#endif
-XBT_LOG_NEW_DEFAULT_SUBCATEGORY(surf_lagrange, surf, "Logging specific to SURF (lagrange)");
-XBT_LOG_NEW_SUBCATEGORY(surf_lagrange_dichotomy, surf, "Logging specific to SURF (lagrange dichotomy)");
+XBT_LOG_NEW_DEFAULT_SUBCATEGORY(surf_lagrange, surf,
+ "Logging specific to SURF (lagrange)");
+XBT_LOG_NEW_SUBCATEGORY(surf_lagrange_dichotomy, surf,
+ "Logging specific to SURF (lagrange dichotomy)");
/*
* Local prototypes to implement the lagrangian optimization with optimal step, also called dichotomy.
*/
//solves the proportional fairness using a lagrange optimizition with dichotomy step
-void lagrange_solve (lmm_system_t sys);
+void lagrange_solve(lmm_system_t sys);
//computes the value of the dichotomy using a initial values, init, with a specific variable or constraint
-double dichotomy(double init, double diff(double, void*), void *var_cnst, double min_error);
+double dichotomy(double init, double diff(double, void *), void *var_cnst,
+ double min_error);
//computes the value of the differential of variable param_var applied to mu
-double partial_diff_mu (double mu, void * param_var);
+double partial_diff_mu(double mu, void *param_var);
//computes the value of the differential of constraint param_cnst applied to lambda
-double partial_diff_lambda (double lambda, void * param_cnst);
+double partial_diff_lambda(double lambda, void *param_cnst);
//auxiliar function to compute the partial_diff
double diff_aux(lmm_variable_t var, double x);
-static int __check_kkt(xbt_swag_t cnst_list, xbt_swag_t var_list,int warn)
+static int __check_kkt(xbt_swag_t cnst_list, xbt_swag_t var_list, int warn)
{
- xbt_swag_t elem_list = NULL;
- lmm_element_t elem = NULL;
- lmm_constraint_t cnst = NULL;
- lmm_variable_t var = NULL;
-
+ xbt_swag_t elem_list = NULL;
+ lmm_element_t elem = NULL;
+ lmm_constraint_t cnst = NULL;
+ lmm_variable_t var = NULL;
+
double tmp;
//verify the KKT property for each link
- xbt_swag_foreach(cnst, cnst_list){
+ xbt_swag_foreach(cnst, cnst_list) {
tmp = 0;
elem_list = &(cnst->element_set);
xbt_swag_foreach(elem, elem_list) {
var = elem->variable;
- if(var->weight<=0) continue;
+ if (var->weight <= 0)
+ continue;
tmp += var->value;
}
-
- if(double_positive(tmp - cnst->bound)) {
- if(warn) WARN3("The link (%p) is over-used. Expected less than %f and got %f", cnst, cnst->bound, tmp);
+
+ if (double_positive(tmp - cnst->bound)) {
+ if (warn)
+ WARN3
+ ("The link (%p) is over-used. Expected less than %f and got %f",
+ cnst, cnst->bound, tmp);
return 0;
}
- DEBUG3("Checking KKT for constraint (%p): sat = %f, lambda = %f ",cnst, tmp - cnst->bound, cnst->lambda);
-
+ DEBUG3("Checking KKT for constraint (%p): sat = %f, lambda = %f ",
+ cnst, tmp - cnst->bound, cnst->lambda);
+
/* if(!((fabs(tmp - cnst->bound)<MAXMIN_PRECISION && cnst->lambda>=MAXMIN_PRECISION) || */
/* (fabs(tmp - cnst->bound)>=MAXMIN_PRECISION && cnst->lambda<MAXMIN_PRECISION))) { */
/* if(warn) WARN1("The KKT condition is not verified for cnst %p...", cnst); */
/* return 0; */
/* } */
}
-
+
//verify the KKT property of each flow
- xbt_swag_foreach(var, var_list){
- if(var->bound < 0 || var->weight <= 0) continue;
- DEBUG3("Checking KKT for variable (%p): sat = %f mu = %f",var, var->value - var->bound,var->mu);
-
- if(double_positive(var->value - var->bound)) {
- if(warn) WARN3("The variable (%p) is too large. Expected less than %f and got %f", var, var->bound, var->value);
+ xbt_swag_foreach(var, var_list) {
+ if (var->bound < 0 || var->weight <= 0)
+ continue;
+ DEBUG3("Checking KKT for variable (%p): sat = %f mu = %f", var,
+ var->value - var->bound, var->mu);
+
+ if (double_positive(var->value - var->bound)) {
+ if (warn)
+ WARN3
+ ("The variable (%p) is too large. Expected less than %f and got %f",
+ var, var->bound, var->value);
return 0;
}
-
+
/* if(!((fabs(var->value - var->bound)<MAXMIN_PRECISION && var->mu>=MAXMIN_PRECISION) || */
/* (fabs(var->value - var->bound)>=MAXMIN_PRECISION && var->mu<MAXMIN_PRECISION))) { */
/* if(warn) WARN1("The KKT condition is not verified for var %p...",var); */
/*
* Lagrange Variables.
