From: afanfakh <afanfakh@fanfakh.afanfakh>
Date: Mon, 17 Mar 2014 14:56:43 +0000 (+0100)
Subject: Merge branch 'master' of ssh://info.iut-bm.univ-fcomte.fr/mpi-energy
X-Git-Tag: ispa14_submission~34
X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/mpi-energy.git/commitdiff_plain/b2e13cc196d2e0b917988a193d737cdcb4d983ee?ds=sidebyside;hp=--cc

Merge branch 'master' of ssh://info.iut-bm.univ-fcomte.fr/mpi-energy

Conflicts:
	paper.tex
---

b2e13cc196d2e0b917988a193d737cdcb4d983ee
diff --cc paper.tex
index 8d86a9d,89f43e9..d7ced09
--- a/paper.tex
+++ b/paper.tex
@@@ -565,10 -564,13 +564,10 @@@ same time over all available scales
    \label{fig:nas}
  \end{figure*}
  \begin{table}[htb]
 -  \caption{Optimal Scaling Factors Results}
 +  \caption{The EPSA Scaling Factors Results}
    % title of Table
    \centering
-   \begin{tabular}{ | l | l | l |l | r |}
 -  \AG{Use the same number of decimals for all numbers in a column,
 -    and vertically align the numbers along the decimal points.
 -    The same for all the following tables.}
+   \begin{tabular}{|l|*{4}{r|}}
      \hline
      Program & Optimal & Energy  & Performance&Energy-Perf.\\
      Name & Scaling Factor& Saving \%&Degradation \% &Distance  \\ \hline
@@@ -755,12 -757,14 +754,12 @@@ than the first
    \includegraphics[width=.33\textwidth]{compare_class_A.pdf}
    \includegraphics[width=.33\textwidth]{compare_class_B.pdf}
    \includegraphics[width=.33\textwidth]{compare_class_c.pdf}
-   \caption{Comparing Our EPSA with Rauber and R\"{u}nger Methods}
+   \caption{Comparing Our EPSA with Rauber and Rünger Methods}
    \label{fig:compare}
  \end{figure}
 -
  \section{Conclusion}
  \label{sec.concl}
 -
 -\AG{the conclusion needs to be written\dots{} one day}
 +In this paper we develop the simultaneous energy-performance algorithm. It is works based on the trade off relation between the energy and performance. The results showed that when the scaling factor is big value leads to more energy saving. Also, it show that when the the scaling factor is small value leads to the fact that the scaling factor has bigger impact on performance than energy. Then the algorithm optimize the energy saving and performance in the same time to have positive trade off. The optimal trade off refer to maximum distance between the energy and the inversed performance curves. Also, the results explained when setting the slowest task to maximum frequency usually not have a big improvement on performance. 
  
  \section*{Acknowledgment}