[simgrid.git] / src / kernel / lmm / maxmin.hpp

/* Copyright (c) 2004-2017. 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. */

#ifndef SURF_MAXMIN_HPP
#define SURF_MAXMIN_HPP

#include "src/internal_config.h"
#include "src/surf/surf_interface.hpp"
#include "surf/surf.hpp"
#include "xbt/asserts.h"
#include "xbt/mallocator.h"
#include "xbt/misc.h"
#include "xbt/swag.h"
#include <boost/intrusive/list.hpp>
#include <cmath>
#include <limits>
#include <vector>

namespace simgrid {
namespace kernel {
namespace lmm {

/** @addtogroup SURF_lmm
 * @details
 * A linear maxmin solver to resolve inequations systems.
 *
 * Most SimGrid model rely on a "fluid/steady-state" modeling that simulate the sharing of resources between actions at
 * relatively coarse-grain.  Such sharing is generally done by solving a set of linear inequations. Let's take an
 * example and assume we have the variables \f$x_1\f$, \f$x_2\f$, \f$x_3\f$, and \f$x_4\f$ . Let's say that \f$x_1\f$
 * and \f$x_2\f$ correspond to activities running and the same CPU \f$A\f$ whose capacity is \f$C_A\f$. In such a
 * case, we need to enforce:
 *
 *   \f[ x_1 + x_2 \leq C_A \f]
 *
 * Likewise, if \f$x_3\f$ (resp. \f$x_4\f$) corresponds to a network flow \f$F_3\f$ (resp. \f$F_4\f$) that goes through
 * a set of links \f$L_1\f$ and \f$L_2\f$ (resp. \f$L_2\f$ and \f$L_3\f$), then we need to enforce:
 *
 *   \f[ x_3  \leq C_{L_1} \f]
 *   \f[ x_3 + x_4 \leq C_{L_2} \f]
 *   \f[ x_4 \leq C_{L_3} \f]
 *
 * One could set every variable to 0 to make sure the constraints are satisfied but this would obviously not be very
 * realistic. A possible objective is to try to maximize the minimum of the \f$x_i\f$ . This ensures that all the
 * \f$x_i\f$ are positive and "as large as possible".
 *
 * This is called *max-min fairness* and is the most commonly used objective in SimGrid. Another possibility is to
 * maximize \f$\sum_if(x_i)\f$, where \f$f\f$ is a strictly increasing concave function.
 *
 * Constraint:
 *  - bound (set)
 *  - shared (set)
 *  - usage (computed)
 *
 * Variable:
 *  - weight (set)
 *  - bound (set)
 *  - value (computed)
 *
 * Element:
 *  - value (set)
 *
 * A possible system could be:
 * - three variables: `var1`, `var2`, `var3`
 * - two constraints: `cons1`, `cons2`
 * - four elements linking:
 *  - `elem1` linking `var1` and `cons1`
 *  - `elem2` linking `var2` and `cons1`
 *  - `elem3` linking `var2` and `cons2`
 *  - `elem4` linking `var3` and `cons2`
 *
 * And the corresponding inequations will be:
 *
 *     var1.value <= var1.bound
 *     var2.value <= var2.bound
 *     var3.value <= var3.bound
 *     var1.weight * var1.value * elem1.value + var2.weight * var2.value * elem2.value <= cons1.bound
 *     var2.weight * var2.value * elem3.value + var3.weight * var3.value * elem4.value <= cons2.bound
 *
 * where `var1.value`, `var2.value` and `var3.value` are the unknown values.
 *
 * If a constraint is not shared, the sum is replaced by a max.
 * For example, a third non-shared constraint `cons3` and the associated elements `elem5` and `elem6` could write as:
 *
 *     max( var1.weight * var1.value * elem5.value  ,  var3.weight * var3.value * elem6.value ) <= cons3.bound
 *
 * This is usefull for the sharing of resources for various models.
 * For instance, for the network model, each link is associated to a constraint and each communication to a variable.
 *
 * Implementation details
 *
 * For implementation reasons, we are interested in distinguishing variables that actually participate to the
 * computation of constraints, and those who are part of the equations but are stuck to zero.
 * We call enabled variables, those which var.weight is strictly positive. Zero-weight variables are called disabled
 * variables.
 * Unfortunately this concept of enabled/disabled variables intersects with active/inactive variable.
 * Semantically, the intent is similar, but the conditions under which a variable is active is slightly more strict
 * than the conditions for it to be enabled.
 * A variable is active only if its var.value is non-zero (and, by construction, its var.weight is non-zero).
 * In general, variables remain disabled after their creation, which often models an initialization phase (e.g. first
 * packet propagating in the network). Then, it is enabled by the corresponding model. Afterwards, the max-min solver
 * (lmm_solve()) activates it when appropriate. It is possible that the variable is again disabled, e.g. to model the
 * pausing of an action.
 *
 * Concurrency limit and maximum
 *
 * We call concurrency, the number of variables that can be enabled at any time for each constraint.
 * From a model perspective, this "concurrency" often represents the number of actions that actually compete for one
 * constraint.
 * The LMM solver is able to limit the concurrency for each constraint, and to monitor its maximum value.
 *
 * One may want to limit the concurrency of constraints for essentially three reasons:
 *  - Keep LMM system in a size that can be solved (it does not react very well with tens of thousands of variables per
 *    constraint)
 *  - Stay within parameters where the fluid model is accurate enough.
 *  - Model serialization effects
 *
 * The concurrency limit can also be set to a negative value to disable concurrency limit. This can improve performance
 * slightly.
 *
 * Overall, each constraint contains three fields related to concurrency:
 *  - concurrency_limit which is the limit enforced by the solver
 *  - concurrency_current which is the current concurrency
 *  - concurrency_maximum which is the observed maximum concurrency
 *
 * Variables also have one field related to concurrency: concurrency_share.
 * In effect, in some cases, one variable is involved multiple times (i.e. two elements) in a constraint.
 * For example, cross-traffic is modeled using 2 elements per constraint.
 * concurrency_share formally corresponds to the maximum number of elements that associate the variable and any given
 * constraint.
 */

