X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/ThesisAhmed.git/blobdiff_plain/1e2dba6a4221941261eb9fc136576db92c7b1e56..HEAD:/thesis-presentation/AhmedSlides.tex?ds=sidebyside

diff --git a/thesis-presentation/AhmedSlides.tex b/thesis-presentation/AhmedSlides.tex
index 9bb4b6f..6dbbd81 100644
--- a/thesis-presentation/AhmedSlides.tex
+++ b/thesis-presentation/AhmedSlides.tex
@@ -22,7 +22,7 @@
 \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}
-
+\usepackage{ragged2e}
 \newcommand{\CL}{\Xsub{C}{L}}
 \newcommand{\Dist}{\mathit{Dist}}
 \newcommand{\EdNew}{\Xsub{E}{dNew}}
@@ -109,13 +109,55 @@
 \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    %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{Introduction and problem definition}
- \section{\small {Introduction and Problem definition}}
-   \bf \textcolor{blue}{To get more computing power:}
+\begin{frame}{Approaches to get more computing power}
+ 
+   %\bf \textcolor{blue}{}
      \begin{minipage}{0.5\textwidth} 
       \textcolor{blue}{1)} \small  \bf \textcolor{black}{Increase the frequency of a  processor.\\ (limited due to overheating)}
     \end{minipage}%
@@ -128,7 +170,8 @@
     \end{minipage}%
     \vspace{0.2cm}
     \begin{minipage}{0.5\textwidth} 
-     \textcolor{blue}{2)} \small \bf \textcolor{black}{Use more 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.}  
           
@@ -142,7 +185,6 @@
  
  
  
-
  %%%%%%%%%%%%%%%%%%%
 %%    SLIDE 04   %%
 %%%%%%%%%%%%%%%%%%%% 
@@ -151,26 +193,27 @@
      \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}
 
 %%%%%%%%%%%%%%%%%%%%
-%%    SLIDE 06    %%
+%%    SLIDE 05    %%
 %%%%%%%%%%%%%%%%%%%% 
 \begin{frame}{Techniques for energy consumption reduction}
  
-  \textcolor{blue}{2)} \bf \textcolor{black}{Dynamic voltage and frequency Scaling (DVFS)}
+  \textcolor{blue}{2)} \bf \textcolor{black}{Dynamic Voltage and Frequency Scaling (DVFS)}
      \vspace{-0.9cm}
     \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}
  
-
-
+%%%%%%%%%%%%%%%%%%%%
+%%    SLIDE 06   %%
+%%%%%%%%%%%%%%%%%%%% 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 07    %%
 %%%%%%%%%%%%%%%%%%%% 
@@ -203,7 +246,7 @@
 
  \begin{block}{\textcolor{white}{Challenge and Objective}}
 
-  	\small	\textcolor{blue}{Challenge:} \textcolor{black}{DVFS is used to reduce the energy consumption, \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}
  \small	 \textcolor{blue}{Objective:} \textcolor{black}{Applying the DVFS to minimize the energy consumption while maintaining the performance of the parallel application.}
@@ -239,43 +282,59 @@ for a warehouse-sized computer.
 %%%%%%%%%%%%%%%%%%%% 
  
 \begin{frame}{Objectives}
-        \begin{femtoBlock}{} \vspace{-12 mm}
-                \begin{itemize} \small
-                   \item  Study the effect of the scaling factor on the \textbf{energy consumption and performance } of parallel  applications with iterations. \medskip
+        
+                \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 optimal trade-off} between the energy consumption and the performance. \medskip
-                   \item  Comparing the proposed algorithm to existing methods.
+                   \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}
                  %\let\thefootnote\relax\footnote{}
-          \vspace{-10 mm}
-        \end{femtoBlock}      
+        
+        
 \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}{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}
+
+
+
+
+  
+
+
  
  
  
@@ -284,68 +343,55 @@ for a warehouse-sized computer.
 %%    SLIDE 11   %%
 %%%%%%%%%%%%%%%%%%%% 
 \begin{frame}{Energy model for a 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. 
+      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}: \\ 
-    \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}:\\ 
-   	\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}
 
+
+  
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 12   %%
 %%%%%%%%%%%%%%%%%%%% 
 
 \begin{frame}{Energy model for a 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     
-              
-              
+       \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 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.
+      %  \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}
-  
-  
-%%%%%%%%%%%%%%%%%%%%
-%%    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}
 
 
 
@@ -383,23 +429,23 @@ for a warehouse-sized computer.
 %%%%%%%%%%%%%%%%%%%%
 %%    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   %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{Scaling algorithm example}
+\begin{frame}{Scaling factor selection algorithm}
 \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}
@@ -407,7 +453,7 @@ for a warehouse-sized computer.
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 17   %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{Experimental results }
+\begin{frame}{Experiment over SimGrid }
       \begin{femtoBlock}{}      
         \begin{itemize}
          \small
@@ -431,6 +477,8 @@ for a warehouse-sized computer.
      \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}
@@ -440,45 +488,46 @@ for a warehouse-sized computer.
 %%    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}}}
+         
+         \vspace{2 mm}
          
-            \includegraphics[width=.55\textwidth]{c1/compare-c.pdf}}
+           $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   %%
 %%%%%%%%%%%%%%%%%%%% 
-\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}
+%\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}
+ % \end{figure}
+%\end{frame}
 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 21   %%
 %%%%%%%%%%%%%%%%%%%% 
-\begin{frame}{\large Comparing the new model with Rauber's 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}
 
