From fbec5a3863135d0ac5b17257fff345cb3db39a27 Mon Sep 17 00:00:00 2001
From: Jonathan Rouzaud-Cornabas <jonathan.rouzaud-cornabas@inria.fr>
Date: Tue, 3 Jul 2018 14:46:31 +0200
Subject: [PATCH] Verified version with OpenMP Task without dependency
---
src/libaevol/JumpingMT.cpp | 3 +-
src/libaevol/JumpingMT.h | 2 +-
src/libaevol/SIMD_Individual.cpp | 72 ++++++++++++++++++++------------
src/libaevol/Selection.cpp | 20 +++++++--
4 files changed, 64 insertions(+), 33 deletions(-)
diff --git a/src/libaevol/JumpingMT.cpp b/src/libaevol/JumpingMT.cpp
index 97c4f0277..8d5b61e2b 100644
--- a/src/libaevol/JumpingMT.cpp
+++ b/src/libaevol/JumpingMT.cpp
@@ -236,13 +236,14 @@ double JumpingMT::gaussian_random()
return x1 * r;
}
-int32_t JumpingMT::roulette_random(double* probs, int32_t nb_elts)
+int32_t JumpingMT::roulette_random(double* probs, int32_t nb_elts, bool verbose )
{
double pick_one = 0.0;
while (pick_one == 0.0)
{
pick_one = random();
+ //if (verbose) printf("pick one : %f\n",pick_one);
}
int32_t found_org = 0;
diff --git a/src/libaevol/JumpingMT.h b/src/libaevol/JumpingMT.h
index 4b0e38253..85b3ef6f4 100644
--- a/src/libaevol/JumpingMT.h
+++ b/src/libaevol/JumpingMT.h
@@ -101,7 +101,7 @@ class JumpingMT
inline int64_t random(int64_t max); // ~
int32_t binomial_random(int32_t nb, double prob); // Binomial drawing of parameters (nb, prob)
double gaussian_random(); // Double following a Standard Normal distribution
- int32_t roulette_random(double* probs, int32_t nb_elts); // Roulette selection
+ int32_t roulette_random(double* probs, int32_t nb_elts, bool verbose = false); // Roulette selection
void multinomial_drawing (int32_t* destination, double* source, int32_t nb_drawings, int32_t colors);
// Multinomial drawing of parameters (nb, {source[0], source[1], ... source[colors-1]})
diff --git a/src/libaevol/SIMD_Individual.cpp b/src/libaevol/SIMD_Individual.cpp
index 4d9561aa0..a44d22ef7 100644
--- a/src/libaevol/SIMD_Individual.cpp
+++ b/src/libaevol/SIMD_Individual.cpp
@@ -246,26 +246,32 @@ void SIMD_Individual::selection() {
local_fit_array[count] = prev_internal_simd_struct[cur_x*grid_height+cur_y]->fitness;
-/* printf("Local fit %e %d %d %d -> %e\n",local_fit_array[count],cur_x,cur_y,cur_x*grid_height+cur_y,
- prev_internal_simd_struct[cur_x*grid_height+cur_y]->fitness);*/
+// printf("Local fit %e %d %d %d -> %e\n",local_fit_array[count],cur_x,cur_y,cur_x*grid_height+cur_y,
+// prev_internal_simd_struct[cur_x*grid_height+cur_y]->fitness);
local_meta_array[count] = prev_internal_simd_struct[cur_x*grid_height+cur_y]->metaerror;
sum_local_fit += local_fit_array[count];
-/* if (indiv_id == 268)
- printf("SIMD Local SUM Fit %e -- Fitness %e\n",sum_local_fit,local_fit_array[count]);*/
+ /*if (indiv_id == 0)
+ printf("SIMD Local SUM Fit %e -- Fitness %e (CPU %e)\n",sum_local_fit,local_fit_array[count],exp_m_->world()->grid(x,y)->local_fit_array[count]);*/
count++;
}
}
for(int16_t i = 0 ; i < neighborhood_size ; i++) {
probs[i] = local_fit_array[i]/sum_local_fit;
- /*if (i == 0)
- printf("Local fit X %e %d %d %d -> %e\n",local_fit_array[i],cur_x,cur_y,cur_x*grid_height+cur_y,
+
+ /*printf("Local fit X %e %d %d %d -> %e\n",local_fit_array[i],cur_x,cur_y,cur_x*grid_height+cur_y,
prev_internal_simd_struct[cur_x*grid_height+cur_y]->fitness);*/
