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findAlmost.cpp
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findAlmost.cpp
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#include "parFindAlmost.hpp"
#include <unistd.h>
/* being driver */
int main(int argc, char** argv) {
std::srand( unsigned (std::time(0) + getpid()) );
return driver<findAlmost,parFindAlmost>(argc, argv);
}
/* end driver */
/* begin findAlmost methods */
branchSub* findAlmost::blankSub() {
findAlmostSub* newSP = new findAlmostSub;
newSP->setGlobalInfo(this);
return newSP;
}
/* end findAlmost methods */
/* begin findAlmostSub methods */
void findAlmostSub::boundComputation(double* controlParam) {
DEBUGPR(700, ucout << "findAlmostSub::boundComputation(double*) called for " << this
<< " at address " << (void*)this << std::endl);
// if the flag testBranchingStrength is set,
// this only works at the root node, and then terminates
// by killing the root node
// TODO: extend to work at other nodes?
if(global()->testBranchingStrength) {
// do initial refinement pass
refineByDegreeDiff(g,perg,B);
{
int lab[n];
int ptn[n];
perg.components(lab,ptn);
g.callNauty(lab,ptn);
}
// do root node refinement
int * edge_use = new int [LTIdx(n,0)](); //zero-initize new array of ints
refineUntilNone(g, g_fixed, perg, B, edge_use);
findBranchEdge(edge_use);
delete [] edge_use;
std::vector<int> refinedByFixedBranch;
// need an escape in case there's no edge to branch on because the refinement was perfect
if(disjunctEdges.num() == 0) {
testBranchingWriteToGlobal(0, refinedByFixedBranch);
setState(dead);
return;
}
// collect strong branching statistics for left (fixing) child
// first for the branch we would have taken based on the branching rule
// (assuming we just branch on one edge at a time..)
int refinedDefaultBranch = simulateLeftBranch( disjunctEdges.get(0) );
// now collect for all other edges in g
refinedByFixedBranch.reserve(g.numEdges());
DenseGraph::Row gi;
// iterate over all edges
for (int i = 0; i < n; i++){
gi = g.row(i);
for (int j = i; (j = gi.nextVertex(j)) >= 0; ){ //check upper triangle only
Edge sim_branch_edge = Edge(i,j);
refinedByFixedBranch.push_back(simulateLeftBranch(sim_branch_edge));
}
}
testBranchingWriteToGlobal(refinedDefaultBranch, refinedByFixedBranch);
setState(dead);
return;
}
if(boundCompFirstPass) { //called after node is first deleted
if(delNode) {
refineByDegreeDiff(g,perg,B);
{
int lab[n];
int ptn[n];
perg.components(lab,ptn);
g.callNauty(lab,ptn);
}
//get new lowerBound
lowerBound = independentSetHeuristic(perg);
DEBUGPR(500, ucout << "Right branch, after refineByDegreeDiff lowerBound = " << lowerBound << std::endl);
bound = lowerBound;
DEBUGPR(300, ucout << "Right branch, nauty called. Edge deletions here: " << delEdges << std::endl
<< "Orbits here: " << g.orbits << std::endl);
solution * sol = new findAlmostSol(global(),delEdges,g.orbits,g.numOrbits(),g.groupSize());
global()->foundSolution(sol);
if( B <= 0 || g_fixed.numEdges() >= g.numEdges() || lowerBound >= g.numOrbits()) {
DEBUGPR(300, if(B<=0) ucout << "Pruning here because B<=0\n");
DEBUGPR(300, if(g_fixed.numEdges() >= g.numEdges()) ucout << "Pruning here because we fixed all the edges\n");
DEBUGPR(300, if(lowerBound >= g.numOrbits()) ucout << "Pruning here because lowerBound >= g.numOrbits()\n");
DEBUGPR(400, ucout << "g_fixed here: " << g_fixed << std::endl);
setState(dead); //fathom node
return;
}
} else { //delNode is false, so this was a fixed node.