*/
- int max_iterations= 10000;
- double epsilon_min_error = 1e-6;
+ int max_iterations = 10000;
+ double epsilon_min_error = 1e-6;
double dichotomy_min_error = 1e-8;
double overall_error = 1;
* Variables to manipulate the data structure proposed to model the maxmin
* fairness. See docummentation for more details.
*/
- xbt_swag_t cnst_list = NULL;
+ xbt_swag_t cnst_list = NULL;
lmm_constraint_t cnst = NULL;
-
- xbt_swag_t var_list = NULL;
- lmm_variable_t var = NULL;
+
+ xbt_swag_t var_list = NULL;
+ lmm_variable_t var = NULL;
/*
* Auxiliar variables.
*/
- int iteration=0;
- double tmp=0;
+ int iteration = 0;
+ double tmp = 0;
int i;
-
+
DEBUG0("Iterative method configuration snapshot =====>");
DEBUG1("#### Maximum number of iterations : %d", max_iterations);
- DEBUG1("#### Minimum error tolerated : %e", epsilon_min_error);
- DEBUG1("#### Minimum error tolerated (dichotomy) : %e", dichotomy_min_error);
+ DEBUG1("#### Minimum error tolerated : %e",
+ epsilon_min_error);
+ DEBUG1("#### Minimum error tolerated (dichotomy) : %e",
+ dichotomy_min_error);
- if ( !(sys->modified))
+ if (!(sys->modified))
return;
/*
* Associate an index in the swag variables. Initialize mu.
*/
var_list = &(sys->variable_set);
- i=0;
- xbt_swag_foreach(var, var_list) {
- if((var->bound < 0.0) || (var->weight <= 0.0)){
+ i = 0;
+ xbt_swag_foreach(var, var_list) {
+ if ((var->bound < 0.0) || (var->weight <= 0.0)) {
DEBUG1("#### NOTE var(%d) is a boundless (or inactive) variable", i);
var->mu = -1.0;
- } else{
- var->mu = 1.0;
+ } else {
+ var->mu = 1.0;
var->new_mu = 2.0;
}
DEBUG3("#### var(%d) %p ->mu : %e", i, var, var->mu);
/*
* Initialize lambda.
*/
- cnst_list=&(sys->active_constraint_set);
- xbt_swag_foreach(cnst, cnst_list){
+ cnst_list = &(sys->active_constraint_set);
+ xbt_swag_foreach(cnst, cnst_list) {
cnst->lambda = 1.0;
cnst->new_lambda = 2.0;
DEBUG2("#### cnst(%p)->lambda : %e", cnst, cnst->lambda);
}
-
+
/*
* While doesn't reach a minimun error or a number maximum of iterations.
*/
- while(overall_error > epsilon_min_error && iteration < max_iterations){
-
+ while (overall_error > epsilon_min_error && iteration < max_iterations) {
+
iteration++;
- DEBUG1("************** ITERATION %d **************", iteration);
+ DEBUG1("************** ITERATION %d **************", iteration);
/*
* Compute the value of mu_i
*/
//forall mu_i in mu_1, mu_2, ..., mu_n
xbt_swag_foreach(var, var_list) {
- if((var->bound >= 0) && (var->weight > 0) ){
- var->new_mu = dichotomy(var->mu, partial_diff_mu, var, dichotomy_min_error);
- if(var->new_mu < 0) var->new_mu = 0;
- DEBUG3("====> var->mu (%p) : %g -> %g", var, var->mu, var->new_mu);
+ if ((var->bound >= 0) && (var->weight > 0)) {
+ DEBUG1("====> Working on var (%p)", var);
+ var->new_mu =
+ dichotomy(var->mu, partial_diff_mu, var, dichotomy_min_error);
+ if (var->new_mu < 0)
+ var->new_mu = 0;
+ DEBUG3("====> var->mu (%p) : %g -> %g", var, var->mu, var->new_mu);
var->mu = var->new_mu;
- }
+ }
}
/*
*/
//forall lambda_i in lambda_1, lambda_2, ..., lambda_n
xbt_swag_foreach(cnst, cnst_list) {
- cnst->new_lambda = dichotomy(cnst->lambda, partial_diff_lambda, cnst, dichotomy_min_error);
- DEBUG2("====> cnst->lambda (%p) = %e", cnst, cnst->new_lambda);
+ DEBUG1("====> Working on cnst (%p)", cnst);
+ cnst->new_lambda =
+ dichotomy(cnst->lambda, partial_diff_lambda, cnst,
+ dichotomy_min_error);
+ DEBUG2("====> cnst->lambda (%p) = %e", cnst, cnst->new_lambda);
cnst->lambda = cnst->new_lambda;
}
* Now computes the values of each variable (\rho) based on
* the values of \lambda and \mu.
