X-Git-Url: http://info.iut-bm.univ-fcomte.fr/pub/gitweb/simgrid.git/blobdiff_plain/8a76d5717862842060081d52f06c092250a9a573..57d65ecd18c591154169428816b1623be700097a:/src/surf/lagrange.c diff --git a/src/surf/lagrange.c b/src/surf/lagrange.c index 9aa0fd4a0c..8530c65d31 100644 --- a/src/surf/lagrange.c +++ b/src/surf/lagrange.c @@ -17,7 +17,6 @@ #include #endif - XBT_LOG_NEW_DEFAULT_SUBCATEGORY(surf_lagrange, surf, "Logging specific to SURF (lagrange)"); XBT_LOG_NEW_SUBCATEGORY(surf_lagrange_dichotomy, surf, @@ -39,7 +38,7 @@ double partial_diff_lambda(double lambda, void *param_cnst); 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_feasible(xbt_swag_t cnst_list, xbt_swag_t var_list, int warn) { xbt_swag_t elem_list = NULL; lmm_element_t elem = NULL; @@ -48,7 +47,6 @@ static int __check_kkt(xbt_swag_t cnst_list, xbt_swag_t var_list, int warn) double tmp; - //verify the KKT property for each link xbt_swag_foreach(cnst, cnst_list) { tmp = 0; elem_list = &(cnst->element_set); @@ -66,21 +64,14 @@ static int __check_kkt(xbt_swag_t cnst_list, xbt_swag_t var_list, int warn) cnst, cnst->bound, tmp); return 0; } - DEBUG3("Checking KKT for constraint (%p): sat = %f, lambda = %f ", + DEBUG3("Checking feasability for constraint (%p): sat = %f, lambda = %f ", cnst, tmp - cnst->bound, cnst->lambda); - -/* if(!((fabs(tmp - cnst->bound)lambda>=MAXMIN_PRECISION) || */ -/* (fabs(tmp - cnst->bound)>=MAXMIN_PRECISION && cnst->lambdabound < 0 || var->weight <= 0) continue; - DEBUG3("Checking KKT for variable (%p): sat = %f mu = %f", var, + DEBUG3("Checking feasability for variable (%p): sat = %f mu = %f", var, var->value - var->bound, var->mu); if (double_positive(var->value - var->bound)) { @@ -90,12 +81,6 @@ static int __check_kkt(xbt_swag_t cnst_list, xbt_swag_t var_list, int warn) var, var->bound, var->value); return 0; } - -/* if(!((fabs(var->value - var->bound)mu>=MAXMIN_PRECISION) || */ -/* (fabs(var->value - var->bound)>=MAXMIN_PRECISION && var->mu epsilon_min_error && iteration < max_iterations) { + while (overall_modification > epsilon_min_error && iteration < max_iterations) { int dual_updated=0; iteration++; @@ -213,7 +198,7 @@ void lagrange_solve(lmm_system_t sys) * the values of \lambda and \mu. */ DEBUG0("-------------- Check convergence ----------"); - overall_error = 0; + overall_modification = 0; xbt_swag_foreach(var, var_list) { if (var->weight <= 0) var->value = 0.0; @@ -231,20 +216,19 @@ void lagrange_solve(lmm_system_t sys) //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))) { - overall_error = (fabs(var->value - tmp)); + if (overall_modification < (fabs(var->value - tmp)/tmp)) { + overall_modification = (fabs(var->value - tmp)/tmp); } var->value = tmp; - DEBUG3("New value of var (%p) = %e, overall_error = %e", var, - var->value, overall_error); + DEBUG3("New value of var (%p) = %e, overall_modification = %e", var, + var->value, overall_modification); } } - if (!__check_kkt(cnst_list, var_list, 0)) - overall_error = 1.0; - DEBUG2("Iteration %d: Overall_error : %f", iteration, overall_error); + if (!__check_feasible(cnst_list, var_list, 0)) + overall_modification = 1.0; + DEBUG2("Iteration %d: overall_modification : %f", iteration, overall_modification); if(!dual_updated) { WARN1("Could not improve the convergence at iteration %d. Drop it!",iteration); break; @@ -252,13 +236,13 @@ void lagrange_solve(lmm_system_t sys) } - __check_kkt(cnst_list, var_list, 1); + __check_feasible(cnst_list, var_list, 1); - if (overall_error <= epsilon_min_error) { + if (overall_modification <= epsilon_min_error) { 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); } @@ -312,7 +296,7 @@ double dichotomy(double init, double diff(double, void *), void *var_cnst, while (overall_error > min_error) { CDEBUG4(surf_lagrange_dichotomy, - "min, max = %1.20f, %1.20f || diffmin, diffmax %1.20f, %1.20f", min, max, + "[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) { @@ -341,7 +325,9 @@ double dichotomy(double init, double diff(double, void *), void *var_cnst, CDEBUG1(surf_lagrange_dichotomy, "Trying (max+min)/2 : %1.20f",middle); if((min==middle) || (max==middle)) { - WARN0("Cannot improve the convergence!"); + CWARN2(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.", + min, max-min); break; } middle_diff = diff(middle, var_cnst); @@ -350,10 +336,12 @@ double dichotomy(double init, double diff(double, void *), void *var_cnst, CDEBUG0(surf_lagrange_dichotomy, "Increasing min"); min = middle; min_diff = middle_diff; + overall_error = max-middle_diff; } else if (middle_diff > 0) { CDEBUG0(surf_lagrange_dichotomy, "Decreasing max"); max = middle; max_diff = middle_diff; + overall_error = max-middle_diff; } else { overall_error = 0; } @@ -453,9 +441,6 @@ double partial_diff_lambda(double lambda, void *param_cnst) lambda_partial += cnst->bound; - -/* CDEBUG1(surf_lagrange_dichotomy, "returning = %1.20f", lambda_partial); */ - XBT_OUT; return lambda_partial; } @@ -466,17 +451,28 @@ double diff_aux(lmm_variable_t var, double x) 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; } +/** \brief Attribute the value bound to var->bound. + * + * \param func_fpi inverse of the partial differential of f (f prime inverse, (f')^{-1}) + * + * 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_fpi) (lmm_variable_t var, double x)) +{ + func_fpi_def = func_fpi; +} + /**************** Vegas and Reno functions *************************/ /* @@ -485,60 +481,20 @@ double diff_aux(lmm_variable_t var, double x) */ /* - * For Vegas f: $\alpha_f d_f \log\left(x_f\right)$ + * For Vegas: $f(x) = \alpha D_f\ln(x)$ + * Therefore: $fpi(x) = \frac{\alpha D_f}{x}$ */ #define VEGAS_SCALING 1000.0 -double func_vegas_f(lmm_variable_t var, double x){ - return VEGAS_SCALING*var->df * log(x); -} - -/* - * For Vegas fp: $\frac{\alpha D_f}{x}$ - */ -double func_vegas_fp(lmm_variable_t var, double x){ - //avoid a disaster value - c'est du bricolage mais ca marche -/* if(x == 0) x = 10e-8; */ - return VEGAS_SCALING*var->df/x; -} - -/* - * For Vegas fpi: $\frac{\alpha D_f}{x}$ - */ double func_vegas_fpi(lmm_variable_t var, double x){ - //avoid a disaster value - c'est du bricolage mais ca marche -/* if(x == 0) x = 10e-8; */ + xbt_assert0(x>0.0,"Don't call me with stupid values!"); return VEGAS_SCALING*var->df/x; } /* - * For Vegas fpip: $-\frac{\alpha D_f}{x^2}$ - */ -double func_vegas_fpip(lmm_variable_t var, double x){ - //avoid a disaster value - c'est du bricolage mais ca marche -/* if(x == 0) x = 10e-8; */ - return -( VEGAS_SCALING*var->df/(x*x) ) ; -} - - -/* - * For Reno f: $\frac{\sqrt{\frac{3}{2}}}{D_f} \arctan\left(\sqrt{\frac{3}{2}}x_f D_f\right)$ - */ -double func_reno_f(lmm_variable_t var, double x){ - xbt_assert0(var->df>0.0,"Don't call me with stupid values!"); - // \sqrt{3/2} = 0.8164965808 - return (0.8164965808 / var->df) * atan( (0.8164965808 / var->df)*x ); -} - -/* - * For Reno fp: $\frac{3}{3 {D_f}^2 x^2 + 2}$ - */ -double func_reno_fp(lmm_variable_t var, double x){ - return 3 / (3*var->df*var->df*x*x + 2); -} - -/* - * For Reno fpi: $\sqrt{\frac{1}{{D_f}^2 x} - \frac{2}{3{D_f}^2}}$ + * For Reno: $f(x) = \frac{\sqrt{3/2}}{D_f} atan(\sqrt{3/2}D_f x)$ + * Therefore: $fpi(x) = \sqrt{\frac{1}{{D_f}^2 x} - \frac{2}{3{D_f}^2}}$ */ +#define RENO_SCALING 1000.0 double func_reno_fpi(lmm_variable_t var, double x){ double res_fpi; @@ -547,23 +503,7 @@ double func_reno_fpi(lmm_variable_t var, double x){ 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); +/* xbt_assert0(res_fpi>0.0,"Don't call me with stupid values!"); */ + return sqrt(RENO_SCALING*res_fpi); } -/* - * For Reno fpip: $-\frac{1}{2 {D_f}^2 x^2\sqrt{\frac{1}{{D_f}^2 x} - \frac{2}{3{D_f}^2}}}$ - */ -double func_reno_fpip(lmm_variable_t var, double x){ - double res_fpip; - double critical_test; - - 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_fpip = 1/(var->df*var->df*x) - 2/(3*var->df*var->df); - xbt_assert0(res_fpip>0.0,"Don't call me with stupid values!"); - critical_test = (2*var->df*var->df*x*x*sqrt(res_fpip)); - - return -(1.0/critical_test); -}