faster because of cache effects. So there is no need to clutter the
code to allow the user to go for the unefficient mode.
+Network models:
+ - Remove the lagrange-based models (Reno/Reno2/Vegas). The regular
+ models proved to be more accurate than these old experiments.
+
Fixed bugs (FG=FramaGit; GH=GitHub):
- FG#1: Broken link in error messages
- FG#2: missing installation documentation
poorly modeled. This model is described in `A Network Model for
Simulation of Grid Application
<https://hal.inria.fr/inria-00071989/document>`_.
- - **Reno/Reno2/Vegas:** Models from Steven H. Low using lagrange_solve instead of
- lmm_solve (experts only; check the code for more info).
- **NS3** (only available if you compiled SimGrid accordingly):
Use the packet-level network
simulators as network models (see :ref:`pls_ns3`).
> [145.639041] (1:pinger@Tremblay) Pong time (bandwidth bound): 145.638
> [145.639041] (0:maestro@) Total simulation time: 145.639
-p Testing the surf network Reno fairness model using lagrangian approach
-
-$ ${bindir:=.}/s4u-app-pingpong ${platfdir}/small_platform.xml "--cfg=host/model:compound cpu/model:Cas01 network/model:Reno" --log=surf_lagrange.thres=critical "--log=root.fmt:[%10.6r]%e(%i:%P@%h)%e%m%n"
-> [ 0.000000] (0:maestro@) Configuration change: Set 'host/model' to 'compound'
-> [ 0.000000] (0:maestro@) Configuration change: Set 'cpu/model' to 'Cas01'
-> [ 0.000000] (0:maestro@) Configuration change: Set 'network/model' to 'Reno'
-> [ 0.000000] (1:pinger@Tremblay) Ping from mailbox Mailbox 1 to mailbox Mailbox 2
-> [ 0.000000] (2:ponger@Jupiter) Pong from mailbox Mailbox 2 to mailbox Mailbox 1
-> [ 0.019014] (2:ponger@Jupiter) Task received : small communication (latency bound)
-> [ 0.019014] (2:ponger@Jupiter) Ping time (latency bound) 0.019014
-> [ 0.019014] (2:ponger@Jupiter) task_bw->data = 0.019
-> [150.178356] (1:pinger@Tremblay) Task received : large communication (bandwidth bound)
-> [150.178356] (1:pinger@Tremblay) Pong time (bandwidth bound): 150.159
-> [150.178356] (0:maestro@) Total simulation time: 150.178
-
-p Testing the surf network Reno2 fairness model using lagrangian approach
-
-$ ${bindir:=.}/s4u-app-pingpong ${platfdir}/small_platform.xml "--cfg=host/model:compound cpu/model:Cas01 network/model:Reno2" --log=surf_lagrange.thres=critical "--log=root.fmt:[%10.6r]%e(%i:%P@%h)%e%m%n"
-> [ 0.000000] (0:maestro@) Configuration change: Set 'host/model' to 'compound'
-> [ 0.000000] (0:maestro@) Configuration change: Set 'cpu/model' to 'Cas01'
-> [ 0.000000] (0:maestro@) Configuration change: Set 'network/model' to 'Reno2'
-> [ 0.000000] (1:pinger@Tremblay) Ping from mailbox Mailbox 1 to mailbox Mailbox 2
-> [ 0.000000] (2:ponger@Jupiter) Pong from mailbox Mailbox 2 to mailbox Mailbox 1
-> [ 0.019014] (2:ponger@Jupiter) Task received : small communication (latency bound)
-> [ 0.019014] (2:ponger@Jupiter) Ping time (latency bound) 0.019014
-> [ 0.019014] (2:ponger@Jupiter) task_bw->data = 0.019
-> [150.178356] (1:pinger@Tremblay) Task received : large communication (bandwidth bound)
-> [150.178356] (1:pinger@Tremblay) Pong time (bandwidth bound): 150.159
-> [150.178356] (0:maestro@) Total simulation time: 150.178
-
-p Testing the surf network Vegas fairness model using lagrangian approach
-
-$ ${bindir:=.}/s4u-app-pingpong ${platfdir}/small_platform.xml "--cfg=host/model:compound cpu/model:Cas01 network/model:Vegas" "--log=root.fmt:[%10.6r]%e(%i:%P@%h)%e%m%n"
-> [ 0.000000] (0:maestro@) Configuration change: Set 'host/model' to 'compound'
-> [ 0.000000] (0:maestro@) Configuration change: Set 'cpu/model' to 'Cas01'
-> [ 0.000000] (0:maestro@) Configuration change: Set 'network/model' to 'Vegas'
-> [ 0.000000] (1:pinger@Tremblay) Ping from mailbox Mailbox 1 to mailbox Mailbox 2
-> [ 0.000000] (2:ponger@Jupiter) Pong from mailbox Mailbox 2 to mailbox Mailbox 1
-> [ 0.019014] (2:ponger@Jupiter) Task received : small communication (latency bound)
-> [ 0.019014] (2:ponger@Jupiter) Ping time (latency bound) 0.019014
-> [ 0.019014] (2:ponger@Jupiter) task_bw->data = 0.019
-> [150.178356] (1:pinger@Tremblay) Task received : large communication (bandwidth bound)
-> [150.178356] (1:pinger@Tremblay) Pong time (bandwidth bound): 150.159
-> [150.178356] (0:maestro@) Total simulation time: 150.178
-
p Testing the surf network constant model
