X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/mpi-energy2.git/blobdiff_plain/054bc9f5e26028cd84aa816c5c06ed131959fdde..0a891245b5a70f9d2c9408a0b9eaeb03a5beede2:/Heter_paper.tex?ds=sidebyside

diff --git a/Heter_paper.tex b/Heter_paper.tex
index 9d743db..b8c513f 100644
--- a/Heter_paper.tex
+++ b/Heter_paper.tex
@@ -63,8 +63,7 @@
     Arnaud Giersch
   } 
   \IEEEauthorblockA{%
-    FEMTO-ST Institute\\
-    University of Franche-Comté\\
+    FEMTO-ST Institute, University of Franche-Comte\\
     IUT de Belfort-Montbéliard,
     19 avenue du Maréchal Juin, BP 527, 90016 Belfort cedex, France\\
     % Telephone: \mbox{+33 3 84 58 77 86}, % Raphaël
@@ -83,8 +82,7 @@ platforms many techniques have been  used. Dynamic voltage and frequency scaling
 consumption.  However,  lowering the  frequency  of  a  CPU might  increase  the
 execution  time of  an application  running on  that processor.   Therefore, the
 frequency that  gives the best tradeoff  between the energy  consumption and the
-performance of an application must be selected.
-
+performance of an application must be selected.\\
 In this  paper, a new  online frequencies selecting algorithm  for heterogeneous
 platforms is presented.   It selects the frequency which tries  to give the best
 tradeoff  between  energy saving  and  performance  degradation,  for each  node
@@ -240,7 +238,7 @@ nodes to finish  their computations (see Figure~(\ref{fig:heter})).
 Therefore,  the overall execution time  of the program is the execution time of the slowest
 task which has the highest computation time and no slack time.
   
- \begin{figure}[t]
+ \begin{figure}[!t]
   \centering
    \includegraphics[scale=0.6]{fig/commtasks}
   \caption{Parallel tasks on a heterogeneous platform}
@@ -486,7 +484,7 @@ normalized execution time is inverted which gives the normalized performance equ
 \end{multline}
 
 
-\begin{figure}
+\begin{figure}[!t]
   \centering
   \subfloat[Homogeneous platform]{%
     \includegraphics[width=.33\textwidth]{fig/homo}\label{fig:r1}}%
@@ -590,7 +588,7 @@ words, until they reach the higher bound. It can also be noticed that the higher
 the difference between the faster nodes  and the slower nodes is, the bigger the
 maximum distance  between the  energy curve and  the performance curve  is while
  the scaling factors are varying which results in bigger energy savings.
-\begin{figure}[t]
+\begin{figure}[!t]
   \centering
     \includegraphics[scale=0.5]{fig/start_freq}
   \caption{Selecting the initial frequencies}
@@ -717,7 +715,7 @@ remaining  20\%  to  the  static   power),  the  same  assumption  was  made  in
 nodes were connected via an ethernet network with 1 Gbit/s bandwidth.
 
 
-\begin{table}[htb]
+\begin{table}[!t]
   \caption{Heterogeneous nodes characteristics}
   % title of Table
   \centering
@@ -762,7 +760,7 @@ be executed on $1, 4, 9, 16, 36, 64, 144$ nodes.
 
  
  
-\begin{table}[htb]
+\begin{table}[!t]
   \caption{Running NAS benchmarks on 4 nodes }
   % title of Table
   \centering
@@ -789,7 +787,7 @@ be executed on $1, 4, 9, 16, 36, 64, 144$ nodes.
   \label{table:res_4n}
 \end{table}
 
-\begin{table}[htb]
+\begin{table}[!t]
   \caption{Running NAS benchmarks on 8 and 9 nodes }
   % title of Table
   \centering
@@ -816,7 +814,7 @@ be executed on $1, 4, 9, 16, 36, 64, 144$ nodes.
   \label{table:res_8n}
 \end{table}
 
-\begin{table}[htb]
+\begin{table}[!t]
   \caption{Running NAS benchmarks on 16 nodes }
   % title of Table
   \centering
@@ -843,7 +841,7 @@ be executed on $1, 4, 9, 16, 36, 64, 144$ nodes.
   \label{table:res_16n}
 \end{table}
 
-\begin{table}[htb]
+\begin{table}[!t]
   \caption{Running NAS benchmarks on 32 and 36 nodes }
   % title of Table
   \centering
@@ -870,7 +868,7 @@ be executed on $1, 4, 9, 16, 36, 64, 144$ nodes.
   \label{table:res_32n}
 \end{table}
 
-\begin{table}[htb]
+\begin{table}[!t]
   \caption{Running NAS benchmarks on 64 nodes }
   % title of Table
   \centering
@@ -898,7 +896,7 @@ be executed on $1, 4, 9, 16, 36, 64, 144$ nodes.
 \end{table}
 
 
-\begin{table}[htb]
+\begin{table}[!t]
   \caption{Running NAS benchmarks on 128 and 144 nodes }
   % title of Table
   \centering
@@ -959,7 +957,7 @@ small when compared to the communication times.
 
 
  
-\begin{figure}
+\begin{figure}[!t]
   \centering
   \subfloat[Energy saving]{%
     \includegraphics[width=.33\textwidth]{fig/energy}\label{fig:energy}}%
@@ -1040,7 +1038,7 @@ scaling  values which result  in less  energy saving  but also  less performance
 degradation.
 
 
- \begin{table}[htb]
+ \begin{table}[!t]
   \caption{The results of the 70\%-30\% power scenario}
   % title of Table
   \centering
@@ -1069,7 +1067,7 @@ degradation.
 
 
 
-\begin{table}[htb]
+\begin{table}[!t]
   \caption{The results of the 90\%-10\% power scenario}
   % title of Table
   \centering
@@ -1097,7 +1095,7 @@ degradation.
 \end{table}
 
 
-\begin{figure}
+\begin{figure}[!t]
   \centering
   \subfloat[Comparison  between the results on 8 nodes]{%
     \includegraphics[width=.33\textwidth]{fig/sen_comp}\label{fig:sen_comp}}%
@@ -1131,7 +1129,7 @@ degradation values while giving the same weight for both metrics.
 
 
 
-\begin{table}[h]
+\begin{table}[!t]
  \caption{Comparing the proposed algorithm}
  \centering
 \begin{tabular}{|l|l|l|l|l|l|l|l|}
@@ -1154,7 +1152,7 @@ degradation values while giving the same weight for both metrics.
 
 
 
-\begin{figure}[t]
+\begin{figure}[!t]
   \centering
    \includegraphics[scale=0.5]{fig/compare_EDP.pdf}
   \caption{Tradeoff comparison for NAS benchmarks class C}