Barrier for make-sense optimization

USCbiostats · Oct 2, 2023 · 00f2c5b · 00f2c5b
1 parent d6c4555
commit 00f2c5b
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Showing 4 changed files with 17 additions and 5 deletions.
diff --git a/include/barry/model-bones.hpp b/include/barry/model-bones.hpp
@@ -132,7 +132,10 @@ class Model {
      * set of parameters. It will also update the `normalizing_constants` member
      * variable.
     */
-    void update_normalizing_constants(const std::vector< double > & params);
+    void update_normalizing_constants(
+        const std::vector< double > & params,
+        BARRY_NCORES_ARG(=1)
+        );
 
     void set_rengine(std::mt19937 * rengine_, bool delete_ = false) {
 

diff --git a/include/barry/model-meat.hpp b/include/barry/model-meat.hpp
@@ -152,11 +152,16 @@ template <
     typename Data_Rule_Dyn_Type
     >
 inline void Model<Array_Type, Data_Counter_Type, Data_Rule_Type, Data_Rule_Dyn_Type>::update_normalizing_constants(
-    const std::vector< double > & params
+    const std::vector< double > & params,
+    size_t ncores
 ) {
+
+    // Barrier to make sure paralelization makes sense
+    if ((ncores > 1u) && (stats_support.size() < 1000u))
+        ncores = 1u;
 
     #if defined(__OPENMP) || defined(_OPENMP)
-    #pragma omp parallel for firstprivate(params) \
+    #pragma omp parallel for firstprivate(params) num_threads(ncores) \
         shared(stats_support, normalizing_constants, first_calc_done)
     #endif
     for (size_t i = 0u; i < stats_support.size(); ++i)

diff --git a/include/barry/models/geese/flock-meat.hpp b/include/barry/models/geese/flock-meat.hpp
@@ -148,7 +148,7 @@ inline double Flock::likelihood_joint(
     double ans = as_log ? 0.0: 1.0;
 
     std::vector< double > par0(par.begin(), par.end() - nfunctions);
-    model.update_normalizing_constants(par0);
+    model.update_normalizing_constants(par0, ncores);
 
     if (as_log) {
 

diff --git a/include/barry/models/geese/geese-meat-likelihood.hpp b/include/barry/models/geese/geese-meat-likelihood.hpp
@@ -26,7 +26,7 @@ inline double Geese::likelihood(
 
     // Updating normalizing constants
     if (!no_update_normalizing_constant)
-        model->update_normalizing_constants(par0);
+        model->update_normalizing_constants(par0, ncores);
 
     // Following the prunning sequence
     const std::vector< size_t > & preseq = use_reduced_sequence ?
@@ -65,6 +65,10 @@ inline double Geese::likelihood(
             std::vector< std::vector< size_t > > & locations = pset_loc[
                 arrays2support->operator[](array_id)
                 ];
+
+            // Making sure parallelization makes sense
+            if (psets.size() < 1000)
+                ncores = 1u;
 
             // Summation over all possible values of X
             const auto & node_offspring = node.offspring;