-/* Copyright (c) 2004-2014. The SimGrid Team.
+/* Copyright (c) 2004-2015. The SimGrid Team.
* All rights reserved. */
/* This program is free software; you can redistribute it and/or modify it
#ifndef _SURF_MAXMIN_H
#define _SURF_MAXMIN_H
-#include "portable.h"
+#include "src/internal_config.h"
#include "xbt/misc.h"
#include "xbt/asserts.h"
#include "surf/datatypes.h"
#include <math.h>
-//#include <float.h>
-
/** @addtogroup SURF_lmm
* @details
- * A linear maxmin solver to resolves inequations systems.
+ * A linear maxmin solver to resolve inequations systems.
*
- * Most SimGrid model rely on a "fluid/steady-state" modeling that
- * samount to share 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
+ * 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:
+ * 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.
+ * 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)
*
* 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
+ * where `var1.value`, `var2.value` and `var3.value` are the unknown values.
*
- * if a constraint is not shared the sum is replace by a max
+ * 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.
*
- * Its usefull for the sharing of resources for various models.
- * For instance for the network model the link are associated
- * to consrtaint and the communications to variables.
+ * 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.
*/
-extern double sg_maxmin_precision;
-extern double sg_surf_precision;
+XBT_PUBLIC_DATA(double) sg_maxmin_precision;
+XBT_PUBLIC_DATA(double) sg_surf_precision;
+XBT_PUBLIC_DATA(int) sg_concurrency_limit;
-static XBT_INLINE void double_update(double *variable, double value, double precision)
+static inline void double_update(double *variable, double value, double precision)
{
//printf("Updating %g -= %g +- %g\n",*variable,value,precision);
//xbt_assert(value==0 || value>precision);
- //Check that precision is higher than the machine-dependent size of the mantissa. If not, brutal rounding may happen, and the precision mechanism is not active...
+ //Check that precision is higher than the machine-dependent size of the mantissa. If not, brutal rounding may happen,
+ //and the precision mechanism is not active...
//xbt_assert(*variable< (2<<DBL_MANT_DIG)*precision && FLT_RADIX==2);
*variable -= value;
if (*variable < precision)
*variable = 0.0;
}
-static XBT_INLINE int double_positive(double value, double precision)
+static inline int double_positive(double value, double precision)
{
return (value > precision);
}
-static XBT_INLINE int double_equals(double value1, double value2, double precision)
+static inline int double_equals(double value1, double value2, double precision)
{
return (fabs(value1 - value2) < precision);
}
/** @{ @ingroup SURF_lmm */
/**
* @brief Create a new Linear MaxMim system
- *
- * @param selective_update [description]
+ * @param selective_update whether we should do lazy updates
*/
-XBT_PUBLIC(lmm_system_t) lmm_system_new(int selective_update);
+XBT_PUBLIC(lmm_system_t) lmm_system_new(bool selective_update);
/**
* @brief Free an existing Linear MaxMin system
- *
* @param sys The lmm system to free
*/
XBT_PUBLIC(void) lmm_system_free(lmm_system_t sys);
/**
* @brief Create a new Linear MaxMin constraint
- *
* @param sys The system in which we add a constraint
* @param id Data associated to the constraint (e.g.: a network link)
* @param bound_value The bound value of the constraint
*/
-XBT_PUBLIC(lmm_constraint_t) lmm_constraint_new(lmm_system_t sys, void *id,
- double bound_value);
+XBT_PUBLIC(lmm_constraint_t) lmm_constraint_new(lmm_system_t sys, void *id,double bound_value);
/**
* @brief Share a constraint
- * @details [long description]
- *
* @param cnst The constraint to share
*/
XBT_PUBLIC(void) lmm_constraint_shared(lmm_constraint_t cnst);
/**
* @brief Check if a constraint is shared (shared by default)
- *
* @param cnst The constraint to share
* @return 1 if shared, 0 otherwise
*/
-XBT_PUBLIC(int) lmm_constraint_is_shared(lmm_constraint_t cnst);
+XBT_PUBLIC(int) lmm_constraint_sharing_policy(lmm_constraint_t cnst);
/**
* @brief Free a constraint
- *
* @param sys The system associated to the constraint
* @param cnst The constraint to free
*/
/**
* @brief Get the usage of the constraint after the last lmm solve
- *
* @param cnst A constraint
* @return The usage of the constraint
*/
XBT_PUBLIC(double) lmm_constraint_get_usage(lmm_constraint_t cnst);
+/**
+ * @brief Sets the concurrency limit for this constraint
+ * @param cnst A constraint
+ * @param concurrency_limit The concurrency limit to use for this constraint
+ */
+XBT_PUBLIC(void) lmm_constraint_concurrency_limit_set(lmm_constraint_t cnst, int concurrency_limit);
+
+/**
+ * @brief Gets the concurrency limit for this constraint
+ * @param cnst A constraint
+ * @return The concurrency limit used by this constraint
+ */
+XBT_PUBLIC(int) lmm_constraint_concurrency_limit_get(lmm_constraint_t cnst);
+
+/**
+ * @brief Reset the concurrency maximum for a given variable (we will update the maximum to reflect constraint
+ * evolution).
