void defaultExecution(SysEnv &sysEnv, std::string &metricType, RegionTemplateCollection *rtCollection,
std::string tuningPolicy,
float *perf, float *totaldiffs, float *metricPerIteration,
float *diceNotCoolPerIteration,
uint64_t *totalexecutiontimes) {
int versionNorm = 0, versionSeg = 0;
int segCount = 0;
std::vector<int> segComponentIds[rtCollection->getNumRTs()];
std::vector<int> metricComponentIds[rtCollection->getNumRTs()];
std::vector<int> diceNotCoolComponentIds[rtCollection->getNumRTs()];
// Build application dependency graph
// Instantiate application dependency graph
for (int i = 0; i < rtCollection->getNumRTs(); i++) {
int previousSegCompId = 0;
// CREATE NORMALIZATION STEP
ParameterSet parSetNormalization;
std::vector<ArgumentBase *> targetMeanOptions;
ArgumentFloatArray *targetMeanAux = new ArgumentFloatArray(ArgumentFloat(-0.632356));
targetMeanAux->addArgValue(ArgumentFloat(-0.0516004));
targetMeanAux->addArgValue(ArgumentFloat(0.0376543));
targetMeanOptions.push_back(targetMeanAux);
parSetNormalization.addArguments(targetMeanOptions);
parSetNormalization.resetIterator();
std::vector<ArgumentBase *> argSetInstanceNorm = parSetNormalization.getNextArgumentSetInstance();
NormalizationComp *norm = new NormalizationComp();
// normalization parameters
norm->addArgument(new ArgumentInt(versionNorm));
norm->addArgument(argSetInstanceNorm[0]);
norm->addRegionTemplateInstance(rtCollection->getRT(i), rtCollection->getRT(i)->getName());
sysEnv.executeComponent(norm);
std::cout << "BEGIN: Default Execution: ";
std::cout << std::endl;
// Creating segmentation component
Segmentation *seg = new Segmentation();
// version of the data region red. Each parameter instance in norm creates a output w/ different version
seg->addArgument(new ArgumentInt(versionNorm));
// version of the data region generated by the segmentation stage
seg->addArgument(new ArgumentInt(versionSeg));
int blue = 220;
int green = 220;
int red = 220;
float T1 = 5.0;
float T2 = 4.0;
int G1 = 80;
int minSize = 11;
int maxSize = 1000;
int G2 = 45;
int minSizePl = 30;
int minSizeSeg = 21;
int maxSizeSeg = 1000;
int fillHolesConnectivity = 4;
int reconConnectivity = 8;
int watershedConnectivity = 8;
// add remaining (application specific) parameters from the argSegInstance
seg->addArgument(new ArgumentInt(
(int) round(blue)));
seg->addArgument(new ArgumentInt(
(int) round(green)));
seg->addArgument(new ArgumentInt(
(int) round(red)));
seg->addArgument(
new ArgumentFloat((float) (T1)));
seg->addArgument(
new ArgumentFloat((float) (T2)));
seg->addArgument(new ArgumentInt(
(int) round(G1)));
seg->addArgument(new ArgumentInt(
(int) round(G2)));
seg->addArgument(new ArgumentInt(
(int) round(minSize)));
seg->addArgument(new ArgumentInt(
(int) round(maxSize)));
seg->addArgument(new ArgumentInt(
(int) round(minSizePl)));
seg->addArgument(new ArgumentInt(
(int) round(minSizeSeg)));
seg->addArgument(new ArgumentInt(
(int) round(maxSizeSeg)));
seg->addArgument(new ArgumentInt(
(int) round(fillHolesConnectivity)));
seg->addArgument(new ArgumentInt(
(int) round(reconConnectivity)));
seg->addArgument(new ArgumentInt(
(int) round(watershedConnectivity)));
// and region template instance that it is suppose to process
seg->addRegionTemplateInstance(rtCollection->getRT(i), rtCollection->getRT(i)->getName());
seg->addDependency(norm->getId());
std::cout << "Creating DiffMask" << std::endl;
RTPipelineComponentBase *metricComp;
DiceNotCoolMaskComp *diceNotCoolComp;
if (metricType.find("jaccard") != std::string::npos) metricComp = new JaccardMaskComp();
else metricComp = new DiceMaskComp();
if (metricType.find("dicenc") != std::string::npos) diceNotCoolComp = new DiceNotCoolMaskComp();
// version of the data region that will be read. It is created during the segmentation.