//it's possible we've fixed all the edges, in which case we want to prune
if (g_fixed.numEdges() >= g.numEdges()) {
DEBUGPR(300, ucout << "Pruning because g_fixed.numEdges() >= g.numEdges()\n");
DEBUGPR(400, ucout << "g_fixed here: " << g_fixed << std::endl);
setState(dead);
return;
}
//this is very cheap, so we might as well do it here
refineByDegreeDiffFixedEdges(g, g_fixed, perg);
//get new lowerBound
lowerBound = independentSetHeuristic(perg);
DEBUGPR(500, ucout << "Left branch, after refineByDegreeDiffFixedEdges lowerBound = " << lowerBound << std::endl);
bound = lowerBound;
if ( lowerBound >= g.numOrbits() /* || fixBranch->lowerBound >= bGlobal()->incumbentValue*/ ){ //PEBBL should do the latter
DEBUGPR(300, ucout << "Pruning because comp>=g.numOrbits().\n");
DEBUGPR(400, ucout << "g_fixed here: " << g_fixed << std::endl);
setState(dead);
return;
}
}
boundCompFirstPass = false;
return; //this will force PEBBL to update these bounds before doing a matching pass
}
int * edge_use = new int [LTIdx(n,0)](); //zero-initize new array of ints
int perg_edges_bf = perg.numEdges();
// new virtual function
runRefineByMatching(g, g_fixed, perg, B, edge_use);
lowerBound = independentSetHeuristic(perg);
DEBUGPR(500, ucout << "After refineByMatching lowerBound = " << lowerBound << std::endl);
bound = lowerBound;
if(lowerBound >= g.numOrbits()){
delete [] edge_use;
DEBUGPR(300, if(lowerBound >= g.numOrbits()) ucout << "Pruning here because lowerBound >= g.numOrbits()\n");
DEBUGPR(400, ucout << "g_fixed here: " << g_fixed << std::endl);
setState(dead);
return;
}
if(perg_edges_bf == perg.numEdges()){
if (global()->localBranching) {
DenseGraph perg_copy = perg;
DenseGraph g_fixed_copy = g_fixed;
std::fill(edge_use, edge_use+LTIdx(n,0), 0);
int B_heur = 1;
//refineByDegreeDiff(g, perg_copy, B_heur);
// new virtual function
runRefineByMatching(g, g_fixed_copy, perg_copy, B_heur, edge_use, true);
}
findBranchEdge(edge_use);
delete [] edge_use;
// new virtual function
makeBranchingDecisionsAgree();
if (disjunctEdges.num() == 0) {
setState(dead);
} else {
setState(bounded);
}
return;
}
delete [] edge_use;
}
// returns the number refined on simulated fixing disjuction
int findAlmostSub::simulateLeftBranch(const Edge &branch_edge) {
// copy perg, g_fixed
DenseGraph perg_branch = perg;
DenseGraph g_fixed_branch = g_fixed;
// add edge to g_fixed
g_fixed_branch.addEdge(branch_edge.u, branch_edge.v);
int perg_edges_start = perg_branch.numEdges();
// may as well do this first
refineByDegreeDiffFixedEdges(g, g_fixed_branch, perg_branch);
int * edge_use = new int [LTIdx(n,0)]();
refineUntilNone(g, g_fixed_branch, perg_branch, B, edge_use);
delete [] edge_use;
return (perg_edges_start - perg_branch.numEdges());
}
void findAlmostSub::refineUntilNone(const DenseGraph &g, const DenseGraph &g_fixed, DenseGraph &perg, int B, int* edge_use) {
for(;;) {
std::fill(edge_use, edge_use+LTIdx(n,0), 0);
int perg_edges_bf = perg.numEdges();
// new virtual function
runRefineByMatching(g, g_fixed, perg, B, edge_use);
if(perg_edges_bf == perg.numEdges()) return;
}
}
void findAlmostSub::findBranchEdge(int * edge_use) {
DEBUGPR(700, ucout << "findAlmostSub::splitComputation() called for " << this
<< " at address " << (void*)this << std::endl);
int i,j,k,max,best_i,best_j;
DenseGraph::Row gi;
if (global()->trackEdges && (prev_second_choice.u != -1)) {
int place = 0;
int val = edge_use[LTIdx(prev_second_choice.v, prev_second_choice.u)];
for (i = 0, gi = g.row(i) ; i < n; ++i, gi.nextRow()){
for (j = i; (j = gi.nextVertex(j)) >= 0; ){
if ( edge_use[LTIdx(j,i)] > val ) place++;
}
}
global()->rankInChild.push_back(place);
}
if(!(global()->randomBranching)){
for (k = 0; k < global()->DisjunctNum()+int(global()->trackEdges) ; ++k) {
max=0; best_i = -1; best_j = -1;
for (i = 0, gi = g.row(i) ; i < n; ++i, gi.nextRow()){
for (j = i; (j = gi.nextVertex(j)) >= 0; ){
DEBUGPR(1100, /*if(uMPI::rank == uMPI::ioProc)*/ ucout << "edge_use(" << i << ',' << j << ") = "<< edge_use[LTIdx(j,i)] << std::endl);
if (max < edge_use[LTIdx(j,i)]){
max = edge_use[LTIdx(j,i)];
best_i = i;
best_j = j;
}
}
}
//if we didn't find a better edge on this pass
if (max == 0) {
break;
} else {
//zero this out so we don't see him again
if ( k < global()->DisjunctNum() ) {
edge_use[LTIdx(best_j, best_i)] = 0;
disjunctEdges.add(best_i, best_j);
} else {
prev_second_choice.u = best_i; prev_second_choice.v = best_j;
}
}
}
if (disjunctEdges.num() > 0) { //a max was found, and one end point isn't isolated in perg
//(if it was, we wouldn't have set up a matching problem for it in the
// most recent pass. Also, fixed edges won't be deleted because they're
// not used in any solution <= 2B.
