X-Git-Url: http://info.iut-bm.univ-fcomte.fr/pub/gitweb/simgrid.git/blobdiff_plain/0f5828869a4c6d79018e8eca27a10d0fe51979e5..8cd6895f11e7da5ddbb04fbc117ae1f3244cca29:/src/kernel/lmm/lagrange.cpp

diff --git a/src/kernel/lmm/lagrange.cpp b/src/kernel/lmm/lagrange.cpp
index 7d2afe0e98..98b6fd2aeb 100644
--- a/src/kernel/lmm/lagrange.cpp
+++ b/src/kernel/lmm/lagrange.cpp
@@ -12,18 +12,15 @@
 #include "xbt/sysdep.h"
 
 #include <algorithm>
-#include <cstdlib>
-#ifndef MATH
 #include <cmath>
-#endif
+#include <cstdlib>
 
 XBT_LOG_NEW_DEFAULT_SUBCATEGORY(surf_lagrange, surf, "Logging specific to SURF (lagrange)");
 XBT_LOG_NEW_SUBCATEGORY(surf_lagrange_dichotomy, surf_lagrange, "Logging specific to SURF (lagrange dichotomy)");
 
-#define SHOW_EXPR(expr) XBT_CDEBUG(surf_lagrange, #expr " = %g", expr);
-#define VEGAS_SCALING 1000.0
-#define RENO_SCALING 1.0
-#define RENO2_SCALING 1.0
+static constexpr double VEGAS_SCALING = 1000.0;
+static constexpr double RENO_SCALING  = 1.0;
+static constexpr double RENO2_SCALING = 1.0;
 
 namespace simgrid {
 namespace kernel {
@@ -33,20 +30,22 @@ double (*func_f_def)(const Variable&, double);
 double (*func_fp_def)(const Variable&, double);
 double (*func_fpi_def)(const Variable&, double);
 
+System* make_new_lagrange_system(bool selective_update)
+{
+  return new Lagrange(selective_update);
+}
+
 /*
  * Local prototypes to implement the Lagrangian optimization with optimal step, also called dichotomy.
  */
-// solves the proportional fairness using a Lagrangian optimization with dichotomy step
-void lagrange_solve(kernel::lmm::System* sys);
 // computes the value of the dichotomy using a initial values, init, with a specific variable or constraint
 static double dichotomy(double init, double diff(double, const Constraint&), const Constraint& cnst, double min_error);
 // computes the value of the differential of constraint cnst applied to lambda
 static double partial_diff_lambda(double lambda, const Constraint& cnst);
 
-template <class CnstList, class VarList>
-static int __check_feasible(const CnstList& cnst_list, const VarList& var_list, int warn)
+bool Lagrange::check_feasible(bool warn)
 {
-  for (Constraint const& cnst : cnst_list) {
+  for (Constraint const& cnst : active_constraint_set) {
     double tmp = 0;
     for (Element const& elem : cnst.enabled_element_set) {
       Variable* var = elem.variable;
@@ -57,12 +56,12 @@ static int __check_feasible(const CnstList& cnst_list, const VarList& var_list,
     if (double_positive(tmp - cnst.bound, sg_maxmin_precision)) {
       if (warn)
         XBT_WARN("The link (%p) is over-used. Expected less than %f and got %f", &cnst, cnst.bound, tmp);
-      return 0;
+      return false;
     }
     XBT_DEBUG("Checking feasability for constraint (%p): sat = %f, lambda = %f ", &cnst, tmp - cnst.bound, cnst.lambda);
   }
 
-  for (Variable const& var : var_list) {
+  for (Variable const& var : variable_set) {
     if (not var.sharing_weight)
       break;
     if (var.bound < 0)
@@ -72,10 +71,10 @@ static int __check_feasible(const CnstList& cnst_list, const VarList& var_list,
     if (double_positive(var.value - var.bound, sg_maxmin_precision)) {
       if (warn)
         XBT_WARN("The variable (%p) is too large. Expected less than %f and got %f", &var, var.bound, var.value);
-      return 0;
+      return false;
     }
   }
-  return 1;
+  return true;
 }
 
 static double new_value(const Variable& var)
@@ -106,12 +105,11 @@ static double new_mu(const Variable& var)
   return mu_i;
 }
 
-template <class VarList, class CnstList>
-static double dual_objective(const VarList& var_list, const CnstList& cnst_list)
+double Lagrange::dual_objective()
 {
   double obj = 0.0;
 