/** @{ @ingroup SURF_lmm */

/**
 * @brief Solve the lmm system
 * @param sys The lmm system to solve
 */
XBT_PUBLIC(void) lmm_solve(lmm_system_t sys);

XBT_PUBLIC(void) lagrange_solve(lmm_system_t sys);
XBT_PUBLIC(void) bottleneck_solve(lmm_system_t sys);

/** Default functions associated to the chosen protocol. When using the lagrangian approach. */

XBT_PUBLIC(void)
lmm_set_default_protocol_function(double (*func_f)(const s_lmm_variable_t& var, double x),
                                  double (*func_fp)(const s_lmm_variable_t& var, double x),
                                  double (*func_fpi)(const s_lmm_variable_t& var, double x));

XBT_PUBLIC(double) func_reno_f(const s_lmm_variable_t& var, double x);
XBT_PUBLIC(double) func_reno_fp(const s_lmm_variable_t& var, double x);
XBT_PUBLIC(double) func_reno_fpi(const s_lmm_variable_t& var, double x);

XBT_PUBLIC(double) func_reno2_f(const s_lmm_variable_t& var, double x);
XBT_PUBLIC(double) func_reno2_fp(const s_lmm_variable_t& var, double x);
XBT_PUBLIC(double) func_reno2_fpi(const s_lmm_variable_t& var, double x);

XBT_PUBLIC(double) func_vegas_f(const s_lmm_variable_t& var, double x);
XBT_PUBLIC(double) func_vegas_fp(const s_lmm_variable_t& var, double x);
XBT_PUBLIC(double) func_vegas_fpi(const s_lmm_variable_t& var, double x);

/**
 * @brief LMM element
 * Elements can be seen as glue between constraint objects and variable objects.
 * Basically, each variable will have a set of elements, one for each constraint where it is involved.
 * Then, it is used to list all variables involved in constraint through constraint's xxx_element_set lists, or
 * vice-versa list all constraints for a given variable.
 */
XBT_PUBLIC_CLASS s_lmm_element_t
{
public:
  int get_concurrency() const;
  void decrease_concurrency();
  void increase_concurrency();

  void make_active();
  void make_inactive();

