-/* Copyright (c) 2007, 2008, 2009, 2010. The SimGrid Team.
+/* Copyright (c) 2007-2014. The SimGrid Team.
* All rights reserved. */
/* This program is free software; you can redistribute it and/or modify it
*/
#include "xbt/log.h"
#include "xbt/sysdep.h"
-//#include "maxmin_private.h"
-#include "solver.h"
-#include "solver.hpp"
+#include "maxmin_private.hpp"
+
#include <stdlib.h>
#ifndef MATH
#include <math.h>
//computes the value of the differential of constraint param_cnst applied to lambda
static double partial_diff_lambda(double lambda, void *param_cnst);
-static int __check_feasible(std::vector<ConstraintPtr> *cnstList, std::vector<VariablePtr> *varList,
+static int __check_feasible(xbt_swag_t cnst_list, xbt_swag_t var_list,
int warn)
{
- std::vector<ElementPtr> *elemList = NULL;
+ void *_cnst, *_elem, *_var;
+ xbt_swag_t elem_list = NULL;
lmm_element_t elem = NULL;
lmm_constraint_t cnst = NULL;
lmm_variable_t var = NULL;
- std::vector<VariablePtr>::iterator varIt;
- std::vector<ElementPtr>::iterator elemIt;
- std::vector<ConstraintPtr>::iterator cnstIt;
double tmp;
- for (cnstIt=cnstList->begin(); cnstIt!=cnstList->end(); ++cnstIt) {
- cnst = (*cnstIt);
+ xbt_swag_foreach(_cnst, cnst_list) {
+ cnst = (lmm_constraint_t)_cnst;
tmp = 0;
- elemList = &(cnst->m_elementSet);
- for (elemIt=elemList->begin(); elemIt!=elemList->end(); ++elemIt) {
- var = (*elemIt)->p_variable;
- if (var->m_weight <= 0)
+ elem_list = &(cnst->element_set);
+ xbt_swag_foreach(_elem, elem_list) {
+ elem = (lmm_element_t)_elem;
+ var = elem->variable;
+ if (var->weight <= 0)
continue;
- tmp += var->m_value;
+ tmp += var->value;
}
- if (double_positive(tmp - cnst->m_bound)) {
+ 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->m_bound, tmp);
+ cnst, cnst->bound, tmp);
return 0;
}
XBT_DEBUG
("Checking feasability for constraint (%p): sat = %f, lambda = %f ",
- cnst, tmp - cnst->m_bound, cnst->m_lambda);
+ cnst, tmp - cnst->bound, cnst->lambda);
}
- for (varIt=varList->begin(); varIt!=varList->end(); ++varIt) {
- if (!var->m_weight)
+ xbt_swag_foreach(_var, var_list) {
+ var = (lmm_variable_t)_var;
+ if (!var->weight)
break;
- if (var->m_bound < 0)
+ if (var->bound < 0)
continue;
XBT_DEBUG("Checking feasability for variable (%p): sat = %f mu = %f", var,
- var->m_value - var->m_bound, var->m_mu);
+ var->value - var->bound, var->mu);
- if (double_positive(var->m_value - var->m_bound)) {
+ 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->m_bound, var->m_value);
+ var, var->bound, var->value);
return 0;
}
- }
+ }
return 1;
}
{
double tmp = 0;
int i;
- std::vector<ElementPtr>::iterator elemIt;
- for (elemIt=var->m_cnsts.begin(); elemIt!=var->m_cnsts.end(); ++elemIt) {
- tmp += ((*elemIt)->p_constraint)->m_lambda;
+ for (i = 0; i < var->cnsts_number; i++) {
+ tmp += (var->cnsts[i].constraint)->lambda;
}
- if (var->m_bound > 0)
- tmp += var->m_mu;
+ if (var->bound > 0)
+ tmp += var->mu;
XBT_DEBUG("\t Working on var (%p). cost = %e; Weight = %e", var, tmp,
- var->m_weight);
+ var->weight);
//uses the partial differential inverse function
- return var->p_funcFPI(var, tmp);