DEBUGPR(300, /*if (uMPI::rank == uMPI::ioProc)*/ ucout << "EDGE_FOUND, branching on edge(s) " << disjunctEdges << std::endl
<< "Deleted edges here: " << delEdges << std::endl);
DEBUGPR(300, /*if (uMPI::rank == uMPI::ioProc)*/ ucout << "Fixed edges here: " << g_fixed << std::endl);
return;
} else { //if we got here, that means no edge had to be deleted in order
// for the matching to work...this probably means the graph has a decent
// amount of symmetry, so let's try to branch on something that will break
// it in order to fathom quickly further down (for now keep implementation
// the same as code on server)
DEBUGPR(1, ucout << "Warning, no edge had to be deleted in order to make the matching work" << std::endl);
for (i=0, gi = g.row(i); i<n; ++i, gi.nextRow()) {
for (j=i; (j = gi.nextVertex(j)) >= 0; ) {
//don't delete fixed edges
if (g_fixed.isEdge(i,j)) {continue;}
//no point in deleting if this is true
if (perg.isIsolated(i) && perg.isIsolated(j)) {continue;}
// keep adding
disjunctEdges.add(i,j);
// until this is full
if (disjunctEdges.left() == 0) {
DEBUGPR(300,/* if (uMPI::rank == uMPI::ioProc)*/ ucout << "EDGE_FOUND, branching on edge(s) " << disjunctEdges << std::endl
<< "Deleted edges here: " << delEdges << std::endl);
DEBUGPR(300,/* if (uMPI::rank == uMPI::ioProc)*/ ucout << "Fixed edges here: " << g_fixed << std::endl);
return;
}
}
}
if (disjunctEdges.num() > 0) {
DEBUGPR(300,/* if (uMPI::rank == uMPI::ioProc)*/ ucout << "EDGE_FOUND, branching on edge(s) " << disjunctEdges << std::endl
<< "Deleted edges here: " << delEdges << std::endl);
DEBUGPR(300,/* if (uMPI::rank == uMPI::ioProc)*/ ucout << "Fixed edges here: " << g_fixed << std::endl);
return;
}
}
} else { //implement random branching
std::vector<int> randomIterator (n); //make a vector for iterator
std::vector<int> jRandomIterator; //make vector for neighbors
for(i=0; i<n; i++) randomIterator[i] = i;
std::random_shuffle( randomIterator.begin(), randomIterator.end() );
for (i=0; i<n; i++) {
jRandomIterator.clear(); //clear out randomIterator[i]'s neighbors
gi = g.row(randomIterator[i]);
for (j=0; (j = gi.nextVertex(j)) >= 0;) {
jRandomIterator.push_back(j); //load neighbor vector
}
std::random_shuffle( jRandomIterator.begin(), jRandomIterator.end() ); //shuffle neighbor vector
for (std::vector<int>::iterator it=jRandomIterator.begin(); it!=jRandomIterator.end(); ++it) {
//don't delete fixed edges
if (g_fixed.isEdge(randomIterator[i],*it)) {continue;}
//no point in deleting if this is true
if (perg.isIsolated(randomIterator[i]) && perg.isIsolated(*it)) {continue;}
disjunctEdges.add(randomIterator[i], *it);
if (disjunctEdges.left() == 0) {
DEBUGPR(300,/* if (uMPI::rank == uMPI::ioProc)*/ ucout << "EDGE_FOUND, branching on edges "
<< disjunctEdges << std::endl
<< "Deleted edges here: " << delEdges << std::endl);
DEBUGPR(300,/* if (uMPI::rank == uMPI::ioProc)*/ ucout << "Fixed edges here: " << g_fixed << std::endl);
return;
}
}
}
if (disjunctEdges.num() > 0) return;
}
// if we got here either all the edges are fixed or isolated in perg, so this
// node can die
DEBUGPR(400, ucout << "We ran out of edges to fix - deleted edges here:" << delEdges << std::endl);
DEBUGPR(400, ucout << "g_fixed here: " << g_fixed << std::endl);
return;
}
void findAlmostSub::findAlmostSubAsChildOf(findAlmostSub* parent, int whichChild){
//to keep left dive first, i==disjunctEdges.num() ~ fixed child, i<disjunctEdges.num() ~ deleted child
branchSubAsChildOf(parent);
bound = lowerBound = parent->lowerBound;
globalPtr = parent->global();
n = parent->n;
B = parent->B;
g = parent->g;
delEdges = parent->delEdges;