*/
- overall_error=0;
+ overall_error = 0;
xbt_swag_foreach(var, var_list) {
- if(var->weight <=0)
+ if (var->weight <= 0)
var->value = 0.0;
else {
//compute sigma_i + mu_i
tmp = 0;
- for(i=0; i<var->cnsts_number; i++){
+ for (i = 0; i < var->cnsts_number; i++) {
tmp += (var->cnsts[i].constraint)->lambda;
}
- if(var->bound > 0)
- tmp+=var->mu;
- DEBUG3("\t Working on var (%p). cost = %e; Df = %e", var, tmp, var->df);
+ if (var->bound > 0)
+ tmp += var->mu;
+ DEBUG3("\t Working on var (%p). cost = %e; Df = %e", var, tmp,
+ var->df);
//uses the partial differential inverse function
tmp = var->func_fpi(var, tmp);
//computes de overall_error using normalized value
- if(overall_error < (fabs(var->value - tmp)/tmp) ){
- overall_error = (fabs(var->value - tmp)/tmp);
+ if (overall_error < (fabs(var->value - tmp) / tmp)) {
+ overall_error = (fabs(var->value - tmp) / tmp);
}
-
+
var->value = tmp;
}
- DEBUG3("======> value of var (%p) = %e, overall_error = %e", var, var->value, overall_error);
+ DEBUG3("======> value of var (%p) = %e, overall_error = %e", var,
+ var->value, overall_error);
}
- if(!__check_kkt(cnst_list,var_list,0)) overall_error=1.0;
- DEBUG2("Iteration %d: Overall_error : %f",iteration,overall_error);
+ if (!__check_kkt(cnst_list, var_list, 0))
+ overall_error = 1.0;
+ DEBUG2("Iteration %d: Overall_error : %f", iteration, overall_error);
}
- __check_kkt(cnst_list,var_list,1);
+ __check_kkt(cnst_list, var_list, 1);
- if(overall_error <= epsilon_min_error){
+ if (overall_error <= epsilon_min_error) {
DEBUG1("The method converges in %d iterations.", iteration);
}
- if(iteration>= max_iterations) {
- WARN1("Method reach %d iterations, which is the maximum number of iterations allowed.", iteration);
+ if (iteration >= max_iterations) {
+ WARN1
+ ("Method reach %d iterations, which is the maximum number of iterations allowed.",
+ iteration);
}
- INFO1("Method converged after %d iterations", iteration);
+/* INFO1("Method converged after %d iterations", iteration); */
- if(XBT_LOG_ISENABLED(surf_lagrange, xbt_log_priority_debug)) {
+ if (XBT_LOG_ISENABLED(surf_lagrange, xbt_log_priority_debug)) {
lmm_print(sys);
}
}
*
* @return a double correponding to the result of the dichotomyal process
*/
-double dichotomy(double init, double diff(double, void*), void *var_cnst, double min_error){
+double dichotomy(double init, double diff(double, void *), void *var_cnst,
+ double min_error)
+{
double min, max;
double overall_error;
double middle;
double min_diff, max_diff, middle_diff;
- double diff_0=0.0;
+ double diff_0 = 0.0;
min = max = init;
- if(init == 0){
- min = max = 1;
+ XBT_IN;
+
+ if (init == 0.0) {
+ min = max = 0.5;
}
min_diff = max_diff = middle_diff = 0.0;
overall_error = 1;
- if((diff_0=diff(0.0, var_cnst)) >= 0){
- CDEBUG1(surf_lagrange_dichotomy,"====> returning 0.0 (diff = %e)", diff(0.0, var_cnst));
+ if ((diff_0 = diff(1e-16, var_cnst)) >= 0) {
+ CDEBUG1(surf_lagrange_dichotomy, "====> returning 0.0 (diff = %e)",
+ diff_0);
return 0.0;
}
- CDEBUG1(surf_lagrange_dichotomy,"====> not detected positive diff in 0 (%e)",diff_0);