$ ${bindir:=.}/s4u-app-pingpong ${platfdir}/small_platform_constant.xml "--cfg=host/model:compound cpu/model:Cas01 network/model:Constant" "--log=root.fmt:[%10.6r]%e(%i:%P@%h)%e%m%n"
+++ /dev/null
-/* 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. */
-
-/*
- * Modeling the proportional fairness using the Lagrangian Optimization Approach. For a detailed description see:
- * "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"
-
-#include <algorithm>
-#include <cmath>
-#include <cstdlib>
-
-XBT_LOG_NEW_DEFAULT_SUBCATEGORY(surf_lagrange, surf, "Logging specific to SURF (lagrange)");
-XBT_LOG_NEW_SUBCATEGORY(surf_lagrange_dichotomy, surf_lagrange, "Logging specific to SURF (lagrange dichotomy)");
-
-static constexpr double VEGAS_SCALING = 1000.0;
-static constexpr double RENO_SCALING = 1.0;
-static constexpr double RENO2_SCALING = 1.0;
-
-namespace simgrid {
-namespace kernel {
-namespace lmm {
-
-System* make_new_lagrange_system(bool selective_update)
-{
- return new Lagrange(selective_update);
-}
-
-bool Lagrange::check_feasible(bool warn)
-{
- for (Constraint const& cnst : active_constraint_set) {
- double tmp = 0;
- for (Element const& elem : cnst.enabled_element_set_) {
- Variable* var = elem.variable;
- xbt_assert(var->sharing_weight_ > 0);
- tmp += var->value_;
- }
-
- if (double_positive(tmp - cnst.bound_, sg_maxmin_precision)) {
- if (warn)
- XBT_WARN("The link (%p) is over-used. Expected less than %f and got %f", &cnst, cnst.bound_, tmp);
- return false;
- }
- XBT_DEBUG("Checking feasability for constraint (%p): sat = %f, lambda = %f ", &cnst, tmp - cnst.bound_,
- cnst.lambda_);
- }
-
- for (Variable const& var : variable_set) {
- if (not var.sharing_weight_)
- break;
- if (var.bound_ < 0)
- continue;
- XBT_DEBUG("Checking feasability for variable (%p): sat = %f mu = %f", &var, var.value_ - var.bound_, var.mu_);
-
- if (double_positive(var.value_ - var.bound_, sg_maxmin_precision)) {
- if (warn)
- XBT_WARN("The variable (%p) is too large. Expected less than %f and got %f", &var, var.bound_, var.value_);
- return false;
- }
- }
- return true;
-}
-
-double Lagrange::new_value(const Variable& var)
-{
- double tmp = 0;
-
- for (Element const& elem : var.cnsts_) {
- tmp += elem.constraint->lambda_;
- }
- if (var.bound_ > 0)
- tmp += var.mu_;
- XBT_DEBUG("\t Working on var (%p). cost = %e; Weight = %e", &var, tmp, var.sharing_weight_);
- // uses the partial differential inverse function
- return func_fpi(var, tmp);
-}
-
-double Lagrange::new_mu(const Variable& var)
-{
- double mu_i = 0.0;
- double sigma_i = 0.0;
-
- for (Element const& elem : var.cnsts_) {
- sigma_i += elem.constraint->lambda_;
- }
- mu_i = func_fp(var, var.bound_) - sigma_i;
- if (mu_i < 0.0)
- return 0.0;
- return mu_i;
-}
-
-double Lagrange::dual_objective()
-{
- double obj = 0.0;
-
- for (Variable const& var : variable_set) {
- double sigma_i = 0.0;
-
- if (not var.sharing_weight_)
- break;
-
- for (Element const& elem : var.cnsts_)
- sigma_i += elem.constraint->lambda_;
-
- if (var.bound_ > 0)
- sigma_i += var.mu_;
-
- XBT_DEBUG("var %p : sigma_i = %1.20f", &var, sigma_i);
-
- obj += func_f(var, func_fpi(var, sigma_i)) - sigma_i * func_fpi(var, sigma_i);
-
- if (var.bound_ > 0)
- obj += var.mu_ * var.bound_;
- }
-
- for (Constraint const& cnst : active_constraint_set)
- obj += cnst.lambda_ * cnst.bound_;
-
- return obj;
-}
-
-// solves the proportional fairness using a Lagrangian optimization with dichotomy step
-void Lagrange::lagrange_solve()
-{
- /* Lagrange Variables. */
- int max_iterations = 100;
- double epsilon_min_error = 0.00001; /* this is the precision on the objective function so it's none of the
- configurable values and this value is the legacy one */
- double dichotomy_min_error = 1e-14;
- double overall_modification = 1;
-
- XBT_DEBUG("Iterative method configuration snapshot =====>");
- XBT_DEBUG("#### Maximum number of iterations : %d", max_iterations);
- XBT_DEBUG("#### Minimum error tolerated : %e", epsilon_min_error);
- XBT_DEBUG("#### Minimum error tolerated (dichotomy) : %e", dichotomy_min_error);
-
- if (XBT_LOG_ISENABLED(surf_lagrange, xbt_log_priority_debug)) {
- print();
- }
-
- if (not modified_)
- return;
-
- /* Initialize lambda. */
- 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 active variables. Initialize mu.
