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Hadrons: genetic scheduler improvement
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@ -61,10 +61,12 @@ public:
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friend std::ostream & operator<<(std::ostream &out,
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const GeneticScheduler<T> &s)
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{
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out << "[";
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for (auto &p: s.population_)
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{
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out << p.second << ": " << p.first << std::endl;
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out << p.first << ", ";
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}
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out << "\b\b]";
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return out;
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}
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@ -72,10 +74,10 @@ private:
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// randomly initialize population
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void initPopulation(void);
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// genetic operators
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const std::vector<T> & selection(void);
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void crossover(const std::vector<T> &c1,
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const std::vector<T> &c2);
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void mutation(std::vector<T> &c);
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std::vector<T> * select1(void);
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std::pair<std::vector<T> *, std::vector<T> *> select2(void);
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void crossover(void);
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void mutation(void);
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private:
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Graph<T> &graph_;
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const ObjFunc &func_;
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@ -115,38 +117,35 @@ int GeneticScheduler<T>::getMinValue(void)
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template <typename T>
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void GeneticScheduler<T>::nextGeneration(void)
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{
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std::uniform_real_distribution<double> dis(0., 1.);
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// random initialization of the population if necessary
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if (population_.size() != par_.popSize)
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{
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initPopulation();
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}
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// mating
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for (unsigned int i = 0; i < par_.popSize/2; ++i)
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{
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auto &p1 = selection(), &p2 = selection();
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crossover(p1, p2);
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}
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LOG(Debug) << "Starting population:\n" << *this << std::endl;
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// random mutations
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auto buf = population_;
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population_.clear();
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for (auto &c: buf)
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PARALLEL_FOR_LOOP
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for (unsigned int i = 0; i < par_.popSize; ++i)
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{
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if (dis(gen_) < par_.mutationRate)
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{
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mutation(c.second);
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}
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population_.emplace(func_(c.second), c.second);
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mutation();
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}
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LOG(Debug) << "After mutations:\n" << *this << std::endl;
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// mating
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PARALLEL_FOR_LOOP
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for (unsigned int i = 0; i < par_.popSize/2; ++i)
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{
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crossover();
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}
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LOG(Debug) << "After mating:\n" << *this << std::endl;
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// grim reaper
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auto it = population_.begin();
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std::advance(it, par_.popSize);
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population_.erase(it, population_.end());
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LOG(Debug) << "After grim reaper:\n" << *this << std::endl;
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}
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// randomly initialize population //////////////////////////////////////////////
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@ -164,37 +163,66 @@ void GeneticScheduler<T>::initPopulation(void)
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// genetic operators ///////////////////////////////////////////////////////////
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template <typename T>
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const std::vector<T> & GeneticScheduler<T>::selection(void)
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std::vector<T> * GeneticScheduler<T>::select1(void)
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{
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std::uniform_int_distribution<unsigned int> pdis(0, population_.size() - 1);
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auto it = population_.begin();
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std::advance(it, pdis(gen_));
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return &(it->second);
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}
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template <typename T>
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std::pair<std::vector<T> *, std::vector<T> *> GeneticScheduler<T>::select2(void)
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{
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std::vector<double> prob;
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unsigned int ind;
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std::vector<T> *p1, *p2;
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for (auto &c: population_)
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{
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prob.push_back(1./c.first);
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}
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std::discrete_distribution<unsigned int> dis(prob.begin(), prob.end());
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auto rIt = population_.begin();
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std::advance(rIt, dis(gen_));
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do
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{
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double probCpy;
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std::discrete_distribution<unsigned int> dis1(prob.begin(), prob.end());
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auto rIt = population_.begin();
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ind = dis1(gen_);
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std::advance(rIt, ind);
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p1 = &(rIt->second);
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probCpy = prob[ind];
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prob[ind] = 0.;
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std::discrete_distribution<unsigned int> dis2(prob.begin(), prob.end());
