correcting referne\e[2~ce

[ThesisAhmed.git] / thesis-presentation / AhmedSlides.tex

diff --git a/thesis-presentation/AhmedSlides.tex b/thesis-presentation/AhmedSlides.tex
index d4fd8c3611ade4f8fc58d77d8365cff08b1aa6dc..6dbbd81e2f5dc24beada93938c4033eaa2ed422e 100644 (file)
--- a/thesis-presentation/AhmedSlides.tex
+++ b/thesis-presentation/AhmedSlides.tex
@@ -19,10 +19,10 @@
   \todo[color=red!10,#1]{\sffamily\textbf{JC:} #2}\xspace}
 \definecolor{myblue}{RGB}{0,29,119}
 \newcommand{\Xsub}[2]{{\ensuremath{#1_\mathit{#2}}}}
   \todo[color=red!10,#1]{\sffamily\textbf{JC:} #2}\xspace}
 \definecolor{myblue}{RGB}{0,29,119}
 \newcommand{\Xsub}[2]{{\ensuremath{#1_\mathit{#2}}}}

-
+\usepackage{fixltx2e}

 %% used to put some subscripts lower, and make them more legible
 \newcommand{\fxheight}[1]{\ifx#1\relax\relax\else\rule{0pt}{1.52ex}#1\fi}
 %% used to put some subscripts lower, and make them more legible
 \newcommand{\fxheight}[1]{\ifx#1\relax\relax\else\rule{0pt}{1.52ex}#1\fi}

-
+\usepackage{ragged2e}

 \newcommand{\CL}{\Xsub{C}{L}}
 \newcommand{\Dist}{\mathit{Dist}}
 \newcommand{\EdNew}{\Xsub{E}{dNew}}
 \newcommand{\CL}{\Xsub{C}{L}}
 \newcommand{\Dist}{\mathit{Dist}}
 \newcommand{\EdNew}{\Xsub{E}{dNew}}


@@ -75,8 +75,8 @@
 %Iterations using CPU Frequency Scaling} 
 \vspace{2cm}
 
 %Iterations using CPU Frequency Scaling} 
 \vspace{2cm}
 

-\title{   \textbf{Energy Consumption Optimization of   Parallel Applications with Iterations   using CPU Frequency Scaling} \\ \vspace{0.2cm} \hspace{1.8cm}\textbf{\textcolor{cyan}{\small PhD Dissertation Defense}}}\vspace{-1cm}
-\author{ \textbf{Ahmed Badri Muslim Fanfakh} \\ \vspace{0.5cm}\small Under Supervision: \textcolor{cyan}{\small  Raphaël COUTURIER and Jean-Claude CHARR} \\\vspace{0.1cm} \textcolor{blue}{ University of Franche-Comté - FEMTO-ST - DISC Dept.  - AND Team} \\ ~~~~~~~~~~~~~~~~~~~~~ \textbf{\textcolor{blue}{ 17 October 2016 }}} 
+\title{   \textbf{Energy Consumption Optimization of   Parallel Applications with Iterations   using CPU Frequency Scaling} \\ \vspace{0.2cm} \hspace{1.8cm}\textbf{\textcolor{cyan}{\small PhD Dissertation Defense}}}\vspace{-0.5cm}
+\author{ \textbf{Ahmed Badri Muslim Fanfakh} \\ \vspace{0.5cm}\small Under the supervision of: \\ \textcolor{cyan}{\small  Raphaël COUTURIER and Jean-Claude CHARR} \\\vspace{0.1cm} \textcolor{blue}{ UBFC - FEMTO-ST - DISC Dept.  - AND Team} \\ ~~~~~~~~~~~~~~~~~~~~~ \textbf{\textcolor{blue}{ 17 October 2016 }}} 

 
 \date{}
 \vspace{-3cm}
 
 \date{}
 \vspace{-3cm}


@@ -109,15 +109,57 @@
 \tableofcontents
 \end{frame}
 
 \tableofcontents
 \end{frame}
 

+%%%%%%%%%%%%%%%%%%%%
+%%    SLIDE 03    %%
+%%%%%%%%%%%%%%%%%%%% 
+\begin{frame}{Definition of parallel computing}
+\section{\small {Introduction and Problem definition}}
+ \centering
+ \includegraphics[width=0.99\textwidth]{para.pdf} 
+\end{frame}
+
+ 
+
+\begin{frame}{Execution of synchronous parallel tasks}
+\vspace{-0.5 cm}
+\begin{figure}
+  \centering
+  \subfloat[Synchronous imbalanced communications]{%
+    \includegraphics[scale=0.49]{c1/commtasks}\label{fig:h1}}
+  \subfloat[Synchronous imbalanced computations]{%
+    \includegraphics[scale=0.49]{c1/compt}\label{fig:h2}}
+ % \caption{Parallel tasks on homogeneous platform}
+  \label{fig:homo}
+\end{figure}

 
 

+ \end{frame}
+ 
+ 

 %%%%%%%%%%%%%%%%%%%%
 %%%%%%%%%%%%%%%%%%%%

+%%    SLIDE 07   %%
+%%%%%%%%%%%%%%%%%%%% 
+
+
+\begin{frame}{\large Synchronous and asynchronous iterative methods }
+\vspace{-0.5 cm}
+\begin{figure}
+
+\includegraphics[scale=0.42]{syn_tasks.pdf}
+\vspace{0.6 cm}
+\includegraphics[scale=0.42]{Asyn_tasks.pdf}
+\end{figure}
+
+ 
+ \end{frame}
+ 
+ %%%%%%%%%%%%%%%%%%%%

 %%    SLIDE 03    %%
 %%%%%%%%%%%%%%%%%%%% 
 %%    SLIDE 03    %%
 %%%%%%%%%%%%%%%%%%%% 

-\begin{frame}{Introduction and problem definition}
- \section{\small {Introduction and Problem definition}}
-   \bf \textcolor{blue}{Approaches to increase the computing power:}
+\begin{frame}{Approaches to get more computing power}
+ 
+   %\bf \textcolor{blue}{}

      \begin{minipage}{0.5\textwidth} 
      \begin{minipage}{0.5\textwidth} 

-      \textcolor{blue}{1)} \small  \bf \textcolor{black}{Increasing the frequency of processor}
+      \textcolor{blue}{1)} \small  \bf \textcolor{black}{Increase the frequency of a  processor.\\ (limited due to overheating)}

     \end{minipage}%
     \begin{minipage}{0.6\textwidth} 
     
     \end{minipage}%
     \begin{minipage}{0.6\textwidth} 
     


@@ -128,7 +170,11 @@
     \end{minipage}%
     \vspace{0.2cm}
     \begin{minipage}{0.5\textwidth} 
     \end{minipage}%
     \vspace{0.2cm}
     \begin{minipage}{0.5\textwidth} 

-     \textcolor{blue}{2)} \small \bf \textcolor{black}{Increasing the number of nodes}        
+     \textcolor{blue}{2)} \small \bf \textcolor{black}{Increase the number of computing   
+     units.}
+     
+ \textcolor{black}{The supercomputer Tianhe-2 has more than 3 million cores and consumes around 17.8 megawatts.}  
+          

     \end{minipage}%
     \begin{minipage}{0.6\textwidth} 
     \begin{figure}[h!]
     \end{minipage}%
     \begin{minipage}{0.6\textwidth} 
     \begin{figure}[h!]


@@ -139,84 +185,75 @@
  
  
  
  
  
  

-%%%%%%%%%%%%%%%%%%%%
-%%    SLIDE 04    %%
-%%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{Introduction and problem definition}
- \bf \textcolor{blue}{Processor frequency and its energy consumption}
- \vspace{0.4cm}
-   \begin{minipage}{0.5\textwidth} 
-   \textcolor{blue}{$\blacktriangleright$} 
-  \small  \bf \textcolor{black}{ The power consumption of a processor increases exponentially  when its    
-      frequency is increased}
-    \end{minipage}%
-    \begin{minipage}{0.5\textwidth} 
-    \begin{figure}[h!]
-     \includegraphics[width=0.7\textwidth]{fig/freq-power} 
-    \end{figure}
-    \end{minipage}%
-       
-    \begin{minipage}{0.5\textwidth} 
-     \textcolor{blue}{$\blacktriangleright$} 
-     \small \bf \textcolor{black}{The biggest power consumption is consumed by a processor in the computing node}
-      
-    \end{minipage}%
-    \begin{minipage}{0.6\textwidth} 
-    \begin{figure}[h!]
-     \includegraphics[width=0.9\textwidth]{fig/node-power} 
-    \end{figure}
-    \end{minipage}%
-    
- \end{frame}
- 

  %%%%%%%%%%%%%%%%%%%
  %%%%%%%%%%%%%%%%%%%

-%%    SLIDE 05   %%
+%%    SLIDE 04   %%

 %%%%%%%%%%%%%%%%%%%% 
 %%%%%%%%%%%%%%%%%%%% 

-\begin{frame}{Introduction and problem definition}
- \vspace{0.1cm}
- \bf \textcolor{blue}{Techniques for energy consumption reduction}
- 
+\begin{frame}{Techniques for energy consumption reduction}
+

      \textcolor{blue}{1)} \bf \textcolor{black}{Switch-off idle nodes method}  
     \vspace{-0.9cm}
     \begin{figure}
      \textcolor{blue}{1)} \bf \textcolor{black}{Switch-off idle nodes method}  
     \vspace{-0.9cm}
     \begin{figure}

-     \animategraphics[autopause,loop,controls,scale=0.25,buttonsize=0.2cm]{200}{on-off/a-}{0}{69}
+     \animategraphics[autopause,controls,scale=0.26,buttonsize=0.2cm]{200}{on-off/a-}{0}{111}
+     %\includegraphics[width=0.6\textwidth]{on-off/a-69}

