Hi
Thanks for your help. The changes have improved the performance by 6% and 11% with -DFL_USE_FLOAT=ON.
see below for the new performance report:
Nom de la fonction Échantillons inclusifs Échantillons exclusifs % d'échantillons inclusifs % d'échantillons exclusifs
std::_Lockit::_Lockit 164 400 164 400 3,86 3,86
std::_Lockit::~_Lockit 154 973 154 973 3,64 3,64
fl::Antecedent::activationDegree 1 827 003 142 519 42,92 3,35
std::_Iterator_base12::_Adopt 258 770 71 718 6,08 1,68
std::_Iterator_base12::_Orphan_me 69 654 69 654 1,64 1,64
fl::Aggregated::membership 370 004 57 360 8,69 1,35
fl::Operation::isEq 199 016 51 960 4,68 1,22
fl::Operation::isNaN<float> 47 240 47 240 1,11 1,11
fl::Ramp::membership 292 940 43 361 6,88 1,02
fl::Activated::membership 237 920 42 495 5,59 1,00
std::_Iterator_base12::operator= 251 390 36 560 5,91 0,86
std::vector<fl::Activated,std::allocator<fl::Activated> >::size 30 772 30 772 0,72 0,72
std::_Container_base12::_Orphan_all 29 263 29 263 0,69 0,69
std::_Iterator_base12::~_Iterator_base12 260 649 29 018 6,12 0,68
std::_Iterator_base12::_Iterator_base12 280 520 26 367 6,59 0,62
std::_Vector_const_iterator<std::_Vector_val<std::_Simple_types<fl::Hedge *> > >::_Vector_const_iterator<std::_Vector_val<std::_Simple_types<fl::Hedge *> > > 318 347 16 826 7,48 0,40
In Antecedent::activationDegree function, bottlenecks are at this lines :
`37.6%: return conjunction->compute(
this->activationDegree(conjunction, disjunction, fuzzyOperator->left),
this->activationDegree(conjunction, disjunction, fuzzyOperator->right));
14%: if (fuzzyOperator->name == Rule::andKeyword()) {
8.6%: for (std::vector<Hedge*>::const_reverse_iterator rit = proposition->hedges.rbegin();
11.3%: rit != proposition->hedges.rend(); ++rit) {
3.3%: result = proposition->term->membership(inputVariable->getInputValue());`
Cheers