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rIt = population_.begin();
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std::advance(rIt, dis2(gen_));
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p2 = &(rIt->second);
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prob[ind] = probCpy;
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} while (p1 == p2);
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return rIt->second;
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return std::make_pair(p1, p2);
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}
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template <typename T>
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void GeneticScheduler<T>::crossover(const std::vector<T> &p1,
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const std::vector<T> &p2)
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void GeneticScheduler<T>::crossover(void)
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{
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std::uniform_int_distribution<unsigned int> dis(0, p1.size() - 1);
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unsigned int cut = dis(gen_);
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auto p = select2();
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auto &p1 = *(p.first),
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&p2 = *(p.second);
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std::uniform_int_distribution<unsigned int> dis2(0, p1.size() - 1);
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unsigned int cut = dis2(gen_);
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std::vector<T> c1, c2, buf;
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auto cross = [&buf, cut](std::vector<T> &c, const std::vector<T> &p1,
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const std::vector<T> &p2)
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{
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buf = p2;
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buf = p1;
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for (unsigned int i = 0; i < cut; ++i)
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{
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c.push_back(p1[i]);
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buf.erase(std::find(buf.begin(), buf.end(), p1[i]));
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c.push_back(p2[i]);
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buf.erase(std::find(buf.begin(), buf.end(), p2[i]));
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}
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for (unsigned int i = 0; i < buf.size(); ++i)
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{
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@ -204,31 +232,51 @@ void GeneticScheduler<T>::crossover(const std::vector<T> &p1,
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cross(c1, p1, p2);
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cross(c2, p2, p1);
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population_.emplace(func_(c1), c1);
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population_.emplace(func_(c2), c2);
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PARALLEL_CRITICAL
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{
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population_.emplace(func_(c1), c1);
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population_.emplace(func_(c2), c2);
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}
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}
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template <typename T>
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void GeneticScheduler<T>::mutation(std::vector<T> &c)
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void GeneticScheduler<T>::mutation(void)
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{
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std::uniform_int_distribution<unsigned int> dis(0, c.size() - 1);
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unsigned int cut = dis(gen_);
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Graph<T> g = graph_;
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std::vector<T> buf;
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std::uniform_real_distribution<double> mdis(0., 1.);
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for (unsigned int i = cut; i < c.size(); ++i)
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if (mdis(gen_) < par_.mutationRate)
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{
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g.removeVertex(c[i]);
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auto &c = *select1();
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std::uniform_int_distribution<unsigned int> cdis(0, c.size() - 1);
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unsigned int cut = cdis(gen_);
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std::vector<T> buf1, buf2;
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Graph<T> g1 = graph_, g2 = graph_;
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for (unsigned int i = 0; i < cut; ++i)
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{
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g1.removeVertex(c[i]);
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}
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for (unsigned int i = cut; i < c.size(); ++i)
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{
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g2.removeVertex(c[i]);
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}
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if (g1.size() > 0)
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{
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buf1 = g1.topoSort(gen_);
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}
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if (g2.size() > 0)
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{
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buf2 = g2.topoSort(gen_);
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}
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for (unsigned int i = cut; i < c.size(); ++i)
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{
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buf2.push_back(buf1[i - cut]);
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}
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PARALLEL_CRITICAL
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{
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population_.emplace(func_(buf2), buf2);
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}
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}
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if (g.size() > 0)
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{
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buf = g.topoSort(gen_);
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}
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for (unsigned int i = cut; i < c.size(); ++i)
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{
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buf.push_back(c[i]);
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}
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c = buf;
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}
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END_HADRONS_NAMESPACE
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@ -46,11 +46,13 @@ Author: paboyle <paboyle@ph.ed.ac.uk>
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#endif
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#define PARALLEL_NESTED_LOOP2 _Pragma("omp parallel for collapse(2)")
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#define PARALLEL_REGION _Pragma("omp parallel")
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#define PARALLEL_CRITICAL _Pragma("omp critical")
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#else
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#define PARALLEL_FOR_LOOP
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#define PARALLEL_FOR_LOOP_INTERN
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#define PARALLEL_NESTED_LOOP2
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#define PARALLEL_REGION
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#define PARALLEL_CRITICAL
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#endif
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namespace Grid {
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