     \end{figure}
  \end{frame}
 
 %%%%%%%%%%%%%%%%%%%%
     \end{figure}
  \end{frame}
 
 %%%%%%%%%%%%%%%%%%%%

-%%    SLIDE 06    %%
+%%    SLIDE 05    %%

 %%%%%%%%%%%%%%%%%%%% 
 \begin{frame}{Techniques for energy consumption reduction}
  
 %%%%%%%%%%%%%%%%%%%% 
 \begin{frame}{Techniques for energy consumption reduction}
  

-  \textcolor{blue}{2)} \bf \textcolor{black}{Dynamic voltage and frequency Scaling (DVFS)}
-     \vspace{-0.5cm}
+  \textcolor{blue}{2)} \bf \textcolor{black}{Dynamic Voltage and Frequency Scaling (DVFS)}
+     \vspace{-0.9cm}

     \begin{figure}
     \begin{figure}

-     \animategraphics[autopause,controls,scale=0.25,buttonsize=0.2cm]{10}{DVFS-meq/a-}{0}{109}
+    \animategraphics[autopause,controls,scale=0.26,buttonsize=0.2cm]{10}{DVFS-meq/a-}{0}{175}
+     %\includegraphics[width=0.6\textwidth]{DVFS-meq/a-109}

     \end{figure}
     \end{frame}
  
     \end{figure}
     \end{frame}
  

-
-
+%%%%%%%%%%%%%%%%%%%%
+%%    SLIDE 06   %%
+%%%%%%%%%%%%%%%%%%%% 

 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 07    %%
 %%%%%%%%%%%%%%%%%%%% 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 07    %%
 %%%%%%%%%%%%%%%%%%%% 

-\begin{frame}{Using the energy reduction method}
-\section{\small {Using the energy reduction method}}
-\begin{block}{\textcolor{white}{Why we used DVFS method:}}
-\begin{itemize}
-               \item \textcolor{black}{It used to reduce the energy while keeping all node working, thus  it is more conventional with parallel computing.}
-               \item \textcolor{black}{It has a very small overhead compared to switch-off idle nodes method.}
+\begin{frame}{Motivations}
+\vspace{0.05cm}
+\section{\small {Motivations}}
+\textcolor{blue}{Why we used the DVFS method:}
+\vspace{-0.49cm}
+\begin{minipage}{0.5\textwidth} 
+    \vspace{-0.49cm} 
+      \begin{itemize} 
+       \item  \small \textcolor{black}{ The CPU is the component that consumes the  highest amount of energy in a node \textsuperscript{1}. }
+               

         \end{itemize}
         \end{itemize}

-\end{block}

 
 

- \vspace{0.1cm}
+    \end{minipage}%
+    \begin{minipage}{0.5\textwidth}
+     \vspace{-0.49cm} 
+    \begin{figure}[h!]
+     \includegraphics[width=0.85\textwidth]{fig/node-power} 
+     
+    \end{figure}
+    \end{minipage}%
+    
+  \begin{itemize} \item \small  \textcolor{black}{DVFS reduces the energy consumption while 
+   keeping all the nodes working.}
+               \item \small \textcolor{black}{It has a very small overhead compared to switching-off the idle nodes.}  \end{itemize} 
+    
+\vspace{-0.12cm}
+

  \begin{block}{\textcolor{white}{Challenge and Objective}}
 
  \begin{block}{\textcolor{white}{Challenge and Objective}}
 

-               \textcolor{blue}{Challenge:} \textcolor{black}{DVFS is used to reduce the energy, \textcolor{blue}{but} it degrades the performance simultaneously.}
+       \small  \textcolor{blue}{Challenge:} \textcolor{black}{DVFS is used to reduce the energy consumption, \textcolor{blue}{but} it also degrades the performance of the CPU.}

                
                \vspace{0.1cm}
                
                \vspace{0.1cm}

-        \textcolor{blue}{Objective:} \textcolor{black}{Optimizing both energy consumption and performance of a parallel application at the same time when DVFS is used.}
+ \small         \textcolor{blue}{Objective:} \textcolor{black}{Applying the DVFS to minimize the energy consumption while maintaining the performance of the parallel application.}

 \end{block}
 \end{block}

+ 
+ \tiny \textsuperscript{1} Fan, X., Weber, W., and Barroso, L. A. 2007.  Power provisioning
+for a warehouse-sized computer.

 
     \end{frame}
 
 
     \end{frame}
 


@@ -227,13 +264,14 @@
 %%%%%%%%%%%%%%%%%%%% 
 
 
 %%%%%%%%%%%%%%%%%%%% 
 
 

-\begin{frame}{Contributions}
-\section{\small {Contributions}}
-\subsection{\small {3.1 Energy optimization of homogeneous platform}}
+\begin{frame}{The first contribution}
+
+\section{\small {Energy optimization of a homogeneous platform}}
+%\vspace{-3cm}
+ % \includegraphics[width=0.6\textwidth]{white.pdf} 
+

 \begin{center}
 \begin{center}

-\bf \textcolor{black}{First contribution} \\ 
-\vspace{1cm}
-\bf  \Large \textcolor{blue}{Energy optimization of homogeneous platform}
+\bf  \Large \textcolor{blue}{Energy optimization of a parallel application with iterations running over a homogeneous platform}

 \end{center}
  \end{frame}
 
 \end{center}
  \end{frame}
 


@@ -244,41 +282,59 @@
 %%%%%%%%%%%%%%%%%%%% 
  
 \begin{frame}{Objectives}
 %%%%%%%%%%%%%%%%%%%% 
  
 \begin{frame}{Objectives}

-        \begin{femtoBlock}{} \vspace{-12 mm}
-                \begin{itemize} \small
-                   \item  Study the effect of the scaling factor $S$ on \textbf{energy consumption} of parallel iterative applications such as NAS 
-                          Benchmarks. \includegraphics[width=.06\textwidth]{c1/nasa.pdf} \medskip
-                   \item  Study the effect of the scaling factor $S$ on \textbf{performance} of these benchmarks.\medskip
-                   \item  Discovering the \textbf{energy-performance trade-off relation} when changing the frequency.\medskip
-                   \item  We propose an algorithm for selecting the scaling factor $S$ producing \textbf {optimal trade-off} between the energy and performance. \medskip
-                   \item  Improving Rauber and Rünger's\footnote{\tiny Thomas Rauber and Gudula Rünger. Analytical modeling and simulation of the  
-                          energy consumption \\  \quad ~ ~\quad    of  independent tasks. In Proceedings of the Winter Simulation Conference, 2012.} method that our method best on. 
+        
+                \begin{itemize}   \small \justifying
+                 
+                   \item   Studying the effect of the frequency scaling  on the \textbf{energy consumption and performance } of parallel  applications with iterations. \medskip
+                   
+                   \item   Discovering the \textbf{energy-performance trade-off relation} when changing the frequency of the processor.\medskip
+                   \item   Proposing an algorithm for selecting the scaling factor that produces  \textbf {the good trade-off} between the energy consumption and the performance. \medskip
+                   \item   Comparing the proposed algorithm to existing methods.
+                   
+                   
+                   %\footnote{\tiny Thomas Rauber and Gudula Rünger. Analytical modeling and simulation of the  
+                          %energy consumption \\  \quad ~ ~\quad    of  independent tasks. In Proceedings of the Winter Simulation Conference, 2012.} method that our method best on. 

                 \end{itemize}
                 \end{itemize}

-                 \let\thefootnote\relax\footnote{}
-          \vspace{-10 mm}
-        \end{femtoBlock}      
+                 %\let\thefootnote\relax\footnote{}
+        
+        

 \end{frame}
 
 
 
 \end{frame}
 
 
 

+

 %%%%%%%%%%%%%%%%%%%%
 %%%%%%%%%%%%%%%%%%%%

-%%    SLIDE 10    %%
+%%    SLIDE 13   %%

 %%%%%%%%%%%%%%%%%%%% 
 %%%%%%%%%%%%%%%%%%%% 

+\begin{frame}{Performance evaluation of MPI programs}  

 
 

+\small The frequency scaling factor is the ratio between the maximum and the new frequency, \textcolor{blue}{$S = \frac{F_{max}}{F_{new}}$}.  
+    \vspace{5 mm}
+    
+        \begin{femtoBlock}{}
+              \vspace{-5 mm}
+              \begin{block}{\small Execution time prediction model}
+                     \centering{ $ \textcolor{red}{T_{new}} = \textcolor{blue}{T_{Max Comp Old} \cdot S + T_{{Min Comm Old}}}$}
+          \end{block}   
+          \vspace{5 mm}
+           \centering{\includegraphics[width=.4\textwidth]{c1/cg_per}
+           \quad%
+           \includegraphics[width=.4\textwidth]{c1/lu_pre}}
+            \vspace{1 mm}
+            
+           \small The maximum normalized error for CG=0.0073 \textbf{(the smallest)} and LU=0.031 \textbf{(the worst)}.
+           \end{femtoBlock}
+\end{frame}
+
+
+
+
+
+
+
+  

 
 

-\begin{frame}{Parallel tasks execution over Homo. Platform}
-\vspace{-0.5 cm}
-\begin{figure}
-  \centering
-  \subfloat[Sync. imbalanced communications]{%
-    \includegraphics[scale=0.49]{c1/commtasks}\label{fig:h1}}
-  \subfloat[Sync. imbalanced computations]{%
-    \includegraphics[scale=0.49]{c1/compt}\label{fig:h2}}
-  \caption{Parallel tasks on homogeneous platform}
-  \label{fig:homo}
-\end{figure}