- */
- for (Variable& var : variable_set) {
- if (not var.sharing_weight_)
- var.value_ = 0.0;
- else {
- if (var.bound_ < 0.0) {
- XBT_DEBUG("#### NOTE var(%p) is a boundless variable", &var);
- var.mu_ = -1.0;
- } else {
- var.mu_ = 1.0;
- var.new_mu_ = 2.0;
- }
- var.value_ = new_value(var);
- XBT_DEBUG("#### var(%p) ->weight : %e", &var, var.sharing_weight_);
- XBT_DEBUG("#### var(%p) ->mu : %e", &var, var.mu_);
- XBT_DEBUG("#### var(%p) ->weight: %e", &var, var.sharing_weight_);
- XBT_DEBUG("#### var(%p) ->bound: %e", &var, var.bound_);
- auto weighted = std::find_if(begin(var.cnsts_), end(var.cnsts_),
- [](Element const& x) { return x.consumption_weight != 0.0; });
- if (weighted == end(var.cnsts_))
- var.value_ = 1.0;
- }
- }
-
- /* Compute dual objective. */
- double obj = dual_objective();
-
- /* While doesn't reach a minimum error or a number maximum of iterations. */
- int iteration = 0;
- while (overall_modification > epsilon_min_error && iteration < max_iterations) {
- iteration++;
- XBT_DEBUG("************** ITERATION %d **************", iteration);
- XBT_DEBUG("-------------- Gradient Descent ----------");
-
- /* Improve the value of mu_i */
- 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);
- XBT_DEBUG("Updating mu : var->mu (%p) : %1.20f -> %1.20f", &var, var.mu_, var.new_mu_);
- var.mu_ = var.new_mu_;
-
- double new_obj = dual_objective();
- XBT_DEBUG("Improvement for Objective (%g -> %g) : %g", obj, new_obj, obj - new_obj);
- xbt_assert(obj - new_obj >= -epsilon_min_error, "Our gradient sucks! (%1.20f)", obj - new_obj);
- obj = new_obj;
- }
- }
-
- /* Improve the value of lambda_i */
- for (Constraint& cnst : active_constraint_set) {
- XBT_DEBUG("Working on cnst (%p)", &cnst);
- cnst.new_lambda_ = dichotomy(cnst.lambda_, cnst, dichotomy_min_error);
- XBT_DEBUG("Updating lambda : cnst->lambda (%p) : %1.20f -> %1.20f", &cnst, cnst.lambda_, cnst.new_lambda_);
- cnst.lambda_ = cnst.new_lambda_;
-
- double new_obj = dual_objective();
- XBT_DEBUG("Improvement for Objective (%g -> %g) : %g", obj, new_obj, obj - new_obj);
- xbt_assert(obj - new_obj >= -epsilon_min_error, "Our gradient sucks! (%1.20f)", obj - new_obj);
- obj = new_obj;
- }
-
- /* 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 : variable_set) {
- if (var.sharing_weight_ <= 0)
- var.value_ = 0.0;
- else {
- double tmp = new_value(var);
-
- overall_modification = std::max(overall_modification, fabs(var.value_ - tmp));
-
- var.value_ = tmp;
- XBT_DEBUG("New value of var (%p) = %e, overall_modification = %e", &var, var.value_, overall_modification);
- }
- }
-
- XBT_DEBUG("-------------- Check feasability ----------");
- if (not check_feasible(false))
- overall_modification = 1.0;
- XBT_DEBUG("Iteration %d: overall_modification : %f", iteration, overall_modification);
- }
-
- check_feasible(true);
-
- if (overall_modification <= epsilon_min_error) {
- XBT_DEBUG("The method converges in %d iterations.", iteration);
- }
- if (iteration >= max_iterations) {
- XBT_DEBUG("Method reach %d iterations, which is the maximum number of iterations allowed.", iteration);
- }
-
- if (XBT_LOG_ISENABLED(surf_lagrange, xbt_log_priority_debug)) {
- print();
- }
-}
-
-/*
- * 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.
- *
- * @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
- *
- * @return a double corresponding to the result of the dichotomy process
- */
-double Lagrange::dichotomy(double init, const Constraint& cnst, double min_error)
-{
- double min = init;
- double max = init;
- double overall_error;
- double middle;
- double middle_diff;
- double diff_0 = 0.0;
-
- XBT_IN();
-
- if (fabs(init) < 1e-20) {
- min = 0.5;
- max = 0.5;
- }
-
- overall_error = 1;
-
- diff_0 = partial_diff_lambda(1e-16, cnst);
- if (diff_0 >= 0) {
- XBT_CDEBUG(surf_lagrange_dichotomy, "returning 0.0 (diff = %e)", diff_0);
- XBT_OUT();
- return 0.0;
- }
-
- double min_diff = partial_diff_lambda(min, cnst);
- double max_diff = partial_diff_lambda(max, cnst);
-
- while (overall_error > min_error) {
- XBT_CDEBUG(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) {
- XBT_CDEBUG(surf_lagrange_dichotomy, "Decreasing min");
- min = min / 2.0;
- min_diff = partial_diff_lambda(min, cnst);
- } else {
- XBT_CDEBUG(surf_lagrange_dichotomy, "Decreasing max");
- max = min;
- max_diff = min_diff;
- }
- } else if (min_diff < 0 && max_diff < 0) {
- if (min == max) {
- XBT_CDEBUG(surf_lagrange_dichotomy, "Increasing max");
- max = max * 2.0;
- max_diff = partial_diff_lambda(max, cnst);
- } else {
- XBT_CDEBUG(surf_lagrange_dichotomy, "Increasing min");
- min = max;
- min_diff = max_diff;
- }
- } else if (min_diff < 0 && max_diff > 0) {
- middle = (max + min) / 2.0;
- XBT_CDEBUG(surf_lagrange_dichotomy, "Trying (max+min)/2 : %1.20f", middle);
-
- if ((fabs(min - middle) < 1e-20) || (fabs(max - middle) < 1e-20)) {
- XBT_CWARN(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 = partial_diff_lambda(middle, cnst);
-
- if (middle_diff < 0) {
- XBT_CDEBUG(surf_lagrange_dichotomy, "Increasing min");
- min = middle;
- overall_error = max_diff - middle_diff;
- min_diff = middle_diff;
- } else if (middle_diff > 0) {
- XBT_CDEBUG(surf_lagrange_dichotomy, "Decreasing max");
- max = middle;
- overall_error = max_diff - middle_diff;