// region template name
metricComp->addArgument(new ArgumentInt(versionSeg));
metricComp->addRegionTemplateInstance(rtCollection->getRT(i), rtCollection->getRT(i)->getName());
metricComp->addDependency(seg->getId());
// add to the list of diff component ids.
segComponentIds[i].push_back(seg->getId());
metricComponentIds[i].push_back(metricComp->getId());
sysEnv.executeComponent(seg);
sysEnv.executeComponent(metricComp);
if (metricType.find("dicenc") != std::string::npos) {
diceNotCoolComp->addArgument(new ArgumentInt(versionSeg));
diceNotCoolComp->addRegionTemplateInstance(rtCollection->getRT(i),
rtCollection->getRT(i)->getName());
diceNotCoolComp->addDependency(metricComp->getId());
diceNotCoolComponentIds[i].push_back(diceNotCoolComp->getId());
sysEnv.executeComponent(diceNotCoolComp);
}
std::cout << "Manager CompId: " << metricComp->getId() << " fileName: " <<
rtCollection->getRT(i)->getDataRegion(0)->getInputFileName() << std::endl;
segCount++;
versionSeg++;
versionNorm++;
}
// End Creating Dependency Graph
sysEnv.startupExecution();
std::cout << std::endl << std::endl;
//==============================================================================================
//Fetch results from execution workflow
//==============================================================================================
for (int j = 0; j < rtCollection->getNumRTs(); j++) {
float metric = 0;
float secondaryMetric = 0;
float diceNotCoolValue = 0;
std::ostringstream oss;
oss << " Default PARAMS";
for (int i = 0; i < metricComponentIds[j].size(); i++) {
char *metricResultData = sysEnv.getComponentResultData(metricComponentIds[j][i]);
std::cout << "RT name: " << rtCollection->getRT(j)->getDataRegion("RAW")->getInputFileName() <<
" - Diff Id: " << metricComponentIds[j][i];
if (metricResultData != NULL) {
//std::cout << "size: " << ((int *) metricResultData)[0] << " \thadoopgis-metric: " <<
//((float *) metricResultData)[1] <<
//" \tsecondary: " << ((float *) metricResultData)[2] << endl;
metric += ((float *) metricResultData)[1];
secondaryMetric += ((float *) metricResultData)[2];
if (metricType.find("dicenc") != std::string::npos) {
char *diceNotCoolResultData = sysEnv.getComponentResultData(diceNotCoolComponentIds[j][i]);
// std::cout << " \tdiceNotCool: " <<
// ((float *) diceNotCoolResultData)[1] << std::endl;
diceNotCoolValue += ((float *) diceNotCoolResultData)[1];
}
} else {
std::cout << "NULL" << std::endl;
}
char *segExecutionTime = sysEnv.getComponentResultData(segComponentIds[j][i]);
if (segExecutionTime != NULL) {
totalexecutiontimes[j] = ((int *) segExecutionTime)[1];
// cout << "Segmentation execution time:" <<
// totalexecutiontimes[j] << endl;
}
if (metricType.find("dicenc") != std::string::npos)
sysEnv.eraseResultData(diceNotCoolComponentIds[j][i]);
sysEnv.eraseResultData(metricComponentIds[j][i]);
sysEnv.eraseResultData(segComponentIds[j][i]);
}
metricComponentIds[j].clear();
segComponentIds[j].clear();
if (metricType.find("dicenc") != std::string::npos) diceNotCoolComponentIds[j].clear();
float diff;
if (metricType.find("dicenc") != std::string::npos) diff = (metric + diceNotCoolValue) / 2;
else diff = metric;
if (diff <= 0) diff = FLT_EPSILON;
cout << "\tDiff (average of metric and dnc): " << diff << "\tMetric:" << metric << "\tDNC:" <<
diceNotCoolValue << " Segmentation Time: " <<
totalexecutiontimes[j] << endl;
totaldiffs[j] = diff;
metricPerIteration[j] = metric;
diceNotCoolPerIteration[j] = diceNotCoolValue;
}
std::cout << std::endl << std::endl;
}
TuningInterface *multiObjectiveTuning(int argc, char **argv, SysEnv &sysEnv, int max_number_of_tests,
std::string &metricType,
double metricWeight,
double timeWeight,
double &tSlowest, double &tFastest, RegionTemplateCollection *rtCollection,
std::string tuningPolicy,
float *perf, float *totaldiffs, float *metricPerIteration,
float *diceNotCoolPerIteration,
uint64_t *totalexecutiontimes) {