g_fixed = parent->g_fixed;
perg = parent->perg;
disjunctEdges = EdgeList(global()->DisjunctNum());
boundCompFirstPass = true;
if (global()->trackEdges) prev_second_choice = parent->prev_second_choice;
//**************************begin del edge disjunction*******************//
if (whichChild < parent->disjunctEdges.num()) {
delNode = true;
B--; //decrement B
g.delEdge(parent->disjunctEdges.getu(whichChild), parent->disjunctEdges.getv(whichChild));//delete edge from graph
DEBUGPR(300, /*if (uMPI::rank == uMPI::ioProc)*/ ucout << "Deleting edge " << parent->disjunctEdges.get(whichChild) << std::endl);
delEdges.add(parent->disjunctEdges.get(whichChild)); //add to list of deleted edges
}
//*************************end del edge disjunction********************//
//********************Edge fixing child**********************//
if( whichChild == parent->disjunctEdges.num() ){
delNode = false;
for (int k = 0; k < parent->disjunctEdges.num(); ++k)
g_fixed.addEdge(parent->disjunctEdges.getu(k),parent->disjunctEdges.getv(k)); //add to graph of fixings
DEBUGPR(300, /*if (uMPI::rank == uMPI::ioProc)*/ ucout << "Fixing edge(s)" << parent->disjunctEdges << std::endl);
}
//***************************end Fix edge disjunction*********************//
}
/* end findAlmostSub methods */
/* begin parFindAlmost methods */
void parFindAlmostSub::runRefineByMatching( const DenseGraph &g, const DenseGraph &g_fixed, DenseGraph &perg, int B, int* edge_use, bool always_collect_edge_use ) {
if (rampingUp()) {
parRefineByMatching(g, g_fixed, perg, B, edge_use, always_collect_edge_use);
//DEBUGPR(200,
// if (uMPI::rank == uMPI::ioProc) ucout << "During syncronous ramp-up, we refined " << perg_edges_bf - perg.numEdges() << std::endl);
} else {
refineByMatching(g, g_fixed, perg, B, edge_use, always_collect_edge_use);
}
}
void parFindAlmostSub::makeBranchingDecisionsAgree() {
if (global()->randomBranching && rampingUp()) {
// make the disjunctions all the same
// we'll use ioProc's rank
auto packed_edges = utilib::PackBuffer(disjunctEdges.packSize());
disjunctEdges.write(packed_edges);
uMPI::broadcast((char*)packed_edges.buf(),packed_edges.size(),MPI::CHAR,uMPI::ioProc);
auto unpacked_edges = utilib::UnPackBuffer(packed_edges.buf(), packed_edges.size());
disjunctEdges.read(unpacked_edges);
}
}
void parFindAlmostSub::pack(utilib::PackBuffer& outBuffer) {
// We can do better...we don't need to pack g, instead let's get it from global()->gRef() and
// then delete the appropriate edges when we unpack...but we need to pack g's orbits
outBuffer << delEdges << g_fixed << perg << delNode << boundCompFirstPass
<< lowerBound << n << B << disjunctEdges;
for(int i=0; i<n; i++){
outBuffer << g.orbits[i];
}
outBuffer << g.stats.numorbits;
}
void parFindAlmostSub::unpack(utilib::UnPackBuffer& inBuffer) {
inBuffer >> delEdges >> g_fixed >> perg >> delNode >> boundCompFirstPass
>> lowerBound >> n >> B >> disjunctEdges;
g = global()->gRef(); //get g from global branching object
//fix so it's actually the current node
for(int i=0; i<delEdges.num(); i++){
g.delEdge(delEdges.getu(i),delEdges.getv(i));
}
for(int i=0; i<n; i++){
inBuffer >> g.orbits[i];
}
inBuffer >> g.stats.numorbits;
}
int parFindAlmost::spPackSize(){
// g.orbits + g.stats.numorbits + delEdges + g_fixed + perg
return ( ((g.numVertices()+1) + 2*budget + 2)*sizeof(int) + 2*g.DenseGraph::packSize()
+ 3*sizeof(bool) + 5*sizeof(int) );
}
void parFindAlmost::pack(utilib::PackBuffer& outBuffer) {
outBuffer << g << budget;
}
void parFindAlmost::unpack(utilib::UnPackBuffer& inBuffer) {
inBuffer >> g >> budget;
}
parallelBranchSub* parFindAlmost::blankParallelSub() {