  /* hookup to constraint */
  s_xbt_swag_hookup_t enabled_element_set_hookup;
  s_xbt_swag_hookup_t disabled_element_set_hookup;
  s_xbt_swag_hookup_t active_element_set_hookup;

  lmm_constraint_t constraint;
  lmm_variable_t variable;

  // consumption_weight: impact of 1 byte or flop of your application onto the resource (in byte or flop)
  //   - if CPU, then probably 1.
  //   - If network, then 1 in forward direction and 0.05 backward for the ACKs
  double consumption_weight;
};

struct s_lmm_constraint_light_t {
  double remaining_over_usage;
  lmm_constraint_t cnst;
};

/**
 * @brief LMM constraint
 * Each constraint contains several partially overlapping logical sets of elements:
 * \li Disabled elements which variable's weight is zero. This variables are not at all processed by LMM, but eventually
 *     the corresponding action will enable it (at least this is the idea).
 * \li Enabled elements which variable's weight is non-zero. They are utilized in some LMM functions.
 * \li Active elements which variable's weight is non-zero (i.e. it is enabled) AND its element value is non-zero.
 *     LMM_solve iterates over active elements during resolution, dynamically making them active or unactive.
 */
XBT_PUBLIC_CLASS s_lmm_constraint_t
{
public:
  s_lmm_constraint_t() = default;
  s_lmm_constraint_t(void* id_value, double bound_value);

  /** @brief Unshare a constraint. */
  void unshare() { sharing_policy = 0; }

  /**
   * @brief Check if a constraint is shared (shared by default)
   * @return 1 if shared, 0 otherwise
   */
  int get_sharing_policy() const { return sharing_policy; }

  /**
   * @brief Get the usage of the constraint after the last lmm solve
   * @return The usage of the constraint
   */
  double get_usage() const;
  int get_variable_amount() const;

  /**
   * @brief Sets the concurrency limit for this constraint
   * @param concurrency_limit The concurrency limit to use for this constraint
   */
  void set_concurrency_limit(int limit)
  {
    xbt_assert(limit < 0 || concurrency_maximum <= limit,
               "New concurrency limit should be larger than observed concurrency maximum. Maybe you want to call"
               " concurrency_maximum_reset() to reset the maximum?");
    concurrency_limit = limit;
  }

  /**
   * @brief Gets the concurrency limit for this constraint
   * @return The concurrency limit used by this constraint
   */
  int get_concurrency_limit() const { return concurrency_limit; }

  /**
   * @brief Reset the concurrency maximum for a given variable (we will update the maximum to reflect constraint
   * evolution).
   */
  void reset_concurrency_maximum() { concurrency_maximum = 0; }

  /**
   * @brief Get the concurrency maximum for a given variable (which reflects constraint evolution).
   * @return the maximum concurrency of the constraint
   */
  int get_concurrency_maximum() const
  {
    xbt_assert(concurrency_limit < 0 || concurrency_maximum <= concurrency_limit,
               "Very bad: maximum observed concurrency is higher than limit. This is a bug of SURF, please report it.");
    return concurrency_maximum;
  }

  int get_concurrency_slack() const
  {
    return concurrency_limit < 0 ? std::numeric_limits<int>::max() : concurrency_limit - concurrency_current;
  }

  /**
   * @brief Get a var associated to a constraint
   * @details Get the first variable of the next variable of elem if elem is not NULL
   * @param elem A element of constraint of the constraint or NULL
   * @return A variable associated to a constraint
   */
  lmm_variable_t get_variable(const_lmm_element_t* elem) const;

  /**
   * @brief Get a var associated to a constraint
   * @details Get the first variable of the next variable of elem if elem is not NULL
   * @param elem A element of constraint of the constraint or NULL
   * @param nextelem A element of constraint of the constraint or NULL, the one after elem
   * @param numelem parameter representing the number of elements to go
   * @return A variable associated to a constraint
   */
  lmm_variable_t get_variable_safe(const_lmm_element_t* elem, const_lmm_element_t* nextelem, int* numelem) const;

