to continue)
if ((ordering == "natural" || ordering == "random") &&
neighOfINode.size() < minNodesPerAggregate) {
continue;
}
LO numAggregatedNeighbours = 0;
for (int j = 0; j < neighOfINode.size(); j++) {
LO neigh = neighOfINode[j];
if (neigh != rootCandidate && graph.isLocalNeighborVertex(neigh)) {
if (aggStat[neigh] == READY || aggStat[neigh] == NOTSEL) {
// If aggregate size does not exceed max size, add node to the
// tentative aggregate
// NOTE: We do not exit the loop over all neighbours since we have
// still to count all aggregated neighbour nodes for the
// aggregation criteria
// NOTE: We check here for the maximum aggregation size. If we
// would do it below with all the other check too big aggregates
// would not be accepted at all.
if (aggSize < as<size_t>(maxNodesPerAggregate))
aggList[aggSize++] = neigh;
} else {
numAggregatedNeighbours++;
}
}
}
// Step 3: check if tentative aggregate is acceptable
if ((numAggregatedNeighbours <= maxNeighAlreadySelected) && // too many connections to other aggregates
(aggSize >= as<size_t>(minNodesPerAggregate))) { // too few nodes in the tentative aggregate
// Accept new aggregate
// rootCandidate becomes the root of the newly formed aggregate
aggregates.SetIsRoot(rootCandidate);
aggIndex = numLocalAggregates++;
for (size_t k = 0; k < aggSize; k++) {
aggStat [aggList[k]] = AGGREGATED;
vertex2AggId[aggList[k]] = aggIndex;
procWinner [aggList[k]] = myRank;
}
numNonAggregatedNodes -= aggSize;
} else {
// Aggregate is not accepted
aggStat[rootCandidate] = NOTSEL;
// Need this for the "graph" ordering below
// The original candidate is always aggList[0]
aggSize = 1;
}
if (ordering == "graph") {
// Add candidates to the list of nodes
// NOTE: the code have slightly different meanings depending on context:
// - if aggregate was accepted, we add neighbors of neighbors of the original candidate
// - if aggregate was not accepted, we add neighbors of the original candidate
for (size_t k = 0; k < aggSize; k++) {
// TODO replace this
//ArrayView<const LO> neighOfJNode = graph.getNeighborVertices(aggList[k]);
ArrayView<const LO> neighOfJNode;
for (int j = 0; j < neighOfJNode.size(); j++) {
LO neigh = neighOfJNode[j];
if (graph.isLocalNeighborVertex(neigh) && aggStat[neigh] == READY)
graphOrderQueue.push(neigh);
}
}
}
}
// Reset all NOTSEL vertices to READY
// This simplifies other algorithms
for (LO i = 0; i < numRows; i++)
if (aggStat[i] == NOTSEL)
aggStat[i] = READY;
// update aggregate object
aggregates.SetNumAggregates(numLocalAggregates);
}
void UncoupledAggregationAlgorithm<LocalOrdinal, GlobalOrdinal, Node, LocalMatOps>::
BuildAggregates(const ParameterList& params, const GraphBase& graph, Aggregates& aggregates, std::vector<unsigned>& aggStat,
LO& numNonAggregatedNodes) const {
Monitor m(*this, "BuildAggregates");
AggOptions::Ordering ordering = params.get<AggOptions::Ordering>("Ordering");
LO MaxNeighAlreadySelected = params.get<LO> ("MaxNeighAlreadySelected");
LO MinNodesPerAggregate = params.get<LO> ("MinNodesPerAggregate");
LO MaxNodesPerAggregate = params.get<LO> ("MaxNodesPerAggregate");
TEUCHOS_TEST_FOR_EXCEPTION(MaxNodesPerAggregate < MinNodesPerAggregate, Exceptions::RuntimeError, "MueLu::UncoupledAggregationAlgorithm::BuildAggregates: MinNodesPerAggregate must be smaller or equal to MaxNodePerAggregate!");
if (ordering != NATURAL && ordering != RANDOM && ordering != GRAPH)
throw Exceptions::RuntimeError("UncoupledAggregation::BuildAggregates : bad aggregation ordering option");
const LO nRows = graph.GetNodeNumVertices();
const int myRank = graph.GetComm()->getRank();
// vertex ids for output
Teuchos::ArrayRCP<LO> vertex2AggId = aggregates.GetVertex2AggId()->getDataNonConst(0);
Teuchos::ArrayRCP<LO> procWinner = aggregates.GetProcWinner() ->getDataNonConst(0);
// some internal variables
LO nLocalAggregates = aggregates.GetNumAggregates(); // number of local aggregates on current proc
std::queue<LO> graph_ordering_inodes; // inodes for graph ordering
ArrayRCP<LO> randomVector;
if (ordering == RANDOM) {
randomVector = arcp<LO>(nRows);
for (LO i = 0; i < nRows; i++)
randomVector[i] = i;
RandomReorder(randomVector);
}
int aggIndex = -1;
size_t aggSize = 0;
std::vector<int> aggList(graph.getNodeMaxNumRowEntries());
// Main loop over all local rows of graph(A)
for (LO iNode2 = 0; iNode2 < nRows; iNode2++) {
// Step 1: pick the next node to aggregate
LO iNode1 = 0;
if (ordering == NATURAL) iNode1 = iNode2;
else if (ordering == RANDOM) iNode1 = randomVector[iNode2];
else if (ordering == GRAPH) {