+ CDEBUG1(surf_lagrange_dichotomy,
+ "====> not detected positive diff in 0 (%e)", diff_0);
- while(overall_error > min_error){
+ while (overall_error > min_error) {
min_diff = diff(min, var_cnst);
max_diff = diff(max, var_cnst);
- CDEBUG2(surf_lagrange_dichotomy,"DICHOTOMY ===> min = %1.20f , max = %1.20f", min, max);
- CDEBUG2(surf_lagrange_dichotomy,"DICHOTOMY ===> diffmin = %1.20f , diffmax = %1.20f", min_diff, max_diff);
+ CDEBUG2(surf_lagrange_dichotomy,
+ "DICHOTOMY ===> min = %1.20f , max = %1.20f", min, max);
+ CDEBUG2(surf_lagrange_dichotomy,
+ "DICHOTOMY ===> diffmin = %1.20f , diffmax = %1.20f", min_diff,
+ max_diff);
- if( min_diff > 0 && max_diff > 0 ){
- if(min == max){
- CDEBUG0(surf_lagrange_dichotomy,"Decreasing min");
+ if (min_diff > 0 && max_diff > 0) {
+ if (min == max) {
+ CDEBUG0(surf_lagrange_dichotomy, "Decreasing min");
min = min / 2.0;
- }else{
- CDEBUG0(surf_lagrange_dichotomy,"Decreasing max");
+ } else {
+ CDEBUG0(surf_lagrange_dichotomy, "Decreasing max");
max = min;
}
- }else if( min_diff < 0 && max_diff < 0 ){
- if(min == max){
- CDEBUG0(surf_lagrange_dichotomy,"Increasing max");
+ } else if (min_diff < 0 && max_diff < 0) {
+ if (min == max) {
+ CDEBUG0(surf_lagrange_dichotomy, "Increasing max");
max = max * 2.0;
- }else{
- CDEBUG0(surf_lagrange_dichotomy,"Increasing min");
+ } else {
+ CDEBUG0(surf_lagrange_dichotomy, "Increasing min");
min = max;
}
- }else if( min_diff < 0 && max_diff > 0 ){
- middle = (max + min)/2.0;
+ } else if (min_diff < 0 && max_diff > 0) {
+ middle = (max + min) / 2.0;
middle_diff = diff(middle, var_cnst);
- if(max != 0.0 && min != 0.0){
- overall_error = fabs(min - max)/max;
+ if (max != 0.0 && min != 0.0) {
+ overall_error = fabs(min - max) / max;
}
- if( middle_diff < 0 ){
+ if (middle_diff < 0) {
min = middle;
- }else if( middle_diff > 0 ){
+ } else if (middle_diff > 0) {
max = middle;
- }else{
- CWARN0(surf_lagrange_dichotomy,"Found an optimal solution with 0 error!");
+ } else {
+ CWARN0(surf_lagrange_dichotomy,
+ "Found an optimal solution with 0 error!");
overall_error = 0;
return middle;
}
- }else if(min_diff == 0){
+ } else if (min_diff == 0) {
return min;
- }else if(max_diff == 0){
+ } else if (max_diff == 0) {
return max;
- }else if(min_diff > 0 && max_diff < 0){
- CWARN0(surf_lagrange_dichotomy,"The impossible happened, partial_diff(min) > 0 && partial_diff(max) < 0");
- }else {
- CWARN0(surf_lagrange_dichotomy,"diffmin or diffmax are something I don't know, taking no action.");
+ } else if (min_diff > 0 && max_diff < 0) {
+ CWARN0(surf_lagrange_dichotomy,
+ "The impossible happened, partial_diff(min) > 0 && partial_diff(max) < 0");
+ } else {
+ CWARN2(surf_lagrange_dichotomy,
+ "diffmin (%1.20f) or diffmax (%1.20f) are something I don't know, taking no action.",
+ min_diff, max_diff);
+ abort();
}
}
+ XBT_OUT;
- CDEBUG1(surf_lagrange_dichotomy,"====> returning %e", (min+max)/2.0);
- return ((min+max)/2.0);
+ CDEBUG1(surf_lagrange_dichotomy, "====> returning %e",
+ (min + max) / 2.0);
+ return ((min + max) / 2.0);
}
/*
*
*/