  /**
   * @brief Get the data associated to a constraint
   * @return The data associated to the constraint
   */
  void* get_id() const { return id; }

  /* hookup to system */
  boost::intrusive::list_member_hook<> constraint_set_hook;
  boost::intrusive::list_member_hook<> active_constraint_set_hook;
  boost::intrusive::list_member_hook<> modified_constraint_set_hook;
  boost::intrusive::list_member_hook<> saturated_constraint_set_hook;
  s_xbt_swag_t enabled_element_set;  /* a list of lmm_element_t */
  s_xbt_swag_t disabled_element_set; /* a list of lmm_element_t */
  s_xbt_swag_t active_element_set;   /* a list of lmm_element_t */
  double remaining;
  double usage;
  double bound;
  // TODO MARTIN Check maximum value across resources at the end of simulation and give a warning is more than e.g. 500
  int concurrency_current; /* The current concurrency */
  int concurrency_maximum; /* The maximum number of (enabled and disabled) variables associated to the constraint at any
                            * given time (essentially for tracing)*/

  int sharing_policy; /* see @e_surf_link_sharing_policy_t (0: FATPIPE, 1: SHARED, 2: FULLDUPLEX) */
  int id_int;
  double lambda;
  double new_lambda;
  lmm_constraint_light_t cnst_light;

private:
  static int Global_debug_id;
  int concurrency_limit; /* The maximum number of variables that may be enabled at any time (stage variables if
                          * necessary) */
  void* id;
};

/**
 * @brief LMM variable
 *
 * When something prevents us from enabling a variable, we "stage" the weight that we would have like to set, so that as
 * soon as possible we enable the variable with desired weight
 */
XBT_PUBLIC_CLASS s_lmm_variable_t
{
public:
  void initialize(simgrid::surf::Action * id_value, double sharing_weight_value, double bound_value,
                  int number_of_constraints, unsigned visited_value);

  /**
   * @brief Get the value of the variable after the last lmm solve
   * @return The value of the variable
   */
  double get_value() const { return value; }

  /**
   * @brief Get the maximum value of the variable (-1.0 if no maximum value)
   * @return The bound of the variable
   */
  double get_bound() const { return bound; }

  /**
   * @brief Set the concurrent share of the variable
   * @param concurrency_share The new concurrency share
   */
  void set_concurrency_share(short int value) { concurrency_share = value; }

  /**
   * @brief Get the numth constraint associated to the variable
   * @param num The rank of constraint we want to get
   * @return The numth constraint
   */
  lmm_constraint_t get_constraint(unsigned num) const { return num < cnsts.size() ? cnsts[num].constraint : nullptr; }

  /**
   * @brief Get the weigth of the numth constraint associated to the variable
   * @param num The rank of constraint we want to get
   * @return The numth constraint
   */
  double get_constraint_weight(unsigned num) const { return num < cnsts.size() ? cnsts[num].consumption_weight : 0.0; }

  /**
   * @brief Get the number of constraint associated to a variable
   * @return The number of constraint associated to the variable
   */
  int get_number_of_constraint() const { return cnsts.size(); }

  /**
   * @brief Get the data associated to a variable
   * @return The data associated to the variable
   */
  simgrid::surf::Action* get_id() const { return id; }

  /**
   * @brief Get the weight of a variable
   * @return The weight of the variable
   */
  double get_weight() const { return sharing_weight; }

  /** @brief Measure the minimum concurrency slack across all constraints where the given var is involved */
  int get_min_concurrency_slack() const;

  /** @brief Check if a variable can be enabled
   * Make sure to set staged_weight before, if your intent is only to check concurrency
   */
  int can_enable() const { return staged_weight > 0 && get_min_concurrency_slack() >= concurrency_share; }

  /* hookup to system */
  s_xbt_swag_hookup_t variable_set_hookup           = {nullptr, nullptr};
  s_xbt_swag_hookup_t saturated_variable_set_hookup = {nullptr, nullptr};

  std::vector<s_lmm_element_t> cnsts;