TuningInterface *tuningClient;
int numClients;
//USING AH
if (tuningPolicy.find("nm") != std::string::npos || tuningPolicy.find("NM") != std::string::npos ||
tuningPolicy.find("pro") != std::string::npos || tuningPolicy.find("PRO") != std::string::npos ||
tuningPolicy.find("random") != std::string::npos || tuningPolicy.find("RANDOM") != std::string::npos) {
numClients = 1;
tuningClient = new ActiveHarmonyTuning(tuningPolicy, max_number_of_tests, numClients);
} else {
//USING GA
int max_number_of_generations = (int) floor(sqrt(max_number_of_tests));
int mutationchance = 30;
int crossoverrate = 50;
int popsize = (int) ceil(sqrt(max_number_of_tests));
if (popsize > 1 && ((popsize % 2) == 1)) {
--popsize;
max_number_of_generations++;
} //Pop size must be an even number for GA.
if (popsize <= 1) popsize++; //pop size must be at least 2.
if (popsize * max_number_of_generations > max_number_of_tests) {
max_number_of_generations--;
}
//int propagationamount = 2;
int propagationamount = (int) ceil(popsize * 0.25); //around 25% of popsize
if ((2 * propagationamount) >= popsize)
propagationamount--; //Elite size(propagation amount) must be less than half the popsize.
numClients = popsize; //popsize
tuningClient = new GeneticAlgorithm(max_number_of_generations, popsize, mutationchance,
crossoverrate,
propagationamount,
1);
}
double *totalExecutionTimesNormalized = (double *) malloc(sizeof(double) * max_number_of_tests);
std::vector<int> segComponentIds[numClients];
std::vector<int> metricComponentIds[numClients];
std::vector<int> diceNotCoolComponentIds[numClients];
std::map<std::string, double> perfDataBase; //Checks if a param has been tested already
int versionNorm = 0, versionSeg = 0;
resetPerf(perf, max_number_of_tests);
bool executedAlready[numClients];
int repeatCounter = 0;
if (tuningClient->initialize(argc, argv) != 0) {
fprintf(stderr, "Failed to initialize tuning session.\n");
return NULL;
};
if (tuningClient->declareParam("blue", 210, 240, 10) != 0 ||
tuningClient->declareParam("green", 210, 240, 10) != 0 ||
tuningClient->declareParam("red", 210, 240, 10) != 0 ||
tuningClient->declareParam("T1", 2.5, 7.5, 0.5) != 0 ||
tuningClient->declareParam("T2", 2.5, 7.5, 0.5) != 0 ||
tuningClient->declareParam("G1", 5, 80, 5) != 0 ||
tuningClient->declareParam("minSize", 2, 40, 2) != 0 ||
tuningClient->declareParam("maxSize", 900, 1500, 50) != 0 ||
tuningClient->declareParam("G2", 2, 40, 2) != 0 ||
tuningClient->declareParam("minSizePl", 5, 80, 5) != 0 ||
tuningClient->declareParam("minSizeSeg", 2, 40, 2) != 0 ||
tuningClient->declareParam("maxSizeSeg", 900, 1500, 50) != 0 ||
tuningClient->declareParam("fillHoles", 4, 8, 4) != 0 ||
tuningClient->declareParam("recon", 4, 8, 4) != 0 ||
tuningClient->declareParam("watershed", 4, 8, 4) != 0) {
fprintf(stderr, "Failed to define tuning session\n");
return NULL;
}
if (tuningClient->configure() != 0) {
fprintf(stderr, "Failed to initialize tuning session.\n");
return NULL;
};
for (; !tuningClient->hasConverged();) {
cout << "ITERATION: " << tuningClient->getIteration() << endl;
//Get new param suggestions from the tuning client
tuningClient->fetchParams();
//Apply fitness function for each individual
for (int i = 0; i < numClients; i++) {
std::ostringstream oss;
oss << "PARAMS";
typedef std::map<std::string, double *>::iterator it_type;
for (it_type iterator = tuningClient->getParamSet(i)->paramSet.begin();
iterator != tuningClient->getParamSet(i)->paramSet.end(); iterator++) {
//iterator.first key
//iterator.second value
oss << " - " << iterator->first << ": " << *(iterator->second);
}
// / if not found in performance database
if (perfDataBase.find(oss.str()) != perfDataBase.end()) {
perf[tuningClient->getIteration() * numClients +
(i)] = perfDataBase.find(oss.str())->second;
std::cout << "Parameters already tested: " << oss.str() << " perf: " << perf << std::endl;
executedAlready[i] = true;
