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 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
namespace simgrid {
namespace surf {
-double (*func_f_def) (lmm_variable_t, double);
-double (*func_fp_def) (lmm_variable_t, double);
-double (*func_fpi_def) (lmm_variable_t, double);
+double (*func_f_def)(lmm_variable_t, double);
+double (*func_fp_def)(lmm_variable_t, double);
+double (*func_fpi_def)(lmm_variable_t, double);
/*
* Local prototypes to implement the Lagrangian optimization with optimal step, also called dichotomy.
*/
-//solves the proportional fairness using a Lagrangian optimization with dichotomy step
+// solves the proportional fairness using a Lagrangian optimization with dichotomy step
void lagrange_solve(lmm_system_t 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, void *), void *var_cnst, double min_error);
-//computes the value of the differential of constraint param_cnst applied to lambda
-static double partial_diff_lambda(double lambda, void *param_cnst);
+// 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, void*), void* var_cnst, double min_error);
+// 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(xbt_swag_t cnst_list, xbt_swag_t var_list, int warn)
{
void* _cnst;
void* _elem;
void* _var;
- xbt_swag_t elem_list = nullptr;
- lmm_element_t elem = nullptr;
+ xbt_swag_t elem_list = nullptr;
+ lmm_element_t elem = nullptr;
lmm_constraint_t cnst = nullptr;
- lmm_variable_t var = nullptr;
+ lmm_variable_t var = nullptr;
- xbt_swag_foreach(_cnst, cnst_list) {
+ xbt_swag_foreach(_cnst, cnst_list)
+ {
cnst = static_cast<lmm_constraint_t>(_cnst);
double tmp = 0;
- elem_list = &(cnst->enabled_element_set);
- xbt_swag_foreach(_elem, elem_list) {
+ elem_list = &(cnst->enabled_element_set);
+ xbt_swag_foreach(_elem, elem_list)
+ {
elem = static_cast<lmm_element_t>(_elem);
- var = elem->variable;
+ var = elem->variable;
xbt_assert(var->sharing_weight > 0);
tmp += var->value;
}
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);
+ XBT_WARN("The link (%p) is over-used. Expected less than %f and got %f", cnst, cnst->bound, tmp);
return 0;
}
- XBT_DEBUG ("Checking feasability for constraint (%p): sat = %f, lambda = %f ", cnst, tmp - cnst->bound,
- cnst->lambda);
+ XBT_DEBUG("Checking feasability for constraint (%p): sat = %f, lambda = %f ", cnst, tmp - cnst->bound,
+ cnst->lambda);
}
- xbt_swag_foreach(_var, var_list) {
+ xbt_swag_foreach(_var, var_list)
+ {
var = static_cast<lmm_variable_t>(_var);
if (not var->sharing_weight)
break;
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);
+ XBT_WARN("The variable (%p) is too large. Expected less than %f and got %f", var, var->bound, var->value);
return 0;
}
}
if (var->bound > 0)
tmp += var->mu;
XBT_DEBUG("\t Working on var (%p). cost = %e; Weight = %e", var, tmp, var->sharing_weight);
- //uses the partial differential inverse function
+ // uses the partial differential inverse function
return var->func_fpi(var, tmp);
}
static double new_mu(lmm_variable_t var)
{
- double mu_i = 0.0;
+ double mu_i = 0.0;
double sigma_i = 0.0;
for (s_lmm_element_t const& elem : var->cnsts) {
static double dual_objective(xbt_swag_t var_list, xbt_swag_t cnst_list)
{
- void *_cnst;
- void *_var;
+ void* _cnst;
+ void* _var;
lmm_constraint_t cnst = nullptr;
- lmm_variable_t var = nullptr;
+ lmm_variable_t var = nullptr;
double obj = 0.0;
- xbt_swag_foreach(_var, var_list) {
- var = static_cast<lmm_variable_t>(_var);
+ xbt_swag_foreach(_var, var_list)
+ {
+ var = static_cast<lmm_variable_t>(_var);
double sigma_i = 0.0;
if (not var->sharing_weight)
obj += var->mu * var->bound;
}
- xbt_swag_foreach(_cnst, cnst_list) {
+ xbt_swag_foreach(_cnst, cnst_list)
+ {
cnst = static_cast<lmm_constraint_t>(_cnst);
obj += cnst->lambda * cnst->bound;
}
void lagrange_solve(lmm_system_t sys)
{
/* Lagrange Variables. */
- int max_iterations = 100;
- 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;