-double partial_diff_mu(double mu, void *param_var){
- double mu_partial=0.0;
- double sigma_mu=0.0;
- lmm_variable_t var = (lmm_variable_t)param_var;
+double partial_diff_mu(double mu, void *param_var)
+{
+ double mu_partial = 0.0;
+ double sigma_mu = 0.0;
+ lmm_variable_t var = (lmm_variable_t) param_var;
int i;
-
+ XBT_IN;
//compute sigma_i
- for(i=0; i<var->cnsts_number; i++)
+ for (i = 0; i < var->cnsts_number; i++)
sigma_mu += (var->cnsts[i].constraint)->lambda;
-
+
//compute sigma_i + mu_i
sigma_mu += mu;
-
+
//use auxiliar function passing (sigma_i + mu_i)
- mu_partial = diff_aux(var, sigma_mu) ;
-
+ mu_partial = diff_aux(var, sigma_mu);
+
//add the RTT limit
mu_partial += var->bound;
+ XBT_OUT;
return mu_partial;
}
/*
*
*/
-double partial_diff_lambda(double lambda, void *param_cnst){
+double partial_diff_lambda(double lambda, void *param_cnst)
+{
int i;
xbt_swag_t elem_list = NULL;
lmm_element_t elem = NULL;
lmm_variable_t var = NULL;
- lmm_constraint_t cnst= (lmm_constraint_t) param_cnst;
- double lambda_partial=0.0;
- double sigma_i=0.0;
+ lmm_constraint_t cnst = (lmm_constraint_t) param_cnst;
+ double lambda_partial = 0.0;
+ double sigma_i = 0.0;
+ XBT_IN;
elem_list = &(cnst->element_set);
- DEBUG1("Computting diff of cnst (%p)", cnst);
-
+ CDEBUG1(surf_lagrange_dichotomy,"Computting diff of cnst (%p)", cnst);
+
xbt_swag_foreach(elem, elem_list) {
var = elem->variable;
- if(var->weight<=0) continue;
-
+ if (var->weight <= 0)
+ continue;
+
//initilize de sumation variable
sigma_i = 0.0;
//compute sigma_i of variable var
- for(i=0; i<var->cnsts_number; i++){
+ for (i = 0; i < var->cnsts_number; i++) {
sigma_i += (var->cnsts[i].constraint)->lambda;
}
-
+
//add mu_i if this flow has a RTT constraint associated
- if(var->bound > 0) sigma_i += var->mu;
+ if (var->bound > 0)
+ sigma_i += var->mu;
//replace value of cnst->lambda by the value of parameter lambda
sigma_i = (sigma_i - cnst->lambda) + lambda;
-
+
//use the auxiliar function passing (\sigma_i + \mu_i)
lambda_partial += diff_aux(var, sigma_i);
}
lambda_partial += cnst->bound;
- CDEBUG1(surf_lagrange_dichotomy,"returnning = %1.20f", lambda_partial);
+ CDEBUG1(surf_lagrange_dichotomy, "returning = %1.20f", lambda_partial);
+ XBT_OUT;
return lambda_partial;
}
-double diff_aux(lmm_variable_t var, double x){
- double tmp_fp, tmp_fpi, tmp_fpip, result;
+double diff_aux(lmm_variable_t var, double x)
+{
+ double tmp_fpi, result;
- xbt_assert0(var->func_fp, "Initialize the protocol functions first create variables before.");
+ XBT_IN2("(var (%p), x (%1.20f))", var, x);
+ xbt_assert0(var->func_fp,
+ "Initialize the protocol functions first create variables before.");
- tmp_fp = var->func_fp(var, x);
tmp_fpi = var->func_fpi(var, x);
- tmp_fpip = var->func_fpip(var, x);
-
- result = tmp_fpip*(var->func_fp(var, tmp_fpi));
-
- result = result - tmp_fpi;
+ result = - tmp_fpi;
- result = result - (tmp_fpip * x);
-
- CDEBUG2(surf_lagrange_dichotomy,"diff_aux(%1.20f) = %1.20f", x, result);
+ CDEBUG1(surf_lagrange_dichotomy, "returning %1.20f", result);
+ XBT_OUT;
return result;
-}
-
-
-
-
-
-
-
-
+}