- max_diff = middle_diff;
- } else {
- overall_error = 0;
- }
- } else if (fabs(min_diff) < 1e-20) {
- max = min;
- overall_error = 0;
- } else if (fabs(max_diff) < 1e-20) {
- min = max;
- overall_error = 0;
- } else if (min_diff > 0 && max_diff < 0) {
- XBT_CWARN(surf_lagrange_dichotomy, "The impossible happened, partial_diff(min) > 0 && partial_diff(max) < 0");
- xbt_abort();
- } else {
- XBT_CWARN(surf_lagrange_dichotomy,
- "diffmin (%1.20f) or diffmax (%1.20f) are something I don't know, taking no action.", min_diff,
- max_diff);
- xbt_abort();
- }
- }
-
- XBT_CDEBUG(surf_lagrange_dichotomy, "returning %e", (min + max) / 2.0);
- XBT_OUT();
- return ((min + max) / 2.0);
-}
-
-double Lagrange::partial_diff_lambda(double lambda, const Constraint& cnst)
-{
- double diff = 0.0;
-
- XBT_IN();
-
- XBT_CDEBUG(surf_lagrange_dichotomy, "Computing diff of cnst (%p)", &cnst);
-
- for (Element const& elem : cnst.enabled_element_set_) {
- Variable& var = *elem.variable;
- xbt_assert(var.sharing_weight_ > 0);
- XBT_CDEBUG(surf_lagrange_dichotomy, "Computing sigma_i for var (%p)", &var);
- // Initialize the summation variable
- double sigma_i = 0.0;
-
- // Compute sigma_i
- for (Element const& elem2 : var.cnsts_)
- sigma_i += elem2.constraint->lambda_;
-
- // add mu_i if this flow has a RTT constraint associated
- if (var.bound_ > 0)
- sigma_i += var.mu_;
-
- // replace value of cnst.lambda by the value of parameter lambda
- sigma_i = (sigma_i - cnst.lambda_) + lambda;
-
- diff += -func_fpi(var, sigma_i);
- }
-
- diff += cnst.bound_;
-
- XBT_CDEBUG(surf_lagrange_dichotomy, "d D/d lambda for cnst (%p) at %1.20f = %1.20f", &cnst, lambda, diff);
- XBT_OUT();
- return diff;
-}
-
-/** @brief Attribute the value bound to var->bound.
- *
- * @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 (*f)(const Variable& var, double x),
- double (*fp)(const Variable& var, double x),
- double (*fpi)(const Variable& var, double x))
-{
- func_f = f;
- func_fp = fp;
- func_fpi = fpi;
-}
-
-double (*Lagrange::func_f)(const Variable&, double);
-double (*Lagrange::func_fp)(const Variable&, double);
-double (*Lagrange::func_fpi)(const Variable&, double);
-
-/**************** Vegas and Reno functions *************************/
-/* 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: $fpi(x) = @frac{@alpha D_f}{x}$
- */
-double func_vegas_f(const Variable& var, double x)
-{
- xbt_assert(x > 0.0, "Don't call me with stupid values! (%1.20f)", x);
- return VEGAS_SCALING * var.sharing_weight_ * log(x);
-}
-
-double func_vegas_fp(const Variable& var, double x)
-{
- xbt_assert(x > 0.0, "Don't call me with stupid values! (%1.20f)", x);
- return VEGAS_SCALING * var.sharing_weight_ / x;
-}
-
-double func_vegas_fpi(const Variable& var, double x)
-{
- xbt_assert(x > 0.0, "Don't call me with stupid values! (%1.20f)", x);
- return var.sharing_weight_ / (x / VEGAS_SCALING);
-}
-
-/*
- * 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)
-{
- xbt_assert(var.sharing_weight_ > 0.0, "Don't call me with stupid values!");
-
- return RENO_SCALING * sqrt(3.0 / 2.0) / var.sharing_weight_ * atan(sqrt(3.0 / 2.0) * var.sharing_weight_ * x);
-}
-
-double func_reno_fp(const Variable& var, double x)
-{
- return RENO_SCALING * 3.0 / (3.0 * var.sharing_weight_ * var.sharing_weight_ * x * x + 2.0);
-}
-
-double func_reno_fpi(const Variable& var, double x)
-{
- double res_fpi;
-
- xbt_assert(var.sharing_weight_ > 0.0, "Don't call me with stupid values!");
- xbt_assert(x > 0.0, "Don't call me with stupid values!");
-
- res_fpi = 1.0 / (var.sharing_weight_ * var.sharing_weight_ * (x / RENO_SCALING)) -
- 2.0 / (3.0 * var.sharing_weight_ * var.sharing_weight_);
- if (res_fpi <= 0.0)
- return 0.0;
- 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
- */
-double func_reno2_f(const Variable& var, double x)
-{
- xbt_assert(var.sharing_weight_ > 0.0, "Don't call me with stupid values!");
- return RENO2_SCALING * (1.0 / var.sharing_weight_) *
- log((x * var.sharing_weight_) / (2.0 * x * var.sharing_weight_ + 3.0));
-}
-
-double func_reno2_fp(const Variable& var, double x)
-{
- return RENO2_SCALING * 3.0 / (var.sharing_weight_ * x * (2.0 * var.sharing_weight_ * x + 3.0));
-}
-
-double func_reno2_fpi(const Variable& var, double x)
-{
- xbt_assert(x > 0.0, "Don't call me with stupid values!");
- double tmp = x * var.sharing_weight_ * var.sharing_weight_;
- double 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;
-}
-}
-}
-}
/** @{ @ingroup SURF_lmm */
-/** Default functions associated to the chosen protocol. When using the lagrangian approach. */
-
-XBT_PUBLIC double func_reno_f(const Variable& var, double x);
-XBT_PUBLIC double func_reno_fp(const Variable& var, double x);
-XBT_PUBLIC double func_reno_fpi(const Variable& var, double x);
-
-XBT_PUBLIC double func_reno2_f(const Variable& var, double x);
-XBT_PUBLIC double func_reno2_fp(const Variable& var, double x);
-XBT_PUBLIC double func_reno2_fpi(const Variable& var, double x);
-
-XBT_PUBLIC double func_vegas_f(const Variable& var, double x);
-XBT_PUBLIC double func_vegas_fp(const Variable& var, double x);
-XBT_PUBLIC double func_vegas_fpi(const Variable& var, double x);
-
/**
* @brief LMM element
* Elements can be seen as glue between constraint objects and variable objects.