+ int max_iterations = 100;
+ 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;
XBT_DEBUG("Iterative method configuration snapshot =====>");
/* Initialize lambda. */
xbt_swag_t cnst_list = &(sys->active_constraint_set);
void* _cnst;
- xbt_swag_foreach(_cnst, cnst_list) {
+ xbt_swag_foreach(_cnst, cnst_list)
+ {
lmm_constraint_t cnst = (lmm_constraint_t)_cnst;
- cnst->lambda = 1.0;
- cnst->new_lambda = 2.0;
+ cnst->lambda = 1.0;
+ cnst->new_lambda = 2.0;
XBT_DEBUG("#### cnst(%p)->lambda : %e", cnst, cnst->lambda);
}
*/
xbt_swag_t var_list = &(sys->variable_set);
void* _var;
- xbt_swag_foreach(_var, var_list) {
+ xbt_swag_foreach(_var, var_list)
+ {
lmm_variable_t var = static_cast<lmm_variable_t>(_var);
if (not var->sharing_weight)
var->value = 0.0;
else {
if (var->bound < 0.0) {
XBT_DEBUG("#### NOTE var(%p) is a boundless variable", var);
- var->mu = -1.0;
+ var->mu = -1.0;
} else {
var->mu = 1.0;
var->new_mu = 2.0;
XBT_DEBUG("-------------- Gradient Descent ----------");
/* Improve the value of mu_i */
- xbt_swag_foreach(_var, var_list) {
+ xbt_swag_foreach(_var, var_list)
+ {
lmm_variable_t var = static_cast<lmm_variable_t>(_var);
if (var->sharing_weight && var->bound >= 0) {
XBT_DEBUG("Working on var (%p)", var);
}
/* Improve the value of lambda_i */
- xbt_swag_foreach(_cnst, cnst_list) {
+ xbt_swag_foreach(_cnst, cnst_list)
+ {
lmm_constraint_t 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);
/* Now computes the values of each variable (\rho) based on the values of \lambda and \mu. */
XBT_DEBUG("-------------- Check convergence ----------");
overall_modification = 0;
- xbt_swag_foreach(_var, var_list) {
+ xbt_swag_foreach(_var, var_list)
+ {
lmm_variable_t var = static_cast<lmm_variable_t>(_var);
if (var->sharing_weight <= 0)
var->value = 0.0;
XBT_DEBUG("The method converges in %d iterations.", iteration);
}
if (iteration >= max_iterations) {
- XBT_DEBUG ("Method reach %d iterations, which is the maximum number of iterations allowed.", iteration);
+ XBT_DEBUG("Method reach %d iterations, which is the maximum number of iterations allowed.", iteration);
}
if (XBT_LOG_ISENABLED(surf_lagrange, xbt_log_priority_debug)) {
*
* @return a double corresponding to the result of the dichotomy process
*/
-static double dichotomy(double init, double diff(double, void *), void *var_cnst, double min_error)
+static double dichotomy(double init, double diff(double, void*), void* var_cnst, double min_error)
{
- double min =init;
- double max= init;
+ double min = init;
+ double max = init;
double overall_error;
double middle;
double middle_diff;
double max_diff = diff(max, var_cnst);
while (overall_error > min_error) {
- XBT_CDEBUG(surf_lagrange_dichotomy, "[min, max] = [%1.20f, %1.20f] || diffmin, diffmax = %1.20f, %1.20f",
- min, max, min_diff, max_diff);
+ XBT_CDEBUG(surf_lagrange_dichotomy, "[min, max] = [%1.20f, %1.20f] || diffmin, diffmax = %1.20f, %1.20f", min, max,
+ min_diff, max_diff);
if (min_diff > 0 && max_diff > 0) {
if (min == max) {
XBT_CDEBUG(surf_lagrange_dichotomy, "Decreasing min");
- min = min / 2.0;
+ min = min / 2.0;
min_diff = diff(min, var_cnst);
} else {
XBT_CDEBUG(surf_lagrange_dichotomy, "Decreasing max");
- max = min;
+ max = min;
max_diff = min_diff;
}
} else if (min_diff < 0 && max_diff < 0) {
if (min == max) {
XBT_CDEBUG(surf_lagrange_dichotomy, "Increasing max");
- max = max * 2.0;
+ max = max * 2.0;
max_diff = diff(max, var_cnst);
} else {
XBT_CDEBUG(surf_lagrange_dichotomy, "Increasing min");
- min = max;
+ min = max;
min_diff = max_diff;
}
} else if (min_diff < 0 && max_diff > 0) {
middle = (max + min) / 2.0;
XBT_CDEBUG(surf_lagrange_dichotomy, "Trying (max+min)/2 : %1.20f", middle);
- if ((fabs(min - middle) < 1e-20) || (fabs(max - middle) < 1e-20)){
- XBT_CWARN(surf_lagrange_dichotomy, "Cannot improve the convergence! min=max=middle=%1.20f, diff = %1.20f."
