conclusion corrected

diff --git a/mpi-energy2-extension/Heter_paper.tex b/mpi-energy2-extension/Heter_paper.tex
index f00d0654ef85249aa932af30f4d08dea4dea937d..cd8702488d3530b69f9d5eff04988468dcc4799d 100644 (file)
--- a/mpi-energy2-extension/Heter_paper.tex
+++ b/mpi-energy2-extension/Heter_paper.tex
@@ -1205,8 +1205,8 @@ distance percentages for the these static power scenarios are not significantly
 
 Finding the frequencies that gives the best tradeoff between the energy consumption and the performance for a parallel 
 application is not a trivial task.  Many algorithms have been proposed to tackle this problem.  
 
 Finding the frequencies that gives the best tradeoff between the energy consumption and the performance for a parallel 
 application is not a trivial task.  Many algorithms have been proposed to tackle this problem.  

-In this section, the proposed frequencies selecting algorithm is compared to well known  energy and delay product method, $EDP=energy \times delay$, that have been used by many researchers  \cite{EDP_for_multi_processors,Energy_aware_application_scheduling,Exploring_Energy_Performance_TradeOffs}. 
-This method  was also used by Spiliopoulos et al. algorithm \cite{Spiliopoulos_Green.governors.Adaptive.DVFS} where they select the frequencies that minimize the EDP product and apply them with DVFS operations to  the multi-cores 
+In this section, the proposed frequencies selecting algorithm is compared to a method that uses the well known  energy and delay product objective function, $EDP=energy \times delay$, that has been used by many researchers  \cite{EDP_for_multi_processors,Energy_aware_application_scheduling,Exploring_Energy_Performance_TradeOffs}. 
+This objective function  was also used by Spiliopoulos et al. algorithm \cite{Spiliopoulos_Green.governors.Adaptive.DVFS} where they select the frequencies that minimize the EDP product and apply them with DVFS operations to  the multi-cores 

 architecture. Their online algorithm predicts the energy consumption and execution time of a processor before using the EDP method.
 
 To fairly compare the proposed frequencies scaling algorithm to  Spiliopoulos et al. algorithm, called Maxdist and EDP respectively, both algorithms use the same energy model,  equation \ref{eq:energy} and
 architecture. Their online algorithm predicts the energy consumption and execution time of a processor before using the EDP method.
 
 To fairly compare the proposed frequencies scaling algorithm to  Spiliopoulos et al. algorithm, called Maxdist and EDP respectively, both algorithms use the same energy model,  equation \ref{eq:energy} and


@@ -1257,37 +1257,36 @@ maximum number of available frequencies. When Maxdist is applied to a benchmark
 
 \section{Conclusion}
 \label{sec.concl}
 
 \section{Conclusion}
 \label{sec.concl}

-\textcolor{blue}{
-This paper has been  presented a new online frequencies selection algorithm.
-It works based on objective function that maximized the tradeoff distance 
+This paper has presented a new online frequencies selection algorithm.
+ The algorithm selects the best vector of 
+frequencies that maximizes  the tradeoff distance 

 between the predicted energy consumption and the predicted execution time of the distributed 
 between the predicted energy consumption and the predicted execution time of the distributed 

-iterative applications running over heterogeneous grid. The algorithm selects the best vector of the 
-frequencies which maximized the objective function has been used. A new energy model 
-used by the proposed algorithm for measuring and predicting the energy consumption 
-of the distributed iterative message passing application running over grid architecture.
+iterative applications running over a heterogeneous grid. A new energy model 
+is used by the proposed algorithm to predict the energy consumption 
+of the distributed iterative message passing application running over a grid architecture.

 To evaluate the proposed method on a real heterogeneous grid platform, it was applied on the  
 To evaluate the proposed method on a real heterogeneous grid platform, it was applied on the  

-NAS parallel benchmarks  class D instance  and executed over grid'5000 testbed platform. 
-The experimental results showed that the algorithm saves the energy consumptions on average 
-for all NAS benchmarks up to 30\%  while gives only 3\% percentage on average for the performance 
-degradation for the same instance. The algorithm also selecting different frequencies according to the 
-computations and communication times ratio, and according to the values of the static and measured dynamic power of the CPUs. The computations to communications ratio was varied between different scenarios have been used, concerning to the distribution of the computing nodes between different clusters' sites and using one core or multi-cores per node.
-Finally, the proposed algorithm was compared to other algorithm which it
-used the will known energy and delay product as an objective function. The comparison results showed 
-that the proposed algorithm outperform the other one in term of energy-time tradeoff.
+ NAS parallel benchmarks   and the  class D instance was executed over the  grid'5000 testbed platform. 
+ The experimental results showed that the algorithm reduces  on average 30\% of the energy consumption
+for all the NAS benchmarks   while  only degrading by 3\% on average  the performance. 
+The Maxdist algorithm was also evaluated in different scenarios that vary in the distribution of the computing nodes between different clusters' sites,  use one core or multi-cores per node or assume different values for the consumed static power. The algorithm selects different vector of frequencies according to the 
+computations and communication times ratios, and  the values of the static and measured dynamic powers of the CPUs. 
+Finally, the proposed algorithm was compared to another method that uses
+the well known energy and delay product as an objective function. The comparison results showed 
+that the proposed algorithm outperforms the latter by selecting a vector of frequencies that gives a better tradeoff  between energy consumption reduction and performance. 
+

 In the near future, we would like to develop a similar method that is adapted to
 In the near future, we would like to develop a similar method that is adapted to

-asynchronous iterative applications where each task does not
-wait for other tasks to finish their works. The development of
+asynchronous iterative applications where iterations are not synchronized and communications are overlapped with computations. 
+ The development of

 such a method might require a new energy model because the
 number of iterations is not known in advance and depends on
 the global convergence of the iterative system.
 such a method might require a new energy model because the
 number of iterations is not known in advance and depends on
 the global convergence of the iterative system.

-}
+

 
 
 \section*{Acknowledgment}
 
 This work  has been  partially supported by  the Labex ACTION  project (contract
 
 
 \section*{Acknowledgment}
 
 This work  has been  partially supported by  the Labex ACTION  project (contract

-``ANR-11-LABX-01-01'').  Computations  have been performed  on the supercomputer
-facilities  of the  Mésocentre de  calcul de  Franche-Comté. As  a  PhD student,
+``ANR-11-LABX-01-01'').  Computations  have been performed  on the Grid'5000 platform. As  a  PhD student,

 Mr. Ahmed  Fanfakh, would  like to  thank the University  of Babylon  (Iraq) for
 supporting his work.
 
 Mr. Ahmed  Fanfakh, would  like to  thank the University  of Babylon  (Iraq) for
 supporting his work.