void bottleneck_solve();
};
-class XBT_PUBLIC Lagrange : public System {
-public:
- explicit Lagrange(bool selective_update) : System(selective_update) {}
- void solve() final { lagrange_solve(); }
-
- static void 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));
-
-private:
- void lagrange_solve();
-
- bool check_feasible(bool warn);
- double dual_objective();
-
- static double (*func_f)(const Variable& var, double x); /* (f) */
- static double (*func_fp)(const Variable& var, double x); /* (f') */
- static double (*func_fpi)(const Variable& var, double x); /* (f')^{-1} */
-
- /*
- * Local prototypes to implement the Lagrangian optimization with optimal step, also called dichotomy.
- */
- // computes the value of the dichotomy using a initial values, init, with a specific variable or constraint
- static double dichotomy(double init, const Constraint& cnst, double min_error);
- // computes the value of the differential of constraint cnst applied to lambda
- static double partial_diff_lambda(double lambda, const Constraint& cnst);
-
- static double new_value(const Variable& var);
- static double new_mu(const Variable& var);
-};
-
XBT_PUBLIC System* make_new_maxmin_system(bool selective_update);
XBT_PUBLIC System* make_new_fair_bottleneck_system(bool selective_update);
-XBT_PUBLIC System* make_new_lagrange_system(bool selective_update);
/** @} */
}
/* 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. */
-#include <algorithm>
-#include <numeric>
-
#include "network_cm02.hpp"
#include "simgrid/s4u/Host.hpp"
#include "simgrid/sg_config.hpp"
#include "src/surf/surf_interface.hpp"
#include "surf/surf.hpp"
+#include <algorithm>
+#include <numeric>
+
XBT_LOG_EXTERNAL_DEFAULT_CATEGORY(surf_network);
double sg_latency_factor = 1.0; /* default value; can be set by model or from command line */
surf_network_model = new simgrid::kernel::resource::NetworkCm02Model();
}
-/***************************************************************************/
-/* The models from Steven H. Low */
-/***************************************************************************/
-/* @article{Low03, */
-/* author={Steven H. Low}, */
-/* title={A Duality Model of {TCP} and Queue Management Algorithms}, */
-/* year={2003}, */
-/* journal={{IEEE/ACM} Transactions on Networking}, */
-/* volume={11}, number={4}, */
-/* } */
-void surf_network_model_init_Reno()
-{
- xbt_assert(surf_network_model == nullptr, "Cannot set the network model twice");
-
- namespace lmm = simgrid::kernel::lmm;
- lmm::Lagrange::set_default_protocol_function(lmm::func_reno_f, lmm::func_reno_fp, lmm::func_reno_fpi);
-
- simgrid::config::set_default<double>("network/latency-factor", 13.01);
- simgrid::config::set_default<double>("network/bandwidth-factor", 0.97);
- simgrid::config::set_default<double>("network/weight-S", 20537);
-
- surf_network_model = new simgrid::kernel::resource::NetworkCm02Model(&simgrid::kernel::lmm::make_new_lagrange_system);
-}
-
-
-void surf_network_model_init_Reno2()
-{
- xbt_assert(surf_network_model == nullptr, "Cannot set the network model twice");
-
- namespace lmm = simgrid::kernel::lmm;
- lmm::Lagrange::set_default_protocol_function(lmm::func_reno2_f, lmm::func_reno2_fp, lmm::func_reno2_fpi);
-
- simgrid::config::set_default<double>("network/latency-factor", 13.01);
- simgrid::config::set_default<double>("network/bandwidth-factor", 0.97);
- simgrid::config::set_default<double>("network/weight-S", 20537);
-
- surf_network_model = new simgrid::kernel::resource::NetworkCm02Model(&simgrid::kernel::lmm::make_new_lagrange_system);
-}
-
-void surf_network_model_init_Vegas()
-{
- xbt_assert(surf_network_model == nullptr, "Cannot set the network model twice");
-
- namespace lmm = simgrid::kernel::lmm;
- lmm::Lagrange::set_default_protocol_function(lmm::func_vegas_f, lmm::func_vegas_fp, lmm::func_vegas_fpi);
-
- simgrid::config::set_default<double>("network/latency-factor", 13.01);
- simgrid::config::set_default<double>("network/bandwidth-factor", 0.97);
- simgrid::config::set_default<double>("network/weight-S", 20537);
-
- surf_network_model = new simgrid::kernel::resource::NetworkCm02Model(&simgrid::kernel::lmm::make_new_lagrange_system);
-}
-
namespace simgrid {
namespace kernel {
namespace resource {
"small messages are thus poorly modeled).",
&surf_network_model_init_CM02},
{"NS3", "Network pseudo-model using the NS3 tcp model instead of an analytic model", &surf_network_model_init_NS3},
- {"Reno",
- "Model from Steven H. Low using lagrange_solve instead of lmm_solve (experts only; check the code for more info).",
- &surf_network_model_init_Reno},
- {"Reno2",
- "Model from Steven H. Low using lagrange_solve instead of lmm_solve (experts only; check the code for more info).",
- &surf_network_model_init_Reno2},
- {"Vegas",
- "Model from Steven H. Low using lagrange_solve instead of lmm_solve (experts only; check the code for more info).",
- &surf_network_model_init_Vegas},
};
#if ! HAVE_SMPI
#endif
XBT_PUBLIC void surf_network_model_init_NS3();
-/** @ingroup SURF_models
- * @brief Initializes the platform with the network model Reno
- *
- * The problem is related to max( sum( arctan(C * Df * xi) ) ).