 
 

- \end{frame}

  
  
  
  
  
  


@@ -286,69 +342,56 @@
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 11   %%
 %%%%%%%%%%%%%%%%%%%% 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 11   %%
 %%%%%%%%%%%%%%%%%%%% 

-\begin{frame}{Energy model for homogeneous platform}    
-      The power consumed by a processor divided into two power metrics: the dynamic (\textcolor{red}{$P_d$}) and static   
-       (\textcolor{red}{$P_s$}) power. 
+\begin{frame}{Energy model for a homogeneous platform}    
+      The power consumed by a processor is divided into two power metrics: the dynamic (\textcolor{red}{$P_d$}) and  the static   
+       (\textcolor{red}{$P_s$}) powers. 

     \begin{equation}
      \label{eq:pd}
      \textcolor{red}{ P_d} = \textcolor{blue}{\alpha \cdot CL \cdot V^2 \cdot F}
    \end{equation}
     \scriptsize \underline{Where}: \\ 
     \begin{equation}
      \label{eq:pd}
      \textcolor{red}{ P_d} = \textcolor{blue}{\alpha \cdot CL \cdot V^2 \cdot F}
    \end{equation}
     \scriptsize \underline{Where}: \\ 

-    \scriptsize {\textcolor{blue}{$\alpha$}: switching activity \hspace{15 mm}  \textcolor{blue}{$CL$}: load capacitance\\     
-    \textcolor{blue}{$V$} the supply voltage \hspace{14 mm} \textcolor{blue}{$F$}: operational frequency}
+    \scriptsize {\textcolor{blue}{$\alpha$}: switching activity. \hspace{15 mm}  \textcolor{blue}{$CL$}: load capacitance [F].\\     
+    \textcolor{blue}{$V$}: the supply voltage [V]. \hspace{8 mm} \textcolor{blue}{$F$}: operational frequency [Hz].}

    \begin{equation}
      \label{eq:ps}
      \small \textcolor{red}{P_s} = \textcolor{blue}{V \cdot N_{trans} \cdot K_{design} \cdot I_{Leak}}
    \end{equation}
     \underline{Where}:\\ 
    \begin{equation}
      \label{eq:ps}
      \small \textcolor{red}{P_s} = \textcolor{blue}{V \cdot N_{trans} \cdot K_{design} \cdot I_{Leak}}
    \end{equation}
     \underline{Where}:\\ 

-       \scriptsize{ \textcolor{blue}{$V$}: the supply voltage.  \hspace{28 mm}   \textcolor{blue}{$N_{trans}$}: number of transistors. \\   
-       \textcolor{blue}{$K_{design}$}: design dependent parameter. \hspace{8 mm} \textcolor{blue}{$I_{leak}$}: technology dependent  
-            parameter.} 
+       \scriptsize{ \textcolor{blue}{$V$}: the supply voltage [V].  \hspace{19 mm}   \textcolor{blue}{$N_{trans}$}: number of transistors. \\   
+       \textcolor{blue}{$K_{design}$}: design dependent parameter. \hspace{3 mm} \textcolor{blue}{$I_{leak}$}: technology dependent  
+            parameter [A].} 
+            
+            

 \end{frame}
 
 \end{frame}
 

+
+  

 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 12   %%
 %%%%%%%%%%%%%%%%%%%% 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 12   %%
 %%%%%%%%%%%%%%%%%%%% 
 

-\begin{frame}{Energy model for homogeneous platform}
-       
-          The frequency scaling factor is the ratio between the maximum and the new frequency, \textcolor{blue}{$S = \frac{F_{max}}{F_{new}}$}.  \medskip     
-              
+\begin{frame}{Energy model for a homogeneous platform}
+       \vspace{-0.77cm} 
+            \begin{figure}
+  \animategraphics[autopause,controls,scale=0.3,buttonsize=0.2cm]{10}{homo-model/a-}{0}{441}
+  %\includegraphics[width=0.6\textwidth]{homo-model/a-356}
+  \end{figure}  

               
               

-              
-        \begin{block}{\small Rauber and Rünger's energy model}
-         $ E = P_{d} \cdot S_1^{-2} \cdot
-         \left( T_1 + \sum_{i=2}^{N} \frac{T_i^3}{T_1^2} \right) +
-            P_{s} \cdot S_1  \cdot T_1 \cdot N$
-        \end{block}     
-           \textcolor{blue}{$S_1$}: the max. scaling factor\\ 
-           \textcolor{blue}{$P_{d}$}: the dynamic power\\
-           \textcolor{blue}{$P_{s}$}: the static power\\
-           \textcolor{blue}{$T_I$}: the time of the slower task\\ 
-           \textcolor{blue}{$T_i$}: the time of the other tasks\\ 
-           \textcolor{blue}{$N$}:  the number of  nodes
+      %  \begin{block}{\small Rauber and Rünger's energy model}
+         %$ E = P_{d} \cdot S_1^{-2} \cdot
+         %\left( T_1 + \sum_{i=2}^{N} \frac{T_i^3}{T_1^2} \right) +
+          %  P_{s} \cdot S_1  \cdot T_1 \cdot N$
+        %\end{block}     
+          % \textcolor{blue}{$S_1$}: the maximum scaling factor.\\ 
+          % \textcolor{blue}{$P_{d}$}: the dynamic power.\\
+          % \textcolor{blue}{$P_{s}$}: the static power.\\
+          % \textcolor{blue}{$T_I$}: the execution time of the slower task.\\ 
+          % \textcolor{blue}{$T_i$}: the execution time of task i.\\ 
+          % \textcolor{blue}{$N$}:  the number of  nodes.
+          
+          

        
 \end{frame}
        
 \end{frame}

-  
-  
-%%%%%%%%%%%%%%%%%%%%
-%%    SLIDE 13   %%
-%%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{Performance evaluation of MPI programs}      
-        \begin{femtoBlock}{}
-              \vspace{-5 mm}
-              \begin{block}{\small Execution time prediction model}
-                     \centering{ $ \textcolor{red}{T_{new}} = \textcolor{blue}{T_{Max Comp Old} \cdot S + T_{{Min Comm Old}}}$}
-          \end{block}   
-          \vspace{10 mm}
-           \centering{\includegraphics[width=.4\textwidth]{c1/cg_per}
-           \quad%
-           \includegraphics[width=.4\textwidth]{c1/lu_pre}}
-            \vspace{5 mm}
-            
-           \small The maximum normalized error for CG=0.0073 \textbf{(the smallest)} and LU=0.031 \textbf{(the worst)}.
-           \end{femtoBlock}
-\end{frame}

 
 
 
 
 
 


@@ -374,9 +417,9 @@
 %\vspace{-0.3cm}
       \small 
          \begin{block}{\small Our objective function}
 %\vspace{-0.3cm}
       \small 
          \begin{block}{\small Our objective function}

-         \centering{$\textbf{\emph {MaxDist}} = \max_{j=1,2,\dots ,F}             
-                    (\overbrace{P_{Norm}(S_j)}^{{Maximize}} - 
-                     \overbrace{E_{Norm}(S_j)}^{{Minimize}} )$}
+         \centering{$\textbf{\emph {\textcolor{red}{MaxDist}}} = \max_{j=1,2,\dots ,F}             
+                    (\overbrace{P_{Norm}(S_j)}^{{\textcolor{blue}{Maximize}}} - 
+                     \overbrace{E_{Norm}(S_j)}^{{\textcolor{blue}{Minimize}}} )$}

                                          
         \end{block}                
         \end{femtoBlock}
                                          
         \end{block}                
         \end{femtoBlock}


@@ -386,39 +429,39 @@
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 15   %%
 %%%%%%%%%%%%%%%%%%%% 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 15   %%
 %%%%%%%%%%%%%%%%%%%% 

- \begin{frame}{Scaling factor selection algorithm}
-\vspace{-0.75cm}
-     \begin{center}
-      \includegraphics[width=.56 \textwidth]{c1/algo-homo}
-     \end{center}
+ %\begin{frame}{Scaling factor selection algorithm}
+%\vspace{-0.75cm}
+    % \begin{center}
+      %\includegraphics[width=.56 \textwidth]{c1/algo-homo}
+     %\end{center}

      
      

-\end{frame}
+%\end{frame}

 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 16   %%
 %%%%%%%%%%%%%%%%%%%% 
 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 16   %%
 %%%%%%%%%%%%%%%%%%%% 

-\begin{frame}{Scaling algorithm example}
+\begin{frame}{Scaling factor selection algorithm}

 \vspace{-0.75cm}
      
      \begin{figure}
 \vspace{-0.75cm}
      
      \begin{figure}

-  \animategraphics[autopause,controls,scale=0.28,buttonsize=0.2cm]{10}{dvfs-homo/a-}{0}{159}
-
+  \animategraphics[autopause,controls,scale=0.29,buttonsize=0.2cm]{10}{dvfs-homo/a-}{0}{335}
+  %\includegraphics[width=0.6\textwidth]{dvfs-homo/a-159}

   \end{figure}
 \end{frame}
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 17   %%
 %%%%%%%%%%%%%%%%%%%% 
   \end{figure}
 \end{frame}
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 17   %%
 %%%%%%%%%%%%%%%%%%%% 

-\begin{frame}{Experimental results }
+\begin{frame}{Experiment over SimGrid }

       \begin{femtoBlock}{}      
         \begin{itemize}
          \small
       \begin{femtoBlock}{}      
         \begin{itemize}
          \small

-           \item Our experiments are executed on the simulator SimGrid/SMPI v3.10.\medskip
-           \item Our algorithm is applied to  NAS parallel benchmarks.\medskip
+           \item The experiments were executed on the simulator SimGrid/SMPI v3.10.\medskip
+           \item The proposed algorithm was applied to the NAS parallel benchmarks.\medskip

            \item Each node in the cluster has 18 frequency values from \textbf{2.5$GHz$} to \textbf{800$MHz$}.\medskip
            \item Each node in the cluster has 18 frequency values from \textbf{2.5$GHz$} to \textbf{800$MHz$}.\medskip

-           \item We run the classes A, B and C on 4, 8 or 9 and 16 nodes respectively.\medskip
-           \item The dynamic power with the highest frequency is equal to \textbf{20 $W$} and the power static is equal to \textbf{4 $W$}.
+           \item The proposed algorithm was evaluated over the A, B and C classes of the benchmarks using 4, 8 or 9 and 16 nodes respectively. \medskip
+           \item $P_d=20W$,  $P_s=4W$.