+ * @param cnst A constraint
+*/
+XBT_PUBLIC(void) lmm_constraint_concurrency_maximum_reset(lmm_constraint_t cnst);
+
+/**
+ * @brief Get the concurrency maximum for a given variable (which reflects constraint evolution).
+ * @param cnst A constraint
+ * @return the maximum concurrency of the constraint
+ */
+XBT_PUBLIC(int) lmm_constraint_concurrency_maximum_get(lmm_constraint_t cnst);
+
/**
* @brief Create a new Linear MaxMin variable
- *
* @param sys The system in which we add a constaint
* @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
*/
-XBT_PUBLIC(lmm_variable_t) lmm_variable_new(lmm_system_t sys, void *id,
- double weight_value,
- double bound,
+XBT_PUBLIC(lmm_variable_t) lmm_variable_new(lmm_system_t sys, void *id, double weight_value, double bound,
int number_of_constraints);
/**
* @brief Free a variable
- *
* @param sys The system associated to the variable
* @param var The variable to free
*/
/**
* @brief Get the value of the variable after the last lmm solve
- *
* @param var A variable
* @return The value of the variable
*/
/**
* @brief Get the maximum value of the variable (-1.0 if no maximum value)
- *
* @param var A variable
* @return The bound of the variable
*/
XBT_PUBLIC(double) lmm_variable_getbound(lmm_variable_t var);
+/**
+ * @brief Set the concurrent share of the variable
+ * @param var A variable
+ * @param concurrency_share The new concurrency share
+ */
+XBT_PUBLIC(void) lmm_variable_concurrency_share_set(lmm_variable_t var, short int concurrency_share);
+
/**
* @brief Remove a variable from a constraint
- *
* @param sys A system
* @param cnst A constraint
* @param var The variable to remove
*/
-XBT_PUBLIC(void) lmm_shrink(lmm_system_t sys, lmm_constraint_t cnst,
- lmm_variable_t var);
+XBT_PUBLIC(void) lmm_shrink(lmm_system_t sys, lmm_constraint_t cnst, lmm_variable_t var);
/**
* @brief Associate a variable to a constraint with a coefficient
- *
* @param sys A system
* @param cnst A constraint
* @param var A variable
* @param value The coefficient associated to the variable in the constraint
*/
-XBT_PUBLIC(void) lmm_expand(lmm_system_t sys, lmm_constraint_t cnst,
- lmm_variable_t var, double value);
+XBT_PUBLIC(void) lmm_expand(lmm_system_t sys, 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
- *
+ * @brief Add value to the coefficient between a constraint and a variable or create one
* @param sys A system
* @param cnst A constraint
* @param var A variable
* @param value The value to add to the coefficient associated to the variable in the constraint
*/
-XBT_PUBLIC(void) lmm_expand_add(lmm_system_t sys, lmm_constraint_t cnst,
- lmm_variable_t var, double value);
+XBT_PUBLIC(void) lmm_expand_add(lmm_system_t sys, lmm_constraint_t cnst, lmm_variable_t var, double value);
/**
* @brief Get the numth constraint associated to the variable
- *
* @param sys The system associated to the variable (not used)
* @param var A variable
* @param num The rank of constraint we want to get
* @return The numth constraint
*/
-XBT_PUBLIC(lmm_constraint_t) lmm_get_cnst_from_var(lmm_system_t sys,
- lmm_variable_t var, int num);
+XBT_PUBLIC(lmm_constraint_t) lmm_get_cnst_from_var(lmm_system_t sys, lmm_variable_t var, int num);
/**
* @brief Get the weigth of the numth constraint associated to the variable
- *
* @param sys The system associated to the variable (not used)
* @param var A variable
* @param num The rank of constraint we want to get
* @return The numth constraint
*/
-XBT_PUBLIC(double) lmm_get_cnst_weight_from_var(lmm_system_t sys, lmm_variable_t var,
- int num);
+XBT_PUBLIC(double) lmm_get_cnst_weight_from_var(lmm_system_t sys, lmm_variable_t var, int num);
/**
* @brief Get the number of constraint associated to a variable
- *
* @param sys The system associated to the variable (not used)
* @param var A variable
* @return The number of constraint associated to the variable
/**
* @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 sys The system associated to the variable (not used)
* @param cnst A constraint
* @param elem A element of constraint of the constraint or NULL