  // sharing_weight: variable's impact on the resource during the sharing
  //   if == 0, the variable is not considered by LMM
  //   on CPU, actions with N threads have a sharing of N
  //   on network, the actions with higher latency have a lesser sharing_weight
  double sharing_weight;

  double staged_weight; /* If non-zero, variable is staged for addition as soon as maxconcurrency constraints will be
                         * met */
  double bound;
  double value;
  short int concurrency_share; /* The maximum number of elements that variable will add to a constraint */
  simgrid::surf::Action* id;
  int id_int;
  unsigned visited; /* used by lmm_update_modified_set */
  /* \begin{For Lagrange only} */
  double mu;
  double new_mu;
  double (*func_f)(const s_lmm_variable_t& var, double x);   /* (f)    */
  double (*func_fp)(const s_lmm_variable_t& var, double x);  /* (f')    */
  double (*func_fpi)(const s_lmm_variable_t& var, double x); /* (f')^{-1}    */
  /* \end{For Lagrange only} */

private:
  static int Global_debug_id;
};

inline void s_lmm_element_t::make_active()
{
  xbt_swag_insert_at_head(this, &constraint->active_element_set);
}
inline void s_lmm_element_t::make_inactive()
{
  xbt_swag_remove(this, &constraint->active_element_set);
}

/**
 * @brief LMM system
 */
XBT_PUBLIC_CLASS s_lmm_system_t
{
public:
  /**
   * @brief Create a new Linear MaxMim system
   * @param selective_update whether we should do lazy updates
   */
  explicit s_lmm_system_t(bool selective_update);
  /** @brief Free an existing Linear MaxMin system */
  ~s_lmm_system_t();

  /**
   * @brief Create a new Linear MaxMin constraint
   * @param id Data associated to the constraint (e.g.: a network link)
   * @param bound_value The bound value of the constraint
   */
  lmm_constraint_t constraint_new(void* id, double bound_value);

  /**
   * @brief Create a new Linear MaxMin variable
   * @param id Data associated to the variable (e.g.: a network communication)
   * @param weight_value The weight of the variable (0.0 if not used)
   * @param bound The maximum value of the variable (-1.0 if no maximum value)
   * @param number_of_constraints The maximum number of constraint to associate to the variable
   */
  lmm_variable_t variable_new(simgrid::surf::Action * id, double weight_value, double bound, int number_of_constraints);

  /**
   * @brief Free a variable
   * @param var The variable to free
   */
  void variable_free(lmm_variable_t var);

  /**
   * @brief Associate a variable to a constraint with a coefficient
   * @param cnst A constraint
   * @param var A variable
   * @param value The coefficient associated to the variable in the constraint
   */
  void expand(lmm_constraint_t cnst, lmm_variable_t var, double value);

  /**
   * @brief Add value to the coefficient between a constraint and a variable or create one
   * @param cnst A constraint
   * @param var A variable
   * @param value The value to add to the coefficient associated to the variable in the constraint
   */
  void expand_add(lmm_constraint_t cnst, lmm_variable_t var, double value);

  /**
   * @brief Update the bound of a variable
   * @param var A constraint
   * @param bound The new bound
   */
  void update_variable_bound(lmm_variable_t var, double bound);

  /**
   * @brief Update the weight of a variable
   * @param var A variable
   * @param weight The new weight of the variable
   */
  void update_variable_weight(lmm_variable_t var, double weight);

  /**
   * @brief Update a constraint bound
   * @param cnst A constraint
   * @param bound The new bound of the consrtaint
   */
  void update_constraint_bound(lmm_constraint_t cnst, double bound);

  /**
   * @brief [brief description]
   * @param cnst A constraint
   * @return [description]
   */
  int constraint_used(lmm_constraint_t cnst) { return cnst->active_constraint_set_hook.is_linked(); }

  /** @brief Print the lmm system */
  void print() const;