- *
- * Reference:
- * [LOW03] S. H. Low. A duality model of TCP and queue management algorithms.
- * IEEE/ACM Transaction on Networking, 11(4):525-536, 2003.
- *
- * Call this function only if you plan using surf_host_model_init_compound.
- */
-XBT_PUBLIC void surf_network_model_init_Reno();
-
-/** @ingroup SURF_models
- * @brief Initializes the platform with the network model Reno2
- *
- * The problem is related to max( sum( arctan(C * Df * xi) ) ).
- *
- * Reference:
- * [LOW01] S. H. Low. A duality model of TCP and queue management algorithms.
- * IEEE/ACM Transaction on Networking, 11(4):525-536, 2003.
- *
- * Call this function only if you plan using surf_host_model_init_compound.
- */
-XBT_PUBLIC void surf_network_model_init_Reno2();
-
-/** @ingroup SURF_models
- * @brief Initializes the platform with the network model Vegas
- *
- * This problem is related to max( sum( a * Df * ln(xi) ) ) which is equivalent to the proportional fairness.
- *
- * Reference:
- * [LOW03] S. H. Low. A duality model of TCP and queue management algorithms.
- * IEEE/ACM Transaction on Networking, 11(4):525-536, 2003.
- *
- * Call this function only if you plan using surf_host_model_init_compound.
- */
-XBT_PUBLIC void surf_network_model_init_Vegas();
-
/** @ingroup SURF_models
* @brief Initializes the platform with the current best network and cpu models at hand
*
> [145.639041] (1:pinger@Tremblay) Pong time (bandwidth bound): 145.638
> [145.639041] (0:maestro@) Total simulation time: 145.639
-p Testing the surf network Reno fairness model using lagrangian approach
-
-$ ${bindir:=.}/app-pingpong ${platfdir}/small_platform.xml app-pingpong_d.xml "--cfg=host/model:compound cpu/model:Cas01 network/model:Reno" --log=surf_lagrange.thres=critical "--log=root.fmt:[%10.6r]%e(%i:%P@%h)%e%m%n"
-> [ 0.000000] (0:maestro@) Configuration change: Set 'host/model' to 'compound'
-> [ 0.000000] (0:maestro@) Configuration change: Set 'cpu/model' to 'Cas01'
-> [ 0.000000] (0:maestro@) Configuration change: Set 'network/model' to 'Reno'
-> [ 0.000000] (1:pinger@Tremblay) Ping -> Jupiter
-> [ 0.000000] (2:ponger@Jupiter) Pong -> Tremblay
-> [ 0.019014] (2:ponger@Jupiter) Task received : small communication (latency bound)
-> [ 0.019014] (2:ponger@Jupiter) Ping time (latency bound) 0.019014
-> [ 0.019014] (2:ponger@Jupiter) task_bw->data = 0.019
-> [150.178356] (1:pinger@Tremblay) Task received : large communication (bandwidth bound)
-> [150.178356] (1:pinger@Tremblay) Pong time (bandwidth bound): 150.159
-> [150.178356] (0:maestro@) Total simulation time: 150.178
-
-p Testing the surf network Reno2 fairness model using lagrangian approach
-
-$ ${bindir:=.}/app-pingpong ${platfdir}/small_platform.xml app-pingpong_d.xml "--cfg=host/model:compound cpu/model:Cas01 network/model:Reno2" --log=surf_lagrange.thres=critical "--log=root.fmt:[%10.6r]%e(%i:%P@%h)%e%m%n"
-> [ 0.000000] (0:maestro@) Configuration change: Set 'host/model' to 'compound'
-> [ 0.000000] (0:maestro@) Configuration change: Set 'cpu/model' to 'Cas01'
-> [ 0.000000] (0:maestro@) Configuration change: Set 'network/model' to 'Reno2'
-> [ 0.000000] (1:pinger@Tremblay) Ping -> Jupiter
-> [ 0.000000] (2:ponger@Jupiter) Pong -> Tremblay
-> [ 0.019014] (2:ponger@Jupiter) Task received : small communication (latency bound)
-> [ 0.019014] (2:ponger@Jupiter) Ping time (latency bound) 0.019014
-> [ 0.019014] (2:ponger@Jupiter) task_bw->data = 0.019
-> [150.178356] (1:pinger@Tremblay) Task received : large communication (bandwidth bound)
-> [150.178356] (1:pinger@Tremblay) Pong time (bandwidth bound): 150.159
-> [150.178356] (0:maestro@) Total simulation time: 150.178
-
-p Testing the surf network Vegas fairness model using lagrangian approach
-
-$ ${bindir:=.}/app-pingpong ${platfdir}/small_platform.xml app-pingpong_d.xml "--cfg=host/model:compound cpu/model:Cas01 network/model:Vegas" "--log=root.fmt:[%10.6r]%e(%i:%P@%h)%e%m%n"
