adding abstract

[mpi-energy2.git] / mpi-energy2-extension / Heter_paper.tex

diff --git a/mpi-energy2-extension/Heter_paper.tex b/mpi-energy2-extension/Heter_paper.tex
index d157b79df7cde05aa2f49f94dc9d82ff634e7ce7..6b38c44777722221793846a3f30281bc8de23e4b 100644 (file)
--- a/mpi-energy2-extension/Heter_paper.tex
+++ b/mpi-energy2-extension/Heter_paper.tex
@@ -87,7 +87,7 @@
 
 
 \begin{abstract}
 
 
 \begin{abstract}

-
+\textcolor{blue}{

   In recent years, green computing topic  has being became an important topic in 
   the domain of the research. The increase in computing power of the computing 
   platforms is increased the energy consumption and the carbon dioxide emissions.
   In recent years, green computing topic  has being became an important topic in 
   the domain of the research. The increase in computing power of the computing 
   platforms is increased the energy consumption and the carbon dioxide emissions.


@@ -98,7 +98,6 @@
   a CPU may increase the execution time of an application running on that 
   processor. Therefore, the frequency that gives the best trade-off between 
   the energy consumption and the performance of an application must be selected. 
   a CPU may increase the execution time of an application running on that 
   processor. Therefore, the frequency that gives the best trade-off between 
   the energy consumption and the performance of an application must be selected. 

-

   In this paper, a new online frequency selecting algorithm for heterogeneous
   grid (heterogeneous CPUs) is presented.  It selects the frequencies and tries to give the best
   trade-off between energy saving and performance degradation, for each node
   In this paper, a new online frequency selecting algorithm for heterogeneous
   grid (heterogeneous CPUs) is presented.  It selects the frequencies and tries to give the best
   trade-off between energy saving and performance degradation, for each node


@@ -108,9 +107,9 @@
   grid. The proposed algorithm is evaluated on real testbed, grid'5000 platform, while
   running the NAS parallel benchmarks.  The experiments show that it reduces the
   energy consumption on average up to \np[\%]{30} while declines the performance
   grid. The proposed algorithm is evaluated on real testbed, grid'5000 platform, while
   running the NAS parallel benchmarks.  The experiments show that it reduces the
   energy consumption on average up to \np[\%]{30} while declines the performance

-  on average by \np[\%]{3} only for the same instance. Finally, the algorithm is 
+  on average by \np[\%]{3}. Finally, the algorithm is 

   compared to an existing method, the comparison results show that it outperforms the
   compared to an existing method, the comparison results show that it outperforms the

-  latter in term of energy and performance trade-off.
+  latter in term of energy and performance trade-off.}

 \end{abstract}
 
 
 \end{abstract}