parFindAlmostSub* newSP = new parFindAlmostSub;
DEBUGPR(700, ucout << "new parFindAlmostSub from parFindAlmost::blankParallelSub(), address: " <<(void*) newSP << std::endl);
newSP->setGlobalInfo(this);
return newSP;
}
/* end parFindAlmost methodes */
/* being findAlmostSol methods */
void findAlmostSol::packContents(utilib::PackBuffer& outBuf){
outBuf << delEdges << n;
for(int i=0; i<n; i++) {
outBuf << orbits[i];
}
outBuf << group_size;
}
void findAlmostSol::unpackContents(utilib::UnPackBuffer& inBuf) {
inBuf >> delEdges >> n;
orbits = new int[n];
for(int i=0; i<n; i++) {
inBuf >> orbits[i];
}
inBuf >> group_size;
}
int findAlmostSol::maxContentsBufSize() {
return ( delEdges.packSize() + (n+1)*sizeof(int) + sizeof(double) );
}
/* writes the solution to the given ostream object */
void findAlmostSol::printContents(std::ostream& os){
os << "Edges deleted: " << delEdges << std::endl;
os << "Nontrival orbits:";
int * thisOrbit = new int[n];
int count;
for( int i=0; i < n ; i++){
if (orbits[i] == i) { //this is the first vertex in this orbit
count = 0;
thisOrbit[count] = i;
count++;
for ( int j=i+1; j < n; j++) { //find the others
if (orbits[j] == i){
thisOrbit[count] = j;
count++;
}
}
if(count > 1) { //if there's more than a singleton we'll put to os
for( int j=0; j<count; j++) os << " " << (thisOrbit[j]+1);
//put number of orbits at end
os << " " << "(" << count << ");";
}
}
}
os << '\n';
os << "Group size: " << group_size << std::endl;
delete [] thisOrbit;
}
/* end findAlmostSol methods */
//************* begin refinement algorithms ******************//
// This function is from libhungarian by Cyrill Stachniss, with slight modifications for speed when repeatedly calling //
// libhungarian is available at: http://www2.informatik.uni-freiburg.de/~stachnis/misc.html
int hungarian_solve(hungarian_problem_t* p)
{
int i, j, m, n, k, l, s, t, q, unmatched, cost;
cost=0;
m =p->num_rows;
n =p->num_cols;
// put these on the stack; they're small
int col_mate[m];
int unchosen_row[m];
int row_dec[m];
int slack_row[m];
int row_mate[n];
int parent_row[n];
int col_inc[n];
int slack[n];
/* //this should be done already
for (i=0;i<p->num_rows;i++) {
col_mate[i]=0;
unchosen_row[i]=0;
row_dec[i]=0;
slack_row[i]=0;
}
for (j=0;j<p->num_cols;j++) {
row_mate[j]=0;
parent_row[j] = 0;
col_inc[j]=0;
slack[j]=0;
}
for (i=0;i<p->num_rows;++i)
for (j=0;j<p->num_cols;++j)
p->assignment[i][j]=HUNGARIAN_NOT_ASSIGNED; */
// Begin subtract column minima in order to start with lots of zeroes 12
for (l=0;l<n;l++)
{
s=p->cost[0][l];
for (k=1;k<m;k++)
if (p->cost[k][l]<s)
s=p->cost[k][l];
cost+=s;
if (s!=0)
for (k=0;k<m;k++)
p->cost[k][l]-=s;
}
// End subtract column minima in order to start with lots of zeroes 12
// Begin initial state 16
t=0;
// replace this with calls to fill
for (l=0;l<n;l++) row_mate[l] = -1;
for (l=0;l<n;l++) parent_row[l] = -1;
for (l=0;l<n;l++) col_inc[l] = 0;
for (l=0;l<n;l++) slack[l] = INF;
for (k=0;k<m;k++) slack_row[k] = 0;
for (k=0;k<m;k++) unchosen_row[k] = 0;
for (k=0;k<m;k++)
{
slack_row[k] = 0;
s=p->cost[k][0];
for (l=1;l<n;l++)
if (p->cost[k][l]<s)
s=p->cost[k][l];
row_dec[k]=s;
for (l=0;l<n;l++)
if (s==p->cost[k][l] && row_mate[l]<0)
{
col_mate[k]=l;
row_mate[l]=k;
goto row_done;
}
col_mate[k]= -1;
unchosen_row[t++]=k;
row_done:
;
}
// End initial state 16
// Begin Hungarian algorithm 18
if (t==0)
goto done;
unmatched=t;
while (1)
{
q=0;
while (1)
{
while (q<t)
{
// Begin explore node q of the forest 19
{
k=unchosen_row[q];
s=row_dec[k];
for (l=0;l<n;l++)
if (slack[l])
{
int del;
del=p->cost[k][l]-s+col_inc[l];
if (del<slack[l])
{