-> [ 0.000000] (0:maestro@) Configuration change: Set 'host/model' to 'compound'
-> [ 0.000000] (0:maestro@) Configuration change: Set 'cpu/model' to 'Cas01'
-> [ 0.000000] (0:maestro@) Configuration change: Set 'network/model' to 'Vegas'
-> [ 0.000000] (1:pinger@Tremblay) Ping -> Jupiter
-> [ 0.000000] (2:ponger@Jupiter) Pong -> Tremblay
-> [ 0.019014] (2:ponger@Jupiter) Task received : small communication (latency bound)
-> [ 0.019014] (2:ponger@Jupiter) Ping time (latency bound) 0.019014
-> [ 0.019014] (2:ponger@Jupiter) task_bw->data = 0.019
-> [150.178356] (1:pinger@Tremblay) Task received : large communication (bandwidth bound)
-> [150.178356] (1:pinger@Tremblay) Pong time (bandwidth bound): 150.159
-> [150.178356] (0:maestro@) Total simulation time: 150.178
-
p Testing the surf network constant model
$ ${bindir:=.}/app-pingpong ${platfdir}/small_platform_constant.xml app-pingpong_d.xml "--cfg=host/model:compound cpu/model:Cas01 network/model:Constant" "--log=root.fmt:[%10.6r]%e(%i:%P@%h)%e%m%n"
> [0.000000] [xbt_cfg/INFO] Configuration change: Set 'cpu/optim' to 'TI'
> [0.000000] [xbt_cfg/INFO] Configuration change: Set 'host/model' to 'compound'
> [0.000000] [xbt_cfg/INFO] Configuration change: Set 'maxmin/precision' to '0.000010'
-> [0.000000] [xbt_cfg/INFO] Configuration change: Set 'network/model' to 'Vegas'
> Workstation number: 1, link number: 1
$ ${bindir:=.}/basic-parsing-test ../platforms/properties.xml --cfg=cpu/optim:TI
> [0.000000] [surf_parse/INFO] The custom configuration 'cpu/optim' is already defined by user!
> [0.000000] [xbt_cfg/INFO] Configuration change: Set 'host/model' to 'compound'
> [0.000000] [xbt_cfg/INFO] Configuration change: Set 'maxmin/precision' to '0.000010'
-> [0.000000] [xbt_cfg/INFO] Configuration change: Set 'network/model' to 'Vegas'
> Workstation number: 1, link number: 1
<prop id="maxmin/precision" value="0.000010"/>
<prop id="cpu/optim" value="TI"/>
<prop id="host/model" value="compound"/>
- <prop id="network/model" value="Vegas"/>
<prop id="path" value="~/"/>
</config>
<zone id="AS0" routing="Full">
/* ==l1== L2 ==L3== */
/* ------ */
-enum method_t { MAXMIN, LAGRANGE_RENO, LAGRANGE_VEGAS };
-
-static lmm::System* new_system(method_t method)
+static lmm::System* new_system()
{
- /* selective update would need real actions instead of NULL as a first parameter to the variable constructor */
- switch (method) {
- case MAXMIN:
- return lmm::make_new_maxmin_system(false);
- case LAGRANGE_VEGAS:
- case LAGRANGE_RENO:
- return lmm::make_new_lagrange_system(false);
- default:
- xbt_die("Invalid method");
- }
+ return lmm::make_new_maxmin_system(false);
}
double a_test_1 = 0;
return ((min + max) / 2.0);
}
-static void test1(method_t method)
+static void test1()
{
double a = 1.0;
double b = 10.0;
- if (method == LAGRANGE_VEGAS)
- lmm::Lagrange::set_default_protocol_function(lmm::func_vegas_f, lmm::func_vegas_fp, lmm::func_vegas_fpi);
- else if (method == LAGRANGE_RENO)
- lmm::Lagrange::set_default_protocol_function(lmm::func_reno_f, lmm::func_reno_fp, lmm::func_reno_fpi);
-
- lmm::System* Sys = new_system(method);
+ lmm::System* Sys = new_system();
lmm::Constraint* L1 = Sys->constraint_new(nullptr, a);
lmm::Constraint* L2 = Sys->constraint_new(nullptr, b);
lmm::Constraint* L3 = Sys->constraint_new(nullptr, a);
Sys->expand(L2, R_2, 1.0);
Sys->expand(L3, R_3, 1.0);
- if (method == MAXMIN) {
- Sys->solve();
- } else {
- double x;
- if (method == LAGRANGE_VEGAS) {
- x = 3 * a / 4 - 3 * b / 8 + sqrt(9 * b * b + 4 * a * a - 4 * a * b) / 8;
- /* Computed with mupad and D_f=1.0 */
- if (x > a) {
- x = a;
- }
- if (x < 0) {
- x = 0;
- }
- } else if (method == LAGRANGE_RENO) {
- a_test_1 = a;
- b_test_1 = b;
- x = dichotomy(0, a, 1e-13);
-
- if (x < 0)