//printf("%d -- prob[%d] : %e : fitness %e (%f) sum %e\n",indiv_id,i,probs[i],
// local_fit_array[i],local_meta_array[i],sum_local_fit);
}
+ //printf("SIMD PRNG\n");
+ /* bool verbose = false;
+ if (indiv_id == 2) {
+ printf("SIMD PRNG\n");
+ verbose = true;
+ }*/
int16_t found_org = exp_m_->world()->grid(x,y)->reprod_prng_simd_->roulette_random(probs, neighborhood_size);
int16_t x_offset = (found_org / selection_scope_x) - 1;
@@ -276,26 +282,27 @@ void SIMD_Individual::selection() {
((y+y_offset+grid_height) % grid_height);
-/* for (int i = 0; i < neighborhood_size; i++) {
+ for (int i = 0; i < neighborhood_size; i++) {
float i_fit_1 = roundf(exp_m_->world()->grid(x,y)->probs[i] * 10000);
float i_fit_2 = roundf(probs[i] * 10000);
- if (found_id != internal_simd_struct[indiv_id]->parent_id) {
+ if (found_id != next_generation_reproducer_[indiv_id]) {
- printf("For individual %d : Selection is diff SIMD %d CPU %d (Meta error %f -- %f || Fitness %e -- %e (%e %e diff %e -- %e %e -- %e %e)\n",
- indiv_id, found_id, internal_simd_struct[indiv_id]->parent_id,
- prev_internal_simd_struct[internal_simd_struct[indiv_id]->parent_id]->metaerror,
+ printf("For individual %d : Selection is diff SIMD %d CPU %d (Meta error %f -- %f || Fitness %e -- %e)\n",
+ // (Probs %e %e diff %e -- Fit Array %e %e -- Sum Fit %e %e)\n",
+ indiv_id, found_id, next_generation_reproducer_[indiv_id],
+ prev_internal_simd_struct[next_generation_reproducer_[indiv_id]]->metaerror,
prev_internal_simd_struct[found_id]->metaerror,
- prev_internal_simd_struct[internal_simd_struct[indiv_id]->parent_id]->fitness,
- prev_internal_simd_struct[found_id]->fitness,exp_m_->world()->grid(x,y)->probs[i],probs[i],
+ prev_internal_simd_struct[next_generation_reproducer_[indiv_id]]->fitness,
+ prev_internal_simd_struct[found_id]->fitness/*,exp_m_->world()->grid(x,y)->probs[i],probs[i],
exp_m_->world()->grid(x,y)->probs[i]-probs[i],
exp_m_->world()->grid(x,y)->local_fit_array[i],local_fit_array[i],
- exp_m_->world()->grid(x,y)->sum_local_fit,sum_local_fit
+ exp_m_->world()->grid(x,y)->sum_local_fit,sum_local_fit*/
);
}
- }*/
+ }
delete [] local_fit_array;
@@ -4078,7 +4085,7 @@ void SIMD_Individual::run_a_step(double w_max, double selection_pressure,bool op
for (int indiv_id = 0; indiv_id < exp_m_->nb_indivs(); indiv_id++) {
#pragma omp task firstprivate(indiv_id)
{
- //if (optim_prom) check_selection(indiv_id);
+ // if (AeTime::time() > 0 && optim_prom) check_selection(indiv_id);
if (standalone_ && optim_prom) {
selection(indiv_id);
@@ -4276,19 +4283,29 @@ void SIMD_Individual::run_a_step(double w_max, double selection_pressure,bool op
//exit(-44);
if (optim_prom) {
// printf("OPT -- Copy to old generation struct\n");
- for (int indiv_id = 0; indiv_id < (int) exp_m_->nb_indivs(); indiv_id++) {
- if (prev_internal_simd_struct[indiv_id]->usage_count_-1 == 0)
- delete prev_internal_simd_struct[indiv_id];
- else
- prev_internal_simd_struct[indiv_id]->usage_count_--;
-
- prev_internal_simd_struct[indiv_id] = internal_simd_struct[indiv_id];
- internal_simd_struct[indiv_id] = nullptr;
- }
+//#pragma omp parallel
+//#pragma omp single
+//#pragma omp taskloop
+ for (int indiv_id = 0; indiv_id < (int) exp_m_->nb_indivs(); indiv_id++) {
+ int usage_cpt = 0;
+
+ //#pragma omp critical
+ {
+ usage_cpt = prev_internal_simd_struct[indiv_id]->usage_count_--;