} else {
executedAlready[i] = false;
}
}
int segCount = 0;
// Build application dependency graph
// Instantiate application dependency graph
for (int i = 0; i < rtCollection->getNumRTs(); i++) {
int previousSegCompId = 0;
// CREATE NORMALIZATION STEP
ParameterSet parSetNormalization;
std::vector<ArgumentBase *> targetMeanOptions;
ArgumentFloatArray *targetMeanAux = new ArgumentFloatArray(ArgumentFloat(-0.632356));
targetMeanAux->addArgValue(ArgumentFloat(-0.0516004));
targetMeanAux->addArgValue(ArgumentFloat(0.0376543));
targetMeanOptions.push_back(targetMeanAux);
parSetNormalization.addArguments(targetMeanOptions);
parSetNormalization.resetIterator();
std::vector<ArgumentBase *> argSetInstanceNorm = parSetNormalization.getNextArgumentSetInstance();
NormalizationComp *norm = new NormalizationComp();
// normalization parameters
norm->addArgument(new ArgumentInt(versionNorm));
norm->addArgument(argSetInstanceNorm[0]);
norm->addRegionTemplateInstance(rtCollection->getRT(i), rtCollection->getRT(i)->getName());
sysEnv.executeComponent(norm);
for (int j = 0; j < numClients; j++) {
if (executedAlready[j] == false) {
std::cout << "BEGIN: LoopIdx: " << tuningClient->getIteration() * numClients + (j);
typedef std::map<std::string, double *>::iterator it_type;
for (it_type iterator = tuningClient->getParamSet(j)->paramSet.begin();
iterator != tuningClient->getParamSet(j)->paramSet.end(); iterator++) {
std::cout << " - " << iterator->first << ": " << *(iterator->second);
}
std::cout << std::endl;
// Creating segmentation component
Segmentation *seg = new Segmentation();
// version of the data region red. Each parameter instance in norm creates a output w/ different version
seg->addArgument(new ArgumentInt(versionNorm));
// version of the data region generated by the segmentation stage
seg->addArgument(new ArgumentInt(versionSeg));
// add remaining (application specific) parameters from the argSegInstance
seg->addArgument(new ArgumentInt(
(int) round(tuningClient->getParamValue("blue", j))));
seg->addArgument(new ArgumentInt(
(int) round(tuningClient->getParamValue("green", j))));
seg->addArgument(new ArgumentInt(
(int) round(tuningClient->getParamValue("red", j))));
seg->addArgument(
new ArgumentFloat((float) (tuningClient->getParamValue("T1", j))));
seg->addArgument(
new ArgumentFloat((float) (tuningClient->getParamValue("T2", j))));
seg->addArgument(new ArgumentInt(
(int) round(tuningClient->getParamValue("G1", j))));
seg->addArgument(new ArgumentInt(
(int) round(tuningClient->getParamValue("G2", j))));
seg->addArgument(new ArgumentInt(
(int) round(tuningClient->getParamValue("minSize", j))));
seg->addArgument(new ArgumentInt(
(int) round(tuningClient->getParamValue("maxSize", j))));
seg->addArgument(new ArgumentInt(
(int) round(tuningClient->getParamValue("minSizePl", j))));
seg->addArgument(new ArgumentInt(
(int) round(tuningClient->getParamValue("minSizeSeg", j))));
seg->addArgument(new ArgumentInt(
(int) round(tuningClient->getParamValue("maxSizeSeg", j))));
seg->addArgument(new ArgumentInt(
(int) round(tuningClient->getParamValue("fillHoles", j))));
seg->addArgument(new ArgumentInt(
(int) round(tuningClient->getParamValue("recon", j))));
seg->addArgument(new ArgumentInt(
(int) round(tuningClient->getParamValue("watershed", j))));
// and region template instance that it is suppose to process
seg->addRegionTemplateInstance(rtCollection->getRT(i), rtCollection->getRT(i)->getName());
seg->addDependency(norm->getId());
std::cout << "Creating DiffMask" << std::endl;
RTPipelineComponentBase *metricComp;
DiceNotCoolMaskComp *diceNotCoolComp;
if (metricType.find("jaccard") != std::string::npos) metricComp = new JaccardMaskComp();
else metricComp = new DiceMaskComp();
if (metricType.find("dicenc") != std::string::npos) diceNotCoolComp = new DiceNotCoolMaskComp();
// version of the data region that will be read. It is created during the segmentation.
