X-Git-Url: http://info.iut-bm.univ-fcomte.fr/pub/gitweb/simgrid.git/blobdiff_plain/2ad68c1e6a0dfbb37bad2a4a4ac434700aab5d33..5d038603f775914afc8c6f35eff53f3682802f5b:/src/surf/lagrange.c diff --git a/src/surf/lagrange.c b/src/surf/lagrange.c index a8701662b7..dab45e3896 100644 --- a/src/surf/lagrange.c +++ b/src/surf/lagrange.c @@ -1,7 +1,9 @@ -/* $Id$ */ -/* Copyright (c) 2007 Arnaud Legrand, Pedro Velho. All rights reserved. */ +/* Copyright (c) 2007, 2008, 2009, 2010. 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. */ + /* * Modelling the proportional fairness using the Lagrange Optimization * Approach. For a detailed description see: @@ -17,9 +19,9 @@ #endif XBT_LOG_NEW_DEFAULT_SUBCATEGORY(surf_lagrange, surf, - "Logging specific to SURF (lagrange)"); + "Logging specific to SURF (lagrange)"); XBT_LOG_NEW_SUBCATEGORY(surf_lagrange_dichotomy, surf_lagrange, - "Logging specific to SURF (lagrange dichotomy)"); + "Logging specific to SURF (lagrange dichotomy)"); #define SHOW_EXPR(expr) CDEBUG1(surf_lagrange,#expr " = %g",expr); @@ -34,14 +36,14 @@ double (*func_fpi_def) (lmm_variable_t, double); 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); + void *var_cnst, double min_error); //computes the value of the differential of variable param_var applied to mu static double partial_diff_mu(double mu, void *param_var); //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) + int warn) { xbt_swag_t elem_list = NULL; lmm_element_t elem = NULL; @@ -56,20 +58,20 @@ static int __check_feasible(xbt_swag_t cnst_list, xbt_swag_t var_list, xbt_swag_foreach(elem, elem_list) { var = elem->variable; if (var->weight <= 0) - continue; + 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); + WARN3 + ("The link (%p) is over-used. Expected less than %f and got %f", + cnst, cnst->bound, tmp); return 0; } DEBUG3 - ("Checking feasability for constraint (%p): sat = %f, lambda = %f ", - cnst, tmp - cnst->bound, cnst->lambda); + ("Checking feasability for constraint (%p): sat = %f, lambda = %f ", + cnst, tmp - cnst->bound, cnst->lambda); } xbt_swag_foreach(var, var_list) { @@ -78,13 +80,13 @@ static int __check_feasible(xbt_swag_t cnst_list, xbt_swag_t var_list, if (var->bound < 0) continue; DEBUG3("Checking feasability for variable (%p): sat = %f mu = %f", var, - var->value - var->bound, var->mu); + 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); + WARN3 + ("The variable (%p) is too large. Expected less than %f and got %f", + var, var->bound, var->value); return 0; } } @@ -101,7 +103,8 @@ static double new_value(lmm_variable_t var) } if (var->bound > 0) tmp += var->mu; - DEBUG3("\t Working on var (%p). cost = %e; Df = %e", var, tmp, var->df); + DEBUG3("\t Working on var (%p). cost = %e; Weight = %e", var, tmp, + var->weight); //uses the partial differential inverse function return var->func_fpi(var, tmp); } @@ -144,7 +147,7 @@ static double dual_objective(xbt_swag_t var_list, xbt_swag_t cnst_list) DEBUG2("var %p : sigma_i = %1.20f", var, sigma_i); obj += var->func_f(var, var->func_fpi(var, sigma_i)) - - sigma_i * var->func_fpi(var, sigma_i); + sigma_i * var->func_fpi(var, sigma_i); if (var->bound > 0) obj += var->mu * var->bound; @@ -187,9 +190,9 @@ void lagrange_solve(lmm_system_t sys) DEBUG0("Iterative method configuration snapshot =====>"); DEBUG1("#### Maximum number of iterations : %d", max_iterations); DEBUG1("#### Minimum error tolerated : %e", - epsilon_min_error); + epsilon_min_error); DEBUG1("#### Minimum error tolerated (dichotomy) : %e", - dichotomy_min_error); + dichotomy_min_error); if (XBT_LOG_ISENABLED(surf_lagrange, xbt_log_priority_debug)) { lmm_print(sys); @@ -221,22 +224,24 @@ void lagrange_solve(lmm_system_t sys) else { int nb = 0; if (var->bound < 0.0) { - DEBUG1("#### NOTE var(%d) is a boundless variable", i); - var->mu = -1.0; - var->value = new_value(var); + DEBUG1("#### NOTE var(%d) is a boundless variable", i); + var->mu = -1.0; + var->value = new_value(var); } else { - var->mu = 1.0; - var->new_mu = 2.0; - var->value = new_value(var); + var->mu = 1.0; + var->new_mu = 2.0; + var->value = new_value(var); } - DEBUG2("#### var(%p) ->df : %e", var, var->df); + DEBUG2("#### var(%p) ->weight : %e", var, var->weight); DEBUG2("#### var(%p) ->mu : %e", var, var->mu); DEBUG2("#### var(%p) ->weight: %e", var, var->weight); DEBUG2("#### var(%p) ->bound: %e", var, var->bound); for (i = 0; i < var->cnsts_number; i++) { - if(var->cnsts[i].value==0.0) nb++; + if (var->cnsts[i].value == 0.0) + nb++; } - if(nb==var->cnsts_number) var->value = 1.0; + if (nb == var->cnsts_number) + var->value = 1.0; } } @@ -249,7 +254,7 @@ void lagrange_solve(lmm_system_t sys) * While doesn't reach a minimun error or a number maximum of iterations. */ while (overall_modification > epsilon_min_error - && iteration < max_iterations) { + && iteration < max_iterations) { /* int dual_updated=0; */ iteration++; @@ -261,22 +266,22 @@ void lagrange_solve(lmm_system_t sys) */ xbt_swag_foreach(var, var_list) { if (!var->weight) - break; + break; if (var->bound >= 0) { - DEBUG1("Working on var (%p)", var); - var->new_mu = new_mu(var); + DEBUG1("Working on var (%p)", var); + var->new_mu = new_mu(var); /* 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; - - new_obj = dual_objective(var_list, cnst_list); - DEBUG3("Improvement for Objective (%g -> %g) : %g", obj, new_obj, - obj - new_obj); - xbt_assert1(obj - new_obj >= -epsilon_min_error, - "Our gradient sucks! (%1.20f)", obj - new_obj); - obj = new_obj; + DEBUG3("Updating mu : var->mu (%p) : %1.20f -> %1.20f", var, + var->mu, var->new_mu); + var->mu = var->new_mu; + + new_obj = dual_objective(var_list, cnst_list); + DEBUG3("Improvement for Objective (%g -> %g) : %g", obj, new_obj, + obj - new_obj); + xbt_assert1(obj - new_obj >= -epsilon_min_error, + "Our gradient sucks! (%1.20f)", obj - new_obj); + obj = new_obj; } } @@ -286,19 +291,19 @@ void lagrange_solve(lmm_system_t sys) xbt_swag_foreach(cnst, cnst_list) { DEBUG1("Working on cnst (%p)", cnst); cnst->new_lambda = - dichotomy(cnst->lambda, partial_diff_lambda, cnst, - dichotomy_min_error); + dichotomy(cnst->lambda, partial_diff_lambda, cnst, + dichotomy_min_error); /* 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, cnst->lambda, cnst->new_lambda); cnst->lambda = cnst->new_lambda; new_obj = dual_objective(var_list, cnst_list); DEBUG3("Improvement for Objective (%g -> %g) : %g", obj, new_obj, - obj - new_obj); + obj - new_obj); xbt_assert1(obj - new_obj >= -epsilon_min_error, - "Our gradient sucks! (%1.20f)", obj - new_obj); + "Our gradient sucks! (%1.20f)", obj - new_obj); obj = new_obj; } @@ -310,16 +315,16 @@ void lagrange_solve(lmm_system_t sys) overall_modification = 0; xbt_swag_foreach(var, var_list) { if (var->weight <= 0) - var->value = 0.0; + var->value = 0.0; else { - tmp = new_value(var); + tmp = new_value(var); - overall_modification = - MAX(overall_modification, fabs(var->value - tmp)); + overall_modification = + MAX(overall_modification, fabs(var->value - tmp)); - var->value = tmp; - DEBUG3("New value of var (%p) = %e, overall_modification = %e", - var, var->value, overall_modification); + var->value = tmp; + DEBUG3("New value of var (%p) = %e, overall_modification = %e", + var, var->value, overall_modification); } } @@ -327,7 +332,7 @@ void lagrange_solve(lmm_system_t sys) if (!