if (graph_ordering_inodes.size() == 0) {
// There are no nodes for graph ordering scheme,
// add exactly one ready node for graph ordering aggregates
for (LO jnode = 0; jnode < nRows; jnode++)
if (aggStat[jnode] == NodeStats::READY) {
graph_ordering_inodes.push(jnode);
break;
}
}
if (graph_ordering_inodes.size() == 0) {
// There are no more ready nodes, end the phase
break;
}
iNode1 = graph_ordering_inodes.front(); // take next node from graph ordering queue
graph_ordering_inodes.pop(); // delete this node in list
}
if (aggStat[iNode1] == NodeStats::READY) {
// Step 2: build tentative aggregate
aggSize = 0;
aggList[aggSize++] = iNode1;
ArrayView<const LO> neighOfINode = graph.getNeighborVertices(iNode1);
LO numAggregatedNeighbours = 0;
// NOTE: if neighOfINode.size() < MinNodesPerAggregate, we could skip this loop,
// but only for NATURAL and RANDOM (for GRAPH we still need the list of local neighbors)
for (LO j = 0; j < neighOfINode.size(); j++) {
LO neigh = neighOfINode[j];
if (neigh != iNode1 && graph.isLocalNeighborVertex(neigh)) {
if (aggStat[neigh] == NodeStats::READY || aggStat[neigh] == NodeStats::NOTSEL) {
// Add neighbor node to tentative aggregate
// but only if aggregate size is not exceeding maximum size
// NOTE: We do not exit the loop over all neighbours since we have still
// to count all aggregated neighbour nodes for the aggregation criteria
// NOTE: We check here for the maximum aggregation size. If we would do it below
// with all the other check too big aggregates would not be accepted at all.
if (aggSize < as<size_t>(MaxNodesPerAggregate))
aggList[aggSize++] = neigh;
} else {
numAggregatedNeighbours++;
}
}
}
// Step 3: check if tentative aggregate is acceptable
if ((numAggregatedNeighbours <= MaxNeighAlreadySelected) && // too many connections to other aggregates
(as<LO>(aggSize) >= MinNodesPerAggregate)) { // too few nodes in the tentative aggregate
// Accept new aggregate
// iNode1 becomes the root of the newly formed aggregate
aggregates.SetIsRoot(iNode1);
aggIndex = nLocalAggregates++;
for (size_t k = 0; k < aggSize; k++) {
aggStat [aggList[k]] = NodeStats::AGGREGATED;
vertex2AggId[aggList[k]] = aggIndex;
procWinner [aggList[k]] = myRank;
if (ordering == GRAPH) {
Teuchos::ArrayView<const LO> neighOfJNode = graph.getNeighborVertices(aggList[k]);
for (int j = 0; j < neighOfJNode.size(); j++) {
LO neigh = neighOfJNode[j];
if (graph.isLocalNeighborVertex(neigh) && aggStat[neigh] == NodeStats::READY)
graph_ordering_inodes.push(neigh);
}
}
}
numNonAggregatedNodes -= aggSize;
} else {
// Aggregate is not accepted
aggStat[iNode1] = NodeStats::NOTSEL;
if (ordering == GRAPH) {
// Even though the aggregate around iNode1 is not perfect, we want to try
// the neighbor nodes of iNode1
for (int j = 0; j < neighOfINode.size(); j++) {
LO neigh = neighOfINode[j];
if (graph.isLocalNeighborVertex(neigh) && aggStat[neigh] == NodeStats::READY)
graph_ordering_inodes.push(neigh);
}
}
}
}
}
// update aggregate object
aggregates.SetNumAggregates(nLocalAggregates);
}
void MaxLinkAggregationAlgorithm<LocalOrdinal, GlobalOrdinal, Node, LocalMatOps>::
BuildAggregates(const ParameterList& params, const GraphBase& graph, Aggregates& aggregates, std::vector<unsigned>& aggStat, LO& numNonAggregatedNodes) const {
Monitor m(*this, "BuildAggregates");
LO MaxNodesPerAggregate = params.get<LO>("MaxNodesPerAggregate");
// vertex ids for output
ArrayRCP<LO> vertex2AggId = aggregates.GetVertex2AggId()->getDataNonConst(0);
ArrayRCP<LO> procWinner = aggregates.GetProcWinner() ->getDataNonConst(0);
ArrayRCP<LO> aggSizes = aggregates.ComputeAggregateSizes(); // contains number of nodes in aggregate with given aggId
const LO nRows = graph.GetNodeNumVertices();
const int myRank = graph.GetComm()->getRank();
size_t aggSize = 0;
std::vector<int> aggList(graph.getNodeMaxNumRowEntries());
//bool recomputeAggregateSizes=false; // variable not used TODO remove it
for (LO iNode = 0; iNode < nRows; iNode++) {
if (aggStat[iNode] == NodeStats::AGGREGATED)
continue;
ArrayView<const LocalOrdinal> neighOfINode = graph.getNeighborVertices(iNode);
aggSize = 0;
for (LO j = 0; j < neighOfINode.size(); j++) {
LO neigh = neighOfINode[j];
// NOTE: we don't need the check (neigh != iNode), as we work only
// if aggStat[neigh] == AGGREGATED, which we know is different from aggStat[iNode]
if (graph.isLocalNeighborVertex(neigh) && aggStat[neigh] == NodeStats::AGGREGATED)
aggList[aggSize++] = vertex2AggId[neigh];
}
// Ideally, we would have a _fast_ hash table here.