if (del==0)
{
if (row_mate[l]<0)
goto breakthru;
slack[l]=0;
parent_row[l]=k;
unchosen_row[t++]=row_mate[l];
}
else
{
slack[l]=del;
slack_row[l]=k;
}
}
}
}
// End explore node q of the forest 19
q++;
}
// Begin introduce a new zero into the matrix 21
s=INF;
for (l=0;l<n;l++)
if (slack[l] && slack[l]<s)
s=slack[l];
for (q=0;q<t;q++)
row_dec[unchosen_row[q]]+=s;
for (l=0;l<n;l++)
if (slack[l])
{
slack[l]-=s;
if (slack[l]==0)
{
// Begin look at a new zero 22
k=slack_row[l];
if (row_mate[l]<0)
{
for (j=l+1;j<n;j++)
if (slack[j]==0)
col_inc[j]+=s;
goto breakthru;
}
else
{
parent_row[l]=k;
unchosen_row[t++]=row_mate[l];
}
// End look at a new zero 22
}
}
else
col_inc[l]+=s;
// End introduce a new zero into the matrix 21
}
breakthru:
// Begin update the matching 20
while (1)
{
j=col_mate[k];
col_mate[k]=l;
row_mate[l]=k;
if (j<0)
break;
k=parent_row[j];
l=j;
}
// End update the matching 20
if (--unmatched==0)
goto done;
// Begin get ready for another stage 17
t=0;
for (l=0;l<n;l++)
{
parent_row[l]= -1;
slack[l]=INF;
}
for (k=0;k<m;k++)
if (col_mate[k]<0)
{
unchosen_row[t++]=k;
}
// End get ready for another stage 17
}
done:
// Begin doublecheck the solution 23
/* don't bother please
for (k=0;k<m;k++)
for (l=0;l<n;l++)
if (p->cost[k][l]<row_dec[k]-col_inc[l])
exit(0);
for (k=0;k<m;k++)
{
l=col_mate[k];
if (l<0 || p->cost[k][l]!=row_dec[k]-col_inc[l])
exit(0);
}
k=0;
for (l=0;l<n;l++)
if (col_inc[l])
k++;
if (k>m)
exit(0);
// End doublecheck the solution 23
*/
// End Hungarian algorithm 18
for (i=0;i<m;++i)
{
p->assignment[i][col_mate[i]]=HUNGARIAN_ASSIGNED;
/*TRACE("%d - %d\n", i, col_mate[i]);*/
}
for (k=0;k<m;++k)
{
for (l=0;l<n;++l)
{
/*TRACE("%d ",p->cost[k][l]-row_dec[k]+col_inc[l]);*/
p->cost[k][l]=p->cost[k][l]-row_dec[k]+col_inc[l];
}
/*TRACE("\n");*/
}
for (i=0;i<m;i++)
cost+=row_dec[i];
for (i=0;i<n;i++)
cost-=col_inc[i];
/* // don't need these for stack-alloc'd arrays
free(slack);
free(col_inc);
free(parent_row);
free(row_mate);
free(slack_row);
free(row_dec);
free(unchosen_row);
free(col_mate);
*/
return cost;
}
void refineByMatching(const DenseGraph &g, const DenseGraph &g_fixed, DenseGraph &perg, int B, int* edge_use, bool always_collect_edge_use){
int i, inf = 4*B, n = g.numVertices();
//begin block for parallel processing
{
int j,k,l,deg_gi,deg_gj,size,u,v;
bool neighbors;
bool collect_edge_use = true;
DenseGraph::Row pergi;
int biSize = n+B;
int* Ni;
int* Nj;
int** biGraph;
int** assignment;
hungarian_problem_t p;
int cost;
biGraph = (int**)malloc(biSize*sizeof(int*));
assignment = (int**)malloc(biSize*sizeof(int*));
Ni = (int*)malloc(n*sizeof(int));
Nj = (int*)malloc(n*sizeof(int));
for (j = 0; j < biSize; ++j){
biGraph[j] = (int*)malloc(biSize*sizeof(int));
assignment[j] = (int*)malloc(biSize*sizeof(int));
}
for (i = 0; i < n; i++){
pergi = perg.row(i);
for (j = i; (j = pergi.nextVertex(j)) >= 0; ){ //check upper triangle only
deg_gi = g.deg(i); deg_gj = g.deg(j);
//set up and solve matching problem
neighbors = false;
size = (deg_gi > deg_gj) ? deg_gi : deg_gj ; //return greater of deg_gi and deg_gj
//printf("B = %d", B);
size += B;
neighbors = g.isEdge(i,j);
if (neighbors) size--; //if i and j are neighbors, we won't add them to the biGraph
buildCostMatrix(i, j, g, g_fixed, perg, size, inf, neighbors, biGraph, Ni, Nj);
for(k = 0; k < size; k++){
memset(assignment[k], 0, size*sizeof(int));
} // zero out assignment matrix
//let's do the initializtion ourselves
p.num_rows = size; p.num_cols = size;
p.cost = biGraph; p.assignment = assignment;
cost = hungarian_solve(&p);
// This information needs to be shared between the treads somehow...