+ return var->func_fpi(var, tmp);
}
static double new_mu(lmm_variable_t var)
double mu_i = 0.0;
double sigma_i = 0.0;
int j;
- std::vector<ElementPtr>::iterator elemIt;
- for (elemIt=var->m_cnsts.begin(); elemIt!=var->m_cnsts.end(); ++elemIt) {
- sigma_i += ((*elemIt)->p_constraint)->m_lambda;
+ for (j = 0; j < var->cnsts_number; j++) {
+ sigma_i += (var->cnsts[j].constraint)->lambda;
}
- mu_i = var->p_funcFP(var, var->m_bound) - sigma_i;
+ mu_i = var->func_fp(var, var->bound) - sigma_i;
if (mu_i < 0.0)
return 0.0;
return mu_i;
}
-static double dual_objective(std::vector<VariablePtr> *varList, std::vector<ConstraintPtr> *cnstList)
+static double dual_objective(xbt_swag_t var_list, xbt_swag_t cnst_list)
{
+ void *_cnst, *_var;
lmm_constraint_t cnst = NULL;
lmm_variable_t var = NULL;
double obj = 0.0;
- std::vector<VariablePtr>::iterator varIt;
- std::vector<ElementPtr>::iterator elemIt;
- std::vector<ConstraintPtr>::iterator cnstIt;
- for (varIt=varList->begin(); varIt!=varList->end(); ++varIt) {
- var = (*varIt);
+ xbt_swag_foreach(_var, var_list) {
+ var = (lmm_variable_t)_var;
double sigma_i = 0.0;
int j;
- if (!var->m_weight)
+ if (!var->weight)
break;
- for (elemIt=var->m_cnsts.begin(); elemIt!=var->m_cnsts.end(); ++elemIt)
- sigma_i += ((*elemIt)->p_constraint)->m_lambda;
-
- if (var->m_bound > 0)
- sigma_i += var->m_mu;
+ for (j = 0; j < var->cnsts_number; j++)
+ sigma_i += (var->cnsts[j].constraint)->lambda;
+
+ if (var->bound > 0)
+ sigma_i += var->mu;
XBT_DEBUG("var %p : sigma_i = %1.20f", var, sigma_i);
- obj += var->p_funcF(var, var->p_funcFPI(var, sigma_i)) -
- sigma_i * var->p_funcFPI(var, sigma_i);
+ obj += var->func_f(var, var->func_fpi(var, sigma_i)) -
+ sigma_i * var->func_fpi(var, sigma_i);
+
+ if (var->bound > 0)
+ obj += var->mu * var->bound;
+ }
- if (var->m_bound > 0)
- obj += var->m_mu * var->m_bound;
+ xbt_swag_foreach(_cnst, cnst_list) {
+ cnst = (lmm_constraint_t)_cnst;
+ obj += cnst->lambda * cnst->bound;
}
- for (cnstIt=cnstList->begin(); cnstIt!=cnstList->end(); ++cnstIt)
- obj += (*cnstIt)->m_lambda * (*cnstIt)->m_bound;
-
return obj;
}
* Lagrange Variables.
*/
int max_iterations = 100;
- double epsilon_min_error = MAXMIN_PRECISION;
+ double epsilon_min_error = 0.00001; /* this is the precision on the objective function so it's none of the configurable values and this value is the legacy one */
double dichotomy_min_error = 1e-14;
double overall_modification = 1;
* Variables to manipulate the data structure proposed to model the maxmin
* fairness. See docummentation for more details.
*/
- std::vector<ConstraintPtr> *cnstList = NULL;
- std::vector<ConstraintPtr>::iterator cnstIt;
+ xbt_swag_t cnst_list = NULL;
+ void *_cnst;
lmm_constraint_t cnst = NULL;
- std::vector<VariablePtr> *varList = NULL;
- std::vector<VariablePtr>::iterator varIt;
+ xbt_swag_t var_list = NULL;
+ void *_var;
lmm_variable_t var = NULL;
- std::vector<ElementPtr>::iterator elemIt;
-
/*
- * Auxiliar variables.
+ * Auxiliary variables.
*/
int iteration = 0;
double tmp = 0;
lmm_print(sys);
}
- if (!(sys->m_modified))
+ if (!(sys->modified))
return;
+
/*
* Initialize lambda.
