X-Git-Url: http://info.iut-bm.univ-fcomte.fr/pub/gitweb/simgrid.git/blobdiff_plain/d0b9afc4d105022cc05b5b13ec06af6479dda020..fc416b3a5a1ebce58eb7a6cabb1895f3d68be5fa:/src/kernel/lmm/lagrange.cpp diff --git a/src/kernel/lmm/lagrange.cpp b/src/kernel/lmm/lagrange.cpp index 37143ad8c3..9df8fb429a 100644 --- a/src/kernel/lmm/lagrange.cpp +++ b/src/kernel/lmm/lagrange.cpp @@ -1,4 +1,4 @@ -/* Copyright (c) 2007-2018. The SimGrid Team. All rights reserved. */ +/* Copyright (c) 2007-2019. 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. */ @@ -8,6 +8,7 @@ * "ssh://username@scm.gforge.inria.fr/svn/memo/people/pvelho/lagrange/ppf.ps". */ #include "src/kernel/lmm/maxmin.hpp" +#include "src/surf/surf_interface.hpp" #include "xbt/log.h" #include "xbt/sysdep.h" @@ -142,22 +143,20 @@ void Lagrange::lagrange_solve() print(); } - if (not modified) + if (not modified_) return; /* Initialize lambda. */ - auto& cnst_list = active_constraint_set; - for (Constraint& cnst : cnst_list) { + for (Constraint& cnst : active_constraint_set) { cnst.lambda = 1.0; cnst.new_lambda = 2.0; XBT_DEBUG("#### cnst(%p)->lambda : %e", &cnst, cnst.lambda); } /* - * Initialize the var_list variable with only the active variables. Initialize mu. + * Initialize the active variables. Initialize mu. */ - auto& var_list = variable_set; - for (Variable& var : var_list) { + for (Variable& var : variable_set) { if (not var.sharing_weight) var.value = 0.0; else { @@ -191,7 +190,7 @@ void Lagrange::lagrange_solve() XBT_DEBUG("-------------- Gradient Descent ----------"); /* Improve the value of mu_i */ - for (Variable& var : var_list) { + for (Variable& var : variable_set) { if (var.sharing_weight && var.bound >= 0) { XBT_DEBUG("Working on var (%p)", &var); var.new_mu = new_mu(var); @@ -206,7 +205,7 @@ void Lagrange::lagrange_solve() } /* Improve the value of lambda_i */ - for (Constraint& cnst : cnst_list) { + for (Constraint& cnst : active_constraint_set) { XBT_DEBUG("Working on cnst (%p)", &cnst); cnst.new_lambda = dichotomy(cnst.lambda, partial_diff_lambda, cnst, dichotomy_min_error); XBT_DEBUG("Updating lambda : cnst->lambda (%p) : %1.20f -> %1.20f", &cnst, cnst.lambda, cnst.new_lambda); @@ -218,10 +217,10 @@ void Lagrange::lagrange_solve() obj = new_obj; } - /* Now computes the values of each variable (\rho) based on the values of \lambda and \mu. */ + /* Now computes the values of each variable (@rho) based on the values of @lambda and @mu. */ XBT_DEBUG("-------------- Check convergence ----------"); overall_modification = 0; - for (Variable& var : var_list) { + for (Variable& var : variable_set) { if (var.sharing_weight <= 0) var.value = 0.0; else { @@ -256,10 +255,10 @@ void Lagrange::lagrange_solve() /* * Returns a double value corresponding to the result of a dichotomy process 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. + * variable/constraint (@mu in the case of a variable or @lambda in case of a constraint) and a initial value init. * - * @param init initial value for \mu or \lambda - * @param diff a function that computes the differential of with respect a \mu or \lambda + * @param init initial value for @mu or @lambda + * @param diff a function that computes the differential of with respect a @mu or @lambda * @param var_cnst a pointer to a variable or constraint * @param min_erro a minimum error tolerated * @@ -402,19 +401,21 @@ double Lagrange::partial_diff_lambda(double lambda, const Constraint& cnst) return diff; } -/** \brief Attribute the value bound to var->bound. +/** @brief Attribute the value bound to var->bound. * - * \param func_fpi inverse of the partial differential of f (f prime inverse, (f')^{-1}) + * @param f function (f) + * @param fp partial differential of f (f prime, (f')) + * @param fpi inverse of the partial differential of f (f prime inverse, (f')^{-1}) * * Set default functions to the ones passed as parameters. */ -void Lagrange::set_default_protocol_function(double (*func_f)(const Variable& var, double x), - double (*func_fp)(const Variable& var, double x), - double (*func_fpi)(const Variable& var, double x)) +void Lagrange::set_default_protocol_function(double (*f)(const Variable& var, double x), + double (*fp)(const Variable& var, double x), + double (*fpi)(const Variable& var, double x)) { - Lagrange::func_f = func_f; - Lagrange::func_fp = func_fp; - Lagrange::func_fpi = func_fpi; + func_f = f; + func_fp = fp; + func_fpi = fpi; } double (*Lagrange::func_f)(const Variable&, double); @@ -425,9 +426,9 @@ double (*Lagrange::func_fpi)(const Variable&, double); /* NOTE for Reno: all functions consider the network coefficient (alpha) equal to 1. */ /* - * For Vegas: $f(x) = \alpha D_f\ln(x)$ - * Therefore: $fp(x) = \frac{\alpha D_f}{x}$ - * Therefore: $fpi(x) = \frac{\alpha D_f}{x}$ + * For Vegas: $f(x) = @alpha D_f@ln(x)$ + * Therefore: $fp(x) = @frac{@alpha D_f}{x}$ + * Therefore: $fpi(x) = @frac{@alpha D_f}{x}$ */ double func_vegas_f(const Variable& var, double x) { @@ -448,9 +449,9 @@ double func_vegas_fpi(const Variable& var, double x) } /* - * For Reno: $f(x) = \frac{\sqrt{3/2}}{D_f} atan(\sqrt{3/2}D_f x)$ - * Therefore: $fp(x) = \frac{3}{3 D_f^2 x^2+2}$ - * Therefore: $fpi(x) = \sqrt{\frac{1}{{D_f}^2 x} - \frac{2}{3{D_f}^2}}$ + * For Reno: $f(x) = @frac{@sqrt{3/2}}{D_f} atan(@sqrt{3/2}D_f x)$ + * Therefore: $fp(x) = @frac{3}{3 D_f^2 x^2+2}$ + * Therefore: $fpi(x) = @sqrt{@frac{1}{{D_f}^2 x} - @frac{2}{3{D_f}^2}}$ */ double func_reno_f(const Variable& var, double x) { @@ -479,7 +480,7 @@ double func_reno_fpi(const Variable& var, double x) } /* Implementing new Reno-2 - * For Reno-2: $f(x) = U_f(x_f) = \frac{{2}{D_f}}*ln(2+x*D_f)$ + * 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 */