__check_feasible(cnst_list, var_list, 0)) overall_modification = 1.0; DEBUG2("Iteration %d: overall_modification : %f", iteration, - overall_modification); + overall_modification); /* if(!dual_updated) { */ /* WARN1("Could not improve the convergence at iteration %d. Drop it!",iteration); */ /* break; */ @@ -341,8 +346,8 @@ void lagrange_solve(lmm_system_t sys) } if (iteration >= max_iterations) { DEBUG1 - ("Method reach %d iterations, which is the maximum number of iterations allowed.", - iteration); + ("Method reach %d iterations, which is the maximum number of iterations allowed.", + iteration); } /* INFO1("Method converged after %d iterations", iteration); */ @@ -364,7 +369,7 @@ void lagrange_solve(lmm_system_t sys) * @return a double correponding to the result of the dichotomyal process */ static double dichotomy(double init, double diff(double, void *), - void *var_cnst, double min_error) + void *var_cnst, double min_error) { double min, max; double overall_error; @@ -393,57 +398,57 @@ static double dichotomy(double init, double diff(double, void *), while (overall_error > min_error) { CDEBUG4(surf_lagrange_dichotomy, - "[min, max] = [%1.20f, %1.20f] || diffmin, diffmax = %1.20f, %1.20f", - min, max, min_diff, max_diff); + "[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); + 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; + 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); + 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; + 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; CDEBUG1(surf_lagrange_dichotomy, "Trying (max+min)/2 : %1.20f", - middle); + middle); if ((min == middle) || (max == middle)) { - CWARN4(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; + CWARN4(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; } middle_diff = diff(middle, var_cnst); if (middle_diff < 0) { - CDEBUG0(surf_lagrange_dichotomy, "Increasing min"); - min = middle; - overall_error = max_diff - middle_diff; - min_diff = middle_diff; + CDEBUG0(surf_lagrange_dichotomy, "Increasing min"); + min = middle; + overall_error = max_diff - middle_diff; + min_diff = middle_diff; /* SHOW_EXPR(overall_error); */ } else if (middle_diff > 0) { - CDEBUG0(surf_lagrange_dichotomy, "Decreasing max"); - max = middle; - overall_error = max_diff - middle_diff; - max_diff = middle_diff; + CDEBUG0(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; + overall_error = 0; /* SHOW_EXPR(overall_error); */ } } else if (min_diff == 0) { @@ -456,12 +461,12 @@ static double dichotomy(double init, double diff(double, void *), /* SHOW_EXPR(overall_error); */ } else if (min_diff > 0 && max_diff < 0) { CWARN0(surf_lagrange_dichotomy, - "The impossible happened, partial_diff(min) > 0 && partial_diff(max) < 0"); + "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.", - min_diff, max_diff); + "diffmin (%1.20f) or diffmax (%1.20f) are something I don't know, taking no