*/
- cnstList = &(sys->m_activeConstraintSet);
- for (cnstIt=cnstList->begin(); cnstIt!=cnstList->end(); ++cnstIt) {
- cnst = *cnstIt;
- cnst->m_lambda = 1.0;
- cnst->m_newLambda = 2.0;
- XBT_DEBUG("#### cnst(%p)->lambda : %e", cnst, cnst->m_lambda);
+ cnst_list = &(sys->active_constraint_set);
+ xbt_swag_foreach(_cnst, cnst_list) {
+ cnst = (lmm_constraint_t)_cnst;
+ cnst->lambda = 1.0;
+ cnst->new_lambda = 2.0;
+ XBT_DEBUG("#### cnst(%p)->lambda : %e", cnst, cnst->lambda);
}
/*
* Initialize the var list variable with only the active variables.
* Associate an index in the swag variables. Initialize mu.
*/
- varList = &(sys->m_variableSet);
+ var_list = &(sys->variable_set);
i = 0;
- for (varIt=varList->begin(); varIt!=varList->end(); ++varIt) {
- var = *varIt;
- if (!var->m_weight)
- var->m_value = 0.0;
+ xbt_swag_foreach(_var, var_list) {
+ var = (lmm_variable_t)_var;
+ if (!var->weight)
+ var->value = 0.0;
else {
int nb = 0;
- if (var->m_bound < 0.0) {
+ if (var->bound < 0.0) {
XBT_DEBUG("#### NOTE var(%d) is a boundless variable", i);
- var->m_mu = -1.0;
- var->m_value = new_value(var);
+ var->mu = -1.0;
+ var->value = new_value(var);
} else {
- var->m_mu = 1.0;
- var->m_newMu = 2.0;
- var->m_value = new_value(var);
+ var->mu = 1.0;
+ var->new_mu = 2.0;
+ var->value = new_value(var);
}
- XBT_DEBUG("#### var(%p) ->weight : %e", var, var->m_weight);
- XBT_DEBUG("#### var(%p) ->mu : %e", var, var->m_mu);
- XBT_DEBUG("#### var(%p) ->weight: %e", var, var->m_weight);
- XBT_DEBUG("#### var(%p) ->bound: %e", var, var->m_bound);
- for (elemIt=var->m_cnsts.begin(); elemIt!=var->m_cnsts.end(); ++elemIt) {
- if ((*elemIt)->m_value == 0.0)
+ XBT_DEBUG("#### var(%p) ->weight : %e", var, var->weight);
+ XBT_DEBUG("#### var(%p) ->mu : %e", var, var->mu);
+ XBT_DEBUG("#### var(%p) ->weight: %e", var, var->weight);
+ XBT_DEBUG("#### var(%p) ->bound: %e", var, var->bound);
+ for (i = 0; i < var->cnsts_number; i++) {
+ if (var->cnsts[i].value == 0.0)
nb++;
}
- if (nb == var->m_cnsts.size())
- var->m_value = 1.0;
+ if (nb == var->cnsts_number)
+ var->value = 1.0;
}
}
/*
* Compute dual objective.
*/
- obj = dual_objective(varList, cnstList);
+ obj = dual_objective(var_list, cnst_list);
/*
* While doesn't reach a minimun error or a number maximum of iterations.
/*
* Improve the value of mu_i
*/
- for (varIt=varList->begin(); varIt!=varList->end(); ++varIt) {
- var = *varIt;
- if (!var->m_weight)
+ xbt_swag_foreach(_var, var_list) {
+ var = (lmm_variable_t)_var;
+ if (!var->weight)
break;
- if (var->m_bound >= 0) {
+ if (var->bound >= 0) {
XBT_DEBUG("Working on var (%p)", var);
- var->m_newMu = new_mu(var);
+ var->new_mu = new_mu(var);
/* dual_updated += (fabs(var->new_mu-var->mu)>dichotomy_min_error); */
/* XBT_DEBUG("dual_updated (%d) : %1.20f",dual_updated,fabs(var->new_mu-var->mu)); */
XBT_DEBUG("Updating mu : var->mu (%p) : %1.20f -> %1.20f", var,
- var->m_mu, var->m_newMu);
- var->m_mu = var->m_newMu;
+ var->mu, var->new_mu);
+ var->mu = var->new_mu;
- new_obj = dual_objective(varList, cnstList);
+ new_obj = dual_objective(var_list, cnst_list);
XBT_DEBUG("Improvement for Objective (%g -> %g) : %g", obj, new_obj,
obj - new_obj);
xbt_assert(obj - new_obj >= -epsilon_min_error,
/*
* Improve the value of lambda_i