                 \end{itemize}
         \end{femtoBlock}
 \end{frame}
                 \end{itemize}
         \end{femtoBlock}
 \end{frame}


@@ -434,6 +477,8 @@
      \includegraphics[width=.35\textwidth]{c1/cg}
      \includegraphics[width=.35\textwidth]{c1/bt}}
      
      \includegraphics[width=.35\textwidth]{c1/cg}
      \includegraphics[width=.35\textwidth]{c1/bt}}
      

+\hspace{0.5cm}     
+     

      \centering {\includegraphics[width=.55\textwidth]{c1/results.pdf}}
  \end{femtoBlock}
 \end{frame}
      \centering {\includegraphics[width=.55\textwidth]{c1/results.pdf}}
  \end{femtoBlock}
 \end{frame}


@@ -443,42 +488,46 @@
 %%    SLIDE 19   %%
 %%%%%%%%%%%%%%%%%%%% 
 \begin{frame}{Results comparison}
 %%    SLIDE 19   %%
 %%%%%%%%%%%%%%%%%%%% 
 \begin{frame}{Results comparison}

-         \begin{block}{\small Rauber and Rünger's optimal scaling factor} 
-           $S_{opt} = \sqrt[3]{\frac{2}{N} \cdot \frac{P_{dyn}}{P_{static}} \cdot
-            \left( 1 + \sum_{i=2}^{N} \frac{T_i^3}{T_1^3}\right) } $
-        \end{block}   
-    \centering {
-         %\includegraphics[width=.33\textwidth]{c1/c1.pdf}
-         %\qquad
-         %\includegraphics[width=.33\textwidth]{c1/c2.pdf}}
-           
+         \small \textcolor{blue}{Rauber and Rünger's  scaling factor  \textcolor{black}{ \tiny \textsuperscript{2}}}

          
          

-            \includegraphics[width=.55\textwidth]{c1/compare_c.pdf}}
+         \vspace{2 mm}
+         
+           $S_{opt} = \sqrt[3]{\frac{2}{N} \cdot \frac{P_{dyn}}{P_{static}} \cdot
+            \left( 1 + \sum_{i=2}^{N} \frac{T_i^3}{T_1^3}\right) } $ 
+     

         
         

+   \begin{center}
+            \includegraphics[width=.55\textwidth]{c1/compare-c.pdf}
+   \end{center}
+            
+                     
+\vspace{-2 mm}
+         \tiny \textsuperscript{2}  Thomas Rauber and Gudula Rünger. Analytical modeling and simulation of the energy consumption of  independent tasks. In Proceedings of the Winter Simulation Conference, 2012.

 \end{frame}
 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 20   %%
 %%%%%%%%%%%%%%%%%%%% 
 \end{frame}
 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 20   %%
 %%%%%%%%%%%%%%%%%%%% 

-\begin{frame}{The proposed new energy model}
-    \vspace{-0.75cm}     
-  \begin{figure}
-  \animategraphics[autopause,controls,scale=0.28,buttonsize=0.2cm]{10}{homo-model/a-}{0}{356}
-  \end{figure}
-\end{frame}
+%\begin{frame}{The proposed new energy model}
+   % \vspace{-0.75cm}     
+  %\begin{figure}
+ % \animategraphics[autopause,controls,scale=0.28,buttonsize=0.2cm]{10}{homo-model/a-}{0}{356}
+  %\includegraphics[width=0.6\textwidth]{homo-model/a-356}
+ % \end{figure}
+%\end{frame}

 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 21   %%
 %%%%%%%%%%%%%%%%%%%% 
 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 21   %%
 %%%%%%%%%%%%%%%%%%%% 

-\begin{frame}{Comparing the new model with Rauber model }
- \vspace{0.1cm}    
- \centering
-    \includegraphics[width=.45\textwidth]{c1/energy_con}
+%\begin{frame}{\large Comparing the new model with Rauber's model }
+% \vspace{0.1cm}    
+% \centering
+    %\includegraphics[width=.45\textwidth]{c1/energy_con}

     
     

-    \includegraphics[width=.5\textwidth]{c1/compare-scales}
-\end{frame}
+   %\includegraphics[width=.5\textwidth]{c1/compare-scales}
+%\end{frame}

 
 
 
 
 
 


@@ -505,13 +554,13 @@
 %%%%%%%%%%%%%%%%%%%% 
 
 
 %%%%%%%%%%%%%%%%%%%% 
 
 

-\begin{frame}{Contribution}
+\begin{frame}{The second contribution}

 
 

-\subsection{\small {3.2 Energy optimization of heterogeneous platform}}
+\section{\small {Energy optimization of a heterogeneous platform}}

 \begin{center}
 \begin{center}

-\bf \textcolor{black}{Second contribution} \\ 
-\vspace{1cm}
-\bf  \Large \textcolor{blue}{Energy optimization of Heterogeneous platform}
+
+
+\bf  \Large \textcolor{blue}{Energy optimization of a parallel application with iterations running over a Heterogeneous platform}

 \end{center}
  \end{frame}
  
 \end{center}
  \end{frame}
  


@@ -524,13 +573,13 @@
 \begin{frame}{Objectives}
         \begin{femtoBlock}{} \vspace{-12 mm}
                 \begin{itemize} \small
 \begin{frame}{Objectives}
         \begin{femtoBlock}{} \vspace{-12 mm}
                 \begin{itemize} \small

-                  \item   Evaluating the  \textcolor{blue}{new energy and performance models} of message passing  applications with iterations running  
-                          over a heterogeneous platform (cluster and Grid). \medskip
-                   \item  Study the effect of the scaling factor $S$ on both \textcolor{blue}{energy consumption  and the performance} of
+                  \item   Proposing  \textcolor{blue}{new energy and performance models} for message passing  applications with iterations running  
+                          over a heterogeneous platform (cluster or Grid). \medskip
+                   \item  Studying the effect of the scaling factor $S$ on both the \textcolor{blue}{energy consumption  and the performance} of

                           message passing iterative applications.    \medskip                      
                    
                           message passing iterative applications.    \medskip                      
                    

-                   \item  Computing  the vector of scaling factors ($S_1, S_2, ..., S_n$)  producing \textcolor{blue} {optimal trade-off} between
-                           energy consumption and performance. 
+                   \item  Computing  the vector of scaling factors ($S_1, S_2, ..., S_n$)  producing \textcolor{blue} {the good trade-off} between
+                          the energy consumption and the performance. 

                 \end{itemize}
                  
           \vspace{-10 mm}
                 \end{itemize}
                  
           \vspace{-10 mm}


@@ -564,27 +613,28 @@
  %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 25    %%
 %%%%%%%%%%%%%%%%%%%%
  %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 25    %%
 %%%%%%%%%%%%%%%%%%%%

- \begin{frame}{The energy consumption model} 
-    -The overall energy consumption of a message passing synchronous distributed application executed over a
-    heterogeneous platform is computed as  follows:
-    \begin{multline}
-     \label{eq:energy}
-     \textcolor{red}{E} = \textcolor{blue}{\sum_{i=1}^{N} {(S_i^{-2} \cdot Pd_i \cdot  Tcp_i)}} + {} \\
-     \textcolor{blue}{\sum_{i=1}^{N} (Ps_i \cdot (\max_{i=1,2,\dots,N} (Tcp_i \cdot S_{i}) + {\min_{i=1,2,\dots,N} (Tcm_i))}}   
-      \hspace{10 mm}
-    \end{multline}
-    \underline{where}:\\
-    \textcolor{blue}{N} : is the number of nodes.
-\end{frame}
+ %\begin{frame}{The energy consumption model} 
+   % The overall energy consumption of a message passing synchronous  application executed over
+   %  a heterogeneous platform can be computed as  follows:
+   % \begin{multline}
+    % \label{eq:energy}
+   %  \textcolor{red}{E} = \textcolor{blue}{\sum_{i=1}^{N} {(S_i^{-2} \cdot Pd_i \cdot  Tcp_i)}} + {} \\
+  %   \textcolor{blue}{\sum_{i=1}^{N} (Ps_i \cdot (\max_{i=1,2,\dots,N} (Tcp_i \cdot S_{i}) + {\min_{i=1,2,\dots,N} (Tcm_i))}}   
+   %   \hspace{10 mm}
+   % \end{multline}
+   % \underline{where}:\\
+   % \textcolor{blue}{N} : is the number of nodes.
+%\end{frame}

  
  
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 26    %%
 %%%%%%%%%%%%%%%%%%%%
  
  
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 26    %%
 %%%%%%%%%%%%%%%%%%%%

-  \begin{frame}{The  energy  model example for heter. cluster}
-  \vspace{-0.5cm}
+  \begin{frame}{The energy  model  for heterogeneous cluster}
+  \vspace{-0.77cm}

  \begin{figure}
  \begin{figure}

-  \animategraphics[autopause,controls,scale=0.28,buttonsize=0.2cm]{10}{heter-model/a-}{0}{272}
+  \animategraphics[autopause,controls,scale=0.3,buttonsize=0.2cm]{10}{heter-model/a-}{0}{350}
+  %\includegraphics[width=0.6\textwidth]{heter-model/a-272}

