co.turnus.profiling.util.ProfilingWeightsEstimator.java Source code

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Here is the source code for co.turnus.profiling.util.ProfilingWeightsEstimator.java

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/* 
 * TURNUS, the co-exploration framework
 * 
 * Copyright (C) 2014 EPFL SCI STI MM
 *
 * This file is part of TURNUS.
 *
 * TURNUS is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * TURNUS is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with TURNUS.  If not, see <http://www.gnu.org/licenses/>.
 * 
 * Additional permission under GNU GPL version 3 section 7
 * 
 * If you modify this Program, or any covered work, by linking or combining it
 * with Eclipse (or a modified version of Eclipse or an Eclipse plugin or 
 * an Eclipse library), containing parts covered by the terms of the 
 * Eclipse Public License (EPL), the licensors of this Program grant you 
 * additional permission to convey the resulting work.  Corresponding Source 
 * for a non-source form of such a combination shall include the source code 
 * for the parts of Eclipse libraries used as well as that of the  covered work.
 * 
 */
package co.turnus.profiling.util;

import java.util.HashMap;
import java.util.Map;
import java.util.Map.Entry;

import org.apache.commons.math3.util.FastMath;
import org.eclipse.emf.common.util.EMap;

import co.turnus.common.Operator;
import co.turnus.common.StatisticalData;
import co.turnus.dataflow.Action;
import co.turnus.dataflow.Actor;
import co.turnus.profiling.ActionProfilingData;
import co.turnus.profiling.ActionProfilingWeights;
import co.turnus.profiling.ActorProfilingWeights;
import co.turnus.profiling.ProfilingData;
import co.turnus.profiling.ProfilingFactory;
import co.turnus.profiling.ProfilingWeights;

import com.google.common.collect.Table;

public class ProfilingWeightsEstimator {

    public static final double DEFAULT_OPERATOR_COST = 1.0;

    private Map<Operator, Double> operatorsWeightMap;

    public ProfilingWeightsEstimator() {
        operatorsWeightMap = new HashMap<Operator, Double>();
        for (Operator op : Operator.values()) {
            operatorsWeightMap.put(op, DEFAULT_OPERATOR_COST);
        }
    }

    public ProfilingWeights estimate(ProfilingData data) {
        ProfilingFactory f = ProfilingFactory.eINSTANCE;
        ProfilingWeights netWeights = f.createProfilingWeights();
        netWeights.setNetwork(data.getNetwork());

        Table<Actor, Action, ActionProfilingData> table = data.asTable();
        double networkCost = estimateNetworkCost(data);

        for (Actor actor : table.rowKeySet()) {
            ActorProfilingWeights actorWeights = f.createActorProfilingWeights();
            actorWeights.setActor(actor);
            double actorCost = 0;

            for (Entry<Action, ActionProfilingData> actionEntry : table.row(actor).entrySet()) {

                ActionProfilingData aData = actionEntry.getValue();
                ActionProfilingWeights actionWeights = f.createActionProfilingWeights();
                actionWeights.setAction(actionEntry.getKey());

                EMap<Operator, StatisticalData> opsMap = aData.getOperatorsCall();
                int samples = opsMap.size();

                double mean = 0;
                double min = 0;
                double max = 0;
                double sum = 0;

                if (samples > 0) {
                    min = Double.MAX_VALUE;
                    max = Double.MIN_VALUE;

                    for (Entry<Operator, StatisticalData> entry : opsMap.entrySet()) {
                        double c = operatorsWeightMap.get(entry.getKey());
                        sum += c * entry.getValue().getMean();
                        min = FastMath.min(min, c * entry.getValue().getMin());
                        max = FastMath.max(max, c * entry.getValue().getMax());
                    }

                    mean = sum / samples;
                }

                // set clock cycles
                actionWeights.setClockcycles(mean);
                actionWeights.setClockcyclesMin(min);
                actionWeights.setClockcyclesMax(max);

                // set workload
                actionWeights.setWorkload(sum / networkCost * 100);
                actorCost += sum;

                // finally, add it to the list
                actorWeights.getActionsWeights().add(actionWeights);
            }

            // set workload
            actorWeights.setWorkload(actorCost / networkCost * 100);

            // finally, add it to the list
            netWeights.getActorsWeights().add(actorWeights);

        }

        return netWeights;
    }

    private double estimateNetworkCost(ProfilingData data) {
        EMap<Operator, StatisticalData> opsMap = new ProfilingDataAnalyser(data).getSumExecData()
                .getOperatorsCall();
        int samples = opsMap.size();

        double sum = 0;

        if (samples > 0) {
            for (Entry<Operator, StatisticalData> entry : opsMap.entrySet()) {
                double c = operatorsWeightMap.get(entry.getKey());
                sum += c * entry.getValue().getMean();
            }
        }

        return sum;
    }

    public void setOperatorCost(Operator op, double cost) {
        cost = cost > 0 ? cost : 0;
        operatorsWeightMap.put(op, cost);
    }

    public void setOperatorCosts(Map<Operator, Double> costsMap) {
        for (Entry<Operator, Double> entry : costsMap.entrySet()) {
            setOperatorCost(entry.getKey(), entry.getValue());
        }
    }

}