// region template name
metricComp->addArgument(new ArgumentInt(versionSeg));
metricComp->addRegionTemplateInstance(rtCollection->getRT(i), rtCollection->getRT(i)->getName());
metricComp->addDependency(seg->getId());
// add to the list of diff component ids.
segComponentIds[j].push_back(seg->getId());
metricComponentIds[j].push_back(metricComp->getId());
sysEnv.executeComponent(seg);
sysEnv.executeComponent(metricComp);
if (metricType.find("dicenc") != std::string::npos) {
diceNotCoolComp->addArgument(new ArgumentInt(versionSeg));
diceNotCoolComp->addRegionTemplateInstance(rtCollection->getRT(i),
rtCollection->getRT(i)->getName());
diceNotCoolComp->addDependency(metricComp->getId());
diceNotCoolComponentIds[j].push_back(diceNotCoolComp->getId());
sysEnv.executeComponent(diceNotCoolComp);
}
std::cout << "Manager CompId: " << metricComp->getId() << " fileName: " <<
rtCollection->getRT(i)->getDataRegion(0)->getInputFileName() << std::endl;
segCount++;
versionSeg++;
}
}
versionNorm++;
}
// End Creating Dependency Graph
sysEnv.startupExecution();
//==============================================================================================
//Fetch results from execution workflow
//==============================================================================================
for (int j = 0; j < numClients; j++) {
float metric = 0;
float secondaryMetric = 0;
float diceNotCoolValue = 0;
std::ostringstream oss;
oss << "PARAMS";
typedef std::map<std::string, double *>::iterator it_type;
for (it_type iterator = tuningClient->getParamSet(j)->paramSet.begin();
iterator != tuningClient->getParamSet(j)->paramSet.end(); iterator++) {
oss << " - " << iterator->first << ": " << *(iterator->second);
}
if (executedAlready[j] == false) {
for (int i = 0; i < metricComponentIds[j].size(); i++) {
char *metricResultData = sysEnv.getComponentResultData(metricComponentIds[j][i]);
std::cout << "Diff Id: " << metricComponentIds[j][i] << " \tmetricResultData: ";
if (metricResultData != NULL) {
std::cout << "size: " << ((int *) metricResultData)[0] << " \thadoopgis-metric: " <<
((float *) metricResultData)[1] <<
" \tsecondary: " << ((float *) metricResultData)[2] << endl;
metric += ((float *) metricResultData)[1];
secondaryMetric += ((float *) metricResultData)[2];
if (metricType.find("dicenc") != std::string::npos) {
char *diceNotCoolResultData = sysEnv.getComponentResultData(diceNotCoolComponentIds[j][i]);
std::cout << " \tdiceNotCool: " <<
((float *) diceNotCoolResultData)[1] << std::endl;
diceNotCoolValue += ((float *) diceNotCoolResultData)[1];
}
} else {
std::cout << "NULL" << std::endl;
}
char *segExecutionTime = sysEnv.getComponentResultData(segComponentIds[j][i]);
if (segExecutionTime != NULL) {
totalexecutiontimes[tuningClient->getIteration() * numClients +
(j)] = ((int *) segExecutionTime)[1];
cout << "Segmentation execution time:" <<
totalexecutiontimes[tuningClient->getIteration() * numClients + (j)] << endl;
}
if (metricType.find("dicenc") != std::string::npos)
sysEnv.eraseResultData(diceNotCoolComponentIds[j][i]);
sysEnv.eraseResultData(metricComponentIds[j][i]);
sysEnv.eraseResultData(segComponentIds[j][i]);
}
metricComponentIds[j].clear();
segComponentIds[j].clear();
if (metricType.find("dicenc") != std::string::npos) diceNotCoolComponentIds[j].clear();
