-/* Copyright (c) 2007-2014. The SimGrid Team.
- * All rights reserved. */
+/* Copyright (c) 2007-2017. The SimGrid Team. All rights reserved. */
/* This program is free software; you can redistribute it and/or modify it
* under the terms of the license (GNU LGPL) which comes with this package. */
#include "xbt/sysdep.h"
#include "maxmin_private.hpp"
-#include <stdlib.h>
+#include <cstdlib>
#ifndef MATH
-#include <math.h>
+#include <cmath>
#endif
XBT_LOG_NEW_DEFAULT_SUBCATEGORY(surf_lagrange, surf, "Logging specific to SURF (lagrange)");
lmm_constraint_t cnst = nullptr;
lmm_variable_t var = nullptr;
- double tmp;
-
xbt_swag_foreach(_cnst, cnst_list) {
- cnst = static_cast<lmm_constraint_t>(_cnst);
- tmp = 0;
+ cnst = static_cast<lmm_constraint_t>(_cnst);
+ double tmp = 0;
elem_list = &(cnst->enabled_element_set);
xbt_swag_foreach(_elem, elem_list) {
elem = static_cast<lmm_element_t>(_elem);
var = elem->variable;
- xbt_assert(var->weight > 0);
+ xbt_assert(var->sharing_weight > 0);
tmp += var->value;
}
xbt_swag_foreach(_var, var_list) {
var = static_cast<lmm_variable_t>(_var);
- if (not var->weight)
+ if (not var->sharing_weight)
break;
if (var->bound < 0)
continue;
}
if (var->bound > 0)
tmp += var->mu;
- XBT_DEBUG("\t Working on var (%p). cost = %e; Weight = %e", var, tmp, var->weight);
+ XBT_DEBUG("\t Working on var (%p). cost = %e; Weight = %e", var, tmp, var->sharing_weight);
//uses the partial differential inverse function
return var->func_fpi(var, tmp);
}
var = static_cast<lmm_variable_t>(_var);
double sigma_i = 0.0;
- if (not var->weight)
+ if (not var->sharing_weight)
break;
for (int j = 0; j < var->cnsts_number; j++)
i = 0;
xbt_swag_foreach(_var, var_list) {
var = static_cast<lmm_variable_t>(_var);
- if (not var->weight)
+ if (not var->sharing_weight)
var->value = 0.0;
else {
int nb = 0;
var->new_mu = 2.0;
var->value = new_value(var);
}
- XBT_DEBUG("#### var(%p) ->weight : %e", var, var->weight);
+ XBT_DEBUG("#### var(%p) ->weight : %e", var, var->sharing_weight);
XBT_DEBUG("#### var(%p) ->mu : %e", var, var->mu);
- XBT_DEBUG("#### var(%p) ->weight: %e", var, var->weight);
+ XBT_DEBUG("#### var(%p) ->weight: %e", var, var->sharing_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)
+ if (var->cnsts[i].consumption_weight == 0.0)
nb++;
}
if (nb == var->cnsts_number)
/* Improve the value of mu_i */
xbt_swag_foreach(_var, var_list) {
var = static_cast<lmm_variable_t>(_var);
- if (not var->weight)
+ if (not var->sharing_weight)
break;
if (var->bound >= 0) {
XBT_DEBUG("Working on var (%p)", 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->mu, var->new_mu);
var->mu = var->new_mu;
cnst = static_cast<lmm_constraint_t>(_cnst);
XBT_DEBUG("Working on cnst (%p)", 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->lambda, cnst->new_lambda);
cnst->lambda = cnst->new_lambda;
overall_modification = 0;
xbt_swag_foreach(_var, var_list) {
var = static_cast<lmm_variable_t>(_var);
- if (var->weight <= 0)
+ if (var->sharing_weight <= 0)
var->value = 0.0;
else {
tmp = new_value(var);
if (not __check_feasible(cnst_list, var_list, 0))
overall_modification = 1.0;
XBT_DEBUG("Iteration %d: overall_modification : %f", iteration, overall_modification);
- /* if(not dual_updated) { */
- /* XBT_WARN("Could not improve the convergence at iteration %d. Drop it!",iteration); */
- /* break; */
- /* } */
}
__check_feasible(cnst_list, var_list, 1);
min = middle;
overall_error = max_diff - middle_diff;
min_diff = middle_diff;
-/* SHOW_EXPR(overall_error); */
} else if (middle_diff > 0) {
XBT_CDEBUG(surf_lagrange_dichotomy, "Decreasing max");
max = middle;
overall_error = max_diff - middle_diff;
max_diff = middle_diff;
-/* SHOW_EXPR(overall_error); */
} else {
overall_error = 0;
-/* SHOW_EXPR(overall_error); */
}
} else if (fabs(min_diff) < 1e-20) {
max = min;
overall_error = 0;
-/* SHOW_EXPR(overall_error); */
} else if (fabs(max_diff) < 1e-20) {
min = max;
overall_error = 0;