-  for (Variable const& var : var_list) {
+  for (Variable const& var : variable_set) {
     double sigma_i = 0.0;
 
     if (not var.sharing_weight)
@@ -131,13 +129,14 @@ static double dual_objective(const VarList& var_list, const CnstList& cnst_list)
       obj += var.mu * var.bound;
   }
 
-  for (Constraint const& cnst : cnst_list)
+  for (Constraint const& cnst : active_constraint_set)
     obj += cnst.lambda * cnst.bound;
 
   return obj;
 }
 
-void lagrange_solve(kernel::lmm::System* sys)
+// solves the proportional fairness using a Lagrangian optimization with dichotomy step
+void Lagrange::lagrange_solve()
 {
   /* Lagrange Variables. */
   int max_iterations       = 100;
@@ -152,14 +151,14 @@ void lagrange_solve(kernel::lmm::System* sys)
   XBT_DEBUG("#### Minimum error tolerated (dichotomy) : %e", dichotomy_min_error);
 
   if (XBT_LOG_ISENABLED(surf_lagrange, xbt_log_priority_debug)) {
-    sys->print();
+    print();
   }
 
-  if (not sys->modified)
+  if (not modified)
     return;
 
   /* Initialize lambda. */
-  auto& cnst_list = sys->active_constraint_set;
+  auto& cnst_list = active_constraint_set;
   for (Constraint& cnst : cnst_list) {
     cnst.lambda     = 1.0;
     cnst.new_lambda = 2.0;
@@ -169,7 +168,7 @@ void lagrange_solve(kernel::lmm::System* sys)
   /*
    * Initialize the var_list variable with only the active variables. Initialize mu.
    */
-  auto& var_list = sys->variable_set;
+  auto& var_list = variable_set;
   for (Variable& var : var_list) {
     if (not var.sharing_weight)
       var.value = 0.0;
@@ -194,7 +193,7 @@ void lagrange_solve(kernel::lmm::System* sys)
   }
 
   /*  Compute dual objective. */
-  double obj = dual_objective(var_list, cnst_list);
+  double obj = dual_objective();
 
   /* While doesn't reach a minimum error or a number maximum of iterations. */
   int iteration = 0;
@@ -211,7 +210,7 @@ void lagrange_solve(kernel::lmm::System* sys)
         XBT_DEBUG("Updating mu : var->mu (%p) : %1.20f -> %1.20f", &var, var.mu, var.new_mu);
         var.mu = var.new_mu;
 
-        double new_obj = dual_objective(var_list, cnst_list);
+        double new_obj = dual_objective();
         XBT_DEBUG("Improvement for Objective (%g -> %g) : %g", obj, new_obj, obj - new_obj);
         xbt_assert(obj - new_obj >= -epsilon_min_error, "Our gradient sucks! (%1.20f)", obj - new_obj);
         obj = new_obj;
@@ -225,7 +224,7 @@ void lagrange_solve(kernel::lmm::System* sys)
       XBT_DEBUG("Updating lambda : cnst->lambda (%p) : %1.20f -> %1.20f", &cnst, cnst.lambda, cnst.new_lambda);
       cnst.lambda = cnst.new_lambda;
 
-      double new_obj = dual_objective(var_list, cnst_list);
+      double new_obj = dual_objective();
       XBT_DEBUG("Improvement for Objective (%g -> %g) : %g", obj, new_obj, obj - new_obj);
       xbt_assert(obj - new_obj >= -epsilon_min_error, "Our gradient sucks! (%1.20f)", obj - new_obj);
       obj = new_obj;
@@ -248,12 +247,12 @@ void lagrange_solve(kernel::lmm::System* sys)
     }
 
     XBT_DEBUG("-------------- Check feasability ----------");
-    if (not __check_feasible(cnst_list, var_list, 0))
+    if (not check_feasible(false))
       overall_modification = 1.0;
     XBT_DEBUG("Iteration %d: overall_modification : %f", iteration, overall_modification);
   }
 
-  __check_feasible(cnst_list, var_list, 1);
+  check_feasible(true);
 
   if (overall_modification <= epsilon_min_error) {
     XBT_DEBUG("The method converges in %d iterations.", iteration);
@@ -263,7 +262,7 @@ void lagrange_solve(kernel::lmm::System* sys)
   }
 
   if (XBT_LOG_ISENABLED(surf_lagrange, xbt_log_priority_debug)) {
-    sys->print();
+    print();
   }
 }