- x = 0;
- if (x > a)
- x = a;
- } else {
- xbt_die( "Invalid method");
- }
-
- Sys->solve();
-
- double max_deviation = 0.0;
- max_deviation = std::max(max_deviation, fabs(R_1->get_value() - x));
- max_deviation = std::max(max_deviation, fabs(R_3->get_value() - x));
- max_deviation = std::max(max_deviation, fabs(R_2->get_value() - (b - a + x)));
- max_deviation = std::max(max_deviation, fabs(R_1_2_3->get_value() - (a - x)));
-
- if (max_deviation > 0.00001) { // Legacy value used in lagrange.c
- XBT_WARN("Max Deviation from optimal solution : %g", max_deviation);
- XBT_WARN("Found x = %1.20f", x);
- XBT_WARN("Deviation from optimal solution (R_1 = %g): %1.20f", x, R_1->get_value() - x);
- XBT_WARN("Deviation from optimal solution (R_2 = %g): %1.20f", b - a + x, R_2->get_value() - (b - a + x));
- XBT_WARN("Deviation from optimal solution (R_3 = %g): %1.20f", x, R_3->get_value() - x);
- XBT_WARN("Deviation from optimal solution (R_1_2_3 = %g): %1.20f", a - x, R_1_2_3->get_value() - (a - x));
- }
- }
+ Sys->solve();
PRINT_VAR(R_1_2_3);
PRINT_VAR(R_1);
delete Sys;
}
-static void test2(method_t method)
+static void test2()
{
- if (method == LAGRANGE_VEGAS)
- lmm::Lagrange::set_default_protocol_function(lmm::func_vegas_f, lmm::func_vegas_fp, lmm::func_vegas_fpi);
- if (method == LAGRANGE_RENO)
- lmm::Lagrange::set_default_protocol_function(lmm::func_reno_f, lmm::func_reno_fp, lmm::func_reno_fpi);
-
- lmm::System* Sys = new_system(method);
+ lmm::System* Sys = new_system();
lmm::Constraint* CPU1 = Sys->constraint_new(nullptr, 200.0);
lmm::Constraint* CPU2 = Sys->constraint_new(nullptr, 100.0);
delete Sys;
}
-static void test3(method_t method)
+static void test3()
{
int flows = 11;
int links = 10;
A[13][14] = 1.0;
A[14][15] = 1.0;
- if (method == LAGRANGE_VEGAS)
- lmm::Lagrange::set_default_protocol_function(lmm::func_vegas_f, lmm::func_vegas_fp, lmm::func_vegas_fpi);
- if (method == LAGRANGE_RENO)
- lmm::Lagrange::set_default_protocol_function(lmm::func_reno_f, lmm::func_reno_fp, lmm::func_reno_fpi);
-
- lmm::System* Sys = new_system(method);
+ lmm::System* Sys = new_system();
/* Creates the constraints */
lmm::Constraint** tmp_cnst = new lmm::Constraint*[15];
int main(int argc, char** argv)
{
MSG_init(&argc, argv);
- XBT_INFO("***** Test 1 (Max-Min)");
- test1(MAXMIN);
- XBT_INFO("***** Test 1 (Lagrange - Vegas)");
- test1(LAGRANGE_VEGAS);
- XBT_INFO("***** Test 1 (Lagrange - Reno)");
- test1(LAGRANGE_RENO);
-
- XBT_INFO("***** Test 2 (Max-Min)");
- test2(MAXMIN);
- XBT_INFO("***** Test 2 (Lagrange - Vegas)");
- test2(LAGRANGE_VEGAS);
- XBT_INFO("***** Test 2 (Lagrange - Reno)");
- test2(LAGRANGE_RENO);
-
- XBT_INFO("***** Test 3 (Max-Min)");
- test3(MAXMIN);
- XBT_INFO("***** Test 3 (Lagrange - Vegas)");
- test3(LAGRANGE_VEGAS);
- XBT_INFO("***** Test 3 (Lagrange - Reno)");
- test3(LAGRANGE_RENO);
+ XBT_INFO("***** Test 1");
+ test1();
+
+ XBT_INFO("***** Test 2");
+ test2();
+
+ XBT_INFO("***** Test 3");
+ test3();
return 0;
}
#!/usr/bin/env tesh
$ ${bindir:=.}/lmm_usage
-> [0.000000] [surf_test/INFO] ***** Test 1 (Max-Min)
-> [0.000000] [surf_test/INFO] ***** Test 1 (Lagrange - Vegas)
-> [0.000000] [surf_test/INFO] ***** Test 1 (Lagrange - Reno)
-> [0.000000] [surf_test/INFO] ***** Test 2 (Max-Min)
-> [0.000000] [surf_test/INFO] ***** Test 2 (Lagrange - Vegas)
-> [0.000000] [surf_test/INFO] ***** Test 2 (Lagrange - Reno)
-> [0.000000] [surf_test/INFO] ***** Test 3 (Max-Min)
-> [0.000000] [surf_test/INFO] ***** Test 3 (Lagrange - Vegas)
-> [0.000000] [surf_test/INFO] ***** Test 3 (Lagrange - Reno)
+> [0.000000] [surf_test/INFO] ***** Test 1
+> [0.000000] [surf_test/INFO] ***** Test 2
+> [0.000000] [surf_test/INFO] ***** Test 3
set(SURF_SRC
src/kernel/lmm/fair_bottleneck.cpp
- src/kernel/lmm/lagrange.cpp
src/kernel/lmm/maxmin.hpp
src/kernel/lmm/maxmin.cpp