-/* SHOW_EXPR(overall_error); */
} else if (min_diff > 0 && max_diff < 0) {
XBT_CWARN(surf_lagrange_dichotomy, "The impossible happened, partial_diff(min) > 0 && partial_diff(max) < 0");
xbt_abort();
static double partial_diff_lambda(double lambda, void *param_cnst)
{
- int j;
- void *_elem;
- xbt_swag_t elem_list = nullptr;
- lmm_element_t elem = nullptr;
- lmm_variable_t var = nullptr;
lmm_constraint_t cnst = static_cast<lmm_constraint_t>(param_cnst);
double diff = 0.0;
- double sigma_i = 0.0;
XBT_IN();
- elem_list = &(cnst->enabled_element_set);
XBT_CDEBUG(surf_lagrange_dichotomy, "Computing diff of cnst (%p)", cnst);
+ xbt_swag_t elem_list = &(cnst->enabled_element_set);
+ void* _elem;
xbt_swag_foreach(_elem, elem_list) {
- elem = static_cast<lmm_element_t>(_elem);
- var = elem->variable;
- xbt_assert(var->weight > 0);
+ lmm_element_t elem = static_cast<lmm_element_t>(_elem);
+ lmm_variable_t var = elem->variable;
+ xbt_assert(var->sharing_weight > 0);
XBT_CDEBUG(surf_lagrange_dichotomy, "Computing sigma_i for var (%p)", var);
// Initialize the summation variable
- sigma_i = 0.0;
+ double sigma_i = 0.0;
// Compute sigma_i
- for (j = 0; j < var->cnsts_number; j++) {
+ for (int j = 0; j < var->cnsts_number; j++) {
sigma_i += (var->cnsts[j].constraint)->lambda;
}
double func_vegas_f(lmm_variable_t var, double x)
{
xbt_assert(x > 0.0, "Don't call me with stupid values! (%1.20f)", x);
- return VEGAS_SCALING * var->weight * log(x);
+ return VEGAS_SCALING * var->sharing_weight * log(x);
}
double func_vegas_fp(lmm_variable_t var, double x)
{
xbt_assert(x > 0.0, "Don't call me with stupid values! (%1.20f)", x);
- return VEGAS_SCALING * var->weight / x;
+ return VEGAS_SCALING * var->sharing_weight / x;
}
double func_vegas_fpi(lmm_variable_t var, double x)
{
xbt_assert(x > 0.0, "Don't call me with stupid values! (%1.20f)", x);
- return var->weight / (x / VEGAS_SCALING);
+ return var->sharing_weight / (x / VEGAS_SCALING);
}
/*
#define RENO_SCALING 1.0
double func_reno_f(lmm_variable_t var, double x)
{
- xbt_assert(var->weight > 0.0, "Don't call me with stupid values!");
+ xbt_assert(var->sharing_weight > 0.0, "Don't call me with stupid values!");
- return RENO_SCALING * sqrt(3.0 / 2.0) / var->weight * atan(sqrt(3.0 / 2.0) * var->weight * x);
+ return RENO_SCALING * sqrt(3.0 / 2.0) / var->sharing_weight * atan(sqrt(3.0 / 2.0) * var->sharing_weight * x);
}
double func_reno_fp(lmm_variable_t var, double x)
{
- return RENO_SCALING * 3.0 / (3.0 * var->weight * var->weight * x * x + 2.0);
+ return RENO_SCALING * 3.0 / (3.0 * var->sharing_weight * var->sharing_weight * x * x + 2.0);
}
double func_reno_fpi(lmm_variable_t var, double x)
{
double res_fpi;
- xbt_assert(var->weight > 0.0, "Don't call me with stupid values!");
+ xbt_assert(var->sharing_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->weight * var->weight * (x / RENO_SCALING)) - 2.0 / (3.0 * var->weight * var->weight);
+ res_fpi = 1.0 / (var->sharing_weight * var->sharing_weight * (x / RENO_SCALING)) -
+ 2.0 / (3.0 * var->sharing_weight * var->sharing_weight);
if (res_fpi <= 0.0)
return 0.0;
-/* 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->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));
+ xbt_assert(var->sharing_weight > 0.0, "Don't call me with stupid values!");
+ return RENO2_SCALING * (1.0 / var->sharing_weight) *
+ log((x * var->sharing_weight) / (2.0 * x * var->sharing_weight + 3.0));
}
double func_reno2_fp(lmm_variable_t var, double x)
{
- return RENO2_SCALING * 3.0 / (var->weight * x * (2.0 * var->weight * x + 3.0));
+ return RENO2_SCALING * 3.0 / (var->sharing_weight * x * (2.0 * var->sharing_weight * x + 3.0));
}
double func_reno2_fpi(lmm_variable_t var, double x)
{
xbt_assert(x > 0.0, "Don't call me with stupid values!");
- double tmp = x * var->weight * var->weight;
+ double tmp = x * var->sharing_weight * var->sharing_weight;
double res_fpi = tmp * (9.0 * x + 24.0);
if (res_fpi <= 0.0)