* @return A variable associated to a constraint
*/
-XBT_PUBLIC(lmm_variable_t) lmm_get_var_from_cnst(lmm_system_t sys,
- lmm_constraint_t cnst,
- lmm_element_t * elem);
+XBT_PUBLIC(lmm_variable_t) lmm_get_var_from_cnst(lmm_system_t sys, lmm_constraint_t cnst, lmm_element_t * elem);
/**
* @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 sys The system associated to the variable (not used)
* @param cnst A constraint
* @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
*
* @return A variable associated to a constraint
*/
-XBT_PUBLIC(lmm_variable_t) lmm_get_var_from_cnst_safe(lmm_system_t /*sys*/,
- lmm_constraint_t cnst,
- lmm_element_t * elem,
- lmm_element_t * nextelem,
- int * numelem);
+XBT_PUBLIC(lmm_variable_t) lmm_get_var_from_cnst_safe(lmm_system_t sys, lmm_constraint_t cnst,
+ lmm_element_t * elem, lmm_element_t * nextelem, int * numelem);
/**
* @brief Get the first active constraint of a system
- *
* @param sys A system
* @return The first active constraint
*/
/**
* @brief Get the next active constraint of a constraint in a system
- *
* @param sys A system
* @param cnst An active constraint of the system
*
* @return The next active constraint
*/
-XBT_PUBLIC(lmm_constraint_t) lmm_get_next_active_constraint(lmm_system_t sys,
- lmm_constraint_t cnst);
-
-#ifdef HAVE_LATENCY_BOUND_TRACKING
-XBT_PUBLIC(int) lmm_is_variable_limited_by_latency(lmm_variable_t var);
-#endif
+XBT_PUBLIC(lmm_constraint_t) lmm_get_next_active_constraint(lmm_system_t sys, lmm_constraint_t cnst);
/**
* @brief Get the data associated to a constraint
- *
* @param cnst A constraint
* @return The data associated to the constraint
*/
/**
* @brief Get the data associated to a variable
- *
* @param var A variable
* @return The data associated to the variable
*/
/**
* @brief Update the value of element linking the constraint and the variable
- *
* @param sys A system
* @param cnst A constraint
* @param var A variable
* @param value The new value
*/
-XBT_PUBLIC(void) lmm_update(lmm_system_t sys, lmm_constraint_t cnst,
- lmm_variable_t var, double value);
+XBT_PUBLIC(void) lmm_update(lmm_system_t sys, lmm_constraint_t cnst, lmm_variable_t var, double value);
/**
* @brief Update the bound of a variable
- *
* @param sys A system
* @param var A constraint
* @param bound The new bound
*/
-XBT_PUBLIC(void) lmm_update_variable_bound(lmm_system_t sys, lmm_variable_t var,
- double bound);
+XBT_PUBLIC(void) lmm_update_variable_bound(lmm_system_t sys, lmm_variable_t var, double bound);
/**
* @brief Update the weight of a variable
- *
* @param sys A system
* @param var A variable
* @param weight The new weight of the variable
*/
-XBT_PUBLIC(void) lmm_update_variable_weight(lmm_system_t sys,
- lmm_variable_t var,
- double weight);
+XBT_PUBLIC(void) lmm_update_variable_weight(lmm_system_t sys, lmm_variable_t var, double weight);
/**
* @brief Get the weight of a variable
- *
* @param var A variable
* @return The weight of the variable
*/
/**
* @brief Update a constraint bound
- *
* @param sys A system
* @param cnst A constraint
* @param bound The new bound of the consrtaint
*/
-XBT_PUBLIC(void) lmm_update_constraint_bound(lmm_system_t sys,
- lmm_constraint_t cnst,
- double bound);
+XBT_PUBLIC(void) lmm_update_constraint_bound(lmm_system_t sys, lmm_constraint_t cnst, double bound);
/**
* @brief [brief description]
- *
* @param sys A system
* @param cnst A constraint
* @return [description]
*/
XBT_PUBLIC(int) lmm_constraint_used(lmm_system_t sys, lmm_constraint_t cnst);
+/**
+ * @brief Print the lmm system
+ * @param sys The lmm system to print
+ */
+XBT_PUBLIC(void) lmm_print(lmm_system_t sys);
+
/**
* @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.
- */
+/** Default functions associated to the chosen protocol. When using the lagrangian approach. */
-XBT_PUBLIC(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));
+XBT_PUBLIC(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));
XBT_PUBLIC(double func_reno_f) (lmm_variable_t var, double x);
XBT_PUBLIC(double func_reno_fp) (lmm_variable_t var, double x);