#include <math.h>
#endif
+#define VEGAS_SCALING 1000.0
+
XBT_LOG_NEW_DEFAULT_SUBCATEGORY(surf_lagrange, surf,
"Logging specific to SURF (lagrange)");
}
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
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;
}
/*
* Lagrange Variables.
*/
- int max_iterations = 10000;
- double epsilon_min_error = 1e-6;
- double dichotomy_min_error = 1e-8;
+ int max_iterations = 100;
+ double epsilon_min_error = MAXMIN_PRECISION;
+ double dichotomy_min_error = 1e-20;
double overall_error = 1;
/*
* While doesn't reach a minimun error or a number maximum of iterations.
*/
while (overall_error > epsilon_min_error && iteration < max_iterations) {
+ int dual_updated=0;
iteration++;
DEBUG1("************** ITERATION %d **************", iteration);
-
+ DEBUG0("-------------- Gradient Descent ----------");
/*
* 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)) {
- DEBUG1("====> Working on var (%p)", var);
+ 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);
+ dual_updated += (fabs(var->new_mu-var->mu)>dichotomy_min_error);
+ DEBUG2("dual_updated (%d) : %1.20f",dual_updated,fabs(var->new_mu-var->mu));
+ DEBUG3("Updating mu : var->mu (%p) : %1.20f -> %1.20f", 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) {
- DEBUG1("====> Working on cnst (%p)", cnst);
+ 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);
+ dual_updated += (fabs(cnst->new_lambda-cnst->lambda)>dichotomy_min_error);
+ DEBUG2("dual_updated (%d) : %1.20f",dual_updated,fabs(cnst->new_lambda-cnst->lambda));
+ DEBUG3("Updating lambda : cnst->lambda (%p) : %1.20f -> %1.20f", cnst, cnst->lambda, cnst->new_lambda);
cnst->lambda = cnst->new_lambda;
}
* Now computes the values of each variable (\rho) based on
* the values of \lambda and \mu.
*/
+ DEBUG0("-------------- Check convergence ----------");
overall_error = 0;
xbt_swag_foreach(var, var_list) {
if (var->weight <= 0)
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);
+ }
+
+ if (overall_error < (fabs(var->value - tmp))) {
+ overall_error = (fabs(var->value - tmp));
}
var->value = tmp;
+ DEBUG3("New 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(!dual_updated) {
+ DEBUG1("Could not improve the convergence at iteration %d. Drop it!",iteration);
+ break;
+ }
}
DEBUG1("The method converges in %d iterations.", iteration);
}
if (iteration >= max_iterations) {
- WARN1
+ DEBUG1
("Method reach %d iterations, which is the maximum number of iterations allowed.",
iteration);
}
overall_error = 1;
if ((diff_0 = diff(1e-16, var_cnst)) >= 0) {
- CDEBUG1(surf_lagrange_dichotomy, "====> returning 0.0 (diff = %e)",
+ CDEBUG1(surf_lagrange_dichotomy, "returning 0.0 (diff = %e)",
diff_0);
+ XBT_OUT;
return 0.0;
}
- CDEBUG1(surf_lagrange_dichotomy,
- "====> not detected positive diff in 0 (%e)", diff_0);
+ min_diff = diff(min, var_cnst);
+ max_diff = diff(max, var_cnst);
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);
+ CDEBUG4(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) {
CDEBUG0(surf_lagrange_dichotomy, "Decreasing min");
min = min / 2.0;
+ min_diff = diff(min, var_cnst);
} else {
CDEBUG0(surf_lagrange_dichotomy, "Decreasing max");
max = min;
+ max_diff = min_diff;
+
}
} else if (min_diff < 0 && max_diff < 0) {
if (min == max) {
CDEBUG0(surf_lagrange_dichotomy, "Increasing max");
max = max * 2.0;
+ max_diff = diff(max, var_cnst);
} else {
CDEBUG0(surf_lagrange_dichotomy, "Increasing min");
min = max;
+ min_diff = max_diff;
}
} else if (min_diff < 0 && max_diff > 0) {
middle = (max + min) / 2.0;
- middle_diff = diff(middle, var_cnst);
+ CDEBUG1(surf_lagrange_dichotomy, "Trying (max+min)/2 : %1.20f",middle);
- if (max != 0.0 && min != 0.0) {
- overall_error = fabs(min - max) / max;
+ if((min==middle) || (max==middle)) {
+ DEBUG0("Cannot improve the convergence!");
+ break;
}
+ middle_diff = diff(middle, var_cnst);
if (middle_diff < 0) {
+ CDEBUG0(surf_lagrange_dichotomy, "Increasing min");
min = middle;
+ min_diff = middle_diff;
} else if (middle_diff > 0) {
+ CDEBUG0(surf_lagrange_dichotomy, "Decreasing max");
max = middle;
+ max_diff = middle_diff;
} else {
- CWARN0(surf_lagrange_dichotomy,
- "Found an optimal solution with 0 error!");
overall_error = 0;
- return middle;
}
-
} else if (min_diff == 0) {
- return min;
+ max=min;
+ overall_error = 0;
} else if (max_diff == 0) {
- return max;
+ min=max;
+ overall_error = 0;
} else if (min_diff > 0 && max_diff < 0) {
CWARN0(surf_lagrange_dichotomy,
"The impossible happened, partial_diff(min) > 0 && partial_diff(max) < 0");
+ abort();
} else {
CWARN2(surf_lagrange_dichotomy,
"diffmin (%1.20f) or diffmax (%1.20f) are something I don't know, taking no action.",
}
}
+ CDEBUG1(surf_lagrange_dichotomy, "returning %e", (min + max) / 2.0);
XBT_OUT;
-
- CDEBUG1(surf_lagrange_dichotomy, "====> returning %e",
- (min + max) / 2.0);
return ((min + max) / 2.0);
}
lambda_partial += cnst->bound;
-
- CDEBUG1(surf_lagrange_dichotomy, "returning = %1.20f", lambda_partial);
-
XBT_OUT;
return lambda_partial;
}
double tmp_fpi, result;
XBT_IN2("(var (%p), x (%1.20f))", var, x);
- xbt_assert0(var->func_fp,
+ xbt_assert0(var->func_fpi,
"Initialize the protocol functions first create variables before.");
tmp_fpi = var->func_fpi(var, x);
result = - tmp_fpi;
- CDEBUG1(surf_lagrange_dichotomy, "returning %1.20f", result);
XBT_OUT;
return result;
}
+
+
+/**************** Vegas and Reno functions *************************/
+/*
+ * NOTE for Reno: all functions consider the network
+ * coeficient (alpha) equal to 1.
+ */
+
+/*
+ * For Vegas fpi: $\frac{\alpha D_f}{x}$
+ */
+double func_vegas_fpi(lmm_variable_t var, double x){
+ xbt_assert0(x>0.0,"Don't call me with stupid values!");
+ return VEGAS_SCALING*var->df/x;
+}
+
+/*
+ * For Reno fpi: $\sqrt{\frac{1}{{D_f}^2 x} - \frac{2}{3{D_f}^2}}$
+ */
+double func_reno_fpi(lmm_variable_t var, double x){
+ double res_fpi;
+
+ xbt_assert0(var->df>0.0,"Don't call me with stupid values!");
+ xbt_assert0(x>0.0,"Don't call me with stupid values!");
+
+ res_fpi = 1/(var->df*var->df*x) - 2/(3*var->df*var->df);
+ if(res_fpi<=0.0) return 0.0;
+ xbt_assert0(res_fpi>0.0,"Don't call me with stupid values!");
+ return sqrt(res_fpi);
+}
+