//########################################################################################
//Multi Objective Tuning
//########################################################################################
float diff;
if (metricType.find("dicenc") != std::string::npos) diff = (metric + diceNotCoolValue) / 2;
else diff = metric;
if (diff <= 0) diff = FLT_EPSILON;
double timeNormalized;
if (timeWeight > 0) {
timeNormalized =
(tSlowest - (double) totalexecutiontimes[tuningClient->getIteration() * numClients + (j)]) /
(tSlowest - tFastest);
// double timeNormalized = (tSlowest)/
// ((double) totalexecutiontimes[tuningClient->getIteration() * numClients + (j)]) ;
}
double weightedSumOfMetricAndTime = (double) (metricWeight * diff + timeWeight * timeNormalized);
if ((weightedSumOfMetricAndTime > 0) && (diff > FLT_EPSILON)) {
perf[tuningClient->getIteration() * numClients + (j)] = (double) 1 /
weightedSumOfMetricAndTime; //Multi Objective Tuning
} else {
perf[tuningClient->getIteration() * numClients + (j)] = std::numeric_limits<double>::infinity();
}
totalExecutionTimesNormalized[tuningClient->getIteration() * numClients + (j)] = timeNormalized;
if (perf[tuningClient->getIteration() * numClients + (j)] < 0)
perf[tuningClient->getIteration() * numClients + (j)] = -perf[
tuningClient->getIteration() * numClients + (j)];
std::cout << "END: LoopIdx: " << tuningClient->getIteration() * numClients + (j);
typedef std::map<std::string, double *>::iterator it_type;
for (it_type iterator = tuningClient->getParamSet(j)->paramSet.begin();
iterator != tuningClient->getParamSet(j)->paramSet.end(); iterator++) {
//iterator.first key
//iterator.second value
std::cout << " - " << iterator->first << ": " << *(iterator->second);
}
cout << endl << endl << "\tDiff: " << diff << " Secondary Metric: " << secondaryMetric <<
" Time Normalized: " << timeNormalized << " Segmentation Time: " <<
totalexecutiontimes[tuningClient->getIteration() * numClients + (j)] << " Perf: " <<
perf[tuningClient->getIteration() * numClients + (j)] << endl;
totaldiffs[tuningClient->getIteration() * numClients + (j)] = diff;
metricPerIteration[tuningClient->getIteration() * numClients + (j)] = metric;
diceNotCoolPerIteration[tuningClient->getIteration() * numClients + (j)] = diceNotCoolValue;
perfDataBase[oss.str()] = perf[tuningClient->getIteration() * numClients + (j)];
} else {
perf[tuningClient->getIteration() * numClients + (j)] = perfDataBase[oss.str()];
std::cout << "ATTENTION! Param set executed already:" << std::endl;
std::cout << "END: LoopIdx: " << tuningClient->getIteration() * numClients + (j);
std::cout << oss.str() << endl;
std::cout << " perf: " << perf[tuningClient->getIteration() * numClients + (j)] << std::endl;
}
// Report the performance we've just measured.
tuningClient->reportScore(perf[tuningClient->getIteration() * numClients + (j)], j);
}
//Checks if at least one test in this iteration succeeded.
bool shouldIterate = false;
for (int k = 0; k < numClients; ++k) {
shouldIterate |= !executedAlready[k];
}
//Iterates the tuning algorithm
if (shouldIterate == true || (repeatCounter >= MAX_ITERATION_REPEAT)) {
tuningClient->nextIteration();
repeatCounter = 0;
} else {
repeatCounter++;
}
//tuningClient->nextIteration(); //Always iterate - to be fair, all 3 algorithms may repeat values.
}
return tuningClient;
}