action.", + min_diff, max_diff); abort(); } } @@ -493,7 +498,7 @@ static double partial_diff_lambda(double lambda, void *param_cnst) continue; CDEBUG1(surf_lagrange_dichotomy, "Computing sigma_i for var (%p)", - var); + var); // Initialize the summation variable sigma_i = 0.0; @@ -516,8 +521,8 @@ static double partial_diff_lambda(double lambda, void *param_cnst) diff += cnst->bound; CDEBUG3(surf_lagrange_dichotomy, - "d D/d lambda for cnst (%p) at %1.20f = %1.20f", cnst, lambda, - diff); + "d D/d lambda for cnst (%p) at %1.20f = %1.20f", cnst, lambda, + diff); XBT_OUT; return diff; } @@ -529,13 +534,18 @@ static double partial_diff_lambda(double lambda, void *param_cnst) * Set default functions to the ones passed as parameters. This is a polimorfism in C pure, enjoy the roots of 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; @@ -559,19 +569,19 @@ lmm_set_default_protocol_function(double (*func_f) double func_vegas_f(lmm_variable_t var, double x) { xbt_assert1(x > 0.0, "Don't call me with stupid values! (%1.20f)", x); - return VEGAS_SCALING * var->df * log(x); + return VEGAS_SCALING * var->weight * log(x); } double func_vegas_fp(lmm_variable_t var, double x) { xbt_assert1(x > 0.0, "Don't call me with stupid values! (%1.20f)", x); - return VEGAS_SCALING * var->df / x; + return VEGAS_SCALING * var->weight / x; } double func_vegas_fpi(lmm_variable_t var, double x) { xbt_assert1(x > 0.0, "Don't call me with stupid values! (%1.20f)", x); - return var->df / (x / VEGAS_SCALING); + return var->weight / (x / VEGAS_SCALING); } /* @@ -582,29 +592,67 @@ double func_vegas_fpi(lmm_variable_t var, double x) #define RENO_SCALING 1.0 double func_reno_f(lmm_variable_t var, double x) { - xbt_assert0(var->df > 0.0, "Don't call me with stupid values!"); + xbt_assert0(var->weight > 0.0, "Don't call me with stupid values!"); - return RENO_SCALING * sqrt(3.0 / 2.0) / var->df * atan(sqrt(3.0 / 2.0) * - var->df * x); + return RENO_SCALING * sqrt(3.0 / 2.0) / var->weight * + atan(sqrt(3.0 / 2.0) * var->weight * x); } double func_reno_fp(lmm_variable_t var, double x) { - return RENO_SCALING * 3.0 / (3.0 * var->df * var->df * x * x + 2.0); + return RENO_SCALING * 3.0 / (3.0 * var->weight * var->weight * x * x + + 2.0); } 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(var->weight > 0.0, "Don't call me with stupid values!"); xbt_assert0(x > 0.0, "Don't call me with stupid values!"); res_fpi = - 1.0 / (var->df * var->df * (x / RENO_SCALING)) - - 2.0 / (3.0 * var->df * var->df); + 1.0 / (var->weight * var->weight * (x / RENO_SCALING)) - + 2.0 / (3.0 * var->weight * var->weight); 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); } + + +/* Implementing new Reno-2 + * For Reno-2: $f(x) = U_f(x_f) = \frac{{2}{D_f}}*ln(2+x*D_f)$ + * Therefore: $fp(x) = 2/(Weight*x + 2) + * Therefore: $fpi(x) = (2*Weight)/x - 4 + */ +#define RENO2_SCALING 1.0 +double func_reno2_f(lmm_variable_t var, double x) +{ + xbt_assert0(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)); +} + +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)); +} + +double func_reno2_fpi(lmm_variable_t var, double x) +{ + double res_fpi; + double tmp; + + xbt_assert0(x > 0.0, "Don't call me with stupid values!"); + tmp = x * var->weight * var->weight; + res_fpi = tmp * (9.0 * x + 24.0); + + if (res_fpi <= 0.0) + return 0.0; + + res_fpi = RENO2_SCALING * (-3.0 * tmp + sqrt(res_fpi)) / (4.0 * tmp); + return res_fpi; +}