 
 
@@ -529,7 +578,7 @@ for a warehouse-sized computer.
                    \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                      
                    
-                   \item  Computing  the vector of scaling factors ($S_1, S_2, ..., S_n$)  producing \textcolor{blue} {the optimal trade-off} between
+                   \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}
                  
@@ -564,27 +613,27 @@ for a warehouse-sized computer.
  %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 25    %%
 %%%%%%%%%%%%%%%%%%%%
- \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}
+ %\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    %%
 %%%%%%%%%%%%%%%%%%%%
-  \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}
-  \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}
@@ -620,22 +669,22 @@ for a warehouse-sized computer.
 %%%%%%%%%%%%%%%%%%%%
 %%    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    %%
 %%%%%%%%%%%%%%%%%%%%
- \begin{frame}{The scaling algorithm example}
- \vspace{-0.5cm}
+ \begin{frame}{The scaling algorithm for heter. cluster}
+ \vspace{-0.77cm}
  \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}
@@ -646,86 +695,58 @@ for a warehouse-sized computer.
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 30    %%
 %%%%%%%%%%%%%%%%%%%%
-\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
+%\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    %%
 %%%%%%%%%%%%%%%%%%%%
-\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 reduces the energy consumption by \textcolor{red}{29\%} 
-     for the class C of the NAS Benchmarks 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    %%
 %%%%%%%%%%%%%%%%%%%%
-\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  by \textcolor{red}{3.8\%} the performance
-     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 power 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}{Comparing the objective function to EDP}
-     
-     EDP is the products between the energy consumption and the delay.
-    \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} 
-
-
 
 
 %%%%%%%%%%%%%%%%%%%%
@@ -744,10 +765,10 @@ for a warehouse-sized computer.
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 36    %%
 %%%%%%%%%%%%%%%%%%%%
-\begin{frame}{The grid architecture}
-\begin{center}
-\includegraphics[width=.8\textwidth]{c2/init_freq.pdf}
-\end{center}
+%\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}
@@ -779,7 +800,7 @@ for a warehouse-sized computer.
    % \end{block}  
      
      
- \end{frame}
+ %\end{frame}
   
   
   
@@ -837,11 +858,32 @@ for a warehouse-sized computer.
 
 
 
+%%%%%%%%%%%%%%%%%%%%
+%%    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    %%
 %%%%%%%%%%%%%%%%%%%%
-\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}
@@ -853,7 +895,22 @@ for a warehouse-sized computer.
 \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
@@ -893,7 +950,7 @@ for a warehouse-sized computer.
 \textcolor{blue}{The execution of a synchronous parallel iterative application over a grid }
 \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}
@@ -907,7 +964,7 @@ for a warehouse-sized computer.
 \textcolor{blue}{The execution of an asynchronous parallel iterative application over a grid }
 \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}
@@ -921,7 +978,7 @@ for a warehouse-sized computer.
 \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}
@@ -995,11 +1052,11 @@ for a warehouse-sized computer.
 %%%%%%%%%%%%%%%%%%%%
 %%    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}
+%\begin{frame}{The scaling algorithm for Asynch.  applications}
+%\vspace{-0.1 mm}
+%\centering
+%\includegraphics[width=0.55\textwidth]{algo-hybrid.pdf}
+%\end{frame}
 
 
 
@@ -1027,27 +1084,27 @@ for a warehouse-sized computer.
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 48   %%
 %%%%%%%%%%%%%%%%%%%%
-\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}
+%\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=0.42]{c3/energy_saving.eps}
+%\centering
+   % \includegraphics[scale=0.42]{c3/energy_saving.eps}
 
- \centering  The average energy saving  = \textcolor{red}{22\%}
-\end{frame} 
+ %\centering  The average energy saving  = \textcolor{red}{22\%}
+%\end{frame} 
 
 
 
 %%%%%%%%%%%%%%%%%%%%
 %%    SLIDE 49   %%
 %%%%%%%%%%%%%%%%%%%%
-\begin{frame}{The simulation results}
-\centering
+%\begin{frame}{The simulation results}
+%\centering
    
-     \includegraphics[scale=0.42]{c3/perf_degra.eps}
+   %  \includegraphics[scale=0.42]{c3/perf_degra.eps}
      
- \centering    The average speed-up  = \textcolor{red}{5.72\%}
-\end{frame} 
+%\centering    The average speed-up  = \textcolor{red}{5.72\%}
+%\end{frame} 
 
 
 
@@ -1055,7 +1112,7 @@ for a warehouse-sized computer.
 %%    SLIDE 50   %%
 %%%%%%%%%%%%%%%%%%%%
  \begin{frame}{The Grid'5000 results}
-   \vspace{-20 mm}
+   \vspace{-10 mm}
    \begin{figure}[!t]
    \centering
    \hspace{-8 mm}
@@ -1064,6 +1121,9 @@ for a warehouse-sized computer.
    \end{figure}
     \vspace{-5 mm}
      \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} 
 
@@ -1122,7 +1182,7 @@ Multi-splitting} method.
       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}
@@ -1165,6 +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  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}
@@ -1174,7 +1237,7 @@ Multi-splitting} method.
 %%%%%%%%%%%%%%%%%%%%
 \begin{frame}{Fin} \vspace{-10 mm}
 
-            \centering \Large \textcolor{blue}{Thank you for your listening}
+            \centering \Large \textcolor{blue}{Thank you for your attention}
             
             \vspace{2cm}
             \centering \textcolor{blue}{ {\Large Questions?}}