+
+ if (usage_cpt == 0)
+ delete prev_internal_simd_struct[indiv_id];
+ }
+
+ prev_internal_simd_struct[indiv_id] = internal_simd_struct[indiv_id];
+ internal_simd_struct[indiv_id] = nullptr;
+ }
} else {
// printf("Copy to old generation struct\n");
-
- for (int indiv_id = 0; indiv_id < (int) exp_m_->nb_indivs(); indiv_id++) {
+#pragma omp parallel
+#pragma omp single
+#pragma omp taskloop
+ for (int indiv_id = 0; indiv_id < (int) exp_m_->nb_indivs(); indiv_id++) {
prev_internal_simd_struct[indiv_id] = internal_simd_struct[indiv_id];
internal_simd_struct[indiv_id] = nullptr;
@@ -4630,6 +4647,7 @@ Internal_SIMD_Struct::Internal_SIMD_Struct(ExpManager* exp_m, Internal_SIMD_Stru
count_prom = 0;
exp_m_ = exp_m;
+ usage_count_ = 1;
dna_ = new Dna_SIMD(clone->dna_,this,copy_dna);
//promoters.resize(clone->promoters.size());
diff --git a/src/libaevol/Selection.cpp b/src/libaevol/Selection.cpp
index 246f0983b..105352323 100644
--- a/src/libaevol/Selection.cpp
+++ b/src/libaevol/Selection.cpp
@@ -1031,12 +1031,14 @@ Individual *Selection::do_local_competition (int16_t x, int16_t y) {
for (int8_t j = -1 ; j < selection_scope_y_-1 ; j++) {
cur_x = (x + i + grid_width) % grid_width;
cur_y = (y + j + grid_height) % grid_height;
- //printf("%d %d : %lf %d\n",cur_x,cur_y,world->indiv_at(cur_x, cur_y)->fitness(),count);
local_fit_array[count] = world->indiv_at(cur_x, cur_y)->fitness();
sort_fit_array[count] = local_fit_array[count];
initial_location[count] = count;
sum_local_fit += local_fit_array[count];
+
+ //if (0 == x*grid_height+y) printf("%d %d : %e %d\n",cur_x,cur_y,world->indiv_at(cur_x, cur_y)->fitness(),count);
+
/* if (268 == x*grid_height+y)
printf("CPU Local SUM Fit %e -- Fitness %e\n",sum_local_fit,local_fit_array[count]);*/
count++;
@@ -1093,6 +1095,7 @@ Individual *Selection::do_local_competition (int16_t x, int16_t y) {
case FITNESS_PROPORTIONATE : {
for(int16_t i = 0 ; i < neighborhood_size ; i++) {
probs[i] = local_fit_array[i]/sum_local_fit;
+ // if (0 == x*grid_height+y) printf("%d : %e %e\n",i,local_fit_array[i],sum_local_fit);
}
break;
@@ -1104,6 +1107,11 @@ Individual *Selection::do_local_competition (int16_t x, int16_t y) {
}
// pick one organism to reproduce, based on probs[] calculated above, using roulette selection
+ /*bool verbose = false;
+ if (2 == x*grid_height+y) {
+ printf("PRNG CPU\n");
+ verbose = true;
+ }*/
int16_t found_org = world->grid(x,y)->reprod_prng_->roulette_random(probs, neighborhood_size);
int16_t x_offset = (found_org / selection_scope_x_) - 1;
@@ -1113,9 +1121,13 @@ Individual *Selection::do_local_competition (int16_t x, int16_t y) {
delete [] sort_fit_array;
delete [] initial_location;
delete [] probs;
-/* world->grid(x,y)->probs = probs;
- world->grid(x,y)->local_fit_array = local_fit_array;
- world->grid(x,y)->sum_local_fit = sum_local_fit;*/
+
+ //world->grid(x,y)->probs = probs;
+ //world->grid(x,y)->local_fit_array = local_fit_array;
+ //world->grid(x,y)->sum_local_fit = sum_local_fit;
+
+ exp_m_->simd_individual->next_generation_reproducer_[x*grid_height+y] = ((x+x_offset+grid_width) % grid_width)*grid_height+
+ ((y+y_offset+grid_height) % grid_height);
return world->indiv_at((x+x_offset+grid_width) % grid_width,
(y+y_offset+grid_height) % grid_height);
--
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