  /** @brief Solve the lmm system */
  void solve();

private:
  static void* variable_mallocator_new_f();
  static void variable_mallocator_free_f(void* var);

  void var_free(lmm_variable_t var);
  void cnst_free(lmm_constraint_t cnst);
  lmm_variable_t extract_variable() { return static_cast<lmm_variable_t>(xbt_swag_extract(&variable_set)); }
  lmm_constraint_t extract_constraint()
  {
    if (constraint_set.empty())
      return nullptr;
    lmm_constraint_t res = &constraint_set.front();
    constraint_set.pop_front();
    return res;
  }
  void insert_constraint(lmm_constraint_t cnst) { constraint_set.push_back(*cnst); }
  void remove_variable(lmm_variable_t var)
  {
    xbt_swag_remove(var, &variable_set);
    xbt_swag_remove(var, &saturated_variable_set);
  }
  void make_constraint_active(lmm_constraint_t cnst)
  {
    if (not cnst->active_constraint_set_hook.is_linked())
      active_constraint_set.push_back(*cnst);
  }
  void make_constraint_inactive(lmm_constraint_t cnst)
  {
    if (cnst->active_constraint_set_hook.is_linked())
      active_constraint_set.erase(active_constraint_set.iterator_to(*cnst));
    if (cnst->modified_constraint_set_hook.is_linked())
      modified_constraint_set.erase(modified_constraint_set.iterator_to(*cnst));
  }

  void enable_var(lmm_variable_t var);
  void disable_var(lmm_variable_t var);
  void on_disabled_var(lmm_constraint_t cnstr);

  /**
   * @brief Update the value of element linking the constraint and the variable
   * @param cnst A constraint
   * @param var A variable
   * @param value The new value
   */
  void update(lmm_constraint_t cnst, lmm_variable_t var, double value);

  void update_modified_set(lmm_constraint_t cnst);
  void update_modified_set_rec(lmm_constraint_t cnst);

  /** @brief Remove all constraints of the modified_constraint_set. */
  void remove_all_modified_set();
  void check_concurrency() const;

  template <class CnstList> void solve(CnstList& cnst_list);
public:
  bool modified;
  s_xbt_swag_t variable_set;             /* a list of lmm_variable_t */
  boost::intrusive::list<s_lmm_constraint_t,
                         boost::intrusive::member_hook<s_lmm_constraint_t, boost::intrusive::list_member_hook<>,
                                                       &s_lmm_constraint_t::active_constraint_set_hook>>
      active_constraint_set;
  s_xbt_swag_t saturated_variable_set;   /* a list of lmm_variable_t */
  boost::intrusive::list<s_lmm_constraint_t,
                         boost::intrusive::member_hook<s_lmm_constraint_t, boost::intrusive::list_member_hook<>,
                                                       &s_lmm_constraint_t::saturated_constraint_set_hook>>
      saturated_constraint_set;

  simgrid::surf::ActionLmmListPtr keep_track;

  void (*solve_fun)(lmm_system_t self);

private:
  bool selective_update_active; /* flag to update partially the system only selecting changed portions */
  unsigned visited_counter;     /* used by lmm_update_modified_set and lmm_remove_modified_set to cleverly (un-)flag the
                                 * constraints (more details in these functions) */
  boost::intrusive::list<s_lmm_constraint_t,
                         boost::intrusive::member_hook<s_lmm_constraint_t, boost::intrusive::list_member_hook<>,
                                                       &s_lmm_constraint_t::constraint_set_hook>>
      constraint_set;
  boost::intrusive::list<s_lmm_constraint_t,
                         boost::intrusive::member_hook<s_lmm_constraint_t, boost::intrusive::list_member_hook<>,
                                                       &s_lmm_constraint_t::modified_constraint_set_hook>>
      modified_constraint_set;
  xbt_mallocator_t variable_mallocator;
};

extern XBT_PRIVATE double (*func_f_def)(const s_lmm_variable_t&, double);
extern XBT_PRIVATE double (*func_fp_def)(const s_lmm_variable_t&, double);
extern XBT_PRIVATE double (*func_fpi_def)(const s_lmm_variable_t&, double);

/** @} */
}
}
}

#endif