   \end{figure}
  \end{frame}
  
   \end{figure}
  \end{frame}
  


@@ -594,47 +644,48 @@
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 27    %%
 %%%%%%%%%%%%%%%%%%%%
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 27    %%
 %%%%%%%%%%%%%%%%%%%%

-\begin{frame}{The trade-off between energy  and performance}
-    \vspace{-7 mm}
-    \begin{figure}
-     \centering{ \includegraphics[width=.4\textwidth]{c2/heter}}
-    \end{figure}
-    \vspace{-7 mm}
-    \textcolor{red}{\underline{Step1}}: computing the normalized energy \textcolor{blue}{$E_{norm} = \frac{E_{reduced}} 
-     {E_{Max}}$}. \\
-     \textcolor{red}{\underline{Step2}}: computing the normalized performance \textcolor{blue}{$P_{norm} = \frac{T_{Max}}{T_{new}}$}.
+%\begin{frame}{The trade-off between energy  and performance}
+   % \vspace{-7 mm}
+    %\begin{figure}
+   %  \centering{ \includegraphics[width=.4\textwidth]{c2/heter}}
+   % \end{figure}
+   % \vspace{-7 mm}
+   % \textcolor{red}{\underline{Step1}}: computing the normalized energy \textcolor{blue}%{$E_{norm} = \frac{E_{reduced}} 
+    %{E_{Max}}$}. \\
+    % \textcolor{red}{\underline{Step2}}: computing the normalized performance \textcolor{blue}{$P_{norm} = \frac{T_{Max}}{T_{new}}$}.

    
    

-     \begin{block}{\small The tradeoff model}
-     \begin{equation}
-      \label{eq:max}
-      \textcolor{red}{MaxDist} =
-      \mathop {\max_{i=1,\dots F}}_{j=1,\dots,N}
-       (\overbrace{P_{norm}(S_{ij})}^{\text{\textcolor{blue}{Maximize}}} -
-       \overbrace{E_{norm}(S_{ij})}^{\text{\textcolor{blue}{Minimize}}} )
-      \end{equation}
-     \end{block}  
-\end{frame}
+   %  \begin{block}{\small The tradeoff model}
+    % \begin{equation}
+    %  \label{eq:max}
+    %  \textcolor{red}{MaxDist} =
+     % \mathop {\max_{i=1,\dots F}}_{j=1,\dots,N}
+      % (\overbrace{P_{norm}(S_{ij})}^{\text{\textcolor{blue}{Maximize}}} -
+      % \overbrace{E_{norm}(S_{ij})}^{\text{\textcolor{blue}{Minimize}}} )
+      %\end{equation}
+    % \end{block}  
+%\end{frame}

    
  
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 28    %%
 %%%%%%%%%%%%%%%%%%%%
    
  
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 28    %%
 %%%%%%%%%%%%%%%%%%%%

- \begin{frame}{The scaling algorithm for heter. cluster}
+ %\begin{frame}{The scaling algorithm for heter. cluster}

 
 

- \centering
-   \includegraphics[width=.52\textwidth]{algo-heter}
- \end{frame}
+ %\centering
+   %\includegraphics[width=.52\textwidth]{algo-heter}
+ %\end{frame}

  
  
  %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 29    %%
 %%%%%%%%%%%%%%%%%%%%
  
  
  %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 29    %%
 %%%%%%%%%%%%%%%%%%%%

- \begin{frame}{The scaling algorithm example}
- \vspace{-0.5cm}
+ \begin{frame}{The scaling algorithm for heter. cluster}
+ \vspace{-0.77cm}

  \centering
  
   \begin{figure}
  \centering
  
   \begin{figure}

-  \animategraphics[autopause,controls,scale=0.28,buttonsize=0.2cm]{10}{dvfs-heter/a-}{0}{650}
+  \animategraphics[autopause,controls,scale=0.3,buttonsize=0.2cm]{10}{dvfs-heter/a-}{0}{836}
+ % \includegraphics[width=0.6\textwidth]{dvfs-heter/a-650}

   \end{figure}
 \end{frame}
 
   \end{figure}
 \end{frame}
 


@@ -644,134 +695,112 @@
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 30    %%
 %%%%%%%%%%%%%%%%%%%%
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 30    %%
 %%%%%%%%%%%%%%%%%%%%

-\begin{frame}{Experiments over heterogeneous cluster  }   
-        \begin{itemize}
-         \small
-           \item The experiments executed on the simulator SimGrid/SMPI v3.10.\medskip
-           \item The scaling algorithm was applied to the NAS parallel benchmarks class C.\medskip
-           \item Four types of processors with different computing powers were used.\medskip
-           \item We ran the benchmarks on different number of nodes ranging from 4 to 144 nodes.\medskip
-           \item The total power consumption of the chosen CPUs  is composed of $80\%$ for dynamic power and $20\%$ for static power.
-                  \medskip
+%\begin{frame}{Experiments over a heterogeneous cluster  }   
+      %  \begin{itemize}
+        % \small
+          % \item The experiments were executed on the simulator SimGrid/SMPI v3.10.\medskip
+          % \item The scaling algorithm was applied to the NAS parallel benchmarks class C.\medskip
+          % \item Four types of processors with different computing powers were used.\medskip
+          % \item The benchmarks were executed with different number of nodes ranging from 4 to 144 nodes.\medskip
+          % \item It was assumed that the total power consumption of the CPU consist of 80\% dynamic power and 20\% static power.
+                 % \medskip

          
          

-        \end{itemize}
+        %\end{itemize}

 
 

-\end{frame}  
+%\end{frame}  

 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 31    %%
 %%%%%%%%%%%%%%%%%%%%
 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 31    %%
 %%%%%%%%%%%%%%%%%%%%

-\begin{frame}{The experimental results}
-   \vspace{-5 mm}
-   \begin{figure}[!t]
-   \centering
-    \includegraphics[width=0.8\textwidth]{c2/energy_saving.pdf}
+%\begin{frame}{The simulation results}
+  % \vspace{-5 mm}
+  % \begin{figure}[!t]
+   %\centering
+    %\includegraphics[width=0.8\textwidth]{c2/energy_saving.pdf}

     
     

-    \textcolor{blue}{On average, it saves the energy consumption by \textcolor{red}{29\%} 
-     of NAS benchmarks class C executed over 8 nodes}
+   % \textcolor{blue}{On average, it reduces the energy consumption by \textcolor{red}{29\%} 
+     %for the class C of the NAS Benchmarks executed over 8 nodes}

     
     

-   \end{figure}
-\end{frame} 
+  % \end{figure}
+%\end{frame} 

  
  
  
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 32    %%
 %%%%%%%%%%%%%%%%%%%%
  
  
  
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 32    %%
 %%%%%%%%%%%%%%%%%%%%

-\begin{frame}{The experimental results}
-   \vspace{-5 mm}
-   \begin{figure}[!t]
-   \centering
+%\begin{frame}{The simulation results}
+ %  \vspace{-5 mm}
+  % \begin{figure}[!t]
+  % \centering

     
     

-    \includegraphics[width=.8\textwidth]{c2/perf_degra.pdf}
+   % \includegraphics[width=.8\textwidth]{c2/perf_degra.pdf}

    
    

-   \textcolor{blue}{On average, it degrades the performance by \textcolor{red}{3.8\%} 
-     of NAS benchmarks class C executed over 8 nodes}
-     \end{figure}
-\end{frame} 
+  % \textcolor{blue}{On average, it degrades  by \textcolor{red}{3.8\%} the performance
+    % of NAS Benchmarks class C executed over 8 nodes}
+  %   \end{figure}
+%\end{frame} 

  
  
  
  
  
  

-%%%%%%%%%%%%%%%%%%%%
-%%    SLIDE 33    %%
-%%%%%%%%%%%%%%%%%%%%
-\begin{frame}{The results of the three powers scenarios}
-   \vspace{-5 mm}
-   \begin{figure}[!t]
-   \centering
-   \includegraphics[width=.55\textwidth]{c2/three_power.pdf}
-   \vspace{10 mm}
-   \includegraphics[width=.55\textwidth]{c2/three_scenarios.pdf}
-   \end{figure}
-\end{frame}  

 
 
 
 
 
 

-%%%%%%%%%%%%%%%%%%%%
-%%    SLIDE 34    %%
-%%%%%%%%%%%%%%%%%%%%
-\begin{frame}{The comparing our method}
-    The proposed method (MaxDist) was compared to the EDP algorithm that minimizes  the \textcolor{blue}{
-    $\mathit{energy}\times \mathit{delay}$} value.
-    \vspace{-5 mm}
-    \begin{figure}[!t]
-    \centering
-    \includegraphics[width=.55\textwidth]{c2/avg_compare.pdf}
-    
-    \includegraphics[width=.55\textwidth]{c2/compare_with_EDP.pdf}
-    \end{figure}
-\end{frame} 
-
-

 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 35    %%
 %%%%%%%%%%%%%%%%%%%%
 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 35    %%
 %%%%%%%%%%%%%%%%%%%%

-\begin{frame}{Energy optimization of grid platform} 
-   \begin{figure}[!t]
-    \centering
-             \includegraphics[width=.6\textwidth]{c2/grid5000.pdf}
+%\begin{frame}{Energy optimization of grid platform} 
+  % \begin{figure}[!t]
+   % \centering
+         %    \includegraphics[width=.6\textwidth]{c2/grid5000.pdf}

              
              