// But for the absense of that, sorting works just fine.
std::sort(aggList.begin(), aggList.begin() + aggSize);
// terminator
aggList[aggSize] = -1;
// Find an aggregate id with most connections to
LO maxNumConnections = 0, curNumConnections = 0;
LO selectedAggregate = -1;
for (size_t i = 0; i < aggSize; i++) {
curNumConnections++;
if (aggList[i+1] != aggList[i]) {
if (curNumConnections > maxNumConnections && // only select aggregate if it has more connections
aggSizes[aggList[i]] < MaxNodesPerAggregate) { // and if it is not too big (i.e. can have one more node)
maxNumConnections = curNumConnections;
selectedAggregate = aggList[i];
//recomputeAggregateSizes=true;
}
curNumConnections = 0;
}
}
// Add node iNode to aggregate
if (selectedAggregate != -1) {
aggStat[iNode] = NodeStats::AGGREGATED;
vertex2AggId[iNode] = selectedAggregate;
procWinner[iNode] = myRank;
numNonAggregatedNodes--;
}
}
}
void AggregationPhase2aAlgorithm<LocalOrdinal, GlobalOrdinal, Node, LocalMatOps>::BuildAggregates(const ParameterList& params, const GraphBase& graph, Aggregates& aggregates, std::vector<unsigned>& aggStat, LO& numNonAggregatedNodes) const {
Monitor m(*this, "BuildAggregates");
LO minNodesPerAggregate = params.get<LO>("aggregation: min agg size");
LO maxNodesPerAggregate = params.get<LO>("aggregation: max agg size");
const LO numRows = graph.GetNodeNumVertices();
const int myRank = graph.GetComm()->getRank();
ArrayRCP<LO> vertex2AggId = aggregates.GetVertex2AggId()->getDataNonConst(0);
ArrayRCP<LO> procWinner = aggregates.GetProcWinner() ->getDataNonConst(0);
LO numLocalAggregates = aggregates.GetNumAggregates();
LO numLocalNodes = procWinner.size();
LO numLocalAggregated = numLocalNodes - numNonAggregatedNodes;
const double aggFactor = 0.5;
double factor = as<double>(numLocalAggregated)/(numLocalNodes+1);
factor = pow(factor, aggFactor);
int aggIndex = -1;
size_t aggSize = 0;
std::vector<int> aggList(graph.getNodeMaxNumRowEntries());
for (LO rootCandidate = 0; rootCandidate < numRows; rootCandidate++) {
if (aggStat[rootCandidate] != READY)
continue;
aggSize = 0;
ArrayView<const LocalOrdinal> neighOfINode = graph.getNeighborVertices(rootCandidate);
LO numNeighbors = 0;
for (int j = 0; j < neighOfINode.size(); j++) {
LO neigh = neighOfINode[j];
if (neigh != rootCandidate) {
if (graph.isLocalNeighborVertex(neigh) && aggStat[neigh] == READY) {
// If aggregate size does not exceed max size, add node to the tentative aggregate
// NOTE: We do not exit the loop over all neighbours since we have still
// to count all aggregated neighbour nodes for the aggregation criteria
// NOTE: We check here for the maximum aggregation size. If we would do it below
// with all the other check too big aggregates would not be accepted at all.
if (aggSize < as<size_t>(maxNodesPerAggregate))
aggList[aggSize++] = neigh;
}
numNeighbors++;
}
}
// NOTE: ML uses a hardcoded value 3 instead of MinNodesPerAggregate
if (aggSize > as<size_t>(minNodesPerAggregate) &&
aggSize > factor*numNeighbors) {
// Accept new aggregate
// rootCandidate becomes the root of the newly formed aggregate
aggregates.SetIsRoot(rootCandidate);
aggIndex = numLocalAggregates++;
for (size_t k = 0; k < aggSize; k++) {
aggStat [aggList[k]] = AGGREGATED;
vertex2AggId[aggList[k]] = aggIndex;
procWinner [aggList[k]] = myRank;
}
numNonAggregatedNodes -= aggSize;
}
}
// update aggregate object
aggregates.SetNumAggregates(numLocalAggregates);
}