*/
- for (cnstIt=cnstList->begin(); cnstIt!=cnstList->end(); ++cnstIt) {
- cnst = *cnstIt;
+ xbt_swag_foreach(_cnst, cnst_list) {
+ cnst = (lmm_constraint_t)_cnst;
XBT_DEBUG("Working on cnst (%p)", cnst);
- cnst->m_newLambda =
- dichotomy(cnst->m_lambda, partial_diff_lambda, cnst,
+ cnst->new_lambda =
+ dichotomy(cnst->lambda, partial_diff_lambda, cnst,
dichotomy_min_error);
/* dual_updated += (fabs(cnst->new_lambda-cnst->lambda)>dichotomy_min_error); */
/* XBT_DEBUG("dual_updated (%d) : %1.20f",dual_updated,fabs(cnst->new_lambda-cnst->lambda)); */
XBT_DEBUG("Updating lambda : cnst->lambda (%p) : %1.20f -> %1.20f",
- cnst, cnst->m_lambda, cnst->m_newLambda);
- cnst->m_lambda = cnst->m_newLambda;
+ cnst, cnst->lambda, cnst->new_lambda);
+ cnst->lambda = cnst->new_lambda;
- new_obj = dual_objective(varList, cnstList);
+ new_obj = dual_objective(var_list, cnst_list);
XBT_DEBUG("Improvement for Objective (%g -> %g) : %g", obj, new_obj,
obj - new_obj);
xbt_assert(obj - new_obj >= -epsilon_min_error,
*/
XBT_DEBUG("-------------- Check convergence ----------");
overall_modification = 0;
- for (varIt=varList->begin(); varIt!=varList->end(); ++varIt) {
- var = *varIt;
- if (var->m_weight <= 0)
- var->m_value = 0.0;
+ xbt_swag_foreach(_var, var_list) {
+ var = (lmm_variable_t)_var;
+ if (var->weight <= 0)
+ var->value = 0.0;
else {
tmp = new_value(var);
overall_modification =
- MAX(overall_modification, fabs(var->m_value - tmp));
+ MAX(overall_modification, fabs(var->value - tmp));
- var->m_value = tmp;
+ var->value = tmp;
XBT_DEBUG("New value of var (%p) = %e, overall_modification = %e",
- var, var->m_value, overall_modification);
+ var, var->value, overall_modification);
}
}
XBT_DEBUG("-------------- Check feasability ----------");
- if (!__check_feasible(cnstList, varList, 0))
+ if (!__check_feasible(cnst_list, var_list, 0))
overall_modification = 1.0;
XBT_DEBUG("Iteration %d: overall_modification : %f", iteration,
overall_modification);
/* break; */
/* } */
}
- __check_feasible(cnstList, varList, 1);
+
+ __check_feasible(cnst_list, var_list, 1);
if (overall_modification <= epsilon_min_error) {
XBT_DEBUG("The method converges in %d iterations.", iteration);
static double dichotomy(double init, double diff(double, void *),
void *var_cnst, double min_error)
{
- #ifdef TOREPAIR
double min, max;
double overall_error;
double middle;
min = max = 0.5;
}
- min_diff = max_diff = middle_diff = 0.0;
overall_error = 1;
if ((diff_0 = diff(1e-16, var_cnst)) >= 0) {
XBT_CDEBUG(surf_lagrange_dichotomy, "returning %e", (min + max) / 2.0);
XBT_OUT();
return ((min + max) / 2.0);
- #endif
}
static double partial_diff_lambda(double lambda, void *param_cnst)
{
- #ifdef TOREPAIR
+
int j;
+ void *_elem;
xbt_swag_t elem_list = NULL;
lmm_element_t elem = NULL;
lmm_variable_t var = NULL;
XBT_CDEBUG(surf_lagrange_dichotomy, "Computing diff of cnst (%p)", cnst);
- xbt_swag_foreach(elem, elem_list) {
+ xbt_swag_foreach(_elem, elem_list) {
+ elem = (lmm_element_t)_elem;
var = elem->variable;
if (var->weight <= 0)
continue;
diff);
XBT_OUT();
return diff;
- #endif
}
/** \brief Attribute the value bound to var->bound.
* Set default functions to the ones passed as parameters. This is a polimorfism in C pure, enjoy the roots of programming.