-           \small  10 sites distributed over France and Luxembourg
-        \end{figure}
-\end{frame} 
+        %   \small  10 sites distributed over France and Luxembourg
+        %\end{figure}
+%\end{frame} 

 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 36    %%
 %%%%%%%%%%%%%%%%%%%%
 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 36    %%
 %%%%%%%%%%%%%%%%%%%%

- \begin{frame}{Performance, Energy and trade-off models} \small
-  \begin{block}{\small The performance model of grid}
-    \begin{equation}
-  \label{eq:perf}
-  \Tnew = \mathop{\max_{i=1,\dots N}}_{j=1,\dots,M_i}({\TcpOld[ij]} \cdot S_{ij}) 
-  +\mathop{\min_{j=1,\dots,M_h}}  (\Tcm[hj])
-\end{equation}
-    \end{block}   
+%\begin{frame}{The grid architecture}
+%\begin{center}
+%\includegraphics[width=.8\textwidth]{c2/init_freq.pdf}
+%\end{center}
+
+ %\begin{frame}{Performance, Energy and trade-off models} \small
+  %\begin{block}{\small The performance model of grid}
+   % \begin{equation}
+  %\label{eq:perf}
+  %\Tnew = \mathop{\max_{i=1,\dots N}}_{j=1,\dots,M_i}({\TcpOld[ij]} \cdot S_{ij}) 
+ % +\mathop{\min_{j=1,\dots,M_h}}  (\Tcm[hj])
+%\end{equation}
+    %\end{block}   

  
  
  
  

- \begin{block}{\small The energy model of grid}\small
-    \begin{equation}
-  \label{eq:energy}
- E = \sum_{i=1}^{N} \sum_{i=1}^{M_i} {(S_{ij}^{-2} \cdot \Pd[ij] \cdot  \Tcp[ij])} +  
- \sum_{i=1}^{N} \sum_{j=1}^{M_i} (\Ps[ij] \cdot \Tnew)
-\end{equation}
-    \end{block}  
-
-\begin{block}{\small The trade-off model of grid}
-\small
-    \begin{equation}
-   \label{eq:max}
-  \MaxDist =
-  \mathop{  \mathop{\max_{i=1,\dots N}}_{j=1,\dots,M_i}}_{k=1,\dots,F_j}
-      (\overbrace{\Pnorm(S_{ijk})}^{\text{Maximize}} -
-       \overbrace{\Enorm(S_{ijk})}^{\text{Minimize}} )
-\end{equation}
-    \end{block}  
+ %\begin{block}{\small The energy model of grid}\small
+  %  \begin{equation}
+  %\label{eq:energy}
+ %E = \sum_{i=1}^{N} \sum_{i=1}^{M_i} {(S_{ij}^{-2} \cdot \Pd[ij] \cdot  \Tcp[ij])} +  
+% \sum_{i=1}^{N} \sum_{j=1}^{M_i} (\Ps[ij] \cdot \Tnew)
+%\end{equation}
+   % \end{block}  
+
+%\begin{block}{\small The trade-off model of grid}
+%\small
+    %\begin{equation}
+   %\label{eq:max}
+  %\MaxDist =
+  %\mathop{  \mathop{\max_{i=1,\dots N}}_{j=1,\dots,M_i}}_{k=1,\dots,F_j}
+   %   (\overbrace{\Pnorm(S_{ijk})}^{\text{Maximize}} -
+    %   \overbrace{\Enorm(S_{ijk})}^{\text{Minimize}} )
+%\end{equation}
+   % \end{block}  

      
      

- \end{frame}
+     
+ %\end{frame}

   
   
   
   
   
   


@@ -779,18 +808,21 @@
 %%    SLIDE 37    %%
 %%%%%%%%%%%%%%%%%%%%
  \begin{frame}{Experiments over Grid'5000}
 %%    SLIDE 37    %%
 %%%%%%%%%%%%%%%%%%%%
  \begin{frame}{Experiments over Grid'5000}

-  \centering
-
+ 
+   \textcolor{blue}{The experiments were conducted using three 
+          clusters distributed over one or two sites.}
+           \vspace{-7 mm}
+          \begin{center}

           \includegraphics[width=.5\textwidth]{c2/grid5000-2.pdf}
           \includegraphics[width=.5\textwidth]{c2/grid5000-2.pdf}

-          
-          \vspace{-3 mm}
-          \textcolor{blue}{The experiments executed over one site and two sites scenarios}
-          
-              \vspace{1mm}
-
+          \end{center}          
+      \vspace{-10 mm}
+  \textcolor{blue}{Grid'5000 power measurement tools were used.} 
+        \vspace{-9 mm}
+  \begin{center}

           \includegraphics[width=.5\textwidth]{c2/power_consumption.pdf}
           \includegraphics[width=.5\textwidth]{c2/power_consumption.pdf}

+          \end{center}

           
           

-        \textcolor{blue}{We used Grid'5000 power measurement tools} 
+      

 \end{frame}   
 
 
 \end{frame}   
 
 


@@ -802,8 +834,9 @@
 \begin{frame}{Experiments over Grid'5000}
 
    \begin{minipage}{0.4\textwidth}
 \begin{frame}{Experiments over Grid'5000}
 
    \begin{minipage}{0.4\textwidth}

-       \textcolor{blue}{Execution the NAS class D on 16 nodes saves the energy by  
-        \textcolor{red}{30\%}}
+       %\textcolor{blue}{Execution the NAS class D on 16 nodes saves the energy by  
+        %\textcolor{red}{30\%}}
+     \small \textcolor{blue}{The average energy saving =  \textcolor{red}{30\%}}

    \end{minipage}  
      \begin{minipage}{0.55\textwidth}
         \begin{figure}[h!]
    \end{minipage}  
      \begin{minipage}{0.55\textwidth}
         \begin{figure}[h!]


@@ -812,8 +845,9 @@
 \end{minipage}
 
          \begin{minipage}{0.4\textwidth}
 \end{minipage}
 
          \begin{minipage}{0.4\textwidth}

-           \textcolor{blue}{Execution the NAS class D on 16 nodes degrades the 
-                performance by \textcolor{red}{3.2\%}}
+           %\textcolor{blue}{Execution the NAS class D on 16 nodes degrades the 
+                %performance by \textcolor{red}{3.2\%}}
+      \small  \textcolor{blue}{The average performance degradation  =  \textcolor{red}{3.2\%}}  

         \end{minipage}
        \begin{minipage}{0.55\textwidth}
          \begin{figure}[h!] 
         \end{minipage}
        \begin{minipage}{0.55\textwidth}
          \begin{figure}[h!] 


@@ -824,11 +858,32 @@
 
 
 
 
 
 

+%%%%%%%%%%%%%%%%%%%%
+%%    SLIDE 33    %%
+%%%%%%%%%%%%%%%%%%%%
+\begin{frame}{The results of the three power scenarios}
+   \vspace{-5 mm}
+   \begin{figure}[!t]
+   \centering
+   \includegraphics[width=.45\textwidth]{c2/eng_pow.eps}
+   \hspace{0.3cm}
+   \includegraphics[width=.45\textwidth]{c2/per_pow.eps}
+   \vspace{4 mm}
+   \includegraphics[width=.7\textwidth]{c2/three_scenarios.pdf}
+   \end{figure}
+\end{frame}  
+
+
+
+
+
+
+

 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 39    %%
 %%%%%%%%%%%%%%%%%%%%
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 39    %%
 %%%%%%%%%%%%%%%%%%%%

-\begin{frame}{Experiments over Grid'5000}
-   \textcolor{blue}{One core  and Multi-cores per node results:}
+\begin{frame}{One core and Multi-cores per node results}
+   %\textcolor{blue}{One core  and Multi-cores per node results:}

    
   \begin{figure}[h!] 
   \includegraphics[width=.48\textwidth]{c2/eng_s_mc.eps}
    
   \begin{figure}[h!] 
   \includegraphics[width=.48\textwidth]{c2/eng_s_mc.eps}


@@ -836,11 +891,26 @@
   \includegraphics[width=.48\textwidth]{c2/per_d_mc.eps}
   \end{figure} 
   
   \includegraphics[width=.48\textwidth]{c2/per_d_mc.eps}
   \end{figure} 
   

-  \centering \small \textcolor{blue}{Using multi-core per node scenario decreases the computations to communications ratio}.
+  \centering \small \textcolor{blue}{Using multi-cores per node scenario decreases the computations to communications ratio}.

