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 dicotomi.
+ * Local prototypes to implement the lagrangian optimization with optimal step, also called dichotomy.
*/
-//solves the proportional fairness using a lagrange optimizition with dicotomi step
+//solves the proportional fairness using a lagrange optimizition with dichotomy step
void lagrange_solve (lmm_system_t sys);
-//computes the value of the dicotomi using a initial values, init, with a specific variable or constraint
-double dicotomi(double init, double diff(double, void*), void *var_cnst, double min_error);
+//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);
//computes the value of the differential of variable param_var applied to mu
double partial_diff_mu (double mu, void * param_var);
//computes the value of the differential of constraint param_cnst applied to lambda
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)
+{
+ 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){
+ tmp = 0;
+ elem_list = &(cnst->element_set);
+ xbt_swag_foreach(elem, elem_list) {
+ var = elem->variable;
+ 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);
+ return 0;
+ }
+ 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);
+ 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); */
+/* return 0; */
+/* } */
+ }
+ return 1;
+}
+
void lagrange_solve(lmm_system_t sys)
{
/*
*/
int max_iterations= 10000;
double epsilon_min_error = 1e-6;
- double dicotomi_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 elem_list = NULL;
- lmm_element_t elem = NULL;
-
xbt_swag_t cnst_list = NULL;
lmm_constraint_t cnst = NULL;
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 (dicotomi) : %e", dicotomi_min_error);
+ DEBUG1("#### Minimum error tolerated (dichotomy) : %e", dichotomy_min_error);
if ( !(sys->modified))
return;
//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 = dicotomi(var->mu, partial_diff_mu, var, dicotomi_min_error);
+ var->new_mu = dichotomy(var->mu, partial_diff_mu, var, dichotomy_min_error);
if(var->new_mu < 0) var->new_mu = 0;
- DEBUG2("====> var->mu (%p) = %e", var, var->new_mu);
+ 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 = dicotomi(cnst->lambda, partial_diff_lambda, cnst, dicotomi_min_error);
+ 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;
}
}
DEBUG3("======> value of var (%p) = %e, overall_error = %e", var, var->value, overall_error);
}
- }
-
- //verify the KKT property for each link
- 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;
- tmp += var->value;
- }
-
- if(tmp - cnst->bound > epsilon_min_error) {
- WARN3("The link (%p) is over-used. Expected less than %e and got %e", cnst, cnst->bound, tmp);
- }
- if(!((fabs(tmp - cnst->bound)<epsilon_min_error && cnst->lambda>=epsilon_min_error) ||
- (fabs(tmp - cnst->bound)>=epsilon_min_error && cnst->lambda<epsilon_min_error))) {
- WARN1("The KKT condition is not verified for cnst %p...", cnst);
- overall_error=1.0;
- }
+ if(!__check_kkt(cnst_list,var_list,0)) overall_error=1.0;
+ DEBUG2("Iteration %d: Overall_error : %f",iteration,overall_error);
}
-
- //verify the KKT property of each flow
- xbt_swag_foreach(var, var_list){
- if(var->bound < 0 || var->weight <= 0) continue;
- INFO2("Checking KKT: sat = %e mu = %e",var->value - var->bound,var->mu);
- if(!((fabs(var->value - var->bound)<epsilon_min_error && var->mu>=epsilon_min_error) ||
- (fabs(var->value - var->bound)>=epsilon_min_error && var->mu<epsilon_min_error))) {
- WARN1("The KKT condition is not verified for var %p...",var);
- overall_error=1.0;
- }
-/* tmp = 0; */
-/* tmp = (var->value - var->bound); */
-/* if(tmp != 0.0 || var->mu != 0.0){ */
-/* WARN3("The flow (%p) doesn't match the KKT property, value expected (=0) got (lambda=%e) (sum_rho=%e)", var, var->mu, tmp); */
-/* } */
- }
+ __check_kkt(cnst_list,var_list,1);
if(overall_error <= epsilon_min_error){
DEBUG1("The method converges in %d iterations.", iteration);
- }else{
- WARN1("Method reach %d iterations, which is the maxmimun 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);
+
+ if(XBT_LOG_ISENABLED(surf_lagrange, xbt_log_priority_debug)) {
+ lmm_print(sys);
}
}
/*
- * Returns a double value corresponding to the result of a dicotomi proccess with
+ * Returns a double value corresponding to the result of a dichotomy proccess with
* respect to a given variable/constraint (\mu in the case of a variable or \lambda in
* case of a constraint) and a initial value init.
*
* @param var_cnst a pointer to a variable or constraint
* @param min_erro a minimun error tolerated
*
- * @return a double correponding to the result of the dicotomial process
+ * @return a double correponding to the result of the dichotomyal process
*/
-double dicotomi(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;
min = max = init;
if(init == 0){
min_diff = max_diff = middle_diff = 0.0;
overall_error = 1;
- if(diff(0.0, var_cnst) > 0){
- DEBUG1("====> returning 0.0 (diff = %e)", diff(0.0, var_cnst));
+ if((diff_0=diff(0.0, var_cnst)) >= 0){
+ CDEBUG1(surf_lagrange_dichotomy,"====> returning 0.0 (diff = %e)", diff(0.0, var_cnst));
return 0.0;
}
- DEBUG0("====> not detected positive diff in 0");
+ CDEBUG1(surf_lagrange_dichotomy,"====> not detected positive diff in 0 (%e)",diff_0);
while(overall_error > min_error){
min_diff = diff(min, var_cnst);
max_diff = diff(max, var_cnst);
- DEBUG2("DICOTOMI ===> min = %e , max = %e", min, max);
- DEBUG2("DICOTOMI ===> diffmin = %e , diffmax = %e", 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");
min = min / 2.0;
}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");
max = max * 2.0;
}else{
+ CDEBUG0(surf_lagrange_dichotomy,"Increasing min");
min = max;
}
}else if( min_diff < 0 && max_diff > 0 ){
}else if( middle_diff > 0 ){
max = middle;
}else{
- WARN0("Found an optimal solution with 0 error!");
+ CWARN0(surf_lagrange_dichotomy,"Found an optimal solution with 0 error!");
overall_error = 0;
return middle;
}
}else if(max_diff == 0){
return max;
}else if(min_diff > 0 && max_diff < 0){
- WARN0("The impossible happened, partial_diff(min) > 0 && partial_diff(max) < 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.");
}
}
- DEBUG1("====> returning %e", (min+max)/2.0);
+ CDEBUG1(surf_lagrange_dichotomy,"====> returning %e", (min+max)/2.0);
return ((min+max)/2.0);
}
lambda_partial += diff_aux(var, sigma_i);
}
+
lambda_partial += cnst->bound;
+
+ CDEBUG1(surf_lagrange_dichotomy,"returnning = %1.20f", lambda_partial);
+
return lambda_partial;
}
result = result - (tmp_fpip * x);
+ CDEBUG2(surf_lagrange_dichotomy,"diff_aux(%1.20f) = %1.20f", x, result);
return result;
}