if (cost > 2*B){ //we can kill i,j
//printf("Cost = %d, killing this permutation\n", cost);
//printf("Kill permutation (%d, %d) in refineByMatching\n", i, j);
perg.delEdge(i,j);
//if we delete an edge from perg we won't be using the edge_use data,
//so we can save time by not writing it
if (!always_collect_edge_use) collect_edge_use = false;
} else if(collect_edge_use) {
if (neighbors) {
for (k = 0; k < deg_gi-1; ++k){
for (l = deg_gj-1; l < size; ++l){
if (assignment[k][l] == 1){
u = Ni[k];
//printf("edge %d, %d got deleted\n", u, i);
if (i>u) {
edge_use[LTIdx(i,u)]++;
} else { // u>i
edge_use[LTIdx(u,i)]++;
}
break; //if we come across 1 in the row, we shouldn't find others
}
}
}
for ( ; k < size; ++k){
for (l = 0; l < deg_gj-1; ++l){
if (assignment[k][l] == 1){
v = Nj[l];
//printf("edge %d, %d got deleted\n", v, j);
if (j>v) {
edge_use[LTIdx(j,v)]++;
} else { //v>j
edge_use[LTIdx(v,j)]++;
}
break; //sim
}
}
}
} else {
for (k = 0; k < deg_gi; ++k){
for (l = deg_gj; l < size; ++l){
if (assignment[k][l] == 1){
u = Ni[k];
//printf("edge %d, %d got deleted\n", u, i);
if (i>u) {
edge_use[LTIdx(i,u)]++;
} else { // u>i
edge_use[LTIdx(u,i)]++;
}
break;
}
}
}
for ( ; k < size; ++k){
for (l = 0; l < deg_gj; ++l){
if (assignment[k][l] == 1){
v = Nj[l];
//printf("edge %d, %d got deleted\n", v, j);
if (j>v) {
edge_use[LTIdx(j,v)]++;
} else { //v>j
edge_use[LTIdx(v,j)]++;
}
break;
}
}
}
}
//printf("\n");
} //end info needing to be shared
}
}
for (j = 0; j < biSize; ++j){
free(biGraph[j]);
free(assignment[j]);
}
free(Ni); free(Nj);
free(biGraph);
free(assignment);
} //end parallel scope
}
/* TODO: fix logic to handle self-loops in g */
void parRefineByMatching(const DenseGraph &g, const DenseGraph &g_fixed, DenseGraph &perg, int B, int* edge_use, bool always_collect_edge_use ){
int i, inf = 4*B, n = g.numVertices();
//begin block for parallel processing
{
int j,k,l,deg_gi,deg_gj,size,u,v;
bool neighbors;
bool collect_edge_use = true;
DenseGraph::Row pergi;
int biSize = n+B;
int* Ni;
int* Nj;
int** biGraph;
int** assignment;
hungarian_problem_t p;
int cost;
biGraph = (int**)malloc(biSize*sizeof(int*));
assignment = (int**)malloc(biSize*sizeof(int*));
Ni = (int*)malloc(n*sizeof(int));
Nj = (int*)malloc(n*sizeof(int));
for (j = 0; j < biSize; ++j){
biGraph[j] = (int*)malloc(biSize*sizeof(int));
assignment[j] = (int*)malloc(biSize*sizeof(int));
}
//begin figuring out which edges in perg we'll process
int num_iterations = perg.numEdges(); //- n; //we'll only iterate over perg's
int iteration = 0;
bool * perg_del_edges = new bool[num_iterations](); //itilize to 0
int iters_per_proc = num_iterations / (uMPI::size);
int iters_remaining = num_iterations%(uMPI::size);
int my_start_iter = uMPI::rank*iters_per_proc + ((uMPI::rank < iters_remaining) ? (uMPI::rank) : iters_remaining); //return the smaller of rank and iters remaining
int my_end_iter = (uMPI::rank+1)*iters_per_proc + (((uMPI::rank+1) < iters_remaining) ? (uMPI::rank+1) : iters_remaining);
//end
for (i = 0; i < n; i++){
pergi = perg.row(i);
for (j = i; (j = pergi.nextVertex(j)) >= 0; iteration++){ //check upper triangle only
if( iteration >= my_start_iter && iteration < my_end_iter) {
// printf("\n(%d, %d) is an edge in the possible permutations graph\n", i, j);
deg_gi = g.deg(i); deg_gj = g.deg(j);
//set up and solve matching problem
neighbors = false;
size = (deg_gi > deg_gj) ? deg_gi : deg_gj ; //return greater of deg_gi and deg_gj
//printf("B = %d", B);
size += B;
neighbors = g.isEdge(i,j);
if (neighbors) size--; //if i and j are neighbors, we won't add them to the biGraph
buildCostMatrix(i, j, g, g_fixed, perg, size, inf, neighbors, biGraph, Ni, Nj);
for(k = 0; k < size; k++){
memset(assignment[k], 0, size*sizeof(int));
} // zero out assignment matrix
//let's do the initializtion ourselves
p.num_rows = size; p.num_cols = size;
p.cost = biGraph; p.assignment = assignment;
cost = hungarian_solve(&p);
// This information needs to be shared between the treads somehow...