 \end{frame}
 
 
 \end{frame}
 
 

-
+%%%%%%%%%%%%%%%%%%%%
+%%    SLIDE 34    %%
+%%%%%%%%%%%%%%%%%%%%
+\begin{frame}{Comparing the objective function to EDP}
+     
+     EDP is the product between the energy consumption and the delay \tiny\textsuperscript{3}.
+    \vspace{-5 mm}
+    \begin{figure}[!t]
+    \centering
+    \includegraphics[width=.6\textwidth]{c2/edp_dist.eps}
+    
+  
+    \end{figure}
+    
+  \tiny  \textsuperscript{3} Spiliopoulos et al, Green governors: A framework for continuously adaptive dvfs, in International Green Computing Conference and Workshops (IGCC), 2011.
+\end{frame} 

 %\begin{frame}{Summary}
 %\begin{itemize}
      % \small
 %\begin{frame}{Summary}
 %\begin{itemize}
      % \small


@@ -864,12 +934,10 @@
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 40    %%
 %%%%%%%%%%%%%%%%%%%%
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 40    %%
 %%%%%%%%%%%%%%%%%%%%

-\begin{frame}{Continuation}
-\subsection{\small {3.3 Energy optimization of asynchronous applications}}
+\begin{frame}{The third contribution}
+\section{\small {Energy optimization of asynchronous applications}}

 \begin{center}
 \begin{center}

-\bf \textcolor{black}{Third contribution} \\ 
-\vspace{1cm}
-\bf  \Large \textcolor{blue}{Energy optimization of asynchronous applications}
+\bf  \Large \textcolor{blue}{Energy optimization of asynchronous iterative message passing  applications}

 \end{center}
  \end{frame}
 
 \end{center}
  \end{frame}
 


@@ -879,10 +947,11 @@
 %%    SLIDE 41   %%
 %%%%%%%%%%%%%%%%%%%%
 \begin{frame}{Problem definition}\vspace{0.8 mm}
 %%    SLIDE 41   %%
 %%%%%%%%%%%%%%%%%%%%
 \begin{frame}{Problem definition}\vspace{0.8 mm}

-\textcolor{blue}{Execution the parallel iterative application with synchronous communications }
+\textcolor{blue}{The execution of a synchronous parallel iterative application over a grid }

 \vspace{-8 mm}
 \begin{figure}
 \vspace{-8 mm}
 \begin{figure}

-  \animategraphics[autopause,controls,scale=0.25,buttonsize=0.2cm]{10}{syn/a-}{0}{503}
+ \animategraphics[autopause,controls,scale=0.26,buttonsize=0.2cm]{10}{syn/a-}{0}{647}
+ %\includegraphics[width=0.6\textwidth]{syn/a-503}

   \end{figure}
 \end{frame}
 
   \end{figure}
 \end{frame}
 


@@ -892,10 +961,11 @@
 %%    SLIDE 42   %%
 %%%%%%%%%%%%%%%%%%%%
 \begin{frame}{Problem definition}\vspace{0.8 mm}
 %%    SLIDE 42   %%
 %%%%%%%%%%%%%%%%%%%%
 \begin{frame}{Problem definition}\vspace{0.8 mm}

-\textcolor{blue}{Execution the parallel iterative application with synchronous communications }
+\textcolor{blue}{The execution of an asynchronous parallel iterative application over a grid }

 \vspace{-8 mm}
 \begin{figure}
 \vspace{-8 mm}
 \begin{figure}

-  \animategraphics[autopause,controls,scale=0.25,buttonsize=0.2cm]{10}{asyn/a-}{0}{440}
+ \animategraphics[autopause,controls,scale=0.26,buttonsize=0.2cm]{10}{asyn/a-}{0}{556}
+ %\includegraphics[width=0.6\textwidth]{asyn/a-440}

   \end{figure}
 \end{frame}
 
   \end{figure}
 \end{frame}
 


@@ -908,7 +978,8 @@
 \textcolor{blue}{Using asynchronous communications with DVFS }
 \vspace{-8 mm}
 \begin{figure}
 \textcolor{blue}{Using asynchronous communications with DVFS }
 \vspace{-8 mm}
 \begin{figure}

-  \animategraphics[autopause,controls,scale=0.25,buttonsize=0.2cm]{10}{asyn+dvfs/a-}{0}{314}
+  \animategraphics[autopause,controls,scale=0.26,buttonsize=0.2cm]{10}{asyn+dvfs/a-}{0}{344}
+  %\includegraphics[width=0.6\textwidth]{asyn+dvfs/a-314}

   \end{figure}
 \end{frame}
 
   \end{figure}
 \end{frame}
 


@@ -918,77 +989,93 @@
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 44   %%
 %%%%%%%%%%%%%%%%%%%%
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 44   %%
 %%%%%%%%%%%%%%%%%%%%

-\begin{frame}{The performance models}
+%\begin{frame}{The performance models}

 
 

-\begin{block}{\small The performance model of Asynch. Applications}\small
-\begin{equation}
-  \label{eq:asyn_time}
-  \Tnew =  \frac{\sum_{i=1}^{N} \sum_{j=1}^{M_i}({\TcpOld[ij]} \cdot S_{ij})} {N  \cdot M_i }
-\end{equation}
-\end{block}
+%\begin{block}{\small The performance model of Asynch. Applications}\small
+%\begin{equation}
+  %\label{eq:asyn_time}
+ %\Tnew =  \frac{\sum_{i=1}^{N} \sum_{j=1}^{M_i}({\TcpOld[ij]} \cdot S_{ij})} {N  \cdot M_i }
+%\end{equation}
+%\end{block}

 
 
 
 

-\begin{block}{\small The performance model of Hybrid Applications}\small
-\begin{equation}
-  \label{eq:asyn_perf}
-  \Tnew =  \frac{\sum_{i=1}^{N} (\max_{j=1,\dots, M_i} ({\TcpOld[ij]} \cdot S_{ij}) +  
-   \min_{j=1,\dots,M_i} ({\Ltcm[ij]}))}{N}
-\end{equation}
-\end{block}
+%\begin{block}{\small The performance model of Hybrid Applications}\small
+%\begin{equation}
+  %\label{eq:asyn_perf}
+  %\Tnew =  \frac{\sum_{i=1}^{N} (\max_{j=1,\dots, M_i} ({\TcpOld[ij]} \cdot S_{ij}) +  
+   %\min_{j=1,\dots,M_i} ({\Ltcm[ij]}))}{N}
+%\end{equation}
+%\end{block}

 
 
 
 

-\end{frame}
+%\end{frame}

 
 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 45   %%
 %%%%%%%%%%%%%%%%%%%%
 
 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 45   %%
 %%%%%%%%%%%%%%%%%%%%

-\begin{frame}{The energy consumption models}
+%\begin{frame}{The energy consumption models}

 
 

-\begin{block}{\small The energy model of Asynch. Applications}\small
-\begin{equation}
-  \label{eq:asyn_energy1}
- E = \sum_{i=1}^{N} \sum_{j=1}^{M_i} {(S_{ij}^{-2} \cdot  \Tcp[ij] \cdot (\Pd[ij]+\Ps[ij]) )} 
-\end{equation} 
-\end{block}
+%\begin{block}{\small The energy model of Asynch. Applications}\small
+%\begin{equation}
+  %\label{eq:asyn_energy1}
+% E = \sum_{i=1}^{N} \sum_{j=1}^{M_i} {(S_{ij}^{-2} \cdot  \Tcp[ij] \cdot (\Pd[ij]+\Ps[ij]) )} 
+%\end{equation} 
+%\end{block}

 
 
 
 

-\begin{block}{\small The energy model of Hybrid Applications}\small
-\begin{multline}
-  \label{eq:asyn_energy}
- E = \sum_{i=1}^{N} \sum_{j=1}^{M_i} {(S_{ij}^{-2} \cdot \Pd[ij] \cdot  \Tcp[ij])} +  \sum_{i=1}^{N} \sum_{j=1}^{M_i} (\Ps[ij] \cdot \\
- ( \mathop{\max_{j=1,\dots,M_i}} ({\Tcp[ij]} \cdot S_{ij}) + \mathop{\min_{j=1,\dots,M_i}} ({\Ltcm[ij]}))) 
-\end{multline}
-\end{block}
-\end{frame}
+%\begin{block}{\small The energy model of Hybrid Applications}\small
+%\begin{multline}
+  %\label{eq:asyn_energy}
+ %E = \sum_{i=1}^{N} \sum_{j=1}^{M_i} {(S_{ij}^{-2} \cdot \Pd[ij] \cdot  \Tcp[ij])} +  \sum_{i=1}^{N} \sum_{j=1}^{M_i} (\Ps[ij] \cdot \\
+% ( \mathop{\max_{j=1,\dots,M_i}} ({\Tcp[ij]} \cdot S_{ij}) + \mathop{\min_{j=1,\dots,M_i}} ({\Ltcm[ij]}))) 
+%\end{multline}
+%\end{block}
+%\end{frame}

 
 
 
 %%%%%%%%%%%%%%%%%%%%
 
 
 
 %%%%%%%%%%%%%%%%%%%%

-%%    SLIDE 46   %%
+%%    SLIDE 44   %%

 %%%%%%%%%%%%%%%%%%%%
 %%%%%%%%%%%%%%%%%%%%

-\begin{frame}{The scaling algorithm for Asynch.  applications}
-\vspace{-0.1 mm}
+\begin{frame}{The performance and the energy models }
+

 \centering
 \centering

-\includegraphics[width=0.55\textwidth]{algo-hybrid.pdf}
+\includegraphics[width=0.9\textwidth]{syn-vs-asyn.pdf}

 \end{frame}
 
 
 
 \end{frame}
 
 
 

+
+
+%%%%%%%%%%%%%%%%%%%%
+%%    SLIDE 46   %%
+%%%%%%%%%%%%%%%%%%%%
+%\begin{frame}{The scaling algorithm for Asynch.  applications}
+%\vspace{-0.1 mm}
+%\centering
+%\includegraphics[width=0.55\textwidth]{algo-hybrid.pdf}
+%\end{frame}
+
+
+

 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 47   %%
 %%%%%%%%%%%%%%%%%%%%
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 47   %%
 %%%%%%%%%%%%%%%%%%%%

-\begin{frame}{The experimental results}
+\begin{frame}{The experiments}

    \vspace{-5 mm}
    \begin{figure}[!t]
    \vspace{-5 mm}
    \begin{figure}[!t]

-   \centering
+   \begin{itemize}
+      \small
+        \item The architecture of the grid:
+   \end{itemize}

     \includegraphics[width=0.5\textwidth]{c3/hybrid-model.pdf} 
    \end{figure}
    \begin{itemize}
       \small
     \includegraphics[width=0.5\textwidth]{c3/hybrid-model.pdf} 
    \end{figure}
    \begin{itemize}
       \small

-        \item Execution the iterative multi-splitting method over simulated Grid.
-        \item Execution the iterative multi-splitting method over Grid'5000 test-bed.
+        \item Applying the proposed algorithm to the asynchronous iterative message passing multi-splitting method.
+        \item Evaluating the application over the simulator and Grid'5000.

