void RecBipartLB::work(LDStats *stats) {
vector<Vertex *> ptrvector;
/** ========================== INITIALIZATION ============================= */
ProcArray *parr = new ProcArray(stats); // Processor Array
ObjGraph *ogr = new ObjGraph(stats); // Object Graph
/** ============================= STRATEGY ================================ */
level=0;
peno=0;
TOTALLOAD=0;
numparts=CkNumPes();
parray=parr;
double avgLoad = parr->getAverageLoad();
int numPes = parr->procs.size();
parr->resetTotalLoad();
for(int i=0;i<ogr->vertices.size();i++)
{
Vertex_helper *helper = new Vertex_helper();
vhelpers.push_back(helper);
ptrvector.push_back((Vertex *)&(ogr->vertices[i]));
}
RecursiveBiPart(ogr,ptrvector,1,numparts);
/** ============================== CLEANUP ================================ */
ogr->convertDecisions(stats); // Send decisions back to LDStats
}
void GraphBFTLB::work(LDStats *stats) {
/** ========================== INITIALIZATION ============================= */
ProcArray *parr = new ProcArray(stats); // Processor Array
ObjGraph *ogr = new ObjGraph(stats); // Object Graph
/** ============================= STRATEGY ================================ */
double avgLoad = parr->getAverageLoad();
int numPes = parr->procs.size();
// CkPrintf("Average Load %g\n\n", avgLoad);
// for(int i=0; i<numPes; i++)
// CkPrintf("PE [%d] %g %g\n", i, parr->procs[i].getTotalLoad(), parr->procs[i].getOverhead());
parr->resetTotalLoad();
int start = 0, nextPe = 0;
std::queue<int> vertexq;
// start at vertex with id 0
vertexq.push(start);
if(parr->procs[nextPe].getTotalLoad() + ogr->vertices[start].getVertexLoad() > avgLoad) {
nextPe++;
avgLoad += (avgLoad - parr->procs[nextPe].getTotalLoad())/(numPes-nextPe);
}
ogr->vertices[start].setNewPe(nextPe);
// CkPrintf("[%d] %d %d %g %g %g\n", start, ogr->vertices[start].getCurrentPe(), ogr->vertices[start].getNewPe(), parr->procs[nextPe].getTotalLoad(), ogr->vertices[start].getVertexLoad(), parr->procs[nextPe].getTotalLoad() + ogr->vertices[start].getVertexLoad());
parr->procs[nextPe].totalLoad() += ogr->vertices[start].getVertexLoad();
int i, nbr;
// breadth first traversal
while(!vertexq.empty()) {
start = vertexq.front();
vertexq.pop();
for(i = 0; i < ogr->vertices[start].sendToList.size(); i++) {
// look at all neighbors of a node in the queue and map them while
// inserting them in the queue (so we can look at their neighbors next)
nbr = ogr->vertices[start].sendToList[i].getNeighborId();
if(ogr->vertices[nbr].getNewPe() == -1) {
vertexq.push(nbr);
if(parr->procs[nextPe].getTotalLoad() + ogr->vertices[nbr].getVertexLoad() > avgLoad) {
nextPe++;
avgLoad += (avgLoad - parr->procs[nextPe].getTotalLoad())/(numPes-nextPe);
}
ogr->vertices[nbr].setNewPe(nextPe);
// CkPrintf("[%d] %d %d %g %g %g\n", nbr, ogr->vertices[nbr].getCurrentPe(), ogr->vertices[nbr].getNewPe(), parr->procs[nextPe].getTotalLoad(), ogr->vertices[start].getVertexLoad(), parr->procs[nextPe].getTotalLoad() + ogr->vertices[start].getVertexLoad());
parr->procs[nextPe].totalLoad() += ogr->vertices[nbr].getVertexLoad();
}
} // end of for loop
} // end of while loop
/** ============================== CLEANUP ================================ */
ogr->convertDecisions(stats); // Send decisions back to LDStats
}
void RefineSwapLB::work(LDStats* stats)
{
/** ========================== INITIALIZATION ============================= */
ProcArray *parr = new ProcArray(stats); // Processor Array
ObjGraph *ogr = new ObjGraph(stats); // Object Graph
/** ============================= STRATEGY ================================ */
if (_lb_args.debug()>1)
CkPrintf("[%d] In RefineSwapLB strategy\n",CkMyPe());
int vert;
double avg_load = parr->getAverageLoad();
double threshold = avg_load * 0.01;
double lower_bound_load = avg_load - threshold;
double upper_bound_load = avg_load + threshold;
cout <<"Average load " << avg_load << endl;
std::vector<int> min_pe_heap;
std::vector<int> max_pe_heap;
std::vector<int>* pe_obj = new std::vector<int>[parr->procs.size()];
// Create a datastructure to store the objects in a processor
for (int i = 0; i < ogr->vertices.size(); i++) {
pe_obj[ogr->vertices[i].getCurrentPe()].push_back(i);
// CkPrintf("%d pe %d: %lf\n", i, ogr->vertices[i].getCurrentPe(), ogr->vertices[i].getVertexLoad());
}
// Construct max heap of overloaded processors and min heap of underloaded
// processors.
for (int i = 0; i < parr->procs.size(); i++) {
//CkPrintf("%d : %lf\n", i, parr->procs[i].getTotalLoad());
if (parr->procs[i].getTotalLoad() > upper_bound_load) {
max_pe_heap.push_back(i);
} else if (parr->procs[i].getTotalLoad() < lower_bound_load) {
min_pe_heap.push_back(i);
}
}
std::make_heap(max_pe_heap.begin(), max_pe_heap.end(), ProcLoadGreaterIndex(parr));
while (max_pe_heap.size() != 0 && min_pe_heap.size() != 0) {
int p_index = getMax(parr, max_pe_heap);
ProcInfo &pinfo = parr->procs[p_index];
bool success = refine(parr, ogr, max_pe_heap, min_pe_heap, pe_obj, p_index, avg_load, threshold);
if (!success) {
// Swap with something.
if (!refineSwap(parr, ogr, max_pe_heap, min_pe_heap, pe_obj, p_index, avg_load,
threshold)) {
max_pe_heap.push_back(p_index);
std::push_heap(max_pe_heap.begin(), max_pe_heap.end(),
ProcLoadGreaterIndex(parr));
break;
}
}
}
/** ============================== CLEANUP ================================ */
ogr->convertDecisions(stats); // Send decisions back to LDStats
delete[] pe_obj;
delete parr;
delete ogr;
}