+ if ((fabs(min - middle) < 1e-20) || (fabs(max - middle) < 1e-20)) {
+ XBT_CWARN(surf_lagrange_dichotomy,
+ "Cannot improve the convergence! min=max=middle=%1.20f, diff = %1.20f."
" Reaching the 'double' limits. Maybe scaling your function would help ([%1.20f,%1.20f]).",
min, max - min, min_diff, max_diff);
break;
if (middle_diff < 0) {
XBT_CDEBUG(surf_lagrange_dichotomy, "Increasing min");
- min = middle;
+ min = middle;
overall_error = max_diff - middle_diff;
- min_diff = middle_diff;
+ min_diff = middle_diff;
} else if (middle_diff > 0) {
XBT_CDEBUG(surf_lagrange_dichotomy, "Decreasing max");
- max = middle;
+ max = middle;
overall_error = max_diff - middle_diff;
- max_diff = middle_diff;
+ max_diff = middle_diff;
} else {
overall_error = 0;
}
} else if (fabs(min_diff) < 1e-20) {
- max = min;
+ max = min;
overall_error = 0;
} else if (fabs(max_diff) < 1e-20) {
- min = max;
+ min = max;
overall_error = 0;
} 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();
} else {
XBT_CWARN(surf_lagrange_dichotomy,
- "diffmin (%1.20f) or diffmax (%1.20f) are something I don't know, taking no action.",
- min_diff, max_diff);
+ "diffmin (%1.20f) or diffmax (%1.20f) are something I don't know, taking no action.", min_diff,
+ max_diff);
xbt_abort();
}
}
return ((min + max) / 2.0);
}
-static double partial_diff_lambda(double lambda, void *param_cnst)
+static double partial_diff_lambda(double lambda, void* param_cnst)
{
lmm_constraint_t cnst = static_cast<lmm_constraint_t>(param_cnst);
- double diff = 0.0;
+ double diff = 0.0;
XBT_IN();
xbt_swag_t elem_list = &(cnst->enabled_element_set);
void* _elem;
- xbt_swag_foreach(_elem, elem_list) {
+ xbt_swag_foreach(_elem, elem_list)
+ {
lmm_element_t elem = static_cast<lmm_element_t>(_elem);
lmm_variable_t var = elem->variable;
xbt_assert(var->sharing_weight > 0);
sigma_i += elem.constraint->lambda;
}
- //add mu_i if this flow has a RTT constraint associated
+ // add mu_i if this flow has a RTT constraint associated
if (var->bound > 0)
sigma_i += var->mu;
- //replace value of cnst->lambda by the value of parameter lambda
+ // replace value of cnst->lambda by the value of parameter lambda
sigma_i = (sigma_i - cnst->lambda) + lambda;
diff += -var->func_fpi(var, sigma_i);
* 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;
+ func_f_def = func_f;
+ func_fp_def = func_fp;
func_fpi_def = func_fpi;
}