    \end{itemize}
 \end{frame} 
 
    \end{itemize}
 \end{frame} 
 


@@ -997,27 +1084,27 @@
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 48   %%
 %%%%%%%%%%%%%%%%%%%%
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 48   %%
 %%%%%%%%%%%%%%%%%%%%

-\begin{frame}{The simulation results}
-\centering \small \textcolor{blue}{The best scenario in term of energy and performance  is the Async. MS with Sync. DVFS}
+%\begin{frame}{The simulation results}
+%\centering \small \textcolor{blue}{The best scenario in terms of energy and performance  is %the Async. MS with Sync. DVFS}

 
 

-\centering
-    \includegraphics[scale=0.46]{c3/energy_saving.eps}
+%\centering
+   % \includegraphics[scale=0.42]{c3/energy_saving.eps}

 
 

- \centering  The average of energy saving  = \textcolor{red}{22\%}
-\end{frame} 
+ %\centering  The average energy saving  = \textcolor{red}{22\%}
+%\end{frame} 

 
 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 49   %%
 %%%%%%%%%%%%%%%%%%%%
 
 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 49   %%
 %%%%%%%%%%%%%%%%%%%%

-\begin{frame}{The simulation results}
-\centering
+%\begin{frame}{The simulation results}
+%\centering

    
    

-     \includegraphics[scale=0.46]{c3/perf_degra.eps}
+   %  \includegraphics[scale=0.42]{c3/perf_degra.eps}

      
      

- \centering    The average of  speed-up  = \textcolor{red}{5.72\%}
-\end{frame} 
+%\centering    The average speed-up  = \textcolor{red}{5.72\%}
+%\end{frame} 

 
 
 
 
 
 


@@ -1025,7 +1112,7 @@
 %%    SLIDE 50   %%
 %%%%%%%%%%%%%%%%%%%%
  \begin{frame}{The Grid'5000 results}
 %%    SLIDE 50   %%
 %%%%%%%%%%%%%%%%%%%%
  \begin{frame}{The Grid'5000 results}

-   \vspace{-20 mm}
+   \vspace{-10 mm}

    \begin{figure}[!t]
    \centering
    \hspace{-8 mm}
    \begin{figure}[!t]
    \centering
    \hspace{-8 mm}


@@ -1033,8 +1120,11 @@
     \includegraphics[width=0.53\textwidth]{c3/perf-deg-compare.eps}
    \end{figure}
     \vspace{-5 mm}
     \includegraphics[width=0.53\textwidth]{c3/perf-deg-compare.eps}
    \end{figure}
     \vspace{-5 mm}

-     \centering
-   The energy saving = \textcolor{red}{26.93\%}, speeds up =  \textcolor{red}{21.48\%}
+     \centering \footnotesize
+     
+     %\small \textcolor{blue}{The best scenario in terms of energy and performance  is the Async. MS with Sync. DVFS}
+     
+The average energy saving = \textcolor{red}{26.93\%}, the average speed-up =  \textcolor{red}{21.48\%}

 \end{frame} 
 
 
 \end{frame} 
 
 


@@ -1055,26 +1145,24 @@
 %%    SLIDE 52  %%
 %%%%%%%%%%%%%%%%%%%%
 \begin{frame}{Conclusions}
 %%    SLIDE 52  %%
 %%%%%%%%%%%%%%%%%%%%
 \begin{frame}{Conclusions}

-\section{Conclusions}
+\section{Conclusions and Perspectives}

 \begin{itemize}
 
 \begin{itemize}
 

-\small  \barrow  We have proposed \textcolor{blue}{a new energy consumption and performance} models for 
-     synchronous and asynchronous parallel applications with iterations.
-     
+\small  \barrow  Three \textcolor{blue}{ new energy consumption and performance} models were proposed for synchronous or asynchronous parallel applications with iterations running over 
+\textcolor{blue}{homogeneous and  heterogeneous clusters or grids}.  

       
       

-\small \barrow The parallel applications with iterations were executed over different parallel architectures such as: \textcolor{blue}{homogeneous  cluster, heterogeneous  cluster and
-grid}.

 
 

-\small \barrow We have proposed \textcolor{blue}{new objective function} to optimize both the energy consumption and the performance.
+
+\small \barrow \textcolor{blue}{A new objective function} to optimize both the energy consumption and the performance was proposed.

 
 \small \barrow \textcolor{blue}{New online frequency selecting algorithms} for clusters and grids were developed.
 
 \small \barrow The proposed algorithms were applied to the \textcolor{blue}{NAS parallel benchmarks} and \textcolor{blue}{the
 Multi-splitting} method.
 
 
 \small \barrow \textcolor{blue}{New online frequency selecting algorithms} for clusters and grids were developed.
 
 \small \barrow The proposed algorithms were applied to the \textcolor{blue}{NAS parallel benchmarks} and \textcolor{blue}{the
 Multi-splitting} method.
 

-\small \barrow The proposed algorithms were evaluated over the \textcolor{blue}{SimGrid simulator and over  Grid'5000 testbed}.
+\small \barrow The proposed algorithms were evaluated over the \textcolor{blue}{SimGrid simulator} and over  the \textcolor{blue}{Grid'5000 testbed}.

 
 

-\small  \barrow All the proposed methods were compared with either \textcolor{blue}{Rauber and Rünger  method} or  \textcolor{blue}{EDP objective function}.
+\small  \barrow All the proposed methods were compared to either \textcolor{blue}{Rauber and Rünger's  method} or to the \textcolor{blue}{EDP objective function}.

 
 
 \end{itemize}
 
 
 \end{itemize}


@@ -1085,7 +1173,7 @@ Multi-splitting} method.
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 53   %%
 %%%%%%%%%%%%%%%%%%%%
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 53   %%
 %%%%%%%%%%%%%%%%%%%%

-\begin{frame}{Publication}
+\begin{frame}{Publications}

 
 \begin{block}{\small Journal Articles }\scriptsize
 \begin{enumerate}[$\lbrack$1$\rbrack$]
 
 \begin{block}{\small Journal Articles }\scriptsize
 \begin{enumerate}[$\lbrack$1$\rbrack$]


@@ -1094,7 +1182,7 @@ Multi-splitting} method.
       Science}, 2016.
 
 \item Ahmed Fanfakh, Jean-Claude Charr, Raphaël Couturier,  Arnaud Giersch. Energy Consumption Reduction for     
       Science}, 2016.
 
 \item Ahmed Fanfakh, Jean-Claude Charr, Raphaël Couturier,  Arnaud Giersch. Energy Consumption Reduction for     

-      Asynchronous Message Passing Applications.  \textit{Journal of Supercomputing}, 2016, (Submitted)
+      Asynchronous Message Passing Applications.  \textit{Journal of Supercomputing}, 2016, (Accepted with minor revisions)

  
 \end{enumerate}
 \end{block}
  
 \end{enumerate}
 \end{block}


@@ -1126,11 +1214,10 @@ Multi-splitting} method.
 %%    SLIDE 54   %%
 %%%%%%%%%%%%%%%%%%%%
 \begin{frame}{Perspectives}
 %%    SLIDE 54   %%
 %%%%%%%%%%%%%%%%%%%%
 \begin{frame}{Perspectives}

-\section{Perspectives}

 
 \begin{itemize}
 
 
 \begin{itemize}
 

-\small  \barrow We will adapt the proposed algorithms to take into consideration the
+\small  \barrow The proposed algorithms should  take into consideration the

 \textcolor{blue}{variability between some iterations}.
 
 \small  \barrow The proposed algorithms should be applied to \textcolor{blue}{other message passing methods with iterations} in order to see how they adapt to the characteristics of these methods.
 \textcolor{blue}{variability between some iterations}.
 
 \small  \barrow The proposed algorithms should be applied to \textcolor{blue}{other message passing methods with iterations} in order to see how they adapt to the characteristics of these methods.


@@ -1138,6 +1225,9 @@ Multi-splitting} method.
 \small \barrow The proposed algorithms for heterogeneous platforms should be applied to heterogeneous platforms composed of \textcolor{blue}{CPUs and GPUs}.
 
 \small \barrow Comparing the results returned by the energy models to the values given by  \textcolor{blue}{real instruments that measure the energy consumptions} of CPUs during the execution time.
 \small \barrow The proposed algorithms for heterogeneous platforms should be applied to heterogeneous platforms composed of \textcolor{blue}{CPUs and GPUs}.
 
 \small \barrow Comparing the results returned by the energy models to the values given by  \textcolor{blue}{real instruments that measure the energy consumptions} of CPUs during the execution time.

+\small \barrow  Considering the power consumed by the other devices in the node such as 
+\textcolor{blue}{the memory and the hard drive}  in the energy consumption model.
+

 \end{itemize}
 
 \end{frame}
 \end{itemize}
 
 \end{frame}


@@ -1147,7 +1237,7 @@ Multi-splitting} method.
 %%%%%%%%%%%%%%%%%%%%
 \begin{frame}{Fin} \vspace{-10 mm}
 
 %%%%%%%%%%%%%%%%%%%%
 \begin{frame}{Fin} \vspace{-10 mm}
 

-            \centering \Large \textcolor{blue}{Thanks for Your Listening}
+            \centering \Large \textcolor{blue}{Thank you for your attention}

             
             \vspace{2cm}
             \centering \textcolor{blue}{ {\Large Questions?}}
             
             \vspace{2cm}
             \centering \textcolor{blue}{ {\Large Questions?}}