if (cost > 2*B){ //we can kill i,j
//printf("Cost = %d, killing this permutation\n", cost);
//if (uMPI::rank == uMPI::ioProc) ucout << "Planning to kill permutation (" << i << "," << j << ") in refineByMatching, counter = " << counter << std::endl;
//perg.delEdge(i,j);
perg_del_edges[iteration] = true;
//if we delete an edge from perg we won't be using the edge_use data,
//so we can save time by not writing it
if (!always_collect_edge_use) collect_edge_use = false;
} else if(collect_edge_use) {
if (neighbors) {
for (k = 0; k < deg_gi-1; ++k){
for (l = deg_gj-1; l < size; ++l){
if (assignment[k][l] == 1){
u = Ni[k];
//printf("edge %d, %d got deleted\n", u, i);
if (i>u) {
edge_use[LTIdx(i,u)]++;
} else { // u>i
edge_use[LTIdx(u,i)]++;
}
break; //if we come across 1 in the row, we shouldn't find others
}
}
}
for ( ; k < size; ++k){
for (l = 0; l < deg_gj-1; ++l){
if (assignment[k][l] == 1){
v = Nj[l];
//printf("edge %d, %d got deleted\n", v, j);
if (j>v) {
edge_use[LTIdx(j,v)]++;
} else { //v>j
edge_use[LTIdx(v,j)]++;
}
break; //sim
}
}
}
} else {
for (k = 0; k < deg_gi; ++k){
for (l = deg_gj; l < size; ++l){
if (assignment[k][l] == 1){
u = Ni[k];
//printf("edge %d, %d got deleted\n", u, i);
if (i>u) {
edge_use[LTIdx(i,u)]++;
} else { // u>i
edge_use[LTIdx(u,i)]++;
}
break;
}
}
}
for ( ; k < size; ++k){
for (l = 0; l < deg_gj; ++l){
if (assignment[k][l] == 1){
v = Nj[l];
//printf("edge %d, %d got deleted\n", v, j);
if (j>v) {
edge_use[LTIdx(j,v)]++;
} else { //v>j
edge_use[LTIdx(v,j)]++;
}
break;
}
}
}
}
//printf("\n");
} //end info needing to be shared
}
}
}
//if (num_iterations != iteration) ucout << "You're a dumbass, interation = " << iteration << " and num_iterations = " << num_iterations << std::endl;
//collect info and act on it
//set collect_edge_use ... if it's false on some thread it's false
//everywhere, and we'll need to gather up the deleted edges
uMPI::reduceCast(MPI_IN_PLACE,&collect_edge_use,1,MPI::BOOL,MPI_LAND);
if(collect_edge_use){ //in this case, no edges were deleted, so we'll probably be branching
uMPI::reduceCast(MPI_IN_PLACE,edge_use,LTIdx(n,0),MPI::INT,MPI_SUM);
} else { //in this case some edges were deleted, so we need to update perg.
uMPI::reduceCast(MPI_IN_PLACE,perg_del_edges,num_iterations,MPI::BOOL,MPI_LOR);
iteration = 0;
for (i = 0; i < n; i++){
pergi = perg.row(i);
for (j = i; (j = pergi.nextVertex(j)) >= 0; iteration++){ //check upper triangle only
if(perg_del_edges[iteration]){
perg.delEdge(i,j);