*
*/
-void lmm_set_default_protocol_function(double (*func_f) (lmm_variable_t var, double x),
- double (*func_fp) (lmm_variable_t var, double x),
- double (*func_fpi) (lmm_variable_t var, double x))
+void lmm_set_default_protocol_function(double (*func_f)
+
+
+
+
+
+
+ (lmm_variable_t var, double x),
+ double (*func_fp) (lmm_variable_t
+ var, double x),
+ double (*func_fpi) (lmm_variable_t
+ var, double x))
{
func_f_def = func_f;
func_fp_def = func_fp;
double func_vegas_f(lmm_variable_t var, double x)
{
- #ifdef TOREPAIR
xbt_assert(x > 0.0, "Don't call me with stupid values! (%1.20f)", x);
return VEGAS_SCALING * var->weight * log(x);
- #endif
}
double func_vegas_fp(lmm_variable_t var, double x)
{
- #ifdef TOREPAIR
xbt_assert(x > 0.0, "Don't call me with stupid values! (%1.20f)", x);
return VEGAS_SCALING * var->weight / x;
- #endif
}
double func_vegas_fpi(lmm_variable_t var, double x)
{
- #ifdef TOREPAIR
xbt_assert(x > 0.0, "Don't call me with stupid values! (%1.20f)", x);
return var->weight / (x / VEGAS_SCALING);
- #endif
}
/*
#define RENO_SCALING 1.0
double func_reno_f(lmm_variable_t var, double x)
{
- xbt_assert(var->m_weight > 0.0, "Don't call me with stupid values!");
+ xbt_assert(var->weight > 0.0, "Don't call me with stupid values!");
- return RENO_SCALING * sqrt(3.0 / 2.0) / var->m_weight *
- atan(sqrt(3.0 / 2.0) * var->m_weight * x);
+ return RENO_SCALING * sqrt(3.0 / 2.0) / var->weight *
+ atan(sqrt(3.0 / 2.0) * var->weight * x);
}
double func_reno_fp(lmm_variable_t var, double x)
{
- return RENO_SCALING * 3.0 / (3.0 * var->m_weight * var->m_weight * x * x +
+ return RENO_SCALING * 3.0 / (3.0 * var->weight * var->weight * x * x +
2.0);
}
{
double res_fpi;
- xbt_assert(var->m_weight > 0.0, "Don't call me with stupid values!");
+ xbt_assert(var->weight > 0.0, "Don't call me with stupid values!");
xbt_assert(x > 0.0, "Don't call me with stupid values!");
res_fpi =
- 1.0 / (var->m_weight * var->m_weight * (x / RENO_SCALING)) -
- 2.0 / (3.0 * var->m_weight * var->m_weight);
+ 1.0 / (var->weight * var->weight * (x / RENO_SCALING)) -
+ 2.0 / (3.0 * var->weight * var->weight);
if (res_fpi <= 0.0)
return 0.0;
-// xbt_assert(res_fpi>0.0,"Don't call me with stupid values!");
+/* xbt_assert(res_fpi>0.0,"Don't call me with stupid values!"); */
return sqrt(res_fpi);
}
#define RENO2_SCALING 1.0
double func_reno2_f(lmm_variable_t var, double x)
{
- xbt_assert(var->m_weight > 0.0, "Don't call me with stupid values!");
- return RENO2_SCALING * (1.0 / var->m_weight) * log((x * var->m_weight) /
- (2.0 * x * var->m_weight +
+ xbt_assert(var->weight > 0.0, "Don't call me with stupid values!");
+ return RENO2_SCALING * (1.0 / var->weight) * log((x * var->weight) /
+ (2.0 * x * var->weight +
3.0));
}
double func_reno2_fp(lmm_variable_t var, double x)
{
- return RENO2_SCALING * 3.0 / (var->m_weight * x *
- (2.0 * var->m_weight * x + 3.0));
+ return RENO2_SCALING * 3.0 / (var->weight * x *
+ (2.0 * var->weight * x + 3.0));
}
double func_reno2_fpi(lmm_variable_t var, double x)
double tmp;
xbt_assert(x > 0.0, "Don't call me with stupid values!");
- tmp = x * var->m_weight * var->m_weight;
+ tmp = x * var->weight * var->weight;
res_fpi = tmp * (9.0 * x + 24.0);
